type of survey research

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Survey Research – Types, Methods, Examples

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Survey Research

Definition:

Survey Research is a quantitative research method that involves collecting standardized data from a sample of individuals or groups through the use of structured questionnaires or interviews. The data collected is then analyzed statistically to identify patterns and relationships between variables, and to draw conclusions about the population being studied.

Survey research can be used to answer a variety of questions, including:

What are people’s opinions about a certain topic?
What are people’s experiences with a certain product or service?
What are people’s beliefs about a certain issue?

Survey Research Methods

Survey Research Methods are as follows:

Telephone surveys: A survey research method where questions are administered to respondents over the phone, often used in market research or political polling.
Face-to-face surveys: A survey research method where questions are administered to respondents in person, often used in social or health research.
Mail surveys: A survey research method where questionnaires are sent to respondents through mail, often used in customer satisfaction or opinion surveys.
Online surveys: A survey research method where questions are administered to respondents through online platforms, often used in market research or customer feedback.
Email surveys: A survey research method where questionnaires are sent to respondents through email, often used in customer satisfaction or opinion surveys.
Mixed-mode surveys: A survey research method that combines two or more survey modes, often used to increase response rates or reach diverse populations.
Computer-assisted surveys: A survey research method that uses computer technology to administer or collect survey data, often used in large-scale surveys or data collection.
Interactive voice response surveys: A survey research method where respondents answer questions through a touch-tone telephone system, often used in automated customer satisfaction or opinion surveys.
Mobile surveys: A survey research method where questions are administered to respondents through mobile devices, often used in market research or customer feedback.
Group-administered surveys: A survey research method where questions are administered to a group of respondents simultaneously, often used in education or training evaluation.
Web-intercept surveys: A survey research method where questions are administered to website visitors, often used in website or user experience research.
In-app surveys: A survey research method where questions are administered to users of a mobile application, often used in mobile app or user experience research.
Social media surveys: A survey research method where questions are administered to respondents through social media platforms, often used in social media or brand awareness research.
SMS surveys: A survey research method where questions are administered to respondents through text messaging, often used in customer feedback or opinion surveys.
IVR surveys: A survey research method where questions are administered to respondents through an interactive voice response system, often used in automated customer feedback or opinion surveys.
Mixed-method surveys: A survey research method that combines both qualitative and quantitative data collection methods, often used in exploratory or mixed-method research.
Drop-off surveys: A survey research method where respondents are provided with a survey questionnaire and asked to return it at a later time or through a designated drop-off location.
Intercept surveys: A survey research method where respondents are approached in public places and asked to participate in a survey, often used in market research or customer feedback.
Hybrid surveys: A survey research method that combines two or more survey modes, data sources, or research methods, often used in complex or multi-dimensional research questions.

Types of Survey Research

There are several types of survey research that can be used to collect data from a sample of individuals or groups. following are Types of Survey Research:

Cross-sectional survey: A type of survey research that gathers data from a sample of individuals at a specific point in time, providing a snapshot of the population being studied.
Longitudinal survey: A type of survey research that gathers data from the same sample of individuals over an extended period of time, allowing researchers to track changes or trends in the population being studied.
Panel survey: A type of longitudinal survey research that tracks the same sample of individuals over time, typically collecting data at multiple points in time.
Epidemiological survey: A type of survey research that studies the distribution and determinants of health and disease in a population, often used to identify risk factors and inform public health interventions.
Observational survey: A type of survey research that collects data through direct observation of individuals or groups, often used in behavioral or social research.
Correlational survey: A type of survey research that measures the degree of association or relationship between two or more variables, often used to identify patterns or trends in data.
Experimental survey: A type of survey research that involves manipulating one or more variables to observe the effect on an outcome, often used to test causal hypotheses.
Descriptive survey: A type of survey research that describes the characteristics or attributes of a population or phenomenon, often used in exploratory research or to summarize existing data.
Diagnostic survey: A type of survey research that assesses the current state or condition of an individual or system, often used in health or organizational research.
Explanatory survey: A type of survey research that seeks to explain or understand the causes or mechanisms behind a phenomenon, often used in social or psychological research.
Process evaluation survey: A type of survey research that measures the implementation and outcomes of a program or intervention, often used in program evaluation or quality improvement.
Impact evaluation survey: A type of survey research that assesses the effectiveness or impact of a program or intervention, often used to inform policy or decision-making.
Customer satisfaction survey: A type of survey research that measures the satisfaction or dissatisfaction of customers with a product, service, or experience, often used in marketing or customer service research.
Market research survey: A type of survey research that collects data on consumer preferences, behaviors, or attitudes, often used in market research or product development.
Public opinion survey: A type of survey research that measures the attitudes, beliefs, or opinions of a population on a specific issue or topic, often used in political or social research.
Behavioral survey: A type of survey research that measures actual behavior or actions of individuals, often used in health or social research.
Attitude survey: A type of survey research that measures the attitudes, beliefs, or opinions of individuals, often used in social or psychological research.
Opinion poll: A type of survey research that measures the opinions or preferences of a population on a specific issue or topic, often used in political or media research.
Ad hoc survey: A type of survey research that is conducted for a specific purpose or research question, often used in exploratory research or to answer a specific research question.

Types Based on Methodology

Based on Methodology Survey are divided into two Types:

Quantitative Survey Research

Qualitative survey research.

Quantitative survey research is a method of collecting numerical data from a sample of participants through the use of standardized surveys or questionnaires. The purpose of quantitative survey research is to gather empirical evidence that can be analyzed statistically to draw conclusions about a particular population or phenomenon.

In quantitative survey research, the questions are structured and pre-determined, often utilizing closed-ended questions, where participants are given a limited set of response options to choose from. This approach allows for efficient data collection and analysis, as well as the ability to generalize the findings to a larger population.

Quantitative survey research is often used in market research, social sciences, public health, and other fields where numerical data is needed to make informed decisions and recommendations.

Qualitative survey research is a method of collecting non-numerical data from a sample of participants through the use of open-ended questions or semi-structured interviews. The purpose of qualitative survey research is to gain a deeper understanding of the experiences, perceptions, and attitudes of participants towards a particular phenomenon or topic.

In qualitative survey research, the questions are open-ended, allowing participants to share their thoughts and experiences in their own words. This approach allows for a rich and nuanced understanding of the topic being studied, and can provide insights that are difficult to capture through quantitative methods alone.

Qualitative survey research is often used in social sciences, education, psychology, and other fields where a deeper understanding of human experiences and perceptions is needed to inform policy, practice, or theory.

Data Analysis Methods

There are several Survey Research Data Analysis Methods that researchers may use, including:

Descriptive statistics: This method is used to summarize and describe the basic features of the survey data, such as the mean, median, mode, and standard deviation. These statistics can help researchers understand the distribution of responses and identify any trends or patterns.
Inferential statistics: This method is used to make inferences about the larger population based on the data collected in the survey. Common inferential statistical methods include hypothesis testing, regression analysis, and correlation analysis.
Factor analysis: This method is used to identify underlying factors or dimensions in the survey data. This can help researchers simplify the data and identify patterns and relationships that may not be immediately apparent.
Cluster analysis: This method is used to group similar respondents together based on their survey responses. This can help researchers identify subgroups within the larger population and understand how different groups may differ in their attitudes, behaviors, or preferences.
Structural equation modeling: This method is used to test complex relationships between variables in the survey data. It can help researchers understand how different variables may be related to one another and how they may influence one another.
Content analysis: This method is used to analyze open-ended responses in the survey data. Researchers may use software to identify themes or categories in the responses, or they may manually review and code the responses.
Text mining: This method is used to analyze text-based survey data, such as responses to open-ended questions. Researchers may use software to identify patterns and themes in the text, or they may manually review and code the text.

Applications of Survey Research

Here are some common applications of survey research:

Market Research: Companies use survey research to gather insights about customer needs, preferences, and behavior. These insights are used to create marketing strategies and develop new products.
Public Opinion Research: Governments and political parties use survey research to understand public opinion on various issues. This information is used to develop policies and make decisions.
Social Research: Survey research is used in social research to study social trends, attitudes, and behavior. Researchers use survey data to explore topics such as education, health, and social inequality.
Academic Research: Survey research is used in academic research to study various phenomena. Researchers use survey data to test theories, explore relationships between variables, and draw conclusions.
Customer Satisfaction Research: Companies use survey research to gather information about customer satisfaction with their products and services. This information is used to improve customer experience and retention.
Employee Surveys: Employers use survey research to gather feedback from employees about their job satisfaction, working conditions, and organizational culture. This information is used to improve employee retention and productivity.
Health Research: Survey research is used in health research to study topics such as disease prevalence, health behaviors, and healthcare access. Researchers use survey data to develop interventions and improve healthcare outcomes.

Examples of Survey Research

Here are some real-time examples of survey research:

COVID-19 Pandemic Surveys: Since the outbreak of the COVID-19 pandemic, surveys have been conducted to gather information about public attitudes, behaviors, and perceptions related to the pandemic. Governments and healthcare organizations have used this data to develop public health strategies and messaging.
Political Polls During Elections: During election seasons, surveys are used to measure public opinion on political candidates, policies, and issues in real-time. This information is used by political parties to develop campaign strategies and make decisions.
Customer Feedback Surveys: Companies often use real-time customer feedback surveys to gather insights about customer experience and satisfaction. This information is used to improve products and services quickly.
Event Surveys: Organizers of events such as conferences and trade shows often use surveys to gather feedback from attendees in real-time. This information can be used to improve future events and make adjustments during the current event.
Website and App Surveys: Website and app owners use surveys to gather real-time feedback from users about the functionality, user experience, and overall satisfaction with their platforms. This feedback can be used to improve the user experience and retain customers.
Employee Pulse Surveys: Employers use real-time pulse surveys to gather feedback from employees about their work experience and overall job satisfaction. This feedback is used to make changes in real-time to improve employee retention and productivity.

Survey Sample

Purpose of survey research.

The purpose of survey research is to gather data and insights from a representative sample of individuals. Survey research allows researchers to collect data quickly and efficiently from a large number of people, making it a valuable tool for understanding attitudes, behaviors, and preferences.

Here are some common purposes of survey research:

Descriptive Research: Survey research is often used to describe characteristics of a population or a phenomenon. For example, a survey could be used to describe the characteristics of a particular demographic group, such as age, gender, or income.
Exploratory Research: Survey research can be used to explore new topics or areas of research. Exploratory surveys are often used to generate hypotheses or identify potential relationships between variables.
Explanatory Research: Survey research can be used to explain relationships between variables. For example, a survey could be used to determine whether there is a relationship between educational attainment and income.
Evaluation Research: Survey research can be used to evaluate the effectiveness of a program or intervention. For example, a survey could be used to evaluate the impact of a health education program on behavior change.
Monitoring Research: Survey research can be used to monitor trends or changes over time. For example, a survey could be used to monitor changes in attitudes towards climate change or political candidates over time.

When to use Survey Research

there are certain circumstances where survey research is particularly appropriate. Here are some situations where survey research may be useful:

When the research question involves attitudes, beliefs, or opinions: Survey research is particularly useful for understanding attitudes, beliefs, and opinions on a particular topic. For example, a survey could be used to understand public opinion on a political issue.
When the research question involves behaviors or experiences: Survey research can also be useful for understanding behaviors and experiences. For example, a survey could be used to understand the prevalence of a particular health behavior.
When a large sample size is needed: Survey research allows researchers to collect data from a large number of people quickly and efficiently. This makes it a useful method when a large sample size is needed to ensure statistical validity.
When the research question is time-sensitive: Survey research can be conducted quickly, which makes it a useful method when the research question is time-sensitive. For example, a survey could be used to understand public opinion on a breaking news story.
When the research question involves a geographically dispersed population: Survey research can be conducted online, which makes it a useful method when the population of interest is geographically dispersed.

How to Conduct Survey Research

Conducting survey research involves several steps that need to be carefully planned and executed. Here is a general overview of the process:

Define the research question: The first step in conducting survey research is to clearly define the research question. The research question should be specific, measurable, and relevant to the population of interest.
Develop a survey instrument : The next step is to develop a survey instrument. This can be done using various methods, such as online survey tools or paper surveys. The survey instrument should be designed to elicit the information needed to answer the research question, and should be pre-tested with a small sample of individuals.
Select a sample : The sample is the group of individuals who will be invited to participate in the survey. The sample should be representative of the population of interest, and the size of the sample should be sufficient to ensure statistical validity.
Administer the survey: The survey can be administered in various ways, such as online, by mail, or in person. The method of administration should be chosen based on the population of interest and the research question.
Analyze the data: Once the survey data is collected, it needs to be analyzed. This involves summarizing the data using statistical methods, such as frequency distributions or regression analysis.
Draw conclusions: The final step is to draw conclusions based on the data analysis. This involves interpreting the results and answering the research question.

Advantages of Survey Research

There are several advantages to using survey research, including:

Efficient data collection: Survey research allows researchers to collect data quickly and efficiently from a large number of people. This makes it a useful method for gathering information on a wide range of topics.
Standardized data collection: Surveys are typically standardized, which means that all participants receive the same questions in the same order. This ensures that the data collected is consistent and reliable.
Cost-effective: Surveys can be conducted online, by mail, or in person, which makes them a cost-effective method of data collection.
Anonymity: Participants can remain anonymous when responding to a survey. This can encourage participants to be more honest and open in their responses.
Easy comparison: Surveys allow for easy comparison of data between different groups or over time. This makes it possible to identify trends and patterns in the data.
Versatility: Surveys can be used to collect data on a wide range of topics, including attitudes, beliefs, behaviors, and preferences.

Limitations of Survey Research

Here are some of the main limitations of survey research:

Limited depth: Surveys are typically designed to collect quantitative data, which means that they do not provide much depth or detail about people’s experiences or opinions. This can limit the insights that can be gained from the data.
Potential for bias: Surveys can be affected by various biases, including selection bias, response bias, and social desirability bias. These biases can distort the results and make them less accurate.
L imited validity: Surveys are only as valid as the questions they ask. If the questions are poorly designed or ambiguous, the results may not accurately reflect the respondents’ attitudes or behaviors.
Limited generalizability : Survey results are only generalizable to the population from which the sample was drawn. If the sample is not representative of the population, the results may not be generalizable to the larger population.
Limited ability to capture context: Surveys typically do not capture the context in which attitudes or behaviors occur. This can make it difficult to understand the reasons behind the responses.
Limited ability to capture complex phenomena: Surveys are not well-suited to capture complex phenomena, such as emotions or the dynamics of interpersonal relationships.

Following is an example of a Survey Sample:

Welcome to our Survey Research Page! We value your opinions and appreciate your participation in this survey. Please answer the questions below as honestly and thoroughly as possible.

1. What is your age?

A) Under 18
G) 65 or older

2. What is your highest level of education completed?

A) Less than high school
B) High school or equivalent
C) Some college or technical school
D) Bachelor’s degree
E) Graduate or professional degree

3. What is your current employment status?

A) Employed full-time
B) Employed part-time
C) Self-employed
D) Unemployed

4. How often do you use the internet per day?

A) Less than 1 hour
B) 1-3 hours
C) 3-5 hours
D) 5-7 hours
E) More than 7 hours

5. How often do you engage in social media per day?

6. Have you ever participated in a survey research study before?

7. If you have participated in a survey research study before, how was your experience?

A) Excellent
E) Very poor

8. What are some of the topics that you would be interested in participating in a survey research study about?

……………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………….

9. How often would you be willing to participate in survey research studies?

A) Once a week
B) Once a month
C) Once every 6 months
D) Once a year

10. Any additional comments or suggestions?

Thank you for taking the time to complete this survey. Your feedback is important to us and will help us improve our survey research efforts.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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Home Market Research

Survey Research: Definition, Examples and Methods

Survey Research is a quantitative research method used for collecting data from a set of respondents. It has been perhaps one of the most used methodologies in the industry for several years due to the multiple benefits and advantages that it has when collecting and analyzing data.

LEARN ABOUT: Behavioral Research

In this article, you will learn everything about survey research, such as types, methods, and examples.

Survey Research Definition

Survey Research is defined as the process of conducting research using surveys that researchers send to survey respondents. The data collected from surveys is then statistically analyzed to draw meaningful research conclusions. In the 21st century, every organization’s eager to understand what their customers think about their products or services and make better business decisions. Researchers can conduct research in multiple ways, but surveys are proven to be one of the most effective and trustworthy research methods. An online survey is a method for extracting information about a significant business matter from an individual or a group of individuals. It consists of structured survey questions that motivate the participants to respond. Creditable survey research can give these businesses access to a vast information bank. Organizations in media, other companies, and even governments rely on survey research to obtain accurate data.

The traditional definition of survey research is a quantitative method for collecting information from a pool of respondents by asking multiple survey questions. This research type includes the recruitment of individuals collection, and analysis of data. It’s useful for researchers who aim to communicate new features or trends to their respondents.

LEARN ABOUT: Level of Analysis Generally, it’s the primary step towards obtaining quick information about mainstream topics and conducting more rigorous and detailed quantitative research methods like surveys/polls or qualitative research methods like focus groups/on-call interviews can follow. There are many situations where researchers can conduct research using a blend of both qualitative and quantitative strategies.

LEARN ABOUT: Survey Sampling

Survey Research Methods

Survey research methods can be derived based on two critical factors: Survey research tool and time involved in conducting research. There are three main survey research methods, divided based on the medium of conducting survey research:

Online/ Email: Online survey research is one of the most popular survey research methods today. The survey cost involved in online survey research is extremely minimal, and the responses gathered are highly accurate.
Phone: Survey research conducted over the telephone ( CATI survey ) can be useful in collecting data from a more extensive section of the target population. There are chances that the money invested in phone surveys will be higher than other mediums, and the time required will be higher.
Face-to-face: Researchers conduct face-to-face in-depth interviews in situations where there is a complicated problem to solve. The response rate for this method is the highest, but it can be costly.

Further, based on the time taken, survey research can be classified into two methods:

Longitudinal survey research: Longitudinal survey research involves conducting survey research over a continuum of time and spread across years and decades. The data collected using this survey research method from one time period to another is qualitative or quantitative. Respondent behavior, preferences, and attitudes are continuously observed over time to analyze reasons for a change in behavior or preferences. For example, suppose a researcher intends to learn about the eating habits of teenagers. In that case, he/she will follow a sample of teenagers over a considerable period to ensure that the collected information is reliable. Often, cross-sectional survey research follows a longitudinal study .
Cross-sectional survey research: Researchers conduct a cross-sectional survey to collect insights from a target audience at a particular time interval. This survey research method is implemented in various sectors such as retail, education, healthcare, SME businesses, etc. Cross-sectional studies can either be descriptive or analytical. It is quick and helps researchers collect information in a brief period. Researchers rely on the cross-sectional survey research method in situations where descriptive analysis of a subject is required.

Survey research also is bifurcated according to the sampling methods used to form samples for research: Probability and Non-probability sampling. Every individual in a population should be considered equally to be a part of the survey research sample. Probability sampling is a sampling method in which the researcher chooses the elements based on probability theory. The are various probability research methods, such as simple random sampling , systematic sampling, cluster sampling, stratified random sampling, etc. Non-probability sampling is a sampling method where the researcher uses his/her knowledge and experience to form samples.

LEARN ABOUT: Survey Sample Sizes

The various non-probability sampling techniques are :

Convenience sampling
Snowball sampling
Consecutive sampling
Judgemental sampling
Quota sampling

Process of implementing survey research methods:

Decide survey questions: Brainstorm and put together valid survey questions that are grammatically and logically appropriate. Understanding the objective and expected outcomes of the survey helps a lot. There are many surveys where details of responses are not as important as gaining insights about what customers prefer from the provided options. In such situations, a researcher can include multiple-choice questions or closed-ended questions . Whereas, if researchers need to obtain details about specific issues, they can consist of open-ended questions in the questionnaire. Ideally, the surveys should include a smart balance of open-ended and closed-ended questions. Use survey questions like Likert Scale , Semantic Scale, Net Promoter Score question, etc., to avoid fence-sitting.

LEARN ABOUT: System Usability Scale

Finalize a target audience: Send out relevant surveys as per the target audience and filter out irrelevant questions as per the requirement. The survey research will be instrumental in case the target population decides on a sample. This way, results can be according to the desired market and be generalized to the entire population.

LEARN ABOUT: Testimonial Questions

Send out surveys via decided mediums: Distribute the surveys to the target audience and patiently wait for the feedback and comments- this is the most crucial step of the survey research. The survey needs to be scheduled, keeping in mind the nature of the target audience and its regions. Surveys can be conducted via email, embedded in a website, shared via social media, etc., to gain maximum responses.
Analyze survey results: Analyze the feedback in real-time and identify patterns in the responses which might lead to a much-needed breakthrough for your organization. GAP, TURF Analysis , Conjoint analysis, Cross tabulation, and many such survey feedback analysis methods can be used to spot and shed light on respondent behavior. Use a good survey analysis software . Researchers can use the results to implement corrective measures to improve customer/employee satisfaction.

Reasons to conduct survey research

The most crucial and integral reason for conducting market research using surveys is that you can collect answers regarding specific, essential questions. You can ask these questions in multiple survey formats as per the target audience and the intent of the survey. Before designing a study, every organization must figure out the objective of carrying this out so that the study can be structured, planned, and executed to perfection.

LEARN ABOUT: Research Process Steps

Questions that need to be on your mind while designing a survey are:

What is the primary aim of conducting the survey?
How do you plan to utilize the collected survey data?
What type of decisions do you plan to take based on the points mentioned above?

There are three critical reasons why an organization must conduct survey research.

Understand respondent behavior to get solutions to your queries: If you’ve carefully curated a survey, the respondents will provide insights about what they like about your organization as well as suggestions for improvement. To motivate them to respond, you must be very vocal about how secure their responses will be and how you will utilize the answers. This will push them to be 100% honest about their feedback, opinions, and comments. Online surveys or mobile surveys have proved their privacy, and due to this, more and more respondents feel free to put forth their feedback through these mediums.
Present a medium for discussion: A survey can be the perfect platform for respondents to provide criticism or applause for an organization. Important topics like product quality or quality of customer service etc., can be put on the table for discussion. A way you can do it is by including open-ended questions where the respondents can write their thoughts. This will make it easy for you to correlate your survey to what you intend to do with your product or service.
Strategy for never-ending improvements: An organization can establish the target audience’s attributes from the pilot phase of survey research . Researchers can use the criticism and feedback received from this survey to improve the product/services. Once the company successfully makes the improvements, it can send out another survey to measure the change in feedback keeping the pilot phase the benchmark. By doing this activity, the organization can track what was effectively improved and what still needs improvement.

Survey Research Scales

There are four main scales for the measurement of variables:

Nominal Scale: A nominal scale associates numbers with variables for mere naming or labeling, and the numbers usually have no other relevance. It is the most basic of the four levels of measurement.
Ordinal Scale: The ordinal scale has an innate order within the variables along with labels. It establishes the rank between the variables of a scale but not the difference value between the variables.
Interval Scale: The interval scale is a step ahead in comparison to the other two scales. Along with establishing a rank and name of variables, the scale also makes known the difference between the two variables. The only drawback is that there is no fixed start point of the scale, i.e., the actual zero value is absent.
Ratio Scale: The ratio scale is the most advanced measurement scale, which has variables that are labeled in order and have a calculated difference between variables. In addition to what interval scale orders, this scale has a fixed starting point, i.e., the actual zero value is present.

Benefits of survey research

In case survey research is used for all the right purposes and is implemented properly, marketers can benefit by gaining useful, trustworthy data that they can use to better the ROI of the organization.

Other benefits of survey research are:

Minimum investment: Mobile surveys and online surveys have minimal finance invested per respondent. Even with the gifts and other incentives provided to the people who participate in the study, online surveys are extremely economical compared to paper-based surveys.
Versatile sources for response collection: You can conduct surveys via various mediums like online and mobile surveys. You can further classify them into qualitative mediums like focus groups , and interviews and quantitative mediums like customer-centric surveys. Due to the offline survey response collection option, researchers can conduct surveys in remote areas with limited internet connectivity. This can make data collection and analysis more convenient and extensive.
Reliable for respondents: Surveys are extremely secure as the respondent details and responses are kept safeguarded. This anonymity makes respondents answer the survey questions candidly and with absolute honesty. An organization seeking to receive explicit responses for its survey research must mention that it will be confidential.

Survey research design

Researchers implement a survey research design in cases where there is a limited cost involved and there is a need to access details easily. This method is often used by small and large organizations to understand and analyze new trends, market demands, and opinions. Collecting information through tactfully designed survey research can be much more effective and productive than a casually conducted survey.

There are five stages of survey research design:

Decide an aim of the research: There can be multiple reasons for a researcher to conduct a survey, but they need to decide a purpose for the research. This is the primary stage of survey research as it can mold the entire path of a survey, impacting its results.
Filter the sample from target population: Who to target? is an essential question that a researcher should answer and keep in mind while conducting research. The precision of the results is driven by who the members of a sample are and how useful their opinions are. The quality of respondents in a sample is essential for the results received for research and not the quantity. If a researcher seeks to understand whether a product feature will work well with their target market, he/she can conduct survey research with a group of market experts for that product or technology.
Zero-in on a survey method: Many qualitative and quantitative research methods can be discussed and decided. Focus groups, online interviews, surveys, polls, questionnaires, etc. can be carried out with a pre-decided sample of individuals.
Design the questionnaire: What will the content of the survey be? A researcher is required to answer this question to be able to design it effectively. What will the content of the cover letter be? Or what are the survey questions of this questionnaire? Understand the target market thoroughly to create a questionnaire that targets a sample to gain insights about a survey research topic.
Send out surveys and analyze results: Once the researcher decides on which questions to include in a study, they can send it across to the selected sample . Answers obtained from this survey can be analyzed to make product-related or marketing-related decisions.

Survey examples: 10 tips to design the perfect research survey

Picking the right survey design can be the key to gaining the information you need to make crucial decisions for all your research. It is essential to choose the right topic, choose the right question types, and pick a corresponding design. If this is your first time creating a survey, it can seem like an intimidating task. But with QuestionPro, each step of the process is made simple and easy.

Below are 10 Tips To Design The Perfect Research Survey:

Set your SMART goals: Before conducting any market research or creating a particular plan, set your SMART Goals . What is that you want to achieve with the survey? How will you measure it promptly, and what are the results you are expecting?
Choose the right questions: Designing a survey can be a tricky task. Asking the right questions may help you get the answers you are looking for and ease the task of analyzing. So, always choose those specific questions – relevant to your research.
Begin your survey with a generalized question: Preferably, start your survey with a general question to understand whether the respondent uses the product or not. That also provides an excellent base and intro for your survey.
Enhance your survey: Choose the best, most relevant, 15-20 questions. Frame each question as a different question type based on the kind of answer you would like to gather from each. Create a survey using different types of questions such as multiple-choice, rating scale, open-ended, etc. Look at more survey examples and four measurement scales every researcher should remember.
Prepare yes/no questions: You may also want to use yes/no questions to separate people or branch them into groups of those who “have purchased” and those who “have not yet purchased” your products or services. Once you separate them, you can ask them different questions.
Test all electronic devices: It becomes effortless to distribute your surveys if respondents can answer them on different electronic devices like mobiles, tablets, etc. Once you have created your survey, it’s time to TEST. You can also make any corrections if needed at this stage.
Distribute your survey: Once your survey is ready, it is time to share and distribute it to the right audience. You can share handouts and share them via email, social media, and other industry-related offline/online communities.
Collect and analyze responses: After distributing your survey, it is time to gather all responses. Make sure you store your results in a particular document or an Excel sheet with all the necessary categories mentioned so that you don’t lose your data. Remember, this is the most crucial stage. Segregate your responses based on demographics, psychographics, and behavior. This is because, as a researcher, you must know where your responses are coming from. It will help you to analyze, predict decisions, and help write the summary report.
Prepare your summary report: Now is the time to share your analysis. At this stage, you should mention all the responses gathered from a survey in a fixed format. Also, the reader/customer must get clarity about your goal, which you were trying to gain from the study. Questions such as – whether the product or service has been used/preferred or not. Do respondents prefer some other product to another? Any recommendations?

Having a tool that helps you carry out all the necessary steps to carry out this type of study is a vital part of any project. At QuestionPro, we have helped more than 10,000 clients around the world to carry out data collection in a simple and effective way, in addition to offering a wide range of solutions to take advantage of this data in the best possible way.

From dashboards, advanced analysis tools, automation, and dedicated functions, in QuestionPro, you will find everything you need to execute your research projects effectively. Uncover insights that matter the most!

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A Comprehensive Guide to Survey Research Methodologies

For decades, researchers and businesses have used survey research to produce statistical data and explore ideas. The survey process is simple, ask questions and analyze the responses to make decisions. Data is what makes the difference between a valid and invalid statement and as the American statistician, W. Edwards Deming said:

“Without data, you’re just another person with an opinion.” - W. Edwards Deming

In this article, we will discuss what survey research is, its brief history, types, common uses, benefits, and the step-by-step process of designing a survey.

What is Survey Research

A survey is a research method that is used to collect data from a group of respondents in order to gain insights and information regarding a particular subject. It’s an excellent method to gather opinions and understand how and why people feel a certain way about different situations and contexts.

Brief History of Survey Research

Survey research may have its roots in the American and English “social surveys” conducted around the turn of the 20th century. The surveys were mainly conducted by researchers and reformers to document the extent of social issues such as poverty. ( 1 ) Despite being a relatively young field to many scientific domains, survey research has experienced three stages of development ( 2 ):

- First Era (1930-1960)

- Second Era (1960-1990)

- Third Era (1990 onwards)

Over the years, survey research adapted to the changing times and technologies. By exploiting the latest technologies, researchers can gain access to the right population from anywhere in the world, analyze the data like never before, and extract useful information.

Survey Research Methods & Types

Survey research can be classified into seven categories based on objective, data sources, methodology, deployment method, and frequency of deployment.

Types of survey research based on objective, data source, methodology, deployment method, and frequency of deployment.

Surveys based on Objective

Exploratory survey research.

Exploratory survey research is aimed at diving deeper into research subjects and finding out more about their context. It’s important for marketing or business strategy and the focus is to discover ideas and insights instead of gathering statistical data.

Generally, exploratory survey research is composed of open-ended questions that allow respondents to express their thoughts and perspectives. The final responses present information from various sources that can lead to fresh initiatives.

Predictive Survey Research

Predictive survey research is also called causal survey research. It’s preplanned, structured, and quantitative in nature. It’s often referred to as conclusive research as it tries to explain the cause-and-effect relationship between different variables. The objective is to understand which variables are causes and which are effects and the nature of the relationship between both variables.

Descriptive Survey Research

Descriptive survey research is largely observational and is ideal for gathering numeric data. Due to its quantitative nature, it’s often compared to exploratory survey research. The difference between the two is that descriptive research is structured and pre-planned.

The idea behind descriptive research is to describe the mindset and opinion of a particular group of people on a given subject. The questions are every day multiple choices and users must choose from predefined categories. With predefined choices, you don’t get unique insights, rather, statistically inferable data.

Survey Research Types based on Concept Testing

Monadic concept testing.

Monadic testing is a survey research methodology in which the respondents are split into multiple groups and ask each group questions about a separate concept in isolation. Generally, monadic surveys are hyper-focused on a particular concept and shorter in duration. The important thing in monadic surveys is to avoid getting off-topic or exhausting the respondents with too many questions.

Sequential Monadic Concept Testing

Another approach to monadic testing is sequential monadic testing. In sequential monadic surveys, groups of respondents are surveyed in isolation. However, instead of surveying three groups on three different concepts, the researchers survey the same groups of people on three distinct concepts one after another. In a sequential monadic survey, at least two topics are included (in random order), and the same questions are asked for each concept to eliminate bias.

Based on Data Source

Primary data.

Data obtained directly from the source or target population is referred to as primary survey data. When it comes to primary data collection, researchers usually devise a set of questions and invite people with knowledge of the subject to respond. The main sources of primary data are interviews, questionnaires, surveys, and observation methods.

Compared to secondary data, primary data is gathered from first-hand sources and is more reliable. However, the process of primary data collection is both costly and time-consuming.

Secondary Data

Survey research is generally used to collect first-hand information from a respondent. However, surveys can also be designed to collect and process secondary data. It’s collected from third-party sources or primary sources in the past.

This type of data is usually generic, readily available, and cheaper than primary data collection. Some common sources of secondary data are books, data collected from older surveys, online data, and data from government archives. Beware that you might compromise the validity of your findings if you end up with irrelevant or inflated data.

Based on Research Method

Quantitative research.

Quantitative research is a popular research methodology that is used to collect numeric data in a systematic investigation. It’s frequently used in research contexts where statistical data is required, such as sciences or social sciences. Quantitative research methods include polls, systematic observations, and face-to-face interviews.

Qualitative Research

Qualitative research is a research methodology where you collect non-numeric data from research participants. In this context, the participants are not restricted to a specific system and provide open-ended information. Some common qualitative research methods include focus groups, one-on-one interviews, observations, and case studies.

Based on Deployment Method

Online surveys.

With technology advancing rapidly, the most popular method of survey research is an online survey. With the internet, you can not only reach a broader audience but also design and customize a survey and deploy it from anywhere. Online surveys have outperformed offline survey methods as they are less expensive and allow researchers to easily collect and analyze data from a large sample.

Paper or Print Surveys

As the name suggests, paper or print surveys use the traditional paper and pencil approach to collect data. Before the invention of computers, paper surveys were the survey method of choice.

Though many would assume that surveys are no longer conducted on paper, it's still a reliable method of collecting information during field research and data collection. However, unlike online surveys, paper surveys are expensive and require extra human resources.

Telephonic Surveys

Telephonic surveys are conducted over telephones where a researcher asks a series of questions to the respondent on the other end. Contacting respondents over a telephone requires less effort, human resources, and is less expensive.

What makes telephonic surveys debatable is that people are often reluctant in giving information over a phone call. Additionally, the success of such surveys depends largely on whether people are willing to invest their time on a phone call answering questions.

One-on-one Surveys

One-on-one surveys also known as face-to-face surveys are interviews where the researcher and respondent. Interacting directly with the respondent introduces the human factor into the survey.

Face-to-face interviews are useful when the researcher wants to discuss something personal with the respondent. The response rates in such surveys are always higher as the interview is being conducted in person. However, these surveys are quite expensive and the success of these depends on the knowledge and experience of the researcher.

Based on Distribution

The easiest and most common way of conducting online surveys is sending out an email. Sending out surveys via emails has a higher response rate as your target audience already knows about your brand and is likely to engage.

Buy Survey Responses

Purchasing survey responses also yields higher responses as the responders signed up for the survey. Businesses often purchase survey samples to conduct extensive research. Here, the target audience is often pre-screened to check if they're qualified to take part in the research.

Embedding Survey on a Website

Embedding surveys on a website is another excellent way to collect information. It allows your website visitors to take part in a survey without ever leaving the website and can be done while a person is entering or exiting the website.

Post the Survey on Social Media

Social media is an excellent medium to reach abroad range of audiences. You can publish your survey as a link on social media and people who are following the brand can take part and answer questions.

Based on Frequency of Deployment

Cross-sectional studies.

Cross-sectional studies are administered to a small sample from a large population within a short period of time. This provides researchers a peek into what the respondents are thinking at a given time. The surveys are usually short, precise, and specific to a particular situation.

Longitudinal Surveys

Longitudinal surveys are an extension of cross-sectional studies where researchers make an observation and collect data over extended periods of time. This type of survey can be further divided into three types:

- Trend surveys are employed to allow researchers to understand the change in the thought process of the respondents over some time.

- Panel surveys are administered to the same group of people over multiple years. These are usually expensive and researchers must stick to their panel to gather unbiased opinions.

- In cohort surveys, researchers identify a specific category of people and regularly survey them. Unlike panel surveys, the same people do not need to take part over the years, but each individual must fall into the researcher’s primary interest category.

Retrospective Survey

Retrospective surveys allow researchers to ask questions to gather data about past events and beliefs of the respondents. Since retrospective surveys also require years of data, they are similar to the longitudinal survey, except retrospective surveys are shorter and less expensive.

Why Should You Conduct Research Surveys?

“In God we trust. All others must bring data” - W. Edwards Deming

In the information age, survey research is of utmost importance and essential for understanding the opinion of your target population. Whether you’re launching a new product or conducting a social survey, the tool can be used to collect specific information from a defined set of respondents. The data collected via surveys can be further used by organizations to make informed decisions.

Furthermore, compared to other research methods, surveys are relatively inexpensive even if you’re giving out incentives. Compared to the older methods such as telephonic or paper surveys, online surveys have a smaller cost and the number of responses is higher.

What makes surveys useful is that they describe the characteristics of a large population. With a larger sample size , you can rely on getting more accurate results. However, you also need honest and open answers for accurate results. Since surveys are also anonymous and the responses remain confidential, respondents provide candid and accurate answers.

Common Uses of a Survey

Surveys are widely used in many sectors, but the most common uses of the survey research include:

- Market research : surveying a potential market to understand customer needs, preferences, and market demand.

- Customer Satisfaction: finding out your customer’s opinions about your services, products, or companies .

- Social research: investigating the characteristics and experiences of various social groups.

- Health research: collecting data about patients’ symptoms and treatments.

- Politics: evaluating public opinion regarding policies and political parties.

- Psychology: exploring personality traits, behaviors, and preferences.

6 Steps to Conduct Survey Research

An organization, person, or company conducts a survey when they need the information to make a decision but have insufficient data on hand. Following are six simple steps that can help you design a great survey.

Step 1: Objective of the Survey

The first step in survey research is defining an objective. The objective helps you define your target population and samples. The target population is the specific group of people you want to collect data from and since it’s rarely possible to survey the entire population, we target a specific sample from it. Defining a survey objective also benefits your respondents by helping them understand the reason behind the survey.

Step 2: Number of Questions

The number of questions or the size of the survey depends on the survey objective. However, it’s important to ensure that there are no redundant queries and the questions are in a logical order. Rephrased and repeated questions in a survey are almost as frustrating as in real life. For a higher completion rate, keep the questionnaire small so that the respondents stay engaged to the very end. The ideal length of an interview is less than 15 minutes. ( 2 )

Step 3: Language and Voice of Questions

While designing a survey, you may feel compelled to use fancy language. However, remember that difficult language is associated with higher survey dropout rates. You need to speak to the respondent in a clear, concise, and neutral manner, and ask simple questions. If your survey respondents are bilingual, then adding an option to translate your questions into another language can also prove beneficial.

Step 4: Type of Questions

In a survey, you can include any type of questions and even both closed-ended or open-ended questions. However, opt for the question types that are the easiest to understand for the respondents, and offer the most value. For example, compared to open-ended questions, people prefer to answer close-ended questions such as MCQs (multiple choice questions)and NPS (net promoter score) questions.

Step 5: User Experience

Designing a great survey is about more than just questions. A lot of researchers underestimate the importance of user experience and how it affects their response and completion rates. An inconsistent, difficult-to-navigate survey with technical errors and poor color choice is unappealing for the respondents. Make sure that your survey is easy to navigate for everyone and if you’re using rating scales, they remain consistent throughout the research study.

Additionally, don’t forget to design a good survey experience for both mobile and desktop users. According to Pew Research Center, nearly half of the smartphone users access the internet mainly from their mobile phones and 14 percent of American adults are smartphone-only internet users. ( 3 )

Step 6: Survey Logic

Last but not least, logic is another critical aspect of the survey design. If the survey logic is flawed, respondents may not continue in the right direction. Make sure to test the logic to ensure that selecting one answer leads to the next logical question instead of a series of unrelated queries.

How to Effectively Use Survey Research with Starlight Analytics

Designing and conducting a survey is almost as much science as it is an art. To craft great survey research, you need technical skills, consider the psychological elements, and have a broad understanding of marketing.

The ultimate goal of the survey is to ask the right questions in the right manner to acquire the right results.

Bringing a new product to the market is a long process and requires a lot of research and analysis. In your journey to gather information or ideas for your business, Starlight Analytics can be an excellent guide. Starlight Analytics' product concept testing helps you measure your product's market demand and refine product features and benefits so you can launch with confidence. The process starts with custom research to design the survey according to your needs, execute the survey, and deliver the key insights on time.

Survey research in the United States: roots and emergence, 1890-1960 https://searchworks.stanford.edu/view/10733873
How to create a survey questionnaire that gets great responses https://luc.id/knowledgehub/how-to-create-a-survey-questionnaire-that-gets-great-responses/
Internet/broadband fact sheet https://www.pewresearch.org/internet/fact-sheet/internet-broadband/

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Doing Survey Research | A Step-by-Step Guide & Examples

Doing Survey Research | A Step-by-Step Guide & Examples

Published on 6 May 2022 by Shona McCombes . Revised on 10 October 2022.

Survey research means collecting information about a group of people by asking them questions and analysing the results. To conduct an effective survey, follow these six steps:

Determine who will participate in the survey
Decide the type of survey (mail, online, or in-person)
Design the survey questions and layout
Distribute the survey
Analyse the responses
Write up the results

Surveys are a flexible method of data collection that can be used in many different types of research .

What are surveys used for, step 1: define the population and sample, step 2: decide on the type of survey, step 3: design the survey questions, step 4: distribute the survey and collect responses, step 5: analyse the survey results, step 6: write up the survey results, frequently asked questions about surveys.

Surveys are used as a method of gathering data in many different fields. They are a good choice when you want to find out about the characteristics, preferences, opinions, or beliefs of a group of people.

Common uses of survey research include:

Social research: Investigating the experiences and characteristics of different social groups
Market research: Finding out what customers think about products, services, and companies
Health research: Collecting data from patients about symptoms and treatments
Politics: Measuring public opinion about parties and policies
Psychology: Researching personality traits, preferences, and behaviours

Surveys can be used in both cross-sectional studies , where you collect data just once, and longitudinal studies , where you survey the same sample several times over an extended period.

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Before you start conducting survey research, you should already have a clear research question that defines what you want to find out. Based on this question, you need to determine exactly who you will target to participate in the survey.

Populations

The target population is the specific group of people that you want to find out about. This group can be very broad or relatively narrow. For example:

The population of Brazil
University students in the UK
Second-generation immigrants in the Netherlands
Customers of a specific company aged 18 to 24
British transgender women over the age of 50

Your survey should aim to produce results that can be generalised to the whole population. That means you need to carefully define exactly who you want to draw conclusions about.

It’s rarely possible to survey the entire population of your research – it would be very difficult to get a response from every person in Brazil or every university student in the UK. Instead, you will usually survey a sample from the population.

The sample size depends on how big the population is. You can use an online sample calculator to work out how many responses you need.

There are many sampling methods that allow you to generalise to broad populations. In general, though, the sample should aim to be representative of the population as a whole. The larger and more representative your sample, the more valid your conclusions.

There are two main types of survey:

A questionnaire , where a list of questions is distributed by post, online, or in person, and respondents fill it out themselves
An interview , where the researcher asks a set of questions by phone or in person and records the responses

Which type you choose depends on the sample size and location, as well as the focus of the research.

Questionnaires

Sending out a paper survey by post is a common method of gathering demographic information (for example, in a government census of the population).

You can easily access a large sample.
You have some control over who is included in the sample (e.g., residents of a specific region).
The response rate is often low.

Online surveys are a popular choice for students doing dissertation research , due to the low cost and flexibility of this method. There are many online tools available for constructing surveys, such as SurveyMonkey and Google Forms .

You can quickly access a large sample without constraints on time or location.
The data is easy to process and analyse.
The anonymity and accessibility of online surveys mean you have less control over who responds.

If your research focuses on a specific location, you can distribute a written questionnaire to be completed by respondents on the spot. For example, you could approach the customers of a shopping centre or ask all students to complete a questionnaire at the end of a class.

You can screen respondents to make sure only people in the target population are included in the sample.
You can collect time- and location-specific data (e.g., the opinions of a shop’s weekday customers).
The sample size will be smaller, so this method is less suitable for collecting data on broad populations.

Oral interviews are a useful method for smaller sample sizes. They allow you to gather more in-depth information on people’s opinions and preferences. You can conduct interviews by phone or in person.

You have personal contact with respondents, so you know exactly who will be included in the sample in advance.
You can clarify questions and ask for follow-up information when necessary.
The lack of anonymity may cause respondents to answer less honestly, and there is more risk of researcher bias.

Like questionnaires, interviews can be used to collect quantitative data : the researcher records each response as a category or rating and statistically analyses the results. But they are more commonly used to collect qualitative data : the interviewees’ full responses are transcribed and analysed individually to gain a richer understanding of their opinions and feelings.

Next, you need to decide which questions you will ask and how you will ask them. It’s important to consider:

The type of questions
The content of the questions
The phrasing of the questions
The ordering and layout of the survey

Open-ended vs closed-ended questions

There are two main forms of survey questions: open-ended and closed-ended. Many surveys use a combination of both.

Closed-ended questions give the respondent a predetermined set of answers to choose from. A closed-ended question can include:

A binary answer (e.g., yes/no or agree/disagree )
A scale (e.g., a Likert scale with five points ranging from strongly agree to strongly disagree )
A list of options with a single answer possible (e.g., age categories)
A list of options with multiple answers possible (e.g., leisure interests)

Closed-ended questions are best for quantitative research . They provide you with numerical data that can be statistically analysed to find patterns, trends, and correlations .

Open-ended questions are best for qualitative research. This type of question has no predetermined answers to choose from. Instead, the respondent answers in their own words.

Open questions are most common in interviews, but you can also use them in questionnaires. They are often useful as follow-up questions to ask for more detailed explanations of responses to the closed questions.

The content of the survey questions

To ensure the validity and reliability of your results, you need to carefully consider each question in the survey. All questions should be narrowly focused with enough context for the respondent to answer accurately. Avoid questions that are not directly relevant to the survey’s purpose.

When constructing closed-ended questions, ensure that the options cover all possibilities. If you include a list of options that isn’t exhaustive, you can add an ‘other’ field.

Phrasing the survey questions

In terms of language, the survey questions should be as clear and precise as possible. Tailor the questions to your target population, keeping in mind their level of knowledge of the topic.

Use language that respondents will easily understand, and avoid words with vague or ambiguous meanings. Make sure your questions are phrased neutrally, with no bias towards one answer or another.

Ordering the survey questions

The questions should be arranged in a logical order. Start with easy, non-sensitive, closed-ended questions that will encourage the respondent to continue.

If the survey covers several different topics or themes, group together related questions. You can divide a questionnaire into sections to help respondents understand what is being asked in each part.

If a question refers back to or depends on the answer to a previous question, they should be placed directly next to one another.

Before you start, create a clear plan for where, when, how, and with whom you will conduct the survey. Determine in advance how many responses you require and how you will gain access to the sample.

When you are satisfied that you have created a strong research design suitable for answering your research questions, you can conduct the survey through your method of choice – by post, online, or in person.

There are many methods of analysing the results of your survey. First you have to process the data, usually with the help of a computer program to sort all the responses. You should also cleanse the data by removing incomplete or incorrectly completed responses.

If you asked open-ended questions, you will have to code the responses by assigning labels to each response and organising them into categories or themes. You can also use more qualitative methods, such as thematic analysis , which is especially suitable for analysing interviews.

Statistical analysis is usually conducted using programs like SPSS or Stata. The same set of survey data can be subject to many analyses.

Finally, when you have collected and analysed all the necessary data, you will write it up as part of your thesis, dissertation , or research paper .

In the methodology section, you describe exactly how you conducted the survey. You should explain the types of questions you used, the sampling method, when and where the survey took place, and the response rate. You can include the full questionnaire as an appendix and refer to it in the text if relevant.

Then introduce the analysis by describing how you prepared the data and the statistical methods you used to analyse it. In the results section, you summarise the key results from your analysis.

A Likert scale is a rating scale that quantitatively assesses opinions, attitudes, or behaviours. It is made up of four or more questions that measure a single attitude or trait when response scores are combined.

To use a Likert scale in a survey , you present participants with Likert-type questions or statements, and a continuum of items, usually with five or seven possible responses, to capture their degree of agreement.

Individual Likert-type questions are generally considered ordinal data , because the items have clear rank order, but don’t have an even distribution.

Overall Likert scale scores are sometimes treated as interval data. These scores are considered to have directionality and even spacing between them.

The type of data determines what statistical tests you should use to analyse your data.

A questionnaire is a data collection tool or instrument, while a survey is an overarching research method that involves collecting and analysing data from people using questionnaires.

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18 Different Types of Survey Methods + Pros & Cons

There are many reasons why surveys are important. Surveys help researchers find solutions, create discussions, and make decisions. They can also get to the bottom of the really important stuff, like, coffee or tea? Dogs or cats? Elvis or The Beatles? When it comes to finding the answers to these questions, there are 18 different types of survey methods to use.

Create your first survey, form, or poll now!

18 Different Types of Survey Methods

Different surveys serve different purposes, which is why there are a number of them to choose from. “What are the types of surveys I should use,” you ask? Here’s a look at the 18 types of survey methods researchers use today.

1. Interviews

Also known as in-person surveys or household surveys, this used to be one of the most popular types of survey to conduct. Researchers like them because they involve getting face-to-face with individuals. Of course, this method of surveying may seem antiquated when today we have online surveying at our fingertips. However, interviews still serve a purpose.

Researchers conduct interviews when they want to discuss something personal with people. For example, they may have questions that may require extensive probing to uncover the truth. Sure, some interviewees may be more comfortable answering questions confidentially behind a keyboard. However, a skilled interviewer is able to put them at ease and get genuine responses. They can often go deeper than you may be able to using other surveying methods.

Often, in-person interviews are recorded on camera. This way, an expert can review them afterward. They do this to determine if the answers given may be false based on an interviewee’s change in tone. A change in facial expressions and body movements may also be a signal they pick up on.

2. Intercept Surveys

While interviews tend to choose respondents and have controls in place, intercept surveys (or “man on the spot”) surveys are conducted at certain locations or events. This involves having an interviewer, or multiple interviewers, scoping out an area and asking people, generally at random, for their thoughts or viewpoints on a particular topic.

3. Focus Groups

These types of surveys are conducted in person as well. However, focus groups involve a number of people rather than just one individual. The group is generally small but demographically diverse and led by a moderator. The focus group may be sampling new products, or to have a discussion around a particular topic, often a hot-button one.

The purpose of a focus group survey is often to gauge people’s reaction to a product in a group setting or to get people talking, interacting—and yes, arguing—with the moderator taking notes on the group’s behavior and attitudes. This is often the most expensive survey method as a trained moderator must be paid. In addition, locations must be secured, often in various cities, and participants must be heavily incentivized to show up. Gift cards in the $75-100 range for each survey participant are the norm.

4. Panel Sampling

Recruiting survey-takers from a panel maintained by a research company is a surefire way to get respondents. Why? Because people have specifically signed up to take them. The benefit of these types of surveys for research, of course, is there you can be assured responses. In addition, you can filter respondents by a variety of criteria to be sure you’re speaking with your target audience.

The downside is data quality. These individuals get survey offers frequently. So, they may rush through them to get their inventive and move on to the next one. In addition, if you’re constantly tapping into the same people from the same panel, are you truly getting a representative sample?

5. Telephone Surveys

Most telephone survey research types are conducted through random digit dialing (RDD). RDD can reach both listed and unlisted numbers, improving sampling accuracy. Surveys are conducted by interviewers through computer-assisted telephone interviewing (CATI) software. CATI displays the questionnaire to the interviewer with a rotation of questions.

Telephone surveys started in the 1940s. In fact, in a recent blog , we recount how the predictions for the 1948 presidential election were completely wrong because of sampling bias in telephone surveys. Rising in popularity in the late 50s and early 60s when the telephone became common in most American households, telephone surveys are no longer a very popular method of conducting a survey. Why? Because many people refuse to take telephone surveys or simply are not answering calls from a number they don’t recognize.

6. Post-Call Surveys

If a telephone survey is going to be conducted, today it is usually a post-call survey. This is often accomplished through IVR, or interactive voice response. IVR means there is no interviewer involved. Instead, customers record answers to pre-recorded questions using numbers on their touch-tone keypads. If a question is open-ended, the interviewee can respond by speaking and the system records the answer. IVR surveys are often deployed to measure how a customer feels about a service they just received. For example, after calling your bank, you may be asked to stay on the line to answer a series of questions about your experience.

Most post-call surveys are either NPS surveys or customer satisfaction (CSAT) surveys. The former asks the customer “How likely are you to recommend our organization to a f riend or family based on your most recent interaction?” while the CSAT survey asks customers “How satisfied are you with the results of your most recent interaction?”. NPS survey results reflect how the customer feels about the brand, while CSAT surveys a re all about individual agent and contact center performance.

7. SMS Text Surveys

Many people rarely using their phone to talk anymore, and ignore calls from unknown numbers. This has given rise to the SMS (Short Messaging Service) text survey. SMS surveys are delivered via text to people who have opted in to receive notifications from the sender. This means that there is usually some level of engagement, improving response rates. The one downside is that questions typically need to be short, and answers are generally 1-2 words or simply numbers (this is why many NPS surveys, gauging customer satisfaction, are often conducted via SMS text). Be careful not to send too many text surveys, as a person can opt-out just as easily, usually by texting STOP.

8. Mail-in Surveys / Postal Surveys

These are delivered right to respondents’ doorsteps! Mail surveys were frequently used before the advent of the internet when respondents were spread out geographically and budgets were modest. After all, mail-in surveys didn’t require much cost other than the postage.

So are mail-in surveys going the way of the dinosaur? Not necessarily. They are still occasionally more valuable compared to different methods of surveying. Because they are going to a specific name and home address, they often feel more personalized. This personalization can prompt the recipient to complete the survey.

They’re also good for surveys of significant length. Most people have short attention spans, and won’t spend more than a few minutes on the phone or filling out an online survey. At least, not without an incentive! However, with a mail-in survey, the person can complete it at their leisure. They can fill out some of it, set it aside, and then come back to it later. This gives mail-in surveys a relatively high response rate.

9. Kiosk Surveys

These surveys happen on a computer screen at a physical location. You’ve probably seen them popping up in stores, hotel lobbies, hospitals, and office spaces. These days, they’re just about anywhere a researcher or marketer wants to collect data from customers or passers-by. Kiosk surveys provide immediate feedback following a purchase or an interaction. They collect responses while the experience is still fresh in the respondent’s mind. This makes their judgment more trustworthy. Below is an example of a SurveyLegend kiosk survey at McDonald’s. The kiosk survey collects information, thanks the respondent for their feedback, and then resets for the next customer. Read how to create your own kiosk survey here .

10. Email Surveys

Email surveys are one of the most effective surveying methods as they are delivered directly to your audience via their online account. They can be used by anyone for just about anything, and are easily customized for a particular audience. Another good thing about email surveys is you can easily see who did or did not open the survey and make improvements to it for a future send to increase response rates. You can also A/B test subject lines, imagery, and so on to see which is more effective. SurveyLegend offers dozens of different types of online survey questions, which we explore in our blog 12 Different Types of Survey Questions and When to Use Them (with Examples) .

11. Pop-up Surveys

A pop-up survey is a feedback form that pops up on a website or app. Although the main window a person is reading on their screen remains visible, it is temporarily disabled until a user interacts with the pop-up, either agreeing to leave feedback or closing out of it. The survey itself is typically about the company whose site or app the user is currently visiting (as opposed to an intercept survey, which is an invitation to take a survey hosted on a different site).

A pop-up survey attempts to grab website visitors’ attention in a variety of ways, popping up in the middle of the screen, moving in from the side, or covering the entire screen. While they can be intrusive, they also have many benefits. Read about the benefits of pop-up surveys here .

12. Embedded Surveys

The opposite of pop-up surveys, these surveys live directly on your website or another website of your choice. Because the survey cannot be X’ed out of like a pop-up, it takes up valuable real estate on your site, or could be expensive to implement on someone else’s site. In addition, although the embedded survey is there at all times, it may not get the amount of attention a pop-up does since it’s not “in the respondent’s face.”

13. Social Media Surveys

There are more than 3.5 billion people are using social media worldwide, a number projected to increase to almost 4.5 billion in 2025. This makes social media extremely important to marketers and researchers. Using platforms such as Facebook, Twitter, Instagram, and the new Threads, many companies and organizations send out social media surveys regularly. Because people check their social media accounts quite regularly, it’s a good way to collect responses and monitor changes in satisfaction levels or popular opinion. Check out our blog on social media surveys for more benefits and valuable tips.

14. Mobile Surveys

Mobile traffic has now overtaken desktop computers as the most used device for accessing the internet, with more than 54% of the share. But don’t fret – you don’t have to create an entirely new survey to reach people on their phones or tablets. Online poll makers like SurveyLegend are responsive, so when you create a desktop version of a survey, it automatically becomes mobile-friendly. The survey renders, or displays, on any device or screen regardless of size, with elements on the page automatically rearranging themselves, shrinking, or expanding as necessary. Learn more about our responsive surveys .

15. Mobile App Surveys

Today, most companies have a mobile app. These can be an ideal way to conduct surveys as people have to willingly download your app; this means, they already have a level of engagement with your company or brand making them more likely to respond to your surveys.

16. QR Code Surveys

QR Code or QRC is an abbreviation of “Quick Response Code.” These two-dimensional encoded images, when scanned, deliver hidden information that’s stored on it. They’re different from barcodes because they can house a lot more information, including website URLs, phone numbers, or up to 4,000 characters of text. The recent QR code comeback provides a good opportunity for researchers to collect data. Place the QR code anywhere – on flyers, posters, billboards, commercials – and all someone had to do is scan it with the mobile device to have immediate access to a survey. Read more about the benefits of QR code surveys .

17. Delphi Surveys

A Delphi survey is a structured research method used to gather the collective opinions and insights of a panel of experts on a particular topic. The process involves several rounds of questionnaires or surveys. Each round is designed to narrow things down until a consensus or hypothyses can be formed. One of the key features of the Delphi survey research is that participants are unknown to each other, thereby eliminating influence.

18. AI Surveys

Artificial intelligence is the latest types of survey method. Using AI, researchers allow the technology to ask survey questions. These “Chatbots” can even ask follow-up questions on the spot based on a respondent’s answer. There can be drawbacks, however. If a person suspects survey questions are coming from AI, they may be less likely to respond (or may respond incorrectly to mess with the AI). Additionally, AI is not good with emotions, so asking sensitive questions in an emotionless manner could be off putting to people. Read more about AI Surveys .

Online Surveys: Ideal for Collecting Data and Feedback

Statistic: Countries with the largest digital populations in the world as of January 2023 (in millions) | Statista

That’s not all. People can take online surveys just about anywhere thanks to mobile devices. The use of these devices across age groups is balancing out as well. Check out smartphone use by age group below.

Statistic: Share of adults in the United States who owned a smartphone from 2015 to 2021, by age group | Statista

With more and more people accessing the internet through their mobile devices, now you can reach teens while they’re between classes and adults during their subway commute to work. Can’t say that for those other types of surveys !

Online surveys are also extremely cost-efficient. You don’t have to spend money on paper, printing, postage, or an interviewer. This significantly reduces set-up and administration costs. This also allows researchers and companies to send out a survey very expeditiously. Additionally, many online survey tools provide in-depth analysis of survey data. This saves you from having to spend money on further research once the survey is complete.

Researchers have their pick of options when it’s time to survey people. Which method you choose may depend upon cost, reach, and the types of questions.

Now, you may be wondering, “ Where can I make free surveys ?” You can get started with free online surveys using SurveyLegend! He re are a few things that make SurveyLegend the ideal choice for different types of surveys for research ( or for fun) .

When it comes to surveys, brief is best to keep respondents attention. So, SurveyLegend automatically collects some data, such as the participant’s location, reducing the number of questions you have to ask.
People like eye candy and many surveys are just plain dull. SurveyLegend offers beautifully rendered pre-designed surveys that will get your participant’s attention – and keep it through to completion!
Today, most people take surveys on mobile devices. Often surveys desktop surveys don’t translate well, resulting in a high drop-off rate. SurveyLegend’s designs are responsive, automatically adjusting to any screen size.

What’s your favorite method of surveying people? (Hey… that’s a good topic for a survey!) Sound off in the comments!

Frequently Asked Questions (FAQs)

The 10 most common survey methods are online surveys, in-person interviews, focus groups, panel sampling, telephone surveys, post-call surveys, mail-in surveys, pop-up surveys, mobile surveys, and kiosk surveys.

Benefits of online surveys include their ability to reach a broad audience and that they are relatively inexpensive.

Kiosk surveys are surveys on a computer screen at the point of sale.

A focus group is an in-person interview or survey involving a group of people rather than just one individual. The group is generally small but demographically diverse, and led by a moderator.

Jasko Mahmutovic

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Types of Surveys: All You Need to Know About Survey Research Methods

Choose the right survey method : Your method should always align with your research objectives, target audience, budget, time constraints, and the type of data needed.
Pick distribution channels : You can embed surveys in email and use them in-product, as website pop-ups , or in a mobile app. There are also plenty of offline types of surveys. Each has its advantages and is suitable for different contexts.
Select the types of survey questions : Use closed-ended questions for quantifiable data, open-ended questions for richer insights, and mixed-format questions to combine both strengths. The choice of question type impacts the depth and quality of data you can collect.
Decide on survey frequency : Decide if your research requires a cross-sectional survey for a one-time snapshot or a longitudinal survey (trend, cohort, or panel) for tracking changes over time. This choice affects the insights you can derive from the data. Using a tool with in-built AI survey creation features can significantly speed up the process. ‍
Use surveys for your business case : With surveys, you can understand user needs, refine products, and improve online customer experiences . They inform strategic decisions in market or product research , customer experience, and content strategy, driving growth and customer satisfaction .

If you find your questions are going unheard, consider employing surveys as a strategic listening tool.

Designed for anyone collecting data, this article simplifies the choice of survey research methods to align with specific goals and secure trustworthy findings.

We will explore different survey types, their intended purposes, and practical advice for their use. After reading, you'll clearly understand how to apply survey methods to gather and interpret valuable feedback effectively.

What is survey research?

Survey research is a systematic method of collecting data from individuals to gather information and insights. A survey itself is a tool consisting of a series of questions aimed at extracting specific data from a particular group of people. This technique is widely used across various fields, such as marketing, social science, and public health, to uncover trends, attitudes, and behaviors.

Surveys are characterized by their capacity to provide quantitative data —numerical information that can be analyzed statistically— as well as qualitative insights , which delve into the reasoning behind certain trends or opinions.

The process involves selecting a sample that represents a larger population, formulating questions designed to elicit clear responses, and administering the survey through one of several methods, including online, by mail, or in person.

10 benefits of survey research

Survey research offers a range of benefits, making it a popular method in various fields such as social sciences, marketing, health, and public policy. Here are some of the key potential benefits:

1. Cost-effective

Surveys can be relatively inexpensive, especially when conducted online or via email. They allow you to collect data from large samples without the high costs associated with other methods, like user research interviews .

Modern survey tools make it easy for anyone, including those with limited research experience, to design and distribute surveys, democratizing the research process.

2. Large sample sizes = more reliable results

As your research sample sizes increase, the reliability and accuracy of the data also improve, leading to more trustworthy results and stronger conclusions.

Surveys can reach large numbers of respondents, increasing the generalizability of the results. It is particularly important for studies aiming to make inferences about larger audiences.

When drawing conclusions based on Survicate data, the sample size is usually in the thousands, which gives us confidence in the positive impact these changes will have on our customers.

Glen Hamilton , Senior Director of Digital Growth at Fortive

3. Flexibility

You can distribute surveys in many different ways. Online surveys alone can be distributed via email or link, as a website pops up , as an in-product, or as a mobile app . This flexibility allows you to choose the best method for your target audience and research objectives.

We use almost all available channels. We don't send letters with NPS yet, but maybe we'll get there one day 😅

Krzysztof Szymański , Head of CRM at Taxfix

4. Quantifiable data and trend analysis

Surveys often produce quantitative data, which can be easily analyzed using analytics tools. It allows you to create objective comparisons, establish metrics and KPIs, and build trendlines.

By conducting surveys at different points in time, you can track changes in opinions, behaviors, or other variables, allowing for trend analysis over time.

💡A recurrent NPS survey is a great tool to build a sentiment trendline.

You need to start somewhere and then see the baseline. Our business depends on the weather, so our users are probably less satisfied on rainy days. It’s quite the opposite when it’s sunny. We can see this in the surveys, but we needed a year or two to establish a baseline. User satisfaction went up in summer and down a bit in winter. Now we know it’s a normal trend.

Falco Kübler , Senior Product Owner at wetter.com

5. Time-efficient

Surveys can be designed to be quick to complete, minimizing the time burden on respondents. They also allow researchers to gather data in a relatively short time frame compared to other methods like longitudinal studies.

There’s a sports brand for which we can get enough responses with very high statistical significance within just three or four hours. People respond because they want to and because it's something they really are involved in.

Patricia Caldas , UXR Manager at Medialivre

6. Wide geographic reach

Surveys, especially online ones, can be distributed across different regions and even globally, making it possible to collect data from diverse populations.

💡If your audience is international, consider using multilingual surveys that get translated automatically depending on the language your respondents set for their browser.

7. Versatility in question design

Surveys can include a mix of question types, such as multiple-choice, Likert scales , open-ended questions , and more. This way, you can explore different aspects of a topic and collect a rich data set.

Additionally, they can be tailored to specific research needs for targeted data collection on particular issues, demographics, or sectors.

We have implemented Survicate [surveys] to get user feedback in a given context. So, as opposed to the more standard way of fielding surveys, sending an email to invite users to answer several questions, Survicate allows us to get feedback on the particular experience of the site or the app as the user is experiencing it, which makes the answers much more contextual and accurate.

Sandrine Veillet , VP of Global Product at Medscape

8. Anonymity

You can design anonymous surveys , encouraging more honest and accurate responses, especially for sensitive topics.

💡Although in Survicate, we usually advise identifying your respondents, there are cases in which anonymity can work better. It can, for example, reduce social desirability bias, where respondents might otherwise provide answers they think are more socially acceptable.

9. Capability to handle complex questions

Surveys can include complex question designs, for example, by using question logic, which can help delve deeper into the respondents' reasoning.

💡For example, Medscape used email surveys to test its hypothesis regarding a potential development in the brand’s content base. It was complex research, but it was managed with an unmoderated survey and specially designed survey logic that first tested whether the participants were properly prepared to take part in the survey research.

10. Ease of analysis

Customer feedback software easily processes and analyzes survey data, enabling you to gain insights quickly and efficiently.

Survicate's built-in analytics dashboard shows survey results in real-time, automatically measuring net promoter, customer satisfaction, or customer effort scores.

Moreover, you can categorize your qualitative feedback with Insights Hub and ask additional questions to a conversational chat-based Research Assistant that will draw answers from the available feedback.

How to choose the right survey method

When deciding on the best survey method for your needs, take into account the following factors:

Research Objective s: Clearly define what you want to achieve with your survey. Different goals require different survey approaches.
Target Audience : Identify where your audience is most likely to be reached and consider their preferred mode of communication.
Budget Constraints : Match the survey method to the financial resources available. Online surveys can be less costly compared to in-person methods.
Time Availability : Choose a method that fits within your timeline. Online surveys provide quicker results than traditional mail surveys.
Data Type Required : Decide if you need quantitative data, which is easily obtained through structured surveys, or qualitative data, which may necessitate more open-ended questions and discussions.

What formats can research surveys take?

Surveys can be distributed through various channels, each with its own set of advantages. Understanding the different types of survey methods based on distribution can help you select the most effective approach for your research needs. Let's explore the types of surveys based on how you distribute them.

Email surveys

Email surveys are sent directly to participants' inboxes. This method is highly targeted, reaching individuals who have already engaged with your brand or service. It is convenient for recipients, allowing them to respond at their leisure.

➡️ To improve response rates , ensure your survey tool collects partial responses. With this feature, surveys embedded in emails will collect every single answer, even if your respondent doesn't continue to fill out the survey.

One of the online types of surveys - email survey

In-product surveys

In-product surveys are embedded directly within your service or application. They capture feedback at the moment of user interaction, which can lead to more accurate and actionable insights.

➡️ This method is less intrusive and benefits from high engagement rates as it is part of the natural user experience.

Website surveys

Website surveys are a type of online surveys that can take the form of pop-ups, sidebar forms, or embedded questionnaires on a webpage. They are useful for capturing the opinions of site visitors in real-time, providing insights into user experience and satisfaction.

➡️ They should be easy to complete to ensure effectiveness and not disrupt the browsing experience.

One of the online types of surveys - pop-up survey

Link surveys

Surveys distributed via a link can be shared across multiple platforms, including social media, SMS, or digital workspaces. This online survey method offers flexibility in reaching a wider audience and can be used to gather a diverse range of responses.

➡️ It's important to track which platforms yield the best response rates to optimize future survey distributions.

Mobile surveys

With mobile surveys , you can easily collect in-app feedback . They should be brief and optimized for mobile interfaces to fit smaller screens and on-the-go lifestyles.

➡️ Design mobile surveys with concise content and straightforward navigation to maximize engagement.

One of the online types of surveys - in-app mobile survey

Phone surveys

You can achieve a more personal touch with a telephone survey and clarify any ambiguities in real-time. However, they require trained interviewers and may not reach respondents who favor communication via text or email.

➡️ Ensure questions are direct and the call script is standardized to maintain consistency across telephone surveys.

In-person interviews

Face-to-face interviews or in-person surveys can yield comprehensive and nuanced information, as body language and tone provide additional context. They are highly interactive but can be costly and time-consuming.

➡️ Prepare a structured interview guide to keep the face-to-face interviews focused and efficient.

Paper surveys

Paper surveys are traditional tools useful in environments lacking digital access. They do not require internet connectivity, but data entry and analysis for a paper survey research can be labor-intensive.

➡️ To manage this, create questions that are easy to process and analyze from collected paper surveys.

Kiosk surveys

Kiosk surveys are interactive, often touch-screen questionnaires placed in high-traffic areas in a survey kiosk, allowing for immediate feedback.

➡️ They are ideal for capturing real-time customer reactions or satisfaction levels at the point of experience, such as in retail stores or service centers.

Focus groups

Focus groups are small, diverse groups of people whose reactions to specific topics are studied. Moderators lead discussions to gain deep insights into participant attitudes and perceptions, making it a qualitative method valuable for exploring complex issues.

Panel surveys

A panel survey involves a pre-recruited group of individuals who agree to participate in multiple surveys over a period. This method ensures a reliable sample for longitudinal studies, tracking changes in opinions or behaviors among the same set of respondents.

Types of survey questions

When designing a survey, your questions can make or break the data you collect. It is vital to understand the different question types and when to use them to gather meaningful insights effectively.

Closed-ended questions

Closed-ended questions are designed to receive a specific response, such as "yes" or "no," a numerical rating, or a choice from a set list of options. These types of questions are quantifiable, making them straightforward to analyze. Examples include multiple-choice questions and rating scales.

➡️ Best for: quick, concise data collection.

Open-ended questions

Open-ended questions allow respondents to answer in their own words, providing richer, more nuanced information. This format is less restrictive and can yield insights that closed-ended questions might miss. Utilizing open-ended questions can be invaluable for understanding the reasons behind behaviors or opinions, though the data can be more challenging to analyze due to its qualitative nature.

➡️ Best for: understanding the reasons behind behaviors or opinions

Mixed-format questions

Mixed-format questions combine elements of both open and closed-ended questions. They might start with a closed-ended question and then offer an "Other" option where respondents can elaborate. This hybrid approach provides the structured data of closed-ended questions with the depth of open-ended ones, making it a versatile choice for complex topics.

➡️ Best for: Mixed-format questions enable you to gather a wide range of data without limiting respondent expression.

Types of surveys based on frequency

Surveys can be categorized by how often they are conducted. This frequency affects the type of data collected and the insights that can be drawn.

Cross-Sectional Surveys : These are one-time snapshots of a population at a specific point in time. They help in understanding current attitudes or behaviors but do not track changes over time.

Longitudinal Surveys: In contrast, longitudinal surveys are conducted repeatedly over an extended period. They can be further broken down into:

Trend Surveys: measure changes over time within a population, where different individuals may be surveyed in each wave.
Cohort Surveys: Cohort surveys follow a specific sub-group or cohort over time, observing how their responses change.
Panel Surveys: Similar to cohort surveys, panel surveys involve repeatedly surveying the same individuals over time, allowing for detailed tracking of individual changes.

The choice between cross-sectional and longitudinal surveys depends on whether your research aims to capture a momentary picture or observe trends and developments. Each type offers unique benefits and should align with your specific research objectives.

What can businesses do with these types of surveys?

Surveys are powerful tools for businesses seeking to understand their market, customers, and products. They can inform a range of strategic decisions and drive growth when used effectively.

Customer experience

Customer experience surveys are essential for gauging satisfaction and identifying areas for service improvement to enhance customer loyalty.

Net Promoter Score® (NPS) Survey : Measure customer loyalty and predict business growth.

Customer Satisfaction (CSAT) Survey : Obtain immediate feedback on customer satisfaction with a product, service, or interaction.

Product surveys

Product surveys allow businesses to collect user feedback on their offerings, guiding product development and feature optimization.

Product Development Feedback Survey : Gain insights into customers' desired features or improvements.

Product Use and Satisfaction Survey : Understand how customers use your product and their satisfaction levels.

Market research survey

Market research surveys help businesses understand their audience and market landscape. They provide critical insights for informed decision-making and strategic planning.

Customer Demographics Survey : Gather data on age, gender, income, and more to tailor marketing strategies.

Competitor Analysis Survey : Assess how your business stacks up against competitors to identify areas for improvement.

Exit intent surveys

Exit intent surveys reveal the reasons behind user departures, providing actionable insights to reduce churn rates.

Website Exit Survey : Discover why visitors leave without converting to address potential issues.

Brand surveys

Brand surveys measure public perception and awareness, offering valuable data to shape branding and marketing initiatives.

Brand Awareness Survey : Determine how well customers recognize and recall your brand.

Brand Perception Survey : Learn how customers perceive your brand values and positioning.

Lead generation survey

Lead generation surveys assist in identifying potential customers and understanding their needs, optimizing the sales funnel.

Lead Qualification Survey : Identify and understand potential leads to increase conversion rates.

Pre-Sales Survey : Collect information from prospects to personalize sales approaches and improve close rates.

Content evaluation survey

Content evaluation surveys assess the impact and effectiveness of marketing content, helping to refine content strategy and audience engagement.

Blog Feedback Survey : Obtain reader feedback to enhance content relevance and engagement.

Content Effectiveness Survey : Measure how well your content meets audience needs and supports your marketing goals.

Each survey type serves a specific purpose and, when utilized correctly, can provide valuable insights to inform business decisions and strategies. Whether you're looking to delve into market trends, evaluate customer satisfaction, or refine your content strategy, there's a survey designed to meet your needs.

a banner that promotes using Survicate surveys

Run online surveys with Survicate

Choosing the correct survey method is crucial for gathering useful data. Survicate offers a user-friendly survey platform that allows you to create and distribute surveys through email, on your website, in your product, and even on mobile devices.

With Survicate, you can easily collect feedback and turn it into insights that can help improve your business. Using our AI survey builder you can launch your first survey in seconds. Whether gauging customer satisfaction or adjusting product features, this tool assists you in making informed decisions and analyzing the insights you collect. It's straightforward to use and designed to provide valuable information efficiently.

So, why not give it a try? Sign up now , and take advantage of Survicate's 10-day free trial that unlocks all the Business Plan features . It's time to uncover the insights to steer your strategies toward success.

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Survey Research — Types, Methods and Example Questions

Survey research The world of research is vast and complex, but with the right tools and understanding, it's an open field of discovery. Welcome to a journey into the heart of survey research. What is survey research? Survey research is the lens through which we view the opinions, behaviors, and experiences of a population. Think of it as the research world's detective, cleverly sleuthing out the truths hidden beneath layers of human complexity. Why is survey research important? Survey research is a Swiss Army Knife in a researcher's toolbox. It’s adaptable, reliable, and incredibly versatile, but its real power? It gives voice to the silent majority. Whether it's understanding customer preferences or assessing the impact of a social policy, survey research is the bridge between unanswered questions and insightful data. Let's embark on this exploration, armed with the spirit of openness, a sprinkle of curiosity, and the thirst for making knowledge accessible. As we journey further into the realm of survey research, we'll delve deeper into the diverse types of surveys, innovative data collection methods, and the rewards and challenges that come with them. Types of survey research Survey research is like an artist's palette, offering a variety of types to suit your unique research needs. Each type paints a different picture, giving us fascinating insights into the world around us. Cross-Sectional Surveys: Capture a snapshot of a population at a specific moment in time. They're your trusty Polaroid camera, freezing a moment for analysis and understanding. Longitudinal Surveys: Track changes over time, much like a time-lapse video. They help to identify trends and patterns, offering a dynamic perspective of your subject. Descriptive Surveys: Draw a detailed picture of the current state of affairs. They're your magnifying glass, examining the prevalence of a phenomenon or attitudes within a group. Analytical Surveys: Deep dive into the reasons behind certain outcomes. They're the research world's version of Sherlock Holmes, unraveling the complex web of cause and effect. But, what method should you choose for data collection? The plot thickens, doesn't it? Let's unravel this mystery in our next section. Survey research and data collection methods Data collection in survey research is an art form, and there's no one-size-fits-all method. Think of it as your paintbrush, each stroke represents a different way of capturing data. Online Surveys: In the digital age, online surveys have surged in popularity. They're fast, cost-effective, and can reach a global audience. But like a mysterious online acquaintance, respondents may not always be who they say they are. Mail Surveys: Like a postcard from a distant friend, mail surveys have a certain charm. They're great for reaching respondents without internet access. However, they’re slower and have lower response rates. They’re a test of patience and persistence. Telephone Surveys: With the sound of a ringing phone, the human element enters the picture. Great for reaching a diverse audience, they bring a touch of personal connection. But, remember, not all are fans of unsolicited calls. Face-to-Face Surveys: These are the heart-to-heart conversations of the survey world. While they require more resources, they're the gold standard for in-depth, high-quality data. As we journey further, let’s weigh the pros and cons of survey research. Advantages and disadvantages of survey research Every hero has its strengths and weaknesses, and survey research is no exception. Let's unwrap the gift box of survey research to see what lies inside. Advantages: Versatility: Like a superhero with multiple powers, surveys can be adapted to different topics, audiences, and research needs. Accessibility: With online surveys, geographical boundaries dissolve. We can reach out to the world from our living room. Anonymity: Like a confessional booth, surveys allow respondents to share their views without fear of judgment. Disadvantages: Response Bias: Ever met someone who says what you want to hear? Survey respondents can be like that too. Limited Depth: Like a puddle after a rainstorm, some surveys only skim the surface of complex issues. Nonresponse: Sometimes, potential respondents play hard to get, skewing the data. Survey research may have its challenges, but it also presents opportunities to learn and grow. As we forge ahead on our journey, we dive into the design process of survey research. Limitations of survey research Every research method has its limitations, like bumps on the road to discovery. But don't worry, with the right approach, these challenges become opportunities for growth. Misinterpretation: Sometimes, respondents might misunderstand your questions, like a badly translated novel. To overcome this, keep your questions simple and clear. Social Desirability Bias: People often want to present themselves in the best light. They might answer questions in a way that portrays them positively, even if it's not entirely accurate. Overcome this by ensuring anonymity and emphasizing honesty. Sample Representation: If your survey sample isn't representative of the population you're studying, it can skew your results. Aiming for a diverse sample can mitigate this. Now that we're aware of the limitations let's delve into the world of survey design. {loadmoduleid 430} Survey research design Designing a survey is like crafting a roadmap to discovery. It's an intricate process that involves careful planning, innovative strategies, and a deep understanding of your research goals. Let's get started. Approach and Strategy Your approach and strategy are the compasses guiding your survey research. Clear objectives, defined research questions, and an understanding of your target audience lay the foundation for a successful survey. Panel The panel is the heartbeat of your survey, the respondents who breathe life into your research. Selecting a representative panel ensures your research is accurate and inclusive. 9 Tips on Building the Perfect Survey Research Questionnaire Keep It Simple: Clear and straightforward questions lead to accurate responses. Make It Relevant: Ensure every question ties back to your research objectives. Order Matters: Start with easy questions to build rapport and save sensitive ones for later. Avoid Double-Barreled Questions: Stick to one idea per question. Offer a Balanced Scale: For rating scales, provide an equal number of positive and negative options. Provide a ‘Don't Know’ Option: This prevents guessing and keeps your data accurate. Pretest Your Survey: A pilot run helps you spot any issues before the final launch. Keep It Short: Respect your respondents' time. Make It Engaging: Keep your respondents interested with a mix of question types. Survey research examples and questions Examples serve as a bridge connecting theoretical concepts to real-world scenarios. Let's consider a few practical examples of survey research across various domains. User Experience (UX) Imagine being a UX designer at a budding tech start-up. Your app is gaining traction, but to keep your user base growing and engaged, you must ensure that your app's UX is top-notch. In this case, a well-designed survey could be a beacon, guiding you toward understanding user behavior, preferences, and pain points. Here's an example of how such a survey could look: "On a scale of 1 to 10, how would you rate the ease of navigating our app?" (Array question type) "How often do you encounter difficulties while using our app?" (Single choice - List radio question type) "What features do you use most frequently in our app?" (Multiple choice - Buttons question type) "What improvements would you suggest for our app?" (Multiple short text question type) "What features would you like to see in future updates?" (Long free text question type) This line of questioning, while straightforward, provides invaluable insights. It enables the UX designer to identify strengths to capitalize on and weaknesses to improve, ultimately leading to a product that resonates with users. Psychology and Ethics in survey research The realm of survey research is not just about data and numbers, but it's also about understanding human behavior and treating respondents ethically. Psychology: In-depth understanding of cognitive biases and social dynamics can profoundly influence survey design. Let's take the 'Recency Effect,' a psychological principle stating that people tend to remember recent events more vividly than those in the past. While framing questions about user experiences, this insight could be invaluable. For example, a question like "Can you recall an instance in the past week when our customer service exceeded your expectations?" is likely to fetch more accurate responses than asking about an event several months ago. Ethics: On the other hand, maintaining privacy, confidentiality, and informed consent is more than ethical - it's fundamental to the integrity of the research process. Imagine conducting a sensitive survey about workplace culture. Ensuring respondents that their responses will remain confidential and anonymous can encourage more honest responses. An introductory note stating these assurances, along with a clear outline of the survey's purpose, can help build trust with your respondents. Survey research software In the age of digital information, survey research software has become a trusted ally for researchers. It simplifies complex processes like data collection, analysis, and visualization, democratizing research and making it more accessible to a broad audience. LimeSurvey, our innovative, user-friendly tool, brings this vision to life. It stands at the crossroads of simplicity and power, embodying the essence of accessible survey research. Whether you're a freelancer exploring new market trends, a psychology student curious about human behavior, or an HR officer aiming to improve company culture, LimeSurvey empowers you to conduct efficient, effective research. Its suite of features and intuitive design matches your research pace, allowing your curiosity to take the front seat. For instance, consider you're a researcher studying consumer behavior across different demographics. With LimeSurvey, you can easily design demographic-specific questions, distribute your survey across various channels, collect responses in real-time, and visualize your data through intuitive dashboards. This synergy of tools and functionalities makes LimeSurvey a perfect ally in your quest for knowledge. Conclusion If you've come this far, we can sense your spark of curiosity. Are you eager to take the reins and conduct your own survey research? Are you ready to embrace the simple yet powerful tool that LimeSurvey offers? If so, we can't wait to see where your journey takes you next! In the world of survey research, there's always more to explore, more to learn and more to discover. So, keep your curiosity alive, stay open to new ideas, and remember, your exploration is just beginning! We hope that our exploration has been as enlightening for you as it was exciting for us. Remember, the journey doesn't end here. With the power of knowledge and the right tools in your hands, there's no limit to what you can achieve. So, let your curiosity be your guide and dive into the fascinating world of survey research with LimeSurvey! Try it out for free now! Happy surveying! {loadmoduleid 429}

Table Content

Survey research.

The world of research is vast and complex, but with the right tools and understanding, it's an open field of discovery. Welcome to a journey into the heart of survey research.

What is survey research?

Survey research is the lens through which we view the opinions, behaviors, and experiences of a population. Think of it as the research world's detective, cleverly sleuthing out the truths hidden beneath layers of human complexity.

Why is survey research important?

Survey research is a Swiss Army Knife in a researcher's toolbox. It’s adaptable, reliable, and incredibly versatile, but its real power? It gives voice to the silent majority. Whether it's understanding customer preferences or assessing the impact of a social policy, survey research is the bridge between unanswered questions and insightful data.

Let's embark on this exploration, armed with the spirit of openness, a sprinkle of curiosity, and the thirst for making knowledge accessible. As we journey further into the realm of survey research, we'll delve deeper into the diverse types of surveys, innovative data collection methods, and the rewards and challenges that come with them.

Types of survey research

Survey research is like an artist's palette, offering a variety of types to suit your unique research needs. Each type paints a different picture, giving us fascinating insights into the world around us.

Cross-Sectional Surveys: Capture a snapshot of a population at a specific moment in time. They're your trusty Polaroid camera, freezing a moment for analysis and understanding.
Longitudinal Surveys: Track changes over time, much like a time-lapse video. They help to identify trends and patterns, offering a dynamic perspective of your subject.
Descriptive Surveys: Draw a detailed picture of the current state of affairs. They're your magnifying glass, examining the prevalence of a phenomenon or attitudes within a group.
Analytical Surveys: Deep dive into the reasons behind certain outcomes. They're the research world's version of Sherlock Holmes, unraveling the complex web of cause and effect.

But, what method should you choose for data collection? The plot thickens, doesn't it? Let's unravel this mystery in our next section.

Survey research and data collection methods

Data collection in survey research is an art form, and there's no one-size-fits-all method. Think of it as your paintbrush, each stroke represents a different way of capturing data.

Online Surveys: In the digital age, online surveys have surged in popularity. They're fast, cost-effective, and can reach a global audience. But like a mysterious online acquaintance, respondents may not always be who they say they are.
Mail Surveys: Like a postcard from a distant friend, mail surveys have a certain charm. They're great for reaching respondents without internet access. However, they’re slower and have lower response rates. They’re a test of patience and persistence.
Telephone Surveys: With the sound of a ringing phone, the human element enters the picture. Great for reaching a diverse audience, they bring a touch of personal connection. But, remember, not all are fans of unsolicited calls.
Face-to-Face Surveys: These are the heart-to-heart conversations of the survey world. While they require more resources, they're the gold standard for in-depth, high-quality data.

As we journey further, let’s weigh the pros and cons of survey research.

Advantages and disadvantages of survey research

Every hero has its strengths and weaknesses, and survey research is no exception. Let's unwrap the gift box of survey research to see what lies inside.

Advantages:

Versatility: Like a superhero with multiple powers, surveys can be adapted to different topics, audiences, and research needs.
Accessibility: With online surveys, geographical boundaries dissolve. We can reach out to the world from our living room.
Anonymity: Like a confessional booth, surveys allow respondents to share their views without fear of judgment.

Disadvantages:

Response Bias: Ever met someone who says what you want to hear? Survey respondents can be like that too.
Limited Depth: Like a puddle after a rainstorm, some surveys only skim the surface of complex issues.
Nonresponse: Sometimes, potential respondents play hard to get, skewing the data.

Survey research may have its challenges, but it also presents opportunities to learn and grow. As we forge ahead on our journey, we dive into the design process of survey research.

Limitations of survey research

Every research method has its limitations, like bumps on the road to discovery. But don't worry, with the right approach, these challenges become opportunities for growth.

Misinterpretation: Sometimes, respondents might misunderstand your questions, like a badly translated novel. To overcome this, keep your questions simple and clear.

Social Desirability Bias: People often want to present themselves in the best light. They might answer questions in a way that portrays them positively, even if it's not entirely accurate. Overcome this by ensuring anonymity and emphasizing honesty.

Sample Representation: If your survey sample isn't representative of the population you're studying, it can skew your results. Aiming for a diverse sample can mitigate this.

Now that we're aware of the limitations let's delve into the world of survey design.

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Survey research design

Designing a survey is like crafting a roadmap to discovery. It's an intricate process that involves careful planning, innovative strategies, and a deep understanding of your research goals. Let's get started.

Approach and Strategy

Your approach and strategy are the compasses guiding your survey research. Clear objectives, defined research questions, and an understanding of your target audience lay the foundation for a successful survey.

The panel is the heartbeat of your survey, the respondents who breathe life into your research. Selecting a representative panel ensures your research is accurate and inclusive.

9 Tips on Building the Perfect Survey Research Questionnaire

Keep It Simple: Clear and straightforward questions lead to accurate responses.
Make It Relevant: Ensure every question ties back to your research objectives.
Order Matters: Start with easy questions to build rapport and save sensitive ones for later.
Avoid Double-Barreled Questions: Stick to one idea per question.
Offer a Balanced Scale: For rating scales, provide an equal number of positive and negative options.
Provide a ‘Don't Know’ Option: This prevents guessing and keeps your data accurate.
Pretest Your Survey: A pilot run helps you spot any issues before the final launch.
Keep It Short: Respect your respondents' time.
Make It Engaging: Keep your respondents interested with a mix of question types.

Survey research examples and questions

Examples serve as a bridge connecting theoretical concepts to real-world scenarios. Let's consider a few practical examples of survey research across various domains.

User Experience (UX)

Imagine being a UX designer at a budding tech start-up. Your app is gaining traction, but to keep your user base growing and engaged, you must ensure that your app's UX is top-notch. In this case, a well-designed survey could be a beacon, guiding you toward understanding user behavior, preferences, and pain points.

Here's an example of how such a survey could look:

This line of questioning, while straightforward, provides invaluable insights. It enables the UX designer to identify strengths to capitalize on and weaknesses to improve, ultimately leading to a product that resonates with users.

Psychology and Ethics in survey research

The realm of survey research is not just about data and numbers, but it's also about understanding human behavior and treating respondents ethically.

Psychology: In-depth understanding of cognitive biases and social dynamics can profoundly influence survey design. Let's take the 'Recency Effect,' a psychological principle stating that people tend to remember recent events more vividly than those in the past. While framing questions about user experiences, this insight could be invaluable.

For example, a question like "Can you recall an instance in the past week when our customer service exceeded your expectations?" is likely to fetch more accurate responses than asking about an event several months ago.

Ethics: On the other hand, maintaining privacy, confidentiality, and informed consent is more than ethical - it's fundamental to the integrity of the research process.

Imagine conducting a sensitive survey about workplace culture. Ensuring respondents that their responses will remain confidential and anonymous can encourage more honest responses. An introductory note stating these assurances, along with a clear outline of the survey's purpose, can help build trust with your respondents.

Survey research software

In the age of digital information, survey research software has become a trusted ally for researchers. It simplifies complex processes like data collection, analysis, and visualization, democratizing research and making it more accessible to a broad audience.

LimeSurvey, our innovative, user-friendly tool, brings this vision to life. It stands at the crossroads of simplicity and power, embodying the essence of accessible survey research.

Whether you're a freelancer exploring new market trends, a psychology student curious about human behavior, or an HR officer aiming to improve company culture, LimeSurvey empowers you to conduct efficient, effective research. Its suite of features and intuitive design matches your research pace, allowing your curiosity to take the front seat.

For instance, consider you're a researcher studying consumer behavior across different demographics. With LimeSurvey, you can easily design demographic-specific questions, distribute your survey across various channels, collect responses in real-time, and visualize your data through intuitive dashboards. This synergy of tools and functionalities makes LimeSurvey a perfect ally in your quest for knowledge.

If you've come this far, we can sense your spark of curiosity. Are you eager to take the reins and conduct your own survey research? Are you ready to embrace the simple yet powerful tool that LimeSurvey offers? If so, we can't wait to see where your journey takes you next!

In the world of survey research, there's always more to explore, more to learn and more to discover. So, keep your curiosity alive, stay open to new ideas, and remember, your exploration is just beginning!

We hope that our exploration has been as enlightening for you as it was exciting for us. Remember, the journey doesn't end here. With the power of knowledge and the right tools in your hands, there's no limit to what you can achieve. So, let your curiosity be your guide and dive into the fascinating world of survey research with LimeSurvey! Try it out for free now!

Happy surveying!

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Survey Research: Definition, Methods, Examples, and More

Table of Contents

What is Survey Research?

Survey research, as a key research method of marketing research, is defined as the systematic collection and analysis of data gathered from respondent feedback through questionnaires or interviews. This primary research method is designed to gather information about individuals' opinions, behaviors, or characteristics through a series of questions or statements.

The evolution of survey research in market research has been profound, transitioning from paper-based questionnaires posted randomly to respondent’s homes to sophisticated online platforms that offer much more convenient ways to reach the desired audience. Its importance lies not just in the breadth of data it can collect but in the depth of understanding it provides, allowing researchers and businesses alike to tap into the psyche of their target audience.

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Reasons for Conducting Survey Research

The reasons for conducting survey research are as diverse as the questions it seeks to answer, yet they all converge on a common goal: to inform decision-making processes. Here's why survey research is pivotal:

Honest Feedback and Insights: Survey research offers a platform for respondents to provide candid feedback on products, services, or policies, providing businesses with critical insights into consumer satisfaction and areas for improvement.
Privacy and Anonymity Benefits: By ensuring respondent anonymity, surveys encourage honest and uninhibited responses, leading to more accurate and reliable data.
Providing a Platform for Criticism and Improvement Suggestions: Surveys open up a dialogue between businesses and their clientele, offering a structured way for criticism and suggestions to be voiced constructively.
Iterative Feedback Loops: The iterative nature of survey research, with its ability to be conducted periodically, helps businesses track changes in consumer behavior and preferences over time, enabling continuous improvement and adaptation. This ongoing dialogue facilitated by survey research not only enriches the business-consumer relationship but also fosters an environment of continuous learning and improvement, ensuring that businesses remain agile and responsive to the evolving needs and expectations of their target audience.

A woman sitting on a couch taking a phone call. Representing phone interviews (one of the survey research types)

Types of Survey Research Methods & Data Collection Methods

In the world of survey research a range of methods each offer unique advantages tailored to a researcher or businesses specific research goals.

Email Surveys

Email surveys represent a modern approach to data collection, utilizing email addresses stored on client databases to distribute questionnaires. This method is particularly appealing for its cost-effectiveness and efficiency, as it minimizes the financial expenditure associated with other methods. However, many businesses only hold email addresses relating to their current customer base, meaning that any studies performed using this approach will be limited in scope.

Online Panels

Online panels represent the most convenient form of online research. Panel companies source a wide variety of potential respondents which are available for any company to survey on a cost-per-interview (CPI) basis. However, this convenience comes with drawbacks as online panels are known for having potential data quality issues which are likely to impact the results of your survey if not guarded against.

Phone Surveys (CATI)

Computer Assisted Telephone Interviewing (CATI) combines the efficiency of computer-guided surveys with the personal touch of telephone communication. This method is advantageous for its ability to cover wide populations, including those in remote areas, ensuring a broader demographic reach. The direct interaction between the interviewer and respondent can also enhance response rates and clarity on questions. However, personal engagement comes at a cost, making CATI more time-consuming and expensive than online methods.

Face-to-Face Interviews

The most traditional method, face-to-face interviews, involves direct, in-person interaction between the interviewer and the respondent. This approach is highly valued for its high response rates and the depth of insight it can provide, including non-verbal cues that offer additional layers of understanding. Although this method is resource-intensive, requiring significant investment in trained personnel and logistics, the quality of data obtained can be unmatched.

Survey Research Timeframe Methods

Longitudinal Survey Research tracks the same group of respondents over time, offering invaluable insights into trends and changes in behaviors or attitudes. This method is ideal for observing long-term patterns, such as the impact of societal changes on individual behaviors.

Cross-sectional / Ad-hoc Survey Research provides a snapshot of a population at a specific point in time, making it perfect for capturing immediate insights across various demographics. This method's versatility is showcased in applications ranging from consumer satisfaction surveys to public opinion polls, where understanding the current state of affairs is crucial.

Each of these survey research methods brings its own strengths to the table, allowing researchers to tailor their approach to the specific nuances of their study objectives. By selecting the method that best aligns with their goals, researchers can maximize the effectiveness of their data collection efforts, paving the way for impactful insights and informed decision-making.

Uses and Examples of Survey Research

Survey research's versatility allows it to be applied across a myriad of fields, offering insights that drive decision-making and strategic planning. Its applications range from gauging public opinion and consumer preferences to evaluating the effectiveness of policies and programs.

Marketing Research

In marketing research, survey research is pivotal in understanding consumer behavior, preferences, and satisfaction levels. For example, a retail company may conduct online surveys to determine customer satisfaction with its products and services. The feedback collected can highlight areas of success and identify opportunities for improvement, guiding the company in refining its offerings and enhancing the customer experience.

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Political Polling

Political polling represents another significant application of survey research, providing insights into voter attitudes, preferences, and likely behaviors. These surveys can influence campaign strategies, policy development, and understanding of public sentiment on various issues. A notable instance is the use of survey research during electoral campaigns to track the popularity of candidates and the effectiveness of their messages.

Public Health Research

Public health studies frequently utilize survey research to assess health behaviors, awareness of health issues, and the impact of health interventions. For example, a cross-sectional survey might be conducted to evaluate the effectiveness of a public health campaign aimed at reducing smoking rates. The data gathered can inform health officials about the campaign's impact and guide future public health strategies.

Educational Research

Educational research also benefits from survey methods, with studies designed to evaluate educational interventions, student satisfaction, and learning outcomes. For instance, longitudinal surveys can track students' academic progress over time, providing insights into the effectiveness of educational programs and interventions.

These examples underscore the adaptability of survey research, enabling tailored approaches to collecting and analyzing data across various sectors. Its capacity to yield actionable insights makes it an invaluable tool in the pursuit of knowledge and improvement.

Advantages and Disadvantages

Survey research is a powerful tool in the arsenal of researchers, offering numerous advantages while also presenting certain challenges that must be navigated carefully.

Advantages of Survey Research

Cost-Effectiveness: Survey research is often more affordable than other data collection methods, especially beneficial when targeting large populations.
Large Sample Sizes: It enables the collection of data from a large sample size (audience), enhancing the generalizability of findings.
Flexibility in Design: Surveys allow for customization in question formats, delivery methods, and structure, tailoring the approach to specific research needs.
Ease of Administration: With options for online, mail, phone, and in-person surveys, administration can be adapted to best reach the target audience.
Efficient Data Analysis: The quantitative nature of survey responses facilitates straightforward analysis using statistical software, aiding in the quick identification of trends and insights.

Disadvantages of Survey Research

Response Bias: The potential for respondents to provide socially desirable answers rather than truthful ones can lead to biased data .
Sampling Issues: Challenges such as non-response bias and difficulty in reaching certain populations can compromise the representativeness of the sample.
Questionnaire Design Challenges: Crafting questions that are clear and unbiased while avoiding ambiguity is complex and can impact the validity of the results.
Lack of Response Context: Surveys may not capture the nuances behind responses, limiting understanding of the reasons behind certain behaviors or opinions.
Time and Resource Constraints: Designing, administering, and analyzing surveys can be resource-intensive, potentially limiting their scope and depth.
Data Quality: The rise of survey panels has increased the likelihood of either poor quality responses, or even automated bots, affecting survey results.

Understanding these advantages and disadvantages is crucial for researchers as they design and implement survey research studies. By carefully considering these factors, it is possible to leverage the strengths of survey research while mitigating its limitations, ensuring the collection of valuable and actionable insights.

Survey Research Design Process

The design and execution of survey research involve several critical steps, each contributing to the overall quality and reliability of the findings. By following a structured process, researchers can ensure that their survey research effectively meets its objectives.

Define Survey Research Objectives: The first step involves clearly defining what you aim to achieve with your survey. Objectives should be specific, measurable, achievable, relevant, and time-bound (SMART). This clarity guides the subsequent steps of the survey design process.
Identify Your Target Audience: Knowing who you need to survey is crucial. The target audience should align with the research objectives, ensuring that the data collected is relevant and insightful.
Select the Appropriate Method: Based on the objectives and the target audience, choose the most suitable survey method. Consider factors such as budget, time constraints, and the need for depth vs. breadth of data.
Plan and Execute the Study: This involves crafting the survey questionnaire, deciding on the distribution method (online, mail, phone, face-to-face), and determining the timeline for data collection. Ensuring questions are clear, unbiased, and relevant is critical to gathering valuable data.
Analyze Data and Make Decisions: Once data collection is complete, analyze the responses to identify trends, patterns, and insights. Use statistical software for quantitative analysis and consider qualitative methods for open-ended responses. The findings should inform decision-making processes, guiding strategic planning and interventions.

By following these steps, researchers can maximize the effectiveness and reliability of their survey research, paving the way for meaningful insights and informed decision-making.

Sampling Methods in Survey Research

A crucial aspect of survey research is selecting a representative sample from the target population . The sampling method plays a significant role in the quality and generalizability of the research findings. There are two main types of sampling methods: probability sampling and non-probability sampling.

Probability Sampling: This method ensures every member of the target population has a known and equal chance of being selected. Types of probability sampling include simple random sampling, stratified random sampling, and cluster sampling. This method is preferred for its ability to produce representative samples, allowing for generalizations about the population from the sample data.
Non-Probability Sampling: In non-probability sampling, not every member of the population has a known or equal chance of selection. This category includes convenience sampling, quota sampling, and purposive sampling. While less rigorous than probability sampling, non-probability methods are often used when time and resources are limited or when specific, targeted insights are required.

Choosing the right sampling method is critical to the success of survey research. For example, a market research firm aiming to understand consumer preferences across different demographics might use stratified random sampling to ensure that the sample accurately reflects the population's diversity. Conversely, a preliminary study exploring a new phenomenon might opt for convenience sampling to quickly gather initial insights.

Understanding the strengths and limitations of each sampling method allows researchers to make informed choices, balancing rigor with practical constraints to best achieve their research objectives.

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Survey research provides invaluable insights across diverse fields, from consumer behavior to public policy. Its flexibility, cost-effectiveness, and broad reach make it an indispensable tool for researchers aiming to gather actionable data. Despite its challenges, such as response bias and sampling complexities, careful design and methodological rigor can mitigate these issues, enhancing the reliability and validity of findings.

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Ann R Coll Surg Engl
v.95(1); 2013 Jan

A quick guide to survey research

1 University of Cambridge,, UK

2 Cambridge University Hospitals NHS Foundation Trust,, UK

Questionnaires are a very useful survey tool that allow large populations to be assessed with relative ease. Despite a widespread perception that surveys are easy to conduct, in order to yield meaningful results, a survey needs extensive planning, time and effort. In this article, we aim to cover the main aspects of designing, implementing and analysing a survey as well as focusing on techniques that would improve response rates.

Medical research questionnaires or surveys are vital tools used to gather information on individual perspectives in a large cohort. Within the medical realm, there are three main types of survey: epidemiological surveys, surveys on attitudes to a health service or intervention and questionnaires assessing knowledge on a particular issue or topic. 1

Despite a widespread perception that surveys are easy to conduct, in order to yield meaningful results, a survey needs extensive planning, time and effort. In this article, we aim to cover the main aspects of designing, implementing and analysing a survey as well as focusing on techniques that would improve response rates.

Clear research goal

The first and most important step in designing a survey is to have a clear idea of what you are looking for. It will always be tempting to take a blanket approach and ask as many questions as possible in the hope of getting as much information as possible. This type of approach does not work as asking too many irrelevant or incoherent questions reduces the response rate 2 and therefore reduces the power of the study. This is especially important when surveying physicians as they often have a lower response rate than the rest of the population. 3 Instead, you must carefully consider the important data you will be using and work on a ‘need to know’ rather than a ‘would be nice to know’ model. 4

After considering the question you are trying to answer, deciding whom you are going to ask is the next step. With small populations, attempting to survey them all is manageable but as your population gets bigger, a sample must be taken. The size of this sample is more important than you might expect. After lost questionnaires, non-responders and improper answers are taken into account, this sample must still be big enough to be representative of the entire population. If it is not big enough, the power of your statistics will drop and you may not get any meaningful answers at all. It is for this reason that getting a statistician involved in your study early on is absolutely crucial. Data should not be collected until you know what you are going to do with them.

Directed questions

After settling on your research goal and beginning to design a questionnaire, the main considerations are the method of data collection, the survey instrument and the type of question you are going to ask. Methods of data collection include personal interviews, telephone, postal or electronic ( Table 1 ).

Advantages and disadvantages of survey methods

Method of data collection	Advantages	Disadvantages
Personal	• Complex questions	• Expensive
	• Visual aids can be used	• Time inefficient
	• Higher response rates	• Training to avoid bias
Telephone	• Allows clarification	• No visual aids
	• Larger radius than personal	• Difficult to develop rapport
	• Less expensive or time consuming
	• Higher response rates
Postal	• Larger target	• Non-response
	• Visual aids (although limited)	• Time for data compilation
	• Lower response rates
Electronic	• Larger target	• Non-response
	• Visual aids	• Not all subjects accessible
	• Quick response
	• Quick data compilation
	• Lower response rates

Collected data are only useful if they convey information accurately and consistently about the topic in which you are interested. This is where a validated survey instrument comes in to the questionnaire design. Validated instruments are those that have been extensively tested and are correctly calibrated to their target. They can therefore be assumed to be accurate. 1 It may be possible to modify a previously validated instrument but you should seek specialist advice as this is likely to reduce its power. Examples of validated models are the Beck Hopelessness Scale 5 or the Addenbrooke’s Cognitive Examination. 6

The next step is choosing the type of question you are going to ask. The questionnaire should be designed to answer the question you want answered. Each question should be clear, concise and without bias. Normalising statements should be included and the language level targeted towards those at the lowest educational level in your cohort. 1 You should avoid open, double barrelled questions and those questions that include negative items and assign causality. 1 The questions you use may elicit either an open (free text answer) or closed response. Open responses are more flexible but require more time and effort to analyse, whereas closed responses require more initial input in order to exhaust all possible options but are easier to analyse and present.

Questionnaire

Two more aspects come into questionnaire design: aesthetics and question order. While this is not relevant to telephone or personal questionnaires, in self-administered surveys the aesthetics of the questionnaire are crucial. Having spent a large amount of time fine-tuning your questions, presenting them in such a way as to maximise response rates is pivotal to obtaining good results. Visual elements to think of include smooth, simple and symmetrical shapes, soft colours and repetition of visual elements. 7

Once you have attracted your subject’s attention and willingness with a well designed and attractive survey, the order in which you put your questions is critical. To do this you should focus on what you need to know; start by placing easier, important questions at the beginning, group common themes in the middle and keep questions on demographics to near the end. The questions should be arrayed in a logical order, questions on the same topic close together and with sensible sections if long enough to warrant them. Introductory and summary questions to mark the start and end of the survey are also helpful.

Pilot study

Once a completed survey has been compiled, it needs to be tested. The ideal next step should highlight spelling errors, ambiguous questions and anything else that impairs completion of the questionnaire. 8 A pilot study, in which you apply your work to a small sample of your target population in a controlled setting, may highlight areas in which work still needs to be done. Where possible, being present while the pilot is going on will allow a focus group-type atmosphere in which you can discuss aspects of the survey with those who are going to be filling it in. This step may seem non-essential but detecting previously unconsidered difficulties needs to happen as early as possible and it is important to use your participants’ time wisely as they are unlikely to give it again.

Distribution and collection

While it should be considered quite early on, we will now discuss routes of survey administration and ways to maximise results. Questionnaires can be self-administered electronically or by post, or administered by a researcher by telephone or in person. The advantages and disadvantages of each method are summarised in Table 1 . Telephone and personal surveys are very time and resource consuming whereas postal and electronic surveys suffer from low response rates and response bias. Your route should be chosen with care.

Methods for maximising response rates for self-administered surveys are listed in Table 2 , taken from a Cochrane review.2 The differences between methods of maximising responses to postal or e-surveys are considerable but common elements include keeping the questionnaire short and logical as well as including incentives.

Methods for improving response rates in postal and electronic questionnaires 2

Postal	Electronic
Monetary or non-monetary incentives	Non-monetary incentives
Teaser on the envelope	Personalised questionnaires
Pre-notification	Include pictures
Follow-up with another copy included	Not including ‘survey’ in subject line
Handwritten addresses	Male signature
University sponsorship	White background
Use recorded delivery	Short questionnaire
Include return envelope	Offer of results
Avoid sensitive questions	Statement that others have responded

– Involve a statistician early on.
– Run a pilot study to uncover problems.
– Consider using a validated instrument.
– Only ask what you ‘need to know’.
– Consider guidelines on improving response rates.

The collected data will come in a number of forms depending on the method of collection. Data from telephone or personal interviews can be directly entered into a computer database whereas postal data can be entered at a later stage. Electronic questionnaires can allow responses to go directly into a computer database. Problems arise from errors in data entry and when questionnaires are returned with missing data fields. As mentioned earlier, it is essential to have a statistician involved from the beginning for help with data analysis. He or she will have helped to determine the sample size required to ensure your study has enough power. The statistician can also suggest tests of significance appropriate to your survey, such as Student’s t-test or the chi-square test.

Conclusions

Survey research is a unique way of gathering information from a large cohort. Advantages of surveys include having a large population and therefore a greater statistical power, the ability to gather large amounts of information and having the availability of validated models. However, surveys are costly, there is sometimes discrepancy in recall accuracy and the validity of a survey depends on the response rate. Proper design is vital to enable analysis of results and pilot studies are critical to this process.

7 Types of Survey Research Methods & When to Use Them

You rely on data in business for a simple reason; it helps you make informed decisions. The more information you have, up to a point, the higher the chance you’ll make the right decision. You can apply that simple insight of more information equals smarter decision-making to marketing, customer service, product development, or any other sector of your business.

There are many ways to gather data for your business. Too many to cover comprehensively in a single article, that’s for sure!

This guide will focus on several survey research methods. You’ll discover the pros and cons of each approach and learn the best time to use them in your outreach strategy.

In this article

1. Online surveys

2. in-person surveys, 3. focus groups, 4. panel sampling, 5. telephone surveys, 6. mail-in survey, 7. kiosk surveys, it’s time to get some feedback.

Online surveys are probably the most popular and widely used research method, certainly by small and medium-sized businesses. The main benefits of online surveys are threefold:

Easy to run: there are lots of online survey platforms available. That gives you plenty of freedom to design an interesting survey and embed it however and to an extent, wherever you want.
Easy to Analyze: the same software platforms will present the data nicely. That’s great for presenting your findings and analyzing the results.
Cheap or almost free: you can run an online survey on a tiny budget. Assuming you have an email list or a site with lots of visitors, you should get respondents.

Lowering the cost and barrier to entry means many businesses manage online surveys independently. That’s a good thing. Below is an example of what an online survey may look like:

Customer Feedback Template Example – Woorise

If you decide to run an online survey independently, take the time to research proper data collection methods. That’s a general thing to keep in mind for any survey research method on this list.

While online surveys are great, they do have their limitations. One of the biggest issues you’ll have is getting people to fill out your survey. Adding a survey to your site without context will result in a low number of respondents.

Ideally, you need to funnel people to your survey.

When asking people to fill in an online survey, you should always:

Explain the benefits for the respondent
Share how long it will take to complete
Share a link to your survey

If you find it difficult to run your online survey independently, you can always turn to a consulting company to run it for you. Alternatively, there are sites where you can list your survey for free or pay the business for a certain number of respondents.

Overall, online interviews are a great way to get a sense of market or customer sentiment.

It’s important to note that acting and making changes in your processes and products based on data you collect from surveys is one of the things most companies running surveys forget to do. According to a recent study only 17% of companies act on customer insights they collect.

Don’t forget to actually make changes or draw conclusions based on the data you work so hard to collect.

If you want a more personal approach, try the face-to-face survey. Face-to-face interviews are a great survey research method. They are a good way to gain deep insights from the respondent rather than general insights into market trends.

With a face-to-face survey, it’s easier to gain an overall impression of the respondent.

You can pick up things from the tone of voice and facial expressions. You’re also more likely to get longer answers, plus you get to ask follow-up questions. Finally, with each survey you conduct, you’ll gain insights into how to improve your approach for the next time.

As with each of the survey research methods on this list, there are limitations to face-to-face surveys. The most obvious problem is the sample size. The more face-to-face surveys you do, the more time it will take you and the more expensive the research will become.

Another issue you’ll run into is keeping track of responses and analyzing data. Whereas online surveys track everything for you automatically, you’ll need to do this manually with in-person surveys. If you bring a tablet with you to your interviews, you can use Google Sheets as a database for tracking qualitative and quantitative responses and then visualize that data using Sheets’ charts and graphs features.

If your sample is highly targeted, consider using face-to-face surveys. For instance, such surveys might be the better option if you want to determine your staff’s perception of your brand. But if you want to know your customers’ perception of your brand, online surveys may be your best bet since that’s a larger sample.

A focus group is a small group of people you get together to discuss a particular topic or a product. One group typically has five to ten people. The discussion is often facilitated by a moderator who gauges the group’s reaction and collects responses.

If you want to run a focus group, you should make sure your moderator will remain neutral throughout the discussions. They shouldn’t ask leading questions that may influence the answers of members of the group.

But how can you ensure the neutrality of your moderator if humans are inherently biased? You can’t. But you can at least make them act like they are during focus group discussions for the sake of the study. Brief them and make them understand your research goal. The person you assign to be a moderator should also have the following traits and characteristics:

They can listen attentively with sensitivity.
They are someone members of the group can relate to but at the same time, someone who exudes authority. For example, a male moderator is more appropriate if members of the group are males discussing sexual harassment in the workplace.
They have adequate knowledge of the topic being discussed.
They believe everyone has something to offer in the discussion.

Focus groups are one of the more expensive research methods. Companies typically pay $400 to $600 to each participant. Then there’s the amount you pay a trained moderator should you decide to hire one.

Focus groups can be hard to organize. You need to collect a group of people together and get them in one place. Though, video conferencing tools like Zoom or Whereby mean you can run a focus group remotely nowadays.

Focus groups are great for getting detailed impressions from a representative group. If you want to look at customer behavior, attitudes, and even at perceptions of processes, this is a great method for you.

You don’t need to be an offline company to use a focus group.

Fact of the day for you: Twitter used focus groups to come up with their platform. From the focus group discussions, they found people didn’t like Facebook’s cluttered news feed. They used that insight to come up with a more streamlined news feed for Twitter.

Panel sampling involves randomly choosing a group of people to be part of a panel that takes part in a study over time. Panel samples allow researchers to study changes within the population, your customer base, or changes in individual people.

Companies, for instance, use them to generate qualitative data on customer experience as the product develops over time. If you want to track customer happiness over time, you can use panel sampling as well.

Panel sampling is a research method used more by sociologists than businesses. One of the major problems with panel sampling is attrition. It’s hard to keep the same people involved in your study over a period of months, or potentially longer.

Then there’s the fact that members of a panel tend to stick to the attitude or position they showed or expressed right from the start. So, they can end up misrepresenting the general population which they were supposed to represent in the first place. The general public’s attitudes and opinions, after all, are more likely to change over time because of external and internal factors.

Telephone interviews are a popular and widely used survey research method. Here are three good reasons why companies use telephone surveys:

Targeting: you can run surveys targeting a particular demographic of a population
Sample Size: it’s possible to gather a lot of data in a short time period
Cost: it’s affordable. Assuming you have access to relevant contact information

Telephone surveys are often used to gauge customer satisfaction or get a sense of trends. They’re effective because they combine some of the automated benefits of online surveys with some of the personal benefits of in-person surveys.

If you see a poll by Pew, Gallup, or any other big polling firms, there’s a good chance that the data was gathered from telephone surveys. Telephone polling is used a lot all over the world around elections.

If you have an idea for an interesting study, it could be worth contacting a polling company to conduct some research for you. A good study with some interesting insights could be the hook you need for a good PR story.

Thanks to Voice over IP (VoIP) technology, it’s a lot cheaper to run telephone surveys than it used to be. All you need is a VoIP phone service with features like call recording, call queues, and call routing. With that said, if you don’t have the in-house manpower to run a phone survey yourself, you’ll probably want to look at outsourcing this to an agency with a VoIP system and a proven track record.

Mail-in surveys are mailed to respondents by post. They’re relatively inexpensive, and you can target a large geographical area. According to the National Public Research , a medium-scale mail survey can cost at least $5,000. That’s far less than the $10,000 to $15,000 you’ll need at the very least for a telephone survey, for example.

Response rates for mail-in surveys are also surprisingly high compared to other survey research methods. According to the latest benchmark report on surveys, mail-in surveys have a response rate of 50%. It just goes to show that you shouldn’t overlook traditional marketing channels.

The high response rates may have to do with the fact that respondents can answer the survey at their own pace. Because respondents more or less have all the time in the world, they can give comprehensive answers to the questions. They can be honest with their opinions as well since people are typically more comfortable expressing what they think and feel in writing.

With mail-in surveys, however, follow-up questions are not possible. That’s why your questionnaire design should be good from the get-go. If your questions were vague from the start, and you didn’t get the answers you needed, you’ll have just wasted your time and effort in administering the survey. You’ll have wasted the respondent’s time, too.

The final and more niche option for gathering survey feedback is by using a kiosk survey. This is a survey on a computer screen located in physical locations such as offices, stores, lobbies, and hospitals. Kiosk survey research gathers instant feedback for a product or service.

Kiosk surveys are a good way to connect with local shoppers and residents. If you run a local business, it might be worth investing in this survey research method. It’s one way to get real-time feedback from your customers about their experience with your brand. You can then use the results of your survey to make the necessary adjustment to your strategies.

These types of surveys are becoming more and more popular at networking and business conferences. For example, a brand may set up a kiosk survey at their booth to gather reviews for their G2 or Capterra profiles.

This article reviewed the seven types of survey research methods. The survey research methods range from online surveys to face-to-face interviews and mail-in surveys. Each of these research methods has its advantages and disadvantages.

Ultimately, the method you choose depends on your desired outcome and budget constraints.

Consider using a combination of survey methods for more accurate data, too. For instance, if you want to determine qualitative and quantitative data on customer satisfaction, the telephone interview will work well with an online survey. Just determine your goals and the resources you have at your disposal.

Pick that perfect combination that will generate the data you need to inform your business decisions. Your company will then be well on its way to success.

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Christopher Vasiliou

Christopher is the founder of Woorise , a marketing platform to create landing pages, forms, surveys, social promotions and more. An Adobe certified expert with 20+ years experience in marketing, web design, development and photography. When he is not in front of a screen he enjoys traveling, running and cooking.

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Market Research Surveys
What is market research survey

Why use surveys?

Survey research methods.

Conducting market research surveys
Common mistakes with market research surveys?

The different types of survey methods

Survey tools for your survey method, what can businesses do with these types of surveys, how to write a research survey (free example templates), try qualtrics for free, types of market research surveys.

20 min read There are different types of survey research you can run, but the majority of research is conducted with just a handful of research survey methods. We explore what they are and how to use them.

What is a market research survey?

A market research survey is a way of getting feedback directly from the people who have the ultimate say in your organization’s success: your customers.

Unlike focus groups or interviews, market research surveys allow you to get detailed feedback at scale — from behaviors to overall experiences — and in a standardized format. Also, as the data is easy to process, you can quickly turn it into actionable insights .

Surveys are used to collect primary research, which means market research data that you collect yourself. The other type is secondary data, which is obtained from other sources, for example census data.

Surveys are among the most popular methods of primary market research, since they can be used to gather qualitative and quantitative research on market trends, and they can cover a huge range of respondents across your customer base. They’re also a format familiar to many people.

Get started with our free survey software

Surveys are ultimately about understanding your target audience, but they can go beyond your customer base. They can be taken by anyone — employees, potential future customers, and even those who don’t want to engage with your business (helping you to identify the ones that do).

However, a survey isn’t a stand-alone solution. It can work alongside other survey methods, such as focus groups, field studies, observation, and market analysis, to help you get a clear picture of your market and decide what direction to take.

But with all these different types of survey methods, and some being better than others in specific areas (e.g. data quality, collecting feedback), where should you start?

To get the best out of each survey research type, consider what you can invest in terms of:

Time: How quickly do you need the survey research? Do you have time to conduct research?
Money: Do you have the budget to invest in research overheads?
Knowledge of analytics: Are you trained to interpret the collected data? If not, do you have a partner you can work with to get the insights you need?
Research expertise: Do you have clearly defined problems or challenges that you want to explore or understand through surveys?
Technology capability: Is your survey software up to the task of analyzing the data?
Your audience’s response: Is it likely that your audience will respond? What survey types (online surveys, etc.) would they be most receptive to?
Slow responses: Do you have a strategy in place to avoid low response rates?

Conducting market research surveys: best practices

Today’s market research industry is advancing rapidly, thanks in part to new technologies which make it easier to conduct market research, and offer more power and sophistication when it comes to analyzing your data.

Data-driven research is the standard across market research and other disciplines, and within the sector competition between brands is driving progress towards better and better market research tools. Beyond customer satisfaction, demographic questions and competitive analysis, today’s tools can dive deeper into your data, unearthing key drivers behind trends and even providing aggregated data on emotions and attitudes in customer feedback.

However, none of these technological advances can replace humans. To conduct market research successfully, you need to be able to combine tech with insight, intelligence and intuition, especially when you’re dealing directly with target customers, for example during a phone interview or when you’re approaching existing customers whose relationship to your brand needs to be maintained.

As we’ll see in this guide, market research can be used in a huge range of contexts, including brand tracking, customer experience research, employee experience programs, and of course product development. Whichever application you’re looking at, it’s essential to prepare thoroughly before sending out your surveys.

Make sure your research question has been formulated and agreed by everyone involved in the project
Develop a communications plan to maximize the chances of people engaging with your survey, including introductions, publicity, reminders and follow-up
Consider using pre-testing before you fully launch your survey to thoroughly road-test it and iron out any issues
Close the loop – after the study is complete and actions have been taken, let participations know how their contribution helped
Consider a research panel for future surveys, either one you’ve built yourself or one managed by a third party provider

What are some common mistakes with market research surveys?

With the right survey tools and appropriate support from your survey platform provider, everything should go smoothly, even if you’re not an expert at doing your own market research. However, there are a few things to watch out for.

Choosing the wrong people to survey

Figuring out who you’re going to survey in the first place may seem like an obvious first step and not one you need to spend much time on. But in fact it’s possible to get it wrong, survey the wrong people and end up running a market research study with unreliable data. This is sometimes called ‘sample framing error’

Getting your sample size wrong

If your sample is too small, you run the risk of getting a sample group that doesn’t adequately reflect your target population. This can throw your entire market research survey off course. But if the sample is too large, you spend time and money on research that doesn’t add significant value. Have a look at our sample size calculator to help determine the right sample size for your market research surveys.

Using the wrong kinds of analysis

Do you know your conjoint analysis from your T-test? Understanding the basic types of statistical tests you can use to analyze market research survey data is essential if you’re not using a survey tool with built-in analytics. You’ll need to match the kind of data you’re collecting to the analysis method you choose in order to get accurate insights from your market research surveys.

Writing confusing survey questions

Survey questions aren’t like the questions we use in everyday speech, or even like the ones we ask in formal writing. They need to be highly specific, include appropriate context, and be free of any kind of descriptive or persuasive element that might introduce bias. For a primer on writing great market research survey questions, see our guide to great survey questions

You should choose your survey method based on your target audience, distribution capabilities, and the questions you want answered. For example, interviews are far more personal and explorative by nature, but they’re difficult and costly to scale. Online surveys, on the other hand, have far greater reach and much more affordable — but you lose the opportunity to connect with respondents. Let’s go through the different types and how you can use them.

Online surveys

Online surveys are accessible to any participant across the globe, providing they have an internet connection. You can create online surveys using survey platforms and distribute them via email using a link, or respondents can go directly to the online survey and complete it.

Paper surveys

Paper surveys (or written surveys) are printed surveys filled in by hand. This method works well if respondents have enough time (and incentive) to complete the survey, and the researcher is happy to manually collect the data before collating and interpreting the answers.

Mail surveys

Mail surveys provide exceptional geographical coverage as they can be printed off and sent via the post. However, as recipients need to return the surveys for counting, it’s recommended that you include a pre-paid returns envelope in the original envelope, otherwise you’ll have lower response rates.

Telephone surveys

Telephone surveys involve asking respondents a series of questions over the phone. It’s a popular survey method as it’s convenient for researchers and doesn’t require a lot of capital to do. However, researchers may need to invest time to set up interviews with participants and take notes during the process.

In-person interviews / face-to-face surveys

In-person interviews and face-to-face surveys are great opportunities to get more insightful and valuable responses from participants. You can quickly find out why they think and feel the way that they do, providing an unbiased view of a subject or issue. However, like telephone surveys, they require a lot of time to set up and gather data.

Panel surveys

Panel surveys use a pre-selected group of people as the sample, so that the research can be carried out quickly. It presents a happy medium between the speed and quality of research data.

Based on the type of survey method you choose, here are the types of tools you need and can use for each:

A good internet connection is required for participants to access online surveys, though mobile devices data plans mean that most people can connect to the internet easily.

A good survey software platform is needed to give you full functionality and flexibility, so your online surveys can be customized and optimized. However, businesses can get more for their money with a survey software system that does more for the company.

For example, the Qualtrics XM Platform™ is a best-of-breed experience operating system for experience management. It brings all your operational and experience data together from across the organization to help create and improve experiences for employees, customers, prospects and more. It automatically updates records, has an in-built analytics engine and can handle research projects, from start to finish, in a few clicks.

All you need are paper, ink, pens and clipboards — but due to environmental and sustainability concerns, particularly paper waste and ink pollution, you may want to opt for a more digitized solution.

For mail surveys, the resources and concerns are the same as with paper surveys — but the main difference is distribution.

Ultimately, you need a reliable postal service that can deliver to your target audience. It also becomes costly if you want to include international respondents.

As long as you have good connectivity and network coverage, telephone surveys are straightforward. That said, survey calls can last a long time, so if you plan to include international audiences, ensure you can afford the calling costs.

The only requirement for in-person interviews and face-to-face surveys is a venue to hold them in.

These require participants to be available at the time of the research. Traditionally, third-party generated research panels are available as a service to companies that don’t have access to the audiences they need.

The surveys we explored can be used for four purposes in any business:

1. Market surveys

These help you understand who’s out there, what they want, and how you can best meet their needs.

Market description surveys

Purpose: to determine the size and relative market share of the market. Such studies provide key information about market growth, competitive positioning, and tracking share of the market .

Market profiling / segmentation surveys

Purpose: to identify who the customers are , who they are not, and why they are or are not your customers. This is often a descriptive market segmentation and market share analysis.

Stage in the purchase process / tracking surveys

Where is the customer in the adoption process? This information shows Market Awareness – Knowledge – Intention – Trial – Purchase – Repurchase of the product.

2. Customer experience surveys

This kind of survey helps you put yourself in the customer’s shoes and look at your business from their perspective.

Customer intention – purchase analysis surveys

Purpose: Directed at understanding the current customer. What motivates the customer to move from interest in the product to actual purchase? This is key to understanding customer conversion, commitment, and loyalty .

Customer attitudes and expectations surveys

Purpose: Used to direct advertising and improve customer conversion, commitment, and loyalty. Does the product meet customer expectations ? What attitudes have customers formed about the product and/or company?

Learn how you can set up and run customer attitudes and use surveys

Sales lead generation surveys

Purpose: Sales lead generation surveys are for

assuring timely use and follow-up of sales leads
qualifying sales leads (thereby saving valuable sales force time)
providing more effective tracking of sales leads

Customer trust / loyalty / retention analysis surveys

Purpose: Especially helpful for high-priced consumer goods with a long decision and purchase processes (time from need recognition to purchase), this type of study explores the depth of consumer attitudes formed about the product and/or company.

Salesforce effectiveness surveys

Purpose: A combination of measures that focus on the sales activities, performance, and effectiveness in producing the desired and measurable effect or goal. Often measured as a 360-degree survey completed by the salesperson, the client (evaluating the sales call), and the supervisor responsible for evaluating the salesperson.

Customer service surveys

Purpose: Akin to customer satisfaction surveys, customer service surveys instead focus in detail on the actual customer service that was received, the process involved in receiving that service, and the evaluation of the participants in the service process.

Customer service representative (CSR) surveys

Purpose: CSRs often exhibit frustration, burnout, and high turnover . Surveys focus on CSR retention, reducing costs, and increasing the quality of customer relationships.

Attitudes, burnout, turnover, and retention: CSRs hold attitudes that reflect on their job-related activities including:

the allocation of time
solutions to customer needs
how to improve their job
best practices
how well internal departments help customers

3. Product surveys

As part of product development, surveys help you find out what features, benefits and attributes appeal most to your customers, and how best to package your product, experience or service.

New product, service or experience concept analysis surveys

Purpose: Concept test studies are appropriate in the initial screening of new product concepts . Likes and dislikes about the concept and evaluation of acceptability and likelihood of purchase are especially useful measures.

Concept optimization, demand estimation, and cost analysis surveys (conjoint analysis)

Purpose: Determines an optimal bundle of features and benefits, and estimates associated demand. This kind of survey develops market share estimates of market potential for the alternative potential products.

Habits and practices, or attitude and usage surveys

Purpose: Directed at understanding usage situations, including how, when, and where the product is used. Habits and practices studies sometimes include a real or virtual pantry audit. Attitude and usage studies are used to understand consumer attitudes towards the product category and to life in general. They also look at product and brand usage, including how, when and where the product is used.

Product satisfaction surveys (attribute, features, promised benefits)

Purpose: Evaluation of the product’s promised bundle of benefits (both tangible and image). Are expectations created for the product by advertising, packaging , and the product appearance fulfilled by the product?

Competitive benchmarking surveys

Purpose: A “best practices” study of “how does the market view us relative to the competition?” Competitive positioning analyses often compare the attributes and benefits that make up the product using multidimensional scaling. These analyses also include an evaluation of key competitors, looking at the same KPIs and attributes as product satisfaction surveys.

Sales forecasting and market tracking surveys

Purpose: Sales forecasting and market tracking studies can include expert opinion (experts estimate the market), judgmental bootstrapping (expert-based rules describing how to use available secondary market information), conjoint analysis (estimation of consumer intentions based on product attributes that are important in the decision), and intentions evaluations (consumer self-reported intentions of future purchases).

Price setting surveys and elasticity of demand analysis

Purpose: Price surveys estimate the elasticity of demand and show optimal price points, including prices too low or too high. Price surveys may estimate the demand for different product or service segments, or different usage situations.

4. Brand surveys

A survey can help you understand how consumers perceive your brand and what values and ideas they associate with it. You can explore what value your brand has and whether people would choose you over competitors in your market niche.

Brand equity analysis surveys

Purpose: What is the psychological value that a brand holds in the marketplace? Brand equity is a composite of brand awareness , brand quality, brand associations, and brand loyalty measures.

Advertising value identification and analysis surveys

Purpose: Advertising value analysis focuses on mapping the hierarchical attributes, benefits, and values that are associated with and portrayed by an advertisement. Means-end analysis is often part of this type of study.

Advertising message effectiveness surveys (media and message)

Purpose: Message effectiveness testing identifies the impressions, feelings, and effectiveness in moving the respondent to a desired goal (increased awareness, more product information, trial, repeat purchase).

Once you know the right type of survey to run, the next step is to write a survey that your respondents will love to take!

Survey methods can be used to help collect data on real business issues and help you answer questions. Qualtrics supports customer surveys on every channel, at every journey stage to get you answers for more informed decisions.

We’ve put together a range of survey example templates that you can use for free to help you get started:

Employee satisfaction survey template
Employee exit survey template
Customer satisfaction (CSAT) survey template
Ad testing survey template
Brand awareness survey template
Product pricing survey template
Product research survey template
Employee engagement survey template
Customer service survey template
NPS survey template
Product package testing survey template
Product features prioritization survey template

In addition, for large-scale research studies, Qualtrics offers market research services to help with everything from questionnaire design and survey methods, to implementation and analysis.

Related resources

Post event survey questions 10 min read, best survey software 16 min read, close-ended questions 7 min read, survey vs questionnaire 12 min read, response bias 13 min read, double barreled question 11 min read, likert scales 14 min read, request demo.

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Understanding the 3 Main Types of Survey Research & Putting Them to Use

Understanding the 3 Main Types of Survey Research & Putting Them to Use

Surveys establish a powerful primary source of market research. There are three main types of survey research; understanding these will not merely organize your survey studies, but help you form them from the onset of your research campaign.

It is crucial to be proficient in these types of survey research, as surveys should never be used as lone tools. A survey is a vehicle for granting insights, as part of a larger market research or other research campaigns.

Understanding the three types of survey research will help you learn aspects within these forms that you were either not aware of or were not well-versed in.

This article explores the three main types of survey research and teaches you when to best implement each form of research.

Putting the Types of Survey Research into Perspective

With the presence of online surveys and other market research methods such as focus groups , there are ever-growing survey research methods . Before you choose a method, it is critical to decide on the type of survey research you need to conduct.

The type of survey research points to the kind of study you are going to apply in your campaign and all of its implications . The survey research type essentially hosts the research methods, which house the actual surveys . As such, the research type is one of the highest levels of the process, so consider it as a starting point in your research campaign.

Remember, that while there are various research types, the three presented in this article delineate the main types used in survey research. Researchers can apply these types to other research techniques (such as focus groups, interviews, etc.), but they are best suited for surveys.

Descriptive Research

The first main type of survey research is descriptive research. This type is centered on describing, as its name suggests, a topic of study. This can be a population, an occurrence or a phenomenon.

Descriptive research is often the first type of research applied around a research issue, because it paints a picture of a topic, rather than investigating why it exists to begin with.

The Key Aspects of Descriptive Research

The following provides the key attributes of descriptive research, so as to provide a full understanding of it.

Makes up the majority of online survey methods.
Concentrates on the what, when, where and how questions, rather than the why.
Lays out the particulars surrounding a research topic, but not its origin.
Handles quantitative studies.
Deemed conclusive due to its quantitative data.
Provides data that provides statistical inferences on a target population.
Preplanned and highly structured.
Aims to define an occurrence, attitude or opinions of the studied population.
Measures the significance of the results and formulates trends.
Can be used in cross-sectional and longitudinal surveys.

Survey Examples of Descriptive Research

There are various types of surveys to use for descriptive research. In fact, you can apply virtually all of them if they meet the above requirements. Here are the major ones:

Descriptive surveys: These gather data about different subjects. They are set to find how different conditions can be gained by the subjects and the extent thereof. Ex: determining how qualified applicants are to a job are via a survey checking for this.
Descriptive-normative surveys: Much like descriptive surveys, but the results of the survey are compared with a norm.
Descriptive analysis surveys: This survey describes a phenomenon via an analysis that divides the subject into 2 parts. Ex: analyzing employees with the same job role across geolocations.
Correlative Survey: This determines whether the relationship between 2 variables is either positive or negative; sometimes it can be used to find neutrality. For example, if A and B have negative, positive or no correlation.

Exploratory Research

Exploratory research is predicated on unearthing ideas and insights rather than amassing statistics. Also unlike descriptive research, exploratory research is not conclusive. This is because this research is conducted to obtain a better understanding of an existing phenomenon, one that has either not been studied thoroughly or is lacking some information.

Exploratory research is most apt to use at the beginning of a research campaign. In business, this kind of research is necessary for identifying issues within a company, opportunities for growth, adopting new procedures and deciding on which issues require statistical research, i.e., descriptive research.

The Key Aspects of Exploratory Research

Also called interpretative research or grounded theory approach, the following provides the key attributes of exploratory research, including how it differs from descriptive research.

Uses exploratory questions, which are intended to probe subjects in a qualitative manner.
Provides quality information that can uncover other unknown issues or solutions.
Is not meant to provide data that is statistically measurable.
Used to get a familiarity with an existing problem by understanding its specifics.
Starts with a general idea with the outcomes of the research being used to find related issues with the research subject.
Typically exists within open-ended questions.
Its process varies based on the new insights researchers gain and how they choose to go about them.
Usually asks for the what, how and most distinctively, the why.
Due to the absence of past research on the subject, exploratory research is time-consuming,
Not structured and flexible.

Examples of Exploratory Research

Since exploratory research is not structured and often scattered, it can exist within a multitude of survey types. For example, it can be used in an employee feedback survey, a cross-sectional survey and virtually any other that allows you to ask questions on the why and employs open-ended questions.

Here are a few other ways to conduct exploratory research:

Case studies: They help researchers analyze existing cases that deal with a similar phenomenon. This method often involves secondary research , unless your business or organization has case studies on a similar topic. Perhaps one of your competitors offers one as well. With case studies, the researcher needs to study all the variables in the case study in relation to their own.
Field Observations: This method is best suited for researchers who deal with their subjects in physical environments, for example, those studying customers in a store or patients in a clinic. It can also be applied by studying digital behaviors using a session replay tool.
Focus Groups: This involves a group of people, typically 6-10 coming together and speaking with the researcher, as opposed to having a one on one conversation with the researcher. Participants are chosen to provide insights on the topic of study and express it with other members of the focus group, while the researcher observes and acts as a moderator.
Interviews : Interviews can be conducted in person or over the phone. Researchers have the option of interviewing their target market, their overall target population, or subject matter experts. The latter will provide significant and professional-grade insights, the kind that non-experts typically can’t offer.

Causal Research

The final type of survey research is causal research, which, much like descriptive research is structured, preplanned and draws quantitative insights. Also called explanatory research, causal research aims to discover whether there is any causality between the relationships of variables.

As such, focuses primarily on cause-and-effect relationships. In this regard, it stands in opposition with descriptive research, which is far broader. Causal research has only two objects:

Understand which variable are the cause and which are the effect
Decipher the workings of the relationship between the causal variables, including how they will hammer out the effect.

The Key Aspects of Causal Research

The following provides the key traits of causal research, including how it differs from descriptive and exploratory research.

Considered conclusive research due to its structured design, preplanning and quantitative nature.
Its two objectives make this research type more scientific than exploratory and descriptive research.
Focuses on observing the variations in variables suspected as causing the changes in other variables.
Measure changes in both the suspected causal variables and the ones they affect.
Variables suspected of being causal are isolated and tested to meet the aforesaid two objectives.
For example, an advertisement or a sales promotion
Requires setting objectives, preplanning parameters, and identifying potential causal variables and affected variables to reduce researcher bias.
Requires accounting for all the possible causal factors that may be affecting the supposed affected variable, i.e., there can’t be any outside (non-accounted) variables.
All confounding variables that can affect the results have to be kept consistent and controlled to make sure no hidden variable is in any way influencing the relationship between two variables.
To deem a cause and effect relationship, the cause would have needed to precede the effect.

Examples of Causal Research

Causal research depends on the most scientific method out of the three types of survey research. Given that it requires experimentation, a vast amount of surveys can be conducted on the variables to determine if they are causal, non-causal or the ones being affected.

Here are a few examples of use causal research

Product testing: Particularly useful if it’s a new product to test market demand and sales capacity.
Advertising Improvements: Researchers can study buying behaviors to see if there is any causality between ads and how much people buy or if the advertised products reach higher sales. The outcomes of this research can help marketers tweak their ad campaigns, discard them altogether or even consider product updates.
Increase customer retention : This can be conducted in different manners, such as via in-store experimentations, via digital shopping or through different surveys. These experiments will help you understand what current customers prefer and what repels them.
Community Needs : Local governments can conduct the community survey to discover opinions surrounding community issues. For example, researchers can test whether certain local laws, transportation availability and authorizations are well or poorly received and if they correlate with certain happenings.

Deciding on Which of the Types of Research to Conduct

Market researchers and marketers often have several aspects of their discipline that would benefit off of conducting these three types of survey research. What’s most empowering about these types of survey research is that they are not limited to surveys alone.

Instead, they bolster the idea that surveys should not be used as lone tools. Rather, survey research powers an abundance of other market research methods and campaigns. As such, researchers should set aside surveys after they’ve decided on high-level campaigns and their needs.

As such, consider the core of what you need to study. Can your survey be applied to a macro-application? For example, in the business sector, this can be marketing, branding, advertising, etc.

Next, does your study require a methodical approach? For example, does it need to focus on one period of time among one population? If so, you will need to conduct a cross-sectional survey.

Or does it require to be conducted over some period of time? This will require implementing a longitudinal study. Once you figure out these components, you should move on to choosing the type of survey research you’re going to conduct. However, you can also decide on this before you choose one of the methodical methods.

Whichever route you decide to take, you’ll need a strong online survey provider, as this does, after all, involve surveys. The correct online survey platform will set your research up for success.

Frequently asked questions

Why is it important to understand the types of survey research.

The type of survey research informs the kind of study you’ll be conducting. It becomes the backbone of your campaign and all its implications. Basically, the types of survey research host their designated research methods, which house the surveys. Therefore, the types of survey research you decide on are at the highest level of the research process and act as your starting point.

What is exploratory research?

Exploratory research is the most preliminary form of research, establishing the foundation of a research process. focuses on unearthing ideas and insights rather than gathering statistics. It’s not a conclusive form of research-- rather, it is conducted to bolster understanding of a specific phenomenon. It is typically the first form of research, setting the foundation for a research campaign.

What is descriptive research?

Descriptive research focuses on describing a topic of study like a population, an occurrence or a phenomenon. It is performed early on in the overall research process, as it paints an overall picture of a topic, while extracting the key details that you wouldn’t find with exploratory research alone.

What is a cross-sectional survey?

A cross-sectional survey is a survey used to gather research about a particular population at a specific point in time. It is considered to be the snapshot of a studied population.

What is causal research?

Causal research is typically performed in the latter stages of the entire research process, following correlational or descriptive research. It is conducted to find the causality between variables. It involves more than merely observing, as it relies on experiments and the manipulation of variables

How can you decide which types of survey research to conduct?

Take a look at the core of what you need to study. Are you trying to focus on one period of time among a population? Does your survey research need to be conducted over a period of time? Questions like these will lead you to the right research type.

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Methodology

Questionnaire Design | Methods, Question Types & Examples

Questionnaire Design | Methods, Question Types & Examples

Published on July 15, 2021 by Pritha Bhandari . Revised on June 22, 2023.

A questionnaire is a list of questions or items used to gather data from respondents about their attitudes, experiences, or opinions. Questionnaires can be used to collect quantitative and/or qualitative information.

Questionnaires are commonly used in market research as well as in the social and health sciences. For example, a company may ask for feedback about a recent customer service experience, or psychology researchers may investigate health risk perceptions using questionnaires.

Questionnaires vs. surveys, questionnaire methods, open-ended vs. closed-ended questions, question wording, question order, step-by-step guide to design, other interesting articles, frequently asked questions about questionnaire design.

A survey is a research method where you collect and analyze data from a group of people. A questionnaire is a specific tool or instrument for collecting the data.

Designing a questionnaire means creating valid and reliable questions that address your research objectives , placing them in a useful order, and selecting an appropriate method for administration.

But designing a questionnaire is only one component of survey research. Survey research also involves defining the population you’re interested in, choosing an appropriate sampling method , administering questionnaires, data cleansing and analysis, and interpretation.

Sampling is important in survey research because you’ll often aim to generalize your results to the population. Gather data from a sample that represents the range of views in the population for externally valid results. There will always be some differences between the population and the sample, but minimizing these will help you avoid several types of research bias , including sampling bias , ascertainment bias , and undercoverage bias .

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Questionnaires can be self-administered or researcher-administered . Self-administered questionnaires are more common because they are easy to implement and inexpensive, but researcher-administered questionnaires allow deeper insights.

Self-administered questionnaires

Self-administered questionnaires can be delivered online or in paper-and-pen formats, in person or through mail. All questions are standardized so that all respondents receive the same questions with identical wording.

Self-administered questionnaires can be:

cost-effective
easy to administer for small and large groups
anonymous and suitable for sensitive topics

But they may also be:

unsuitable for people with limited literacy or verbal skills
susceptible to a nonresponse bias (most people invited may not complete the questionnaire)
biased towards people who volunteer because impersonal survey requests often go ignored.

Researcher-administered questionnaires

Researcher-administered questionnaires are interviews that take place by phone, in-person, or online between researchers and respondents.

Researcher-administered questionnaires can:

help you ensure the respondents are representative of your target audience
allow clarifications of ambiguous or unclear questions and answers
have high response rates because it’s harder to refuse an interview when personal attention is given to respondents

But researcher-administered questionnaires can be limiting in terms of resources. They are:

costly and time-consuming to perform
more difficult to analyze if you have qualitative responses
likely to contain experimenter bias or demand characteristics
likely to encourage social desirability bias in responses because of a lack of anonymity

Your questionnaire can include open-ended or closed-ended questions or a combination of both.

Using closed-ended questions limits your responses, while open-ended questions enable a broad range of answers. You’ll need to balance these considerations with your available time and resources.

Closed-ended questions

Closed-ended, or restricted-choice, questions offer respondents a fixed set of choices to select from. Closed-ended questions are best for collecting data on categorical or quantitative variables.

Categorical variables can be nominal or ordinal. Quantitative variables can be interval or ratio. Understanding the type of variable and level of measurement means you can perform appropriate statistical analyses for generalizable results.

Examples of closed-ended questions for different variables

Nominal variables include categories that can’t be ranked, such as race or ethnicity. This includes binary or dichotomous categories.

It’s best to include categories that cover all possible answers and are mutually exclusive. There should be no overlap between response items.

In binary or dichotomous questions, you’ll give respondents only two options to choose from.

White Black or African American American Indian or Alaska Native Asian Native Hawaiian or Other Pacific Islander

Ordinal variables include categories that can be ranked. Consider how wide or narrow a range you’ll include in your response items, and their relevance to your respondents.

Likert scale questions collect ordinal data using rating scales with 5 or 7 points.

When you have four or more Likert-type questions, you can treat the composite data as quantitative data on an interval scale . Intelligence tests, psychological scales, and personality inventories use multiple Likert-type questions to collect interval data.

With interval or ratio scales , you can apply strong statistical hypothesis tests to address your research aims.

Pros and cons of closed-ended questions

Well-designed closed-ended questions are easy to understand and can be answered quickly. However, you might still miss important answers that are relevant to respondents. An incomplete set of response items may force some respondents to pick the closest alternative to their true answer. These types of questions may also miss out on valuable detail.

To solve these problems, you can make questions partially closed-ended, and include an open-ended option where respondents can fill in their own answer.

Open-ended questions

Open-ended, or long-form, questions allow respondents to give answers in their own words. Because there are no restrictions on their choices, respondents can answer in ways that researchers may not have otherwise considered. For example, respondents may want to answer “multiracial” for the question on race rather than selecting from a restricted list.

How do you feel about open science?
How would you describe your personality?
In your opinion, what is the biggest obstacle for productivity in remote work?

Open-ended questions have a few downsides.

They require more time and effort from respondents, which may deter them from completing the questionnaire.

For researchers, understanding and summarizing responses to these questions can take a lot of time and resources. You’ll need to develop a systematic coding scheme to categorize answers, and you may also need to involve other researchers in data analysis for high reliability .

Question wording can influence your respondents’ answers, especially if the language is unclear, ambiguous, or biased. Good questions need to be understood by all respondents in the same way ( reliable ) and measure exactly what you’re interested in ( valid ).

Use clear language

You should design questions with your target audience in mind. Consider their familiarity with your questionnaire topics and language and tailor your questions to them.

For readability and clarity, avoid jargon or overly complex language. Don’t use double negatives because they can be harder to understand.

Use balanced framing

Respondents often answer in different ways depending on the question framing. Positive frames are interpreted as more neutral than negative frames and may encourage more socially desirable answers.

Positive frame	Negative frame
Should protests of pandemic-related restrictions be allowed?	Should protests of pandemic-related restrictions be forbidden?

Use a mix of both positive and negative frames to avoid research bias , and ensure that your question wording is balanced wherever possible.

Unbalanced questions focus on only one side of an argument. Respondents may be less likely to oppose the question if it is framed in a particular direction. It’s best practice to provide a counter argument within the question as well.

Unbalanced	Balanced
Do you favor…?	Do you favor or oppose…?
Do you agree that…?	Do you agree or disagree that…?

Avoid leading questions

Leading questions guide respondents towards answering in specific ways, even if that’s not how they truly feel, by explicitly or implicitly providing them with extra information.

It’s best to keep your questions short and specific to your topic of interest.

The average daily work commute in the US takes 54.2 minutes and costs $29 per day. Since 2020, working from home has saved many employees time and money. Do you favor flexible work-from-home policies even after it’s safe to return to offices?
Experts agree that a well-balanced diet provides sufficient vitamins and minerals, and multivitamins and supplements are not necessary or effective. Do you agree or disagree that multivitamins are helpful for balanced nutrition?

Keep your questions focused

Ask about only one idea at a time and avoid double-barreled questions. Double-barreled questions ask about more than one item at a time, which can confuse respondents.

This question could be difficult to answer for respondents who feel strongly about the right to clean drinking water but not high-speed internet. They might only answer about the topic they feel passionate about or provide a neutral answer instead – but neither of these options capture their true answers.

Instead, you should ask two separate questions to gauge respondents’ opinions.

Strongly Agree Agree Undecided Disagree Strongly Disagree

Do you agree or disagree that the government should be responsible for providing high-speed internet to everyone?

You can organize the questions logically, with a clear progression from simple to complex. Alternatively, you can randomize the question order between respondents.

Logical flow

Using a logical flow to your question order means starting with simple questions, such as behavioral or opinion questions, and ending with more complex, sensitive, or controversial questions.

The question order that you use can significantly affect the responses by priming them in specific directions. Question order effects, or context effects, occur when earlier questions influence the responses to later questions, reducing the validity of your questionnaire.

While demographic questions are usually unaffected by order effects, questions about opinions and attitudes are more susceptible to them.

How knowledgeable are you about Joe Biden’s executive orders in his first 100 days?
Are you satisfied or dissatisfied with the way Joe Biden is managing the economy?
Do you approve or disapprove of the way Joe Biden is handling his job as president?

It’s important to minimize order effects because they can be a source of systematic error or bias in your study.

Randomization

Randomization involves presenting individual respondents with the same questionnaire but with different question orders.

When you use randomization, order effects will be minimized in your dataset. But a randomized order may also make it harder for respondents to process your questionnaire. Some questions may need more cognitive effort, while others are easier to answer, so a random order could require more time or mental capacity for respondents to switch between questions.

Step 1: Define your goals and objectives

The first step of designing a questionnaire is determining your aims.

What topics or experiences are you studying?
What specifically do you want to find out?
Is a self-report questionnaire an appropriate tool for investigating this topic?

Once you’ve specified your research aims, you can operationalize your variables of interest into questionnaire items. Operationalizing concepts means turning them from abstract ideas into concrete measurements. Every question needs to address a defined need and have a clear purpose.

Step 2: Use questions that are suitable for your sample

Create appropriate questions by taking the perspective of your respondents. Consider their language proficiency and available time and energy when designing your questionnaire.

Are the respondents familiar with the language and terms used in your questions?
Would any of the questions insult, confuse, or embarrass them?
Do the response items for any closed-ended questions capture all possible answers?
Are the response items mutually exclusive?
Do the respondents have time to respond to open-ended questions?

Consider all possible options for responses to closed-ended questions. From a respondent’s perspective, a lack of response options reflecting their point of view or true answer may make them feel alienated or excluded. In turn, they’ll become disengaged or inattentive to the rest of the questionnaire.

Step 3: Decide on your questionnaire length and question order

Once you have your questions, make sure that the length and order of your questions are appropriate for your sample.

If respondents are not being incentivized or compensated, keep your questionnaire short and easy to answer. Otherwise, your sample may be biased with only highly motivated respondents completing the questionnaire.

Decide on your question order based on your aims and resources. Use a logical flow if your respondents have limited time or if you cannot randomize questions. Randomizing questions helps you avoid bias, but it can take more complex statistical analysis to interpret your data.

Step 4: Pretest your questionnaire

When you have a complete list of questions, you’ll need to pretest it to make sure what you’re asking is always clear and unambiguous. Pretesting helps you catch any errors or points of confusion before performing your study.

Ask friends, classmates, or members of your target audience to complete your questionnaire using the same method you’ll use for your research. Find out if any questions were particularly difficult to answer or if the directions were unclear or inconsistent, and make changes as necessary.

If you have the resources, running a pilot study will help you test the validity and reliability of your questionnaire. A pilot study is a practice run of the full study, and it includes sampling, data collection , and analysis. You can find out whether your procedures are unfeasible or susceptible to bias and make changes in time, but you can’t test a hypothesis with this type of study because it’s usually statistically underpowered .

If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.

Student’s t -distribution
Normal distribution
Null and Alternative Hypotheses
Chi square tests
Confidence interval
Quartiles & Quantiles
Cluster sampling
Stratified sampling
Data cleansing
Reproducibility vs Replicability
Peer review
Prospective cohort study

Research bias

Implicit bias
Cognitive bias
Placebo effect
Hawthorne effect
Hindsight bias
Affect heuristic
Social desirability bias

A questionnaire is a data collection tool or instrument, while a survey is an overarching research method that involves collecting and analyzing data from people using questionnaires.

Closed-ended, or restricted-choice, questions offer respondents a fixed set of choices to select from. These questions are easier to answer quickly.

Open-ended or long-form questions allow respondents to answer in their own words. Because there are no restrictions on their choices, respondents can answer in ways that researchers may not have otherwise considered.

A Likert scale is a rating scale that quantitatively assesses opinions, attitudes, or behaviors. It is made up of 4 or more questions that measure a single attitude or trait when response scores are combined.

To use a Likert scale in a survey , you present participants with Likert-type questions or statements, and a continuum of items, usually with 5 or 7 possible responses, to capture their degree of agreement.

You can organize the questions logically, with a clear progression from simple to complex, or randomly between respondents. A logical flow helps respondents process the questionnaire easier and quicker, but it may lead to bias. Randomization can minimize the bias from order effects.

Questionnaires can be self-administered or researcher-administered.

Researcher-administered questionnaires are interviews that take place by phone, in-person, or online between researchers and respondents. You can gain deeper insights by clarifying questions for respondents or asking follow-up questions.

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Understanding Data Collection: Methods, Types, Examples and Tools

11 minute read
September 13, 2024

Written by:

Smith Alex is a committed data enthusiast and an aspiring leader in the domain of data analytics. With a foundation in engineering and practical experience in the field of data science

Summary: Data collection is crucial for analysis and decision-making. It includes methods like surveys, interviews, and primary and secondary types. Choosing the right approach ensures reliable, actionable data.

Introduction

Data collection is crucial in gathering accurate information for decision-making, research, and analysis. It involves systematically obtaining data from various sources using different data collection methods. Whether you’re a business analysing customer behaviour or a researcher conducting a study, the right example of data collection ensures reliable outcomes.

Data collection is important because it can provide actionable insights. This article will explore the types and methods of data collection and provide practical examples, helping you understand how to choose the best approach for your needs.

What Is Data Collection?

Data collection is the systematic process of gathering information from various sources to analyse, interpret, and make informed decisions. It involves identifying relevant data, organising it, and ensuring accuracy and reliability.

Whether collected from primary sources like surveys and interviews or secondary sources such as databases and research reports, data collection is critical in providing insights for various purposes, including business strategy, scientific research, and social studies.

Role of Data Collection in Data Analysis and Interpretation

Data collection serves as the foundation for data analysis and interpretation. Without accurate and well-organised data, analysis becomes ineffective, and conclusions are unreliable. Once data is gathered, analysts apply statistical methods, machine learning models, or visualisation tools to find patterns, trends, and correlations. This helps organisations and researchers derive meaningful insights from the raw data.

Effective data collection ensures that the information fed into analytical tools is accurate, relevant, and timely, allowing for precise interpretations. This enables decision-makers to respond to trends, solve problems, and predict future outcomes based on reliable evidence. In essence, data collection directly impacts the quality and effectiveness of the analysis, driving better results across industries.

Types of Data Collection

Data collection is a critical process that can be classified into two primary types: primary and secondary. Each type has its own set of methodologies, advantages, and limitations. Understanding these differences helps you select the most appropriate method for your research or business needs.

Primary Data Collection

Primary data collection involves gathering data directly from original sources. This data type is collected firsthand and specific to the researcher’s current study. Common methods include surveys, interviews, observations, and experiments. For instance, a company may survey to understand customer satisfaction, or a researcher might use interviews to gather detailed opinions on a new product.

Relevance : Primary data is tailored to the research question or objective, ensuring high relevance.
Accuracy : Direct data collection minimises the risk of inaccuracies from secondary sources.
Control : Researchers have control over the data collection process, including the methodology and quality of data.

Disadvantages

Cost : Primary data collection can be expensive due to the resources required for surveys, interviews, or experiments.
Time-Consuming : Collecting data firsthand often requires significant time and effort.
Limited Scope : The scope of primary data is often limited to the sample size and geographical area covered during the collection.

Secondary Data Collection

Secondary data collection refers to using data already collected and published by other sources. This data is analysed for purposes other than those for which it was originally collected. Examples include using existing government statistics, academic research papers, or market reports.

For instance, a business might use industry reports to assess market trends rather than conducting surveys.

Cost-Effective : Secondary data is generally less expensive because it involves analysing existing data rather than collecting new data.
Time-Saving : Researchers can save time by leveraging already available data, allowing for quicker analysis and decision-making.
Broad Scope : Secondary data often covers a larger scope and broader context, providing a comprehensive view of trends or patterns.
Relevance : The data may not perfectly align with the research’s specific needs, leading to potential gaps in information.
Quality Issues : Researchers have less control over the quality and accuracy of secondary data, which may affect the reliability of the results.
Outdated Information : Secondary data might be outdated or not reflective of current trends, limiting its usefulness in dynamic environments.

Understanding primary and secondary data collection methods can help you decide which approach best suits your research or business needs.

What are Data Collection Methods?

Employing the right method ensures that the collected data aligns with research goals and yields valuable insights. Here, we explore several common data collection methods, each with its unique characteristics, advantages, and applications. Understanding these methods helps select the most appropriate one for various research or business needs.

Surveys and Questionnaires

Surveys and questionnaires are popular methods for quickly and efficiently collecting data from many respondents. They are typically used to gather quantitative data on various topics, from customer satisfaction to employee feedback.

Surveys consist of a series of structured questions designed to elicit specific information. They can be administered in various formats, including online, by phone, or in person. Online surveys, facilitated by platforms like Google Forms or SurveyMonkey, offer convenience and accessibility, allowing respondents to participate from anywhere at any time.

Surveys and questionnaires have advantages, including their ability to reach a wide audience and collect standardised data that can be easily analysed. However, they also have disadvantages, such as the potential for low response rates and the risk of biased responses if questions are poorly designed.

Interviews involve direct, one-on-one interactions between the interviewer and the interviewee. This method allows for in-depth exploration of topics and provides qualitative insights, often impossible through surveys alone. Depending on the level of control over the conversation, interviews can be structured, semi-structured, or unstructured.

Structured interviews use a fixed set of questions and are often used when consistency across interviews is crucial.
Semi-structured interviews include pre-determined questions and open-ended topics, allowing for flexibility and deeper probing.
Unstructured interviews are more conversational, providing the freedom to explore topics spontaneously based on the interviewee’s responses.

Interviews have the advantage of capturing detailed and nuanced information. However, they can also be time-consuming and resource-intensive, requiring careful planning and skilled interviewers to avoid biases and ensure reliability.

Observations

Observations involve systematically watching and recording behaviour or events in their natural setting. This method is beneficial for collecting data on how individuals or groups interact with their environment.

Observational data can be either participant or non-participant. In participant observation, the researcher becomes involved in the daily activities of the group being studied. In non-participant observation, the researcher remains passive, minimising their impact on the group.

The advantages of observational methods include their ability to provide real-time data and insights into actual behaviours rather than self-reported data. However, challenges include potential observer bias and difficulty generalising findings from a limited sample.

Experiments

Experiments are used to test hypotheses and determine cause-and-effect relationships. This method involves manipulating one or more variables while controlling others to observe the effects on a dependent variable. Experiments can be conducted in laboratory or field settings.

Laboratory experiments offer a controlled environment where variables can be precisely managed. This setting is ideal for testing theories under controlled conditions.
Field experiments are conducted in natural settings, providing more generalisable results but often with less control over extraneous variables.

The advantage of experiments is their ability to establish causal relationships between variables. However, they may suffer from limited external validity if the experimental conditions do not accurately reflect real-world scenarios.

Documents and Records

Documents and records involve collecting data from existing sources such as reports, historical records, and official documents. This method is handy for secondary data analysis and longitudinal studies where historical data is required.

The advantages of using documents and records include their cost-effectiveness and the availability of extensive data that might not be feasible to collect otherwise. However, the disadvantage is that the data may be outdated or incomplete, and researchers may have limited control over the quality of the original data.

Focus Groups

Focus groups involve guided discussions with a small group of participants to gather opinions and insights on specific topics. This method commonly used in marketing, social science, and product development.

A focus group typically comprises 6 to 12 participants who discuss topics guided by a moderator. The interaction among participants can reveal a range of perspectives and generate new ideas.

Focus groups have advantages, including exploring complex issues and generating rich, qualitative data. However, challenges include the potential for groupthink and the need for skilled moderation to manage group dynamics and ensure that all voices are heard.

Data Collection Tools

Data collection tools are essential for gathering information effectively and efficiently. These tools vary widely, from simple manual entry systems to sophisticated software for complex data collection tasks. This section will explore popular data collection tools, detailing their features, use cases, and benefits.

Google Forms (for Surveys and Questionnaires)

Google Forms stands out as a versatile tool for creating surveys and questionnaires. It offers a user-friendly interface that allows users to design and distribute forms quickly. You can create multiple-choice questions, short answers, checkboxes, and more with Google Forms. The tool supports various question types and customisation options, making it ideal for gathering feedback, conducting research, and collecting data from diverse audiences.

One of Google Forms’ key advantages is its integration with other Google Workspace tools like Google Sheets. This integration automatically compiles responses into a spreadsheet, simplifying data analysis and visualisation. Additionally, Google Forms is accessible from any device with internet connectivity, making it convenient for users to complete surveys on the go.

SurveyMonkey (for Surveys)

SurveyMonkey is another powerful tool to survey creation and data collection. It provides extensive features tailored for designing detailed and customised surveys. Users can choose from numerous templates or build surveys from scratch, incorporating various question types and advanced logic to tailor the survey experience to individual respondents.

SurveyMonkey offers robust analytics and reporting features, including data visualisation tools that help users interpret survey results effectively. With its user-friendly interface and comprehensive analytics capabilities, SurveyMonkey well-suited for businesses and researchers who need in-depth insights from their data collection efforts.

Tableau (for Data Visualisation and Analysis)

Tableau renowned for its data visualisation and analysis capabilities. While not a traditional data collection tool, Tableau excels in transforming collected data into interactive and visually appealing dashboards. Users can connect Tableau to various data sources, including spreadsheets, databases, and cloud services, to create dynamic visualisations that reveal trends and patterns.

The strength of Tableau lies in its ability to handle large datasets and efficiently perform complex analyses. Its drag-and-drop interface allows users to build custom reports and dashboards without extensive technical knowledge. Tableau is an invaluable tool for organisations and researchers looking to make sense of their collected data and present it in a compelling format.

Also Read Blogs: What is Data Blending in Tableau? Tableau Data Types: Definition, Usage, and Examples .

KoboToolbox (for Field Data Collection)

KoboToolbox is specifically designed for field data collection, making it ideal for humanitarian and development projects. This tool facilitates data collection in challenging environments, such as remote areas with limited internet access. KoboToolbox supports offline data entry, allowing field workers to collect data without a constant internet connection and synchronise it once they return online.

KoboToolbox features a range of question types and supports multimedia inputs like images and audio recordings. Its user-friendly interface and robust data management capabilities make it a preferred choice for field-based data collection, especially in sectors where on-site data gathering is critical.

Excel and Google Sheets (Manual Data Entry)

Excel and Google Sheets are fundamental tools for manual data entry and management . These spreadsheet applications are widely use due to their simplicity and flexibility. Users can enter data manually, organise it into tables, and perform basic calculations and analyses.

With its advanced functions and formulas, Excel provides a powerful platform for detailed data manipulation and analysis. On the other hand, Google Sheets offers the advantage of real-time collaboration, allowing multiple users to work on the same spreadsheet simultaneously.

Both tools are suitable for smaller-scale data collection tasks and can be a starting point before transitioning to more specialised data collection tools.

Examples of Data Collection in Various Fields

Data collection plays a pivotal role across diverse fields, utilising different methods to gather valuable information. Each field adapts data collection methods to meet specific needs, demonstrating the versatility and importance of collecting accurate data for effective decision-making and analysis. Here’s how data collection applied in various sectors:

Companies gather data through customer feedback surveys, sales reports, and market analysis. This data helps companies to understand consumer preferences, improve products, and make strategic decisions.

Data collection involves patient records, clinical trial results, and health surveys. This information is crucial for monitoring patient outcomes, advancing medical research, and enhancing treatment protocols.

Schools and educational institutions collect data on student performance through assessments, surveys, and attendance records. This data evaluates teaching effectiveness, identifies learning gaps, and improves educational strategies.

Market Research

Market researchers collect data through focus groups, consumer surveys, and social media analytics. This data helps businesses understand market trends, consumer behaviour, and competitive positioning.

Challenges in Data Collection

Data collection is essential for obtaining accurate insights, but it often comes with significant challenges. Addressing these challenges effectively is crucial for ensuring the reliability and validity of collected data. Here are some common issues faced during data collection:

Data Quality Issues

Inaccurate or inconsistent data can arise from human errors, faulty instruments, or poor methodology. Ensuring high-quality data requires rigorous validation and verification processes.

Bias can distort results, often stemming from sampling errors or leading questions in surveys. Mitigating bias involves designing fair and representative data collection methods.

Ethical Considerations

Privacy and consent are paramount. Researchers must handle personal information carefully, obtain informed consent from participants and protect their data from unauthorised access.

Cost and Resource Constraints

It can be expensive and resource-intensive, especially on a large scale. Efficient planning and leveraging cost-effective tools can help manage these constraints.

Data Security

Protecting collected data from breaches and unauthorised access is crucial. Implementing robust security measures and data encryption helps safeguard sensitive information.

By recognising and addressing these challenges, organisations can enhance the effectiveness and integrity of their data collection efforts.

Best Practices for Effective Data Collection

It is essential for obtaining accurate, reliable, and actionable insights. Adhering to best practices ensures that the data gathered meets the desired objectives and supports informed decision-making. Here are critical practices to follow:

Define Clear Objectives : Start by clearly outlining the purpose of data collection. Knowing your aim helps you select the appropriate methods and tools.
Choose the Right Method : Select data collection methods that align with your objectives. Surveys, interviews, and observations have unique strengths and suited for different data types.
Minimise Bias : Design your process to reduce bias. Use neutral language in surveys and ensure that your sampling methods are representative of the population.
Use Reliable Tools : Choose reliable tools and software that meet your needs. Invest in tools that offer accuracy, ease of use, and robust features.
Ensure Data Security and Privacy : Implement measures to protect data integrity and confidentiality. Secure data storage and handle personal information carefully to comply with privacy regulations.

By following these best practices, you enhance the quality and reliability of the data collected, leading to more insightful and actionable outcomes.

Effective data collection is essential for accurate analysis and decision-making. By understanding the different types and methods of data collection—such as surveys, interviews, and observations—organisations and researchers can choose the best approach to gather reliable and relevant information. Implementing best practices ensures high-quality data, ultimately driving more informed outcomes and strategic decisions.

Frequently Asked Questions

What are data collection methods .

Data collection methods include surveys, interviews, observations, and experiments. Each method serves a specific purpose, such as gathering quantitative or qualitative data, depending on the research needs and objectives.

What is an Example of Data Collection?

An example of data collection is conducting a customer satisfaction survey using Google Forms. This method gathers feedback from respondents to assess their experience and improve services.

What are the Types of Data Collection?

The main types of data collection are primary and secondary. Primary data collected directly from sources like surveys and interviews, while secondary data uses existing sources like reports and databases.

Reviewed by:

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One Curve Doesn't Fit All
Table of Contents

A New Standard

New test fixture, new challenges, how we did it, people like different curves and are sure of it, the target (k.i.s.s.), circle of confusion, harman research, on the type 5128 hats, believe in your preferences, one curve doesn't fit all 350 headphone listening tests show that many sound profiles can be preferred.

The quest for one ideal frequency response curve for headphones has been the subject of many heated debates among enthusiasts. However, there is a consensus among research circles: a preference-based approach appears to be the path forward in finding that perfect curve. Some may think that with the large amount of research data from Harman and others, frequency response is a solved problem. However, as other measurement methods and standards enter the headphone testing ecosystem, we must revise these preference curves as they can't be directly translated.

What comes to mind when you think of preference-based target curves for headphones? Maybe you're thinking about how a target curve is created or whose preference it represents. These questions are a great place to start. To answer them, we'll need to go back to the fundamentals: double-blind listening tests!

The results may surprise you as much as they surprised us: thirty-five participants, five curves, two song clips, and no clear preferred curve.

What's the main takeaway from these results? We're here to tell you that it's okay to trust that you like what you like and that you're not wrong. It doesn't mean that frequency response is an unimportant metric—it's the single most important parameter to define the perceived sound quality. It really matters since, based on these measurements, we can provide educated guidance in selecting the right headphones for you. In doing so, we aim to highlight the importance of personal preferences while recognizing the need to accurately assess objective performance.

Now, why go through all the work of building a new target frequency response curve? The reason is our new friend, the B&K Type 5128-B.

The B&K Type 5128-B

Although we recognize that subjectivity will always play a great role in finding the right headphones for you, our commitment here at RTINGS.com is driven by our willingness to provide you with the most accurate objective metrics to help you with your buying decisions. Regarding headphone measurements, this also means staying current with the latest standards, letting us expand the scope of our evaluation.

The Brüel & Kjær (B&K) Type 5128-B Head and Torso Simulator (referred to as the 5128 in the rest of this article) offers a new take on the headphone measurement standards that have been in practice for more than 40 years. We welcome this change because legacy ear couplers like the ones on our HMS II.3 test rig conform to the older but still widely accepted IEC 60318-4 ear simulator standard; this standard is only specified for measurements between 100Hz and 10kHz rather than the full 20Hz to 20kHz audible spectrum. While you can use such devices to take full band measurements, it can't be guaranteed to give the same result as the next unit under the same conditions since there are no indications of tolerance.

So here comes the B&K Type 4620 ear simulator:

The Brüel & Kjær (B&K) Type 4620 ear simulator

A lot of research has gone into the conception of this artificial ear.

It's specified to measure the full audible range of human hearing.
The coupler geometry is representative of an average human ear canal.
It's designed to present the acoustic impedance of an average human ear.

So, are all the headphone measurements we've made so far wrong? No! It doesn't render the huge corpus of measurements from us and others obsolete. Headphone measurements always had a certain level of uncertainty. Not only does the morphology of each individual vary considerably, but there is also unavoidable variability in the process itself, regardless of the testing equipment. We aim to minimize these limitations, but some will remain.

This new test fixture will take measurements that look slightly different from our previous results, but you can interpret what you see in a familiar way. The change will be mostly noticeable in the high frequencies, where our HMS II.3 fixture has quite an uneven response. We did notice some change in the bass responses, too, but there are no repeatable, consistent differences.

The figure below compares the frequency response measured with the 5128-B (top graph) and the frequency response measured with the HMS II.3 (bottom graph) for a few headphones. There aren't night and day differences between the two sets of results, but don't expect to see the same frequency response graphs you're used to.

Comparison of frequency responses from HMS ii.3 and B&K 5128

While this new artificial head and ear simulator brings new possibilities to frequency response measurements, these great measurements don't mean much without a base of comparison. As you may have guessed, we need a target. Since the results are different between the old HMS II.3 and the new 5128, the target must also be different. But the challenge here is that there isn't a direct conversion between measurements made on these two devices.

Moreover, almost all past research on headphone frequency response (led primarily by Harman) was based on IEC-60138-4 compliant couplers, often referred to as the 711. As we adopt the 5128 platform, we're a bit ahead of the curve and have very limited data on what should be a desirable frequency response curve. Although there are a lot of unknowns, we're up for a challenge! And as you'll see, not everything is set in stone in the headphone world.

The Listening Tests: Our Group Knows What They Like

So, we have a nice state-of-the-art tool to measure headphone frequency response (and more), but to assess what people will like, why don't we just ask? Yes, the world needs another double-blind listening test—it's the only way to evaluate whether what we think we like is really what we like. The 35 participants in this study are all employees here at RTINGS.com.

The following figure shows the five sound profile curves that participants were asked to rate from 1 to 10 while listening to two different 25-second music programs: Daft Punk's Get Lucky and Steely Dan's Cousin Dupree.

The five evaluated frequency response curves in our listening tests

Most of these sound profile curves have a certain ground for potentially representing what people consider a balanced sonic signature:

Blue (DF Tilt)

A target curve based on the known neutral diffuse field response of the 5128, on which a -1 dB per Octave tilt has been applied.

Green (SenseLab/Aizu)

A visual approximation of the average preferred curve for the 5128, presented by Ravizza et al. in a recent publication of the Audio Engineering Society 1 . (More on this later!)

Red (RTINGS.com SPK)

The RTINGS.com target curve for speakers. It itself is based on Harman research, to which we apply the diffused field response of the 5128.

Magenta (Harman+Tilt)

A combination of the known bass behavior of the Harman Over-Ear 2018 target and a -1 dB per octave tilt 200Hz upward.

Cyan (Low Bass)

A -4 dB shelving filter below 300Hz and a -5 dB bell filter centered at 3000Hz applied to the magenta curve to achieve a curve with significantly less bass. This curve should be considered an anchor and isn't backed by any research or known principles that suggest people would like it.

Before formally evaluating these sound profiles, we played a 2-minute music program (Dire Straits' Sultans of Swing) for each of our volunteers, during which we randomly switched the EQ curves with no scoring asked from the participant. Then, we proceeded with the tests. The order in which we presented the EQ curves to the participants was randomized and randomized again for the second clip. We calibrated the volume levels at 85 dB SPL A Weighted and compensated for small differences in levels due to the different responses. For listening, we used the Sennheiser HD 650 headphones, which were equalized to match the resulting frequency response to the curve evaluated. We used AutoEQ to create the EQ profiles, Equalizer APO to implement them, and EACS (Equalizer APO Config Switcher) for live profile switching. After the first full sequence, the participants were allowed to listen to any of the five curves as often as they wanted and in their desired order.

By now, you're bursting with anticipation to see the results, right? Let's break the suspense.

Curve	VS Curve	p-Value
DF Tilt	SenseLab/Aizu	1
DF Tilt	RTINGS.com SPK	1
DF Tilt	Harman+Tilt	1
DF Tilt	Low Bass	<0.001
SenseLab/Aizu	RTINGS.com SPK	1
SenseLab/Aizu	Harman+Tilt	1
SenseLab/Aizu	Low Bass	0.024
RTINGS.com SPK	Harman+Tilt	1
RTINGS.com SPK	Low Bass	0.017
Harman+Tilt	Low Bass	0.002

The low bass anchor curve is confirmed to be the least preferred, with high confidence.

These findings and our approach will be received with some scrutiny; we'd be disappointed if it wasn't. We, like you, want to be comprehensive when making statements about sound quality. This small-scale experiment isn't a definitive characterization of what people like. It also doesn't negate the validity of the more thorough testing and results from the Harman group and others. It was, however, conducted meticulously and is a valid double-blind listening test.

One interesting statistic that stood out when analyzing the results is that 63% of the participants picked the same EQ curve as their most preferred while listening to both music clips. This is highly significant. Nobody commented that "they all sound the same." The differences were audible, and participants were engaged and confident with their ratings.

Past studies also have notions of trained vs. untrained listeners, geographic location, gender, and age. Our sample was a bit small for proper statistics to be made on these considerations, but we had a simple survey. While we don't draw any concrete conclusions on these aspects, it didn't make any significant differences in preferences in our experiment, except that women did appear to prefer the Low Bass curve more than men. This agrees with some past research 2 , but considering we only had six female colleagues participating, you should take this with a grain of salt.

Listening test results for different groups of listeners.

While these are interesting observations, the listening tests didn't yield the solution for crafting the one perfect target curve. These results show that although relatively small differences are audible from an individual perspective, there are limits to the principle that a certain exact frequency response will universally be "right. " Saying anything can cut it would be wrong as well. The results of the Low Bass curve confirm that.

So, back to the drawing board.

Considering what we learned from the listening tests, it may be relevant to recall the wise words of the late engineer Kelly Johnson: "Keep it simple, stupid."

Without further ado, here is RTINGS.com's new target curve:

RTINGS.com's target curve for headphones

It was simply constructed by first starting with the response of the 5128 HATS in a flat diffused field. To which:

We applied a -6 dB tilt in the response over the audio band (0.6 dB/octave)
Then applied a 4.3 dB bass shelf (@105Hz, Q .707)
And smoothed the curve to 1/6th octave

Yes. That's it. Let's go over each of these design choices.

The first choice was to start with the 5128's known frequency response in a flat diffuse field. A diffuse field is when the sound pressure is equal at any frequency from any direction—in other words, a theoretically perfectly reflective room.

The graph below shows the response of the ear simulator under these conditions. The peak in the response is the HRTF (Head-Related Transfer Function)—how the HATS' head and artificial ears affect the sound as it arrives at the eardrum. You may have heard the terms ear gain or ear resonance. They're equivalent terms in the context of a HATS in a diffused field. It aims to reproduce a behavior representative of the heads and ears of real humans, but you won't necessarily have the same HRTF. We do know some measurements show less ear gain in real humans. These differences amongst individuals don't matter so much as the graph serves merely as a quantifiable reference. Our model isn't based on absolutes; we're after a preference curve.

Harman's research starts with the concept of good speakers in a good semi-reflective room and how sound reaches the eardrums under these conditions.

A known behavior of speakers in a room is that early reflections will induce a tilt in the frequency response. How much of a tilt depends on the specific room. That said, there are known target curves for speakers that are backed by research. We settled for a 6 dB tilt over the audible band, mainly to stay consistent with our own speaker target curve and some published speaker targets by Dr Floyd Toole and Harman. 3 , 4

It's also a tilt value that made our target match closely with some known Harman-compliant headphones and earbuds in the mid- to treble range, like the TruthEar Crinacle ZERO: RED, the Sennheiser HD 600, and the HiFiMan Sundara 2020. Of course, those are just visual sample checks. Again, let's remember the premise introducing this section.

Three Harman-compliant headphone frequency responses.

The third design choice concerns the bass boost. As there's no theoretical difference in the bass region of the diffuse field response of the 5128 and the GRAS rig used by Harman, we opted to use a bass shelf similar to Harman's to achieve a general sound signature. Since we aren't starting with their in-room response but rather a tilted curve, there are small differences in the bass region, but you get the point by now… it's okay. But didn't we tell you that both HATS measure differently? They do, but the difference between the measurements aren't consistent and repeatable across different headphones.

We also applied a significant amount of smoothing to the curve (1/6th octave). In this case, the initial Diffuse field response is already devoid of significant peaks and dips. Still, as a generality, a smooth response is more representative of the general tonality we are after in a target. Let's note that the frequency response measurements themselves don't use the same smoothing. We use 1/12th octave, which allows for a better inspection of the variations in the response.

So you have it in its essence: a simple approximation of what a majority will find a balanced tonality for headphones—no more, no less.

What Does It Mean For You?

This update to the headphones test bench isn't so revolutionary; we aren't concluding that personal preference makes all headphones equally good sounding. There are definitely headphones that sound "off." There are also sound profiles that are more in line with a balanced spectral presentation. However, we're moving in a direction where the idea of neutrality may or may not be what you are after, and both choices are valid. Our reviews will still provide a Neutral Sound score, but we are gradually bringing in a more descriptive assessment of the sound profiles. We encourage you not to focus on how a pair of headphones scores for Neutral Sound. Rather, look at the Sound Profile graph, see if it suits your taste, and assess if the bass and treble amounts align with your preferences. The target is just an indication, not an absolute measure of sound quality.

You'll also notice that with this test bench update, we went with a single target for headphones and in-ear monitors (IEMs). We opted for this simplified approach as it isn't yet fully understood how IEMs appear to show more differences in bass response between the IEC 711 couplers and Type 4620 ear simulators. We simply don't have strong enough evidence that an IEM target should be significantly more V-shaped.

Nonetheless, what is important is that there's a baseline from which you can work out if a device's sound profile is right for you. If it's any indication, most well-liked IEMs do quite well with our current target!

Our terminology and scoring also reflect the new direction with Headphones v1.8. Here are a few notable updates:

The sound profile box now shows the frequency at which normalization (zero crossing) was applied.
Frequency response measurements are now made at 94 dB SPL, which aligns more with accepted standards (IEC 60268-7).
The terminology is updated to reflect the new direction. "Compliance to Target" replaces Bass-, Mid- and Treble Accuracy. (We're gathering the same measurements, but words matter).
Similarly, "RMS Deviation" replaces "STD Error" to better align with our views.
Scoring on RMS Deviation now penalizes small deviations to a lesser degree. This follows from the idea that some margin of deviation shouldn't be considered a flaw.
Peaks and dips are now scored as an objective metric, and now contribute to the Neutral Sound usage score.

The Relevance of Previous Research

We want to wrap up this article by giving appropriate credit to headphone sound quality researchers and commenting on the state of the art. There have been some real challenges in the field of reproduction of audio through headphones, and enormous leaps have been accomplished, resulting in a large body of work that pushes the knowledge of audio fidelity characterizing standards. This work has benefited everyone, making the music that gets to our ears more enjoyable.

The circle of confusion. This well-known concept in the audio engineering circles, first put forward by Dr. Floyd Toole 3 , is based on a simple idea that makes a great deal of sense: if the listening conditions were standardized when audio content is created, we could use the same standards to reproduce it. The result would be that everybody would enjoy audio content as it was intended to be presented.

Without that, we're in a vicious cycle where listeners can't know how content is supposed to sound, and the creators can't know how people will enjoy their content. Thinking that all headphones should conform to a standardized sound profile, in this context, isn't a realistic design goal and not one that's desirable, either. We don't think it's the goal of any of those studies. Nobody can be against better sound quality for all, and we are thankful for everybody working in this direction. Ultimately, we all have the same objective: helping you get the headphones or earbuds that will produce the best sound (for you).

We can't write an article about headphone listening tests and target curves without mentioning the pioneers of headphone research. Headphone sound quality characterization would still be in its infancy without the work of Dr. Sean Olive, Todd Welti, and the team at Harman. As previously stated, the target curve we are implementing in Headphones v1.8 is closely in line with what Harman proposed without being a direct translation since their testing conditions and in-room response can't be reproduced.

We also agree with the fundamentals (and most of the fine print). A preference-based approach is a good way to develop a valid target as long as the "circle of confusion" isn't solved.

While we fully endorse Harman's methods, they have some limitations. Indeed, the thing about preferences is that they vary—a fact that's clearly demonstrated in our own listening test. We understand the incentive to evolve toward a "neutrality" standard, and to their credit, Harman has tested hundreds of subjects over the years to arrive at their target responses. Perhaps a method of adjustment where listeners have full control of bass and treble levels is the most unbiased way to test listeners' preferences. However, such a method will also, by its nature, converge to a single result when averaged. We also can't know if the final curve would have been slightly different had they started with a different in-room response. Or if some people would have chosen a certain tilt if they could have. What we take from all of this is that an approximation based on simple operations on the diffuse field response may very well be good enough. Some may consider that the research is fully complete and that the "best" frequency response for headphones is already set in stone. However, we need to keep in mind what "preference" means. Harman themselves had a significant variance in listeners' preference. 2 For example, according to Harman's own findings, the bass amount preferred, while largely in line with their target level for the majority of listeners, still shows a 36% proportion who find this baseline either too much (21%) or would prefer more (15%). Our motto won't change; we're committed to helping you find the best headphones for your needs (or preference), hopefully for 100% of you, not 64%.

As we said before, very minimal data exists with which to make the new target for the new test fixture. To the best of our knowledge, only a single formal study has been done on a preference target for the Type 5128 HATS. The publication, An Over-Ear Headphone Target Curve for Brüel & Kjær Head and Torso Simulator Type 5128 measurements , was a joint effort between Senselab Force Tech in Denmark and The University of Aizu in Japan. Their work includes the evaluation of 32 different frequency response curves by 56 participants. It's similar in approach to the listening test we performed, but having so many outliers and odd curves allowed the authors to pick the "best" five to calculate an average. Their research does not conclude in a single "winning" curve, which aligns with our findings. Furthermore, the considerable delta in the bass and treble range in the five preferred curves, as seen below, is reassuring for our own conclusions since it brings the idea of a range of valid frequency response curves.

Frequency response curves from a B&K Type 5128 listening test study

There you have it. It's impossible to completely dissociate perceived headphone sound quality from subjectivity; even the most extensive research is based on that fact. Where there's subjectivity, there will be divergence of opinions and preferences. RTINGS.com will continue to value new developments in the quest for the best fidelity, and there's room for more research.

We view Headphones v1.8 as an important stepping stone. We'll build on this work as we transition to a flexible frequency response graphing tool for v2.0. Our goal is for you to be able to visualize the sound profiles compensated to many known preference targets and some calibrated responses like the diffuse field response. So, to all our colleagues in the headphone testing and research community, when more valid target curves are studied and designed around the Type 5128 platform, we'll definitely consider publishing them!

In the meantime, we want to state again that we aren't proposing a world where manufacturers can come up with just any response and not be judged. We need a reference, and this target that we're bringing you today is our small contribution. But having a reference doesn't mean a signature that deviates from that can't be well-executed and pleasing.

Try equalizing some of the headphones we measured to this target; let us know your thoughts! Also, let us know what you like in headphone sonics; it's a fun hobby in which we can all choose the products that provide us with the most enjoyment.

We hope that you'll like the updated reviews. As always, we want to hear from you; your feedback is key to how test benches evolve!

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Classification of lakebed geologic substrate in autonomously collected benthic imagery using machine learning

Mapping benthic habitats with bathymetric, acoustic, and spectral data requires georeferenced ground-truth information about habitat types and characteristics. New technologies like autonomous underwater vehicles (AUVs) collect tens of thousands of images per mission making image-based ground truthing particularly attractive. Two types of machine learning (ML) models, random forest (RF) and deep neural network (DNN), were tested to determine whether ML models could serve as an accurate substitute for manual classification of AUV images for substrate type interpretation. RF models were trained to predict substrate class as a function of texture, edge, and intensity metrics (i.e., features) calculated for each image. Models were tested using a manually classified image dataset with 9-, 6-, and 2-class schemes based on the Coastal and Marine Ecological Classification Standard (CMECS). Results suggest that both RF and DNN models achieve comparable accuracies, with the 9-class models being least accurate (~73–78%) and the 2-class models being the most accurate (~95–96%). However, the DNN models were more efficient to train and apply because they did not require feature estimation before training or classification. Integrating ML models into benthic habitat mapping process can improve our ability to efficiently and accurately ground-truth large areas of benthic habitat using AUV or similar images.

Citation Information

Publication Year	2024
Title	Classification of lakebed geologic substrate in autonomously collected benthic imagery using machine learning
DOI
Authors	Joseph K. Geisz, Phillipe Alan Wernette, Peter C. Esselman
Publication Type	Article
Publication Subtype	Journal Article
Series Title	Remote Sensing
Index ID
Record Source
USGS Organization	Great Lakes Science Center

Range maps and waterbody occupancy data for 1158 freshwater macroinvertebrate genera in the contiguous USA

Ethan A. Brown ORCID: orcid.org/0000-0003-0827-4906 1 ,
Ronald A. Hellenthal 1 ,
Michael B. Mahon 2 ,
Samantha L. Rumschlag 2 &
Jason R. Rohr ORCID: orcid.org/0000-0001-8285-4912 1

Scientific Data volume 11 , Article number: 993 ( 2024 ) Cite this article

Metrics details

Biogeography
Freshwater ecology

Range maps are used to estimate the geographic extent of taxa, providing valuable information for biodiversity and conservation research and management. Freshwater macroinvertebrates are not well-represented in the range map literature relative to freshwater vertebrates. To address this knowledge gap, we provide range maps for 1158 freshwater macroinvertebrate genera based on two decades of publicly available occurrence data from the USEPA National Aquatic Resource Surveys, which included 11,628 sites and 6,906,990 organisms across the contiguous USA. Maps were created by applying unweighted and weighted pair group method with arithmetic mean clustering and single-linkage clustering algorithms to the occurrence data and creating three layers of polygons from the minimum convex hulls of clusters. A total of 25 freshwater macroinvertebrate classes are represented in the range map dataset. Most mapped genera were insects (394/1158), followed by malacostracans (242/1158), polychaetes (182/1158), and bivalves (121/1158). Additionally, we provide waterbody type percent occupancy data for all genera, detailing how genera are partitioned between boatable streams, wadeable streams, inland lakes, Laurentian Great Lakes, and coastal estuaries.

A database of freshwater macroinvertebrate occurrence records across Cuba

Environmental DNA reveals the fine-grained and hierarchical spatial structure of kelp forest fish communities

Protected areas are not effective for the conservation of freshwater insects in Brazil

Background & summary.

Taxonomic range maps are commonly used in ecology for spatial modelling 1 , 2 , characterizing species richness 2 , 3 , 4 , and aiding in conservation efforts 2 , 5 . The International Union for Conservation of Nature (IUCN) hosts the largest database of expert-drawn range maps and makes them freely available for research applications 4 , 6 . This IUCN repository contains thousands of range maps for mammals, birds, reptiles, amphibians, and fishes 6 .

Historically, range maps consist of polygons that are hand-drawn by experts and are often based on textual range descriptions, country-level occurrence information, museum records, or a combination of regional-scale maps or recorded occurrences compiled from multiple sources. Using these approaches, maps can be slow and costly to produce and may not be directly derived from standardized occurrence data 2 , 7 , 8 . While extensive, the IUCN range map database does not contain maps for certain taxonomic groups, including freshwater benthic macroinvertebrates. Thus, to fill the large gaps in range map availability for underrepresented taxa, it would be useful to automate range map creation by using computational methods in conjunction with occurrence data collected via a spatially balanced, randomized sampling design 1 , 7 , 9 .

Among the least documented groups in the range map literature are aquatic macroinvertebrates 6 . To address this knowledge gap, we harnessed two decades of macroinvertebrate occurrence data from the USEPA National Aquatic Resource Surveys (NARS) 10 to generate range maps for freshwater macroinvertebrate genera in the contiguous United States. The NARS database includes benthic macroinvertebrate sampling data from (1) the National Rivers and Streams Assessment (NRSA), comprised of three nationwide survey cycles of boatable and wadeable streams occurring from 2008–2009, 2013–2014, and 2018–2019; (2) the National Coastal Condition Assessment (NCCA), comprised of four nationwide survey cycles from both US estuaries and the Great Lakes occurring in 1999–2000, 2005–2006, 2010, and 2015; and (3) the National Lakes Assessment (NLA), comprised of three nationwide survey cycles of freshwater lakes occurring in 2007, 2012, and 2017. Each of these NARS programs employed a probabilistic sampling design to provide spatially unbiased data across the contiguous USA 11 , 12 , 13 (Fig. 1 ).

Number of macroinvertebrate genera detected at each National Aquatic Resource Surveys (NARS) sampling site across all sampling dates. We used all benthic macroinvertebrate data from the National Coastal Condition Assessment (NCCA) (1999–2000, 2005–2006, 2010, 2015), National Lakes Assessment (NLA) (2007, 2012, 2017), and National Rivers and Streams Assessment (NRSA) (2008–2009, 2013–2014, 2018–2019) programs, resulting in a total of 11,628 surveyed sites.

Range maps consist of three layers of convex polygons, each corresponding to a different spatial scale (broad-scale, region-scale, hotspot). By generating three polygon layers, these maps address a wide range of uses in aquatic research and management by providing users with multiple abstractions for the range of each macroinvertebrate genus.

Data acquisition

We acquired NLA and NCCA source data through the NARS Data Download Tool, available at https://owshiny.epa.gov/nars-data-download/ . We acquired the NRSA data through the ‘finsyncR’ R package 14 which streamlines the data gathering and cleaning process for the NRSA dataset based on the user’s specific needs. The NLA and NCCA data were cleaned using the same methodology as ‘finsyncR’ (see ‘ Data Cleaning and Filtering ’). We used all data for benthic macroinvertebrates for each survey cycle of NRSA, NLA, and NCCA.

Data cleaning and filtering

After verifying that the taxonomy in the NARS data were current and accurate (see ‘Technical Validation’), we applied filtering criteria to ensure that we were accurately estimating the geographic extent of each genus while also avoiding over- or under-representing the range of any one genus. The goal of filtering was to ensure that range estimates were not biased in favour of certain genera or groups of genera, thus ensuring that the maps are statistically robust and appropriate for use in spatial analysis.

First, to account for differences in sampling effort between NARS sampling events and to ensure that range estimates were consistent between genera, we removed data for a handful of samples with extremely low rates of genus-level identification or area sampled (column ‘PropID’ in the occurrence data). Specifically, we removed samples where less than 5.5% of organisms were identified to genus. This is an important filtering criterion because it avoids biasing the occurrence data in favor of a small number of identified genera when the sample contained many other specimens that were not identified to genus. The area sampled criterion (column ‘AreaSampTot_m2’ in the occurrence data) differed based on the sampling methods of each NARS program: for NRSA we removed samples with less than 0.74 m 2 sampled; for NLA we removed samples with less than 2.74 m 2 sampled; and for NCCA we removed samples with less than 0.04 m 2 sampled. These combined criteria removed data for 724 NARS sampling events, or 4.9% of all samples.

Next, because it can be unreliable to generate range maps based on small amounts of occurrence data, we removed data for exceedingly rare genera that had not been detected at least 10 occasions across at least five sampling locations, resulting in the removal of 602 genera from the dataset. Then, we removed data for any taxon that had not been identified to the genus level in the NARS source data or had been ambiguously identified using ‘slash’ names (i.e. Genus A/Genus B). After that, we identified clusters of genera that have undergone genus lumping or splitting over the survey period (1999–2019) using the methods described in the ‘finsyncR’ R package documentation 14 and Rumschlag et al . 15 . After identifying these clusters or ‘lumped’ genera, we removed any cluster containing more than two genus names. This criterion resulted in the removal of six lumped groups containing a total of 50 genera, thereby reducing uncertainty due to mapping genera that have undergone frequent taxonomic reclassifications. Maps for a total of 33 ‘lumped’ genera are included in the database.

Finally, to ensure maps were not biased against any major taxonomic groups we performed additional filtering to determine whether (1) making genus-level identifications was less common for certain orders and whether (2) the ability of taxonomists to identify genera within some orders has improved over time. To identify such orders, we calculated the proportion of specimens identified to genus within each order and removed data for orders that showed (1) low overall identifications at the genus level or (2) a steep temporal increase in the proportion of organisms identified to genus (Figs. S1 – S3 ). By excluding these orders, an additional 146 genera were removed from the dataset, thereby reducing the likelihood that range maps represent some orders better than others. The resulting dataset contained occurrence data for 1158 freshwater macroinvertebrate genera. Figure 2 and Table 1 summarize the taxonomy of mapped genera by class, order, and family.

Summary of insect orders and families represented in the range map database. For each order, the three families with the highest number of genera were labelled with the exception of Megaloptera, Lepidoptera, and Neuroptera which had relatively few genera represented in the National Aquatic Resource Surveys (NARS) data. Insects were the most common taxonomic class mapped as part of this work, representing 394 out of 1158 macroinvertebrate genera. It should be noted that NARS sampling targeted aquatic habitats, thus, genera with terrestrial lifestages will not be fully represented by range maps. Insect images sourced from Wikimedia Commons users Rolf Dietrich Brecher, Udo Schmidt, Dick Belgers, Jakub Halun, Frank Vassen, Andrew Cattoir, Syrio, Ilia Ustyantsev, Biodehio, and Alvesgaspar.

Map and shapefile creation

Using the filtered occurrence data, we generated maps and shapefiles representing the geographic range of each genus (Fig. 3 ), defined as any location where the genus was detected over the survey period (1999–2019). This process consisted of two primary steps: (1) defining clusters of occurrence data for each genus and (2) creating polygons based on each cluster to estimate the spatial extent of each taxon.

Range map creation workflow diagram ( A ) and example range map ( B ). The workflow diagram shows each step involved in generating the broad-, regional-, and hotspot-scale polygons, including (1) clustering of occurrence data, (2) creation of polygons around each cluster via the minimum convex hull approach, (3) clipping polygons based on HUC boundaries, and (4) clipping polygons based on sampling region. The maps were generated by plotting all three polygon layers with the occurrence and absence (or non-detect) data. The shape of each point indicates the National Aquatic Resource Surveys (NARS) program associated with the occurrence record. For guidance on use and interpretation of each polygon layer, see ‘Interpretation and Use of Each Polygon Layer’. For details on how each layer of polygons was created, see ‘Map and Shapefile Creation’.

First, we selected cluster and polygon creation methods based on precision and accuracy scores, as calculated through cross-validation (see ‘Technical Validation’). Using the results of the cross-validation we determined the optimal polygon generation methods to (1) represent broad-scale patterns (e.g. ‘West Coast’, ‘Midwest’, ‘East Coast’), (2) represent region-scale patterns (e.g. ‘Great Lakes Region’, ‘Pacific Northwest’), and (3) represent hotspots, i.e. areas where there is a high likelihood of detecting a given genus.

Each of the three polygon layers used a different clustering algorithm selected from the cross-validation results. We used Euclidean distance for all clustering operations. For the broad-scale polygons we used single-linkage (SL) clustering (a.k.a. nearest neighbour). For the region-scale polygons we used weighted pair group method with arithmetic mean (WPGMA). For the hotspot-scale polygons we used unweighted pair group method with arithmetic mean (UPGMA) clusters. WPGMA defines clusters by calculating the average distance between all points in two clusters and only joining these clusters if the average distance falls within a defined distance threshold 16 . UPGMA is similar to WPGMA, except a weighting criteria is also applied when averaging the distance between clusters, giving more weight to clusters with more data. SL clustering is a less conservative form of hierarchical clustering that aggregates groups of points based on a friends-of-friends approach; in other words, points will be iteratively added to a cluster if any points in the cluster are within a defined distance threshold of another point. SL clustering often results in larger polygons that can be more elongate in shape, as opposed to polygons generated through a more conservative algorithm such as UPGMA or WPGMA 16 .

Next, we calculated minimum convex polygons for each genus, a common practice in the range maps literature 9 , 17 , 18 , 19 , 20 . Minimum convex polygons, also called convex hulls, represent the smallest polygon around a group of points for which no angle exceeds 180 degrees 20 .

Then, using the quantitative selection criteria described in ‘Technical Validation’, we generated three range map polygon layers. To represent hotspot-scale occurrence, we used polygons with a 200-km UPGMA clustering threshold, for region-scale occurrence patterns we used polygons with a 800-km WPGMA clustering threshold; and for broad-scale patterns we used polygons with a 800-km SLC threshold.

Finally, we conducted a two-phase clipping approach on the polygons: phase one involved clipping polygons to the appropriate Hydrologic Unit Code (HUC) boundaries and phase two involved clipping polygons to the relevant NARS sampling region. For phase one, we clipped the regional-scale polygons to include only the basins (6-digit HUC boundaries) where the genus occurred and hotspot-scale polygons to the sub-basins (8-digit HUC boundaries) where the genus occurred. Broad-scale polygons were not clipped to any HUC boundaries. For phase two, we clipped polygons based on which NARS program(s) the occurrence data associated with the polygon originated from. For polygons derived from NLA and/or NRSA data, we clipped the polygons to the border of the contiguous USA, excluding the Great Lakes. For polygons derived from NCCA data only, we clipped polygons to coastal zones of the contiguous USA and the Great Lakes, as defined by the National Oceanic and Atmospheric Administration (NOAA) Coastal Zone Management Act boundaries 21 . For polygons derived from NCCA and either NRSA or NLA data, we clipped polygons to the combined extent of the contiguous US and all coastal or Great Lakes areas.

After generating polygons, we created the final visualization of the range maps by overlaying all three polygon layers for each genus. The maps also depict point-occurrence data and non-detect data (Fig. 3 ). We provide polygons for each genus as both maps (as *.pdf files) and shapefiles (as *.gpkg files). We also provide occurrence data used to generate maps (as *.csv file).

Waterbody type occupancy data

To supplement the range maps, we calculated the percent waterbody type occupancy for each genus, defined as the relative distribution of a genus among each of the sampled waterbody types as part of the NARS data, adjusted based on sampling effort. The five waterbody types were boatable rivers and streams, wadeable streams, inland lakes, Laurentian Great Lakes, and coastal estuaries. We calculated percent occupancy using Eq. 1 ,

where H ij is the percent occupancy of genus i in waterbody type j ; L ij is the number of NARS sites for waterbody type j where genus i was detected; L i is the total number of sites where genus i was detected; L is the total number of sites in the NARS dataset; and L j is the total number of NARS sites for waterbody type j .

After calculating percent occupancy for all genera, we discovered that 62.0% of genera are specialists (taxa that occupy only a single waterbody type); 14.1% of genera occupy two out of five waterbody types; 14.5% of genera occupy three out of five waterbody types; 5.2% of genera occupy four out of five waterbody types; and 4.2% of genera occupy all five waterbody types. Figure 4 shows the distribution and overlap of the number of genera that occupy each waterbody type.

Venn diagram showing the distribution of genera between the waterbody types represented in the National Aquatic Resource Surveys (NARS) data. Values represent the number of genera that occupy waterbody type or types.

Data Records

All data, code, metadata, shapefiles, and maps are available through the Figshare links referenced below. The repository includes the following items: (1) PDF files containing maps for each macroinvertebrate genus in the NARS dataset, visualized in three ways: a) only range polygons plotted b) range polygons and occurrence data plotted, and c) range polygons, occurrence, and non-detect data plotted 22 ; (2) Shapefiles in GeoPackage (*.gpkg) format for all broad-, region-, and hotspot-scale polygons with attribute data describing taxonomic classification of the genus up to the phylum level 23 ; (3) cleaned and filtered NARS benthic macroinvertebrate occurrence data used to generate polygons and maps 24 ; (4) waterbody type occupancy statistics for each genus 25 ; and (5) R code used to create maps and shapefiles 26 ;, (6) a CSV file listing all genera in the database with taxonomic classification data up to the phylum level 27 , and (7) a metadata document describing each of the aforementioned items in greater detail including definitions for all columns and attributes 28 .

The occurrence data can be directly linked back to the NARS source data using the columns ‘SiteNumber’ (called ‘SITE_ID’ in the source data) and ‘CollectionDate’ (called ‘DATE_COL’ in the source data). As part of the data cleaning process, some columns from the source data have been either renamed or removed. All column definitions, in addition to the source code for cleaning NARS data, can be found in Mahon et al . 14 and its associated Git repository.

Technical Validation

Taxonomy qa.

To confirm that all genus names were current and correct, we cross checked all genus names in the NARS dataset with both the Global Biodiversity Information Facility (GBIF) database 29 , the National Center for Biotechnology Information (NCBI) database 30 , the Integrated Taxonomic Information System (ITIS) database 31 using the ‘taxize’ package in R 32 . Additionally, we performed taxonomy checks using MolluscaBase 33 and the World Register of Marine Species (WoRMS) 34 , both of which are considered international authorities on up-to-date taxonomic classification information and can also be useful in identifying synonymous genus names. Using these databases, we were able to identify and resolve multiple instances of synonymous genus names, outdated higher classifications of genera, and genus names that are no longer recognized as legitimate. We removed data for any genus that did not return an exact match from any of the aforementioned databases.

Clustering method cross validation

To determine the most appropriate methods for generating polygons in range maps, we randomly separated occurrence data into training (90% of data) and testing (remaining 10% of data) datasets and conducted cross validation. Cross validation consisted of (1) defining clusters of occurrence data based on the training dataset, (2) creating polygons based on those clusters, and (3) calculating accuracy and precision scores for the clustering method using the training polygons and the testing dataset, as described below.

For our purposes we define the accuracy score of a clustering method as the proportion of data points in the training data that fell within the polygons generated from the testing data, i.e. Equation 2 :

where N test is the size of the test dataset and N poly is the number of records in the test dataset that fell within the training polygons. Thus, accuracy scores represent the reliability with which polygons predict the occurrences of a genus. We define the precision score of a clustering method as follows:

where E poly is the number of non-detects that fell within the training polygons, or the number of NARS sites where the genus was not detected, and E tot is the total number of non-detects. The precision score of a clustering method represents the degree to which the polygons exclude sites where the genus has never been detected.

We calculated accuracy and precision scores for a total of 70 unique clustering methods, testing seven clustering algorithms (SL, UPGMA, WPGMA, Ward, CL, UPGMC, WPGMC) crossed with ten distance thresholds (25, 50, 100, 200, 300, 400, 500, 600, 700, 800 km). First, we calculated the accuracy and precision scores for each of the 1158 genera in the NARS data. For each genus, we ran 50 simulations of the cross validation, re-randomizing the training and testing data for each iteration. Then, we averaged the accuracy and precision scores from the 50 simulations to get the genus-level accuracy and precision for the clustering method. Finally, we averaged the genus-level accuracy and precision scores ( n = 1158) to get the overall accuracy and precision scores for each clustering method. The results of our cross validation are depicted in the supplement of this manuscript (Figs. S4 , S5 ).

For the broad-scale polygons we used the clustering method with the highest accuracy score without a precision score less than 0.25. SL clustering with a threshold of 800 km met these criteria with an accuracy score of 0.74, the highest accuracy of all tested methods, and a precision score of 0.8.

For the region-scale polygons we selected the polygon method with the highest combined accuracy and precision score with an accuracy score greater than 0.5. We excluded SL clustering from consideration for region-scale polygons because SL clustering is a less conservative approach than many of the average-linkage methods and can lead to large, elongate polygons that often do not accurately represent region-scale occurrence patterns. Thus, the clustering method that best met the criteria for region-scale polygons was WPGMA clustering with a threshold of 800 km which had an accuracy score of 0.68 and a precision score of 0.78.

Finally, to select a method for hotspot-scale polygons, we chose the polygon method with the highest precision, without a decrease in accuracy of more than 0.1 from the next highest distance threshold and did not have a precision score below 0.25. For example, if a clustering method had an accuracy of 0.5 at a 300 km threshold, 0.41 at a 200 km threshold, and 0.3 at 100 km, then the 200 km clustering method would be selected, as the 100 km method resulted in an accuracy decrease of 0.11 which violates the criterion. Based on these criteria, the best clustering method for the hotspot-scale was UPGMA clustering with a 200 km threshold. This result aligns with previous work that has demonstrated that the optimal spatial resolution for hotspot delineation is approximately 200 km 3 .

Usage Notes

The macroinvertebrate range maps accompanying this manuscript were generated using every location where each genus was detected across the entire temporal extent of the dataset. Users who wish to know the geographic range of a genus within a specific timeframe can generate new maps using the provided R code with the NARS data, filtering occurrence data to include only the timeframe of interest, however, because new sites were selected for each NARS survey cycles, users should be aware that timeframe-specific maps may not estimate genus ranges as extensively or accurately as the time-aggregated maps we provide.

It is also possible to generate maps for higher levels of biological organization. The occurrence data contain taxonomic information for each genus up to the phylum level. To generate these higher-order maps, users should aggregate data based on their desired level of biological organization, then re-generate polygons using the cross-validation and clustering methods described in this manuscript.

Interpretation and use of each polygon layer

Each range map is composed of three polygon layers, each providing an abstraction of the genus range at a different spatial scale. When interpreting polygons or using the associated shapefiles for modelling or statistical analysis, users should be aware of the limitations of each layer. For example, when performing analyses at large spatial scales (e.g. estimating genus richness across the US), hotspot-scale polygons may provide an overly-conservative estimate of genus ranges as compared to region- or broad-scale polygons. Conversely, broad- or regional-scale polygons may not be appropriate for analyses at smaller scales (e.g. predicting macroinvertebrate assemblages at specific locations).

Range map limitations and caveats

When using the provided maps and shapefiles, users should be aware of a few key limitations: First, the NARS data were mostly collected during summer, thus, genera that are more abundant during colder seasons may not be well-represented by these data (e.g., genera within Taeniopterygidae [winter stoneflies]). Additionally, taxa that primarily rely on temporary waters as a breeding habitat, e.g. Aedes spp ., may not be well-represented if the NARS sampling did not occur during dry periods when these habitats are not present. Finally, because NARS sampling only included aquatic environments, genera with a terrestrial adult lifestage (e.g. many orders of insects including Ephemeroptera, Plecoptera, and Odonata) will not be fully represented by range estimates, in other words, these maps only estimate the geographic extent of immature lifestages.

Code availability

All code for map creation is provided in the Figshare repository 26 that accompanies this manuscript. We generated maps and shapefiles using packages ‘sp 1.6-0’ 35 , ‘sf 1.0-9’ 36 , and ‘raster 3.6-14’ 37 in R version 4.2.2 38 using RStudio version 2021.9.2.382 39 .

Jetz, W., Sekercioglu, C. H. & Watson, J. E. Ecological correlates and conservation implications of overestimating species geographic ranges. Conserv. Biol. 22 , 110–119, https://doi.org/10.1111/j.1523-1739.2007.00847.x (2008).

Article PubMed Google Scholar

Marsh, C. J. et al . Expert range maps of global mammal distributions harmonised to three taxonomic authorities. J. Biogeogr. 49 , 979–992, https://doi.org/10.1111/jbi.14330 (2022).

Article PubMed PubMed Central Google Scholar

Hurlbert, A. H. & Jetz, W. Species richness, hotspots, and the scale dependence of range maps in ecology and conservation. PNAS 104 , 13384–13389, https://doi.org/10.1073/pnas.0704469104 (2007).

Article ADS CAS PubMed PubMed Central Google Scholar

Marechaux, I., Rodrigues, A. S. L. & Charpentier, A. The value of coarse species range maps to inform local biodiversity conservation in a global context. Ecography 40 , 1166–1176, https://doi.org/10.1111/ecog.02598 (2017).

Article ADS Google Scholar

O’Connor, D. et al . Updated geographic range maps for giraffe, Giraffa spp., throughout sub‐Saharan Africa, and implications of changing distributions for conservation. Mamm. Rev. 49 , 285–299, https://doi.org/10.1111/mam.12165 (2019).

Article Google Scholar

IUCN. Spatial Data and Mapping Resources . IUCN https://www.iucnredlist.org/resources/spatial-data-download (2022).

Huang, R. M. et al . Batch-produced, GIS-informed range maps for birds based on provenanced, crowd-sourced data inform conservation assessments. Plos One 16 , https://doi.org/10.1371/journal.pone.0259299 (2021).

IUCN. Mapping Standards and Data Quality for IUCN Red List Spatial Data . IUCN https://www.iucnredlist.org/resources/mappingstandards (2021).

Joppa, L. N. et al . Impact of alternative metrics on estimates of extent of occurrence for extinction risk assessment. Conserv. Biol. 30 , 362–370, https://doi.org/10.1111/cobi.12591 (2016).

USEPA Office of Water and Office of Research and Development. Manuals Used in the National Aquatic Resource Surveys. USEPA https://www.epa.gov/national-aquatic-resource-surveys/manuals-used-national-aquatic-resource-surveys (2007).

USEPA Office of Water and Office of Research and Development. NRSA 2008-09 Field Operations Manual. USEPA https://www.epa.gov/national-aquatic-resource-surveys/national-rivers-streams-assessment-2008-2009-field-operations (2008).

USEPA Office of Water and Office of Research and Development. NCCA 2015 Field Operations Manual. USEPA https://www.epa.gov/national-aquatic-resource-surveys/national-coastal-condition-assessment-2015-field-operations-0 (2015).

USEPA Office of Water and Office of Research and Development. NLA 2017 Field Operations Manual. USEPA https://www.epa.gov/national-aquatic-resource-surveys/national-lakes-assessment-2017-field-operations-manual (2017).

Mahon, M. B. et al . finsyncR, an R package to synchronize 27 years of fish and invertebrate data across the United States. bioRxiv , https://doi.org/10.1101/2024.02.22.581615 (2024).

Rumschlag, S. L. et al . Density declines, richness increases, and composition shifts in stream macroinvertebrates. Sci. Adv. 9 , eadf4896, https://doi.org/10.1126/sciadv.adf4896 (2023).

Kreft, H. & Jetz, W. A framework for delineating biogeographical regions based on species distributions. J. Biogeogr. 37 , 2029–2053 (2010).

Graham, C. H. & Hijmans, R. J. A comparison of methods for mapping species ranges and species richness. Glob. Ecol. Biogeogr. 15 , 578–587 (2006).

Hatchwell, B., Anderson, C., Ross, D., Fowlie, M. & Blackwell, P. Social organization of cooperatively breeding long-tailed tits: kinship and spatial dynamics. J. Anim. Ecol ., 820–830 (2001).

Okarma, H. et al . Home ranges of wolves in Białowieża Primeval Forest, Poland, compared with other Eurasian populations. J. Mammal. 79 , 842–852 (1998).

Burgman, M. A. & Fox, J. C. in Animal Conservation Forum . 19–28 (Cambridge University Press).

Office for Coastal Management. Coastal Zone Management Act Boundary. National Oceanic and Atmospheric Administration https://www.fisheries.noaa.gov/inport/item/53132 (2024).

Brown, E. A., Hellenthal, R. A., Mahon, M. B., Rumschlag, S. L. & Rohr, J. R. Benthic Macroinvertebrate Range Maps. Figshare https://doi.org/10.6084/m9.figshare.25517416 (2024).

Brown, E. A., Hellenthal, R. A., Mahon, M. B., Rumschlag, S. L. & Rohr, J. R. Benthic Macroinvertebrate Range Map Shapefiles. Figshare https://doi.org/10.6084/m9.figshare.25517437 (2024).

Brown, E. A., Hellenthal, R. A., Mahon, M. B., Rumschlag, S. L. & Rohr, J. R. Filtered NARS Occurrence Data for Range Maps. Figshare https://doi.org/10.6084/m9.figshare.25517455 (2024).

Brown, E. A., Hellenthal, R. A., Mahon, M. B., Rumschlag, S. L. & Rohr, J. R. Benthic Macroinvertebrate Waterbody Occupancy Data. Figshare https://doi.org/10.6084/m9.figshare.25517470 (2024).

Brown, E. A., Hellenthal, R. A., Mahon, M. B., Rumschlag, S. L. & Rohr, J. R. R Code to Generate Benthic Macroinvertebrate Range Maps. Figshare https://doi.org/10.6084/m9.figshare.25517494 (2024).

Brown, E. A., Hellenthal, R. A., Mahon, M. B., Rumschlag, S. L. & Rohr, J. R. Taxonomic Classification Data for Benthic Macroinvertebrates. Figshare https://doi.org/10.6084/m9.figshare.25517482 (2024).

Brown, E. A., Hellenthal, R. A., Mahon, M. B., Rumschlag, S. L. & Rohr, J. R. Metadata Document for Range Maps and Other Supplemental Materials. Figshare https://doi.org/10.6084/m9.figshare.25517485 (2024).

Global Biodiversity Information Facility (GBIF). What is GBIF? https://www.gbif.org/what-is-gbif (2023).

Schoch C. L et al . NCBI Taxonomy: a comprehensive update on curation, resources and tools. Database (Oxford) , https://doi.org/10.1093/database/baaa062 (2020).

Shaw, C. A. in Navigating the Shoals: Evolving User Services in Aquatic and Marine Science Libraries: Proceedings of the 29th Annual Conference of the International Association of Aquatic and Marine Science Libraries and Information Centers (IAMSLIC) . 17 (IAMSLIC).

Chamberlain, S. et al . Package ‘taxize’: Taxonomic Information from Around the Web. CRAN https://cran.r-project.org/web/packages/taxize/index.html (2017).

Bank, R. A. et al . MolluscaBase–announcing a World Register of all Molluscs. (2014).

Costello, M. J. et al . Global coordination and standardisation in marine biodiversity through the World Register of Marine Species (WoRMS) and related databases. Plos One 8 , e51629 (2013).

Pebesma, E. et al . Package ‘sp’: Classes and methods for spatial data in R. CRAN https://cran.r-project.org/web/packages/sp/index.html (2024).

Pebesma, E. et al . Package ‘sf’: Simple Features for R. CRAN https://cran.r-project.org/web/packages/sf/index.html (2024).

Hijmans, R. J. et al . Package ‘Raster’: Geographic data analysis and modeling. CRAN https://cran.r-project.org/web/packages/raster/index.html (2023).

R Development Team. R: A language and environment for statistical computing (R Foundation for Statistical Computing, Vienna, Austria, 2022).

RStudio Development Team. RStudio: Integrated Development for R v. 2021.9.2.382 (RStudio, PBC, Boston, MA, 2022).

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Acknowledgements

Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. government. The findings and conclusions here do not necessarily represent the views or policies of the U.S. Environmental Protection Agency. We are indebted to the federal, state, and tribal biologists and contractors who planned the USEPA NARS surveys, collected the samples in the field, and processed and identified samples. This work was conducted as part of the Analyses of Contaminant Effects in Freshwater Systems: Synthesizing Abiotic and Biotic Stream Datasets for Long-Term Ecological Research Working Group supported by the John Wesley Powell Center for Analysis and Synthesis, funded by the U.S. Geological Survey.

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Ethan A. Brown, Ronald A. Hellenthal & Jason R. Rohr

U.S. EPA Office of Research and Development, Center for Computational Toxicology and Exposure, Great Lakes Toxicology and Ecology Division, 6201 Congdon Blvd., Duluth, MN, USA

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Contributions

All authors helped to conceptualize and plan the project. E.A.B. cleaned and compiled the NLA and NCCA data, prepared the mapping code, and generated all maps and shapefiles. S.L.R. and M.B.M. cleaned and compiled all NRSA data and provided guidance and insights regarding the use of NARS data. R.A.H. updated the taxonomic classification info based on the most current groupings and provided valuable input on map presentation and organization. E.A.B. wrote the manuscript and created figures. All authors provided feedback and revisions to the manuscript.

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Correspondence to Ethan A. Brown .

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Published: 11 September 2024

Physician retention and migration in rural clinics designated for areas without physicians in Japan: descriptive epidemiological study using the national physicians’ survey

Hiroyuki Teraura 1 ,
Kazuhiko Kotani 1 &
Soichi Koike 2

BMC Health Services Research volume 24 , Article number: 1049 ( 2024 ) Cite this article

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In Japan, local governments have rural clinics designated for areas without physicians (RCDA) to secure physicians for rural medical care. Moreover, a medical policy of dispatching physicians between the RCDA and core hospitals for rural areas (CHRA) exists. This study aimed to assess the actual situation of physician migration from RCDAs and those who migrated, and examine the factors associated with their migration.

This retrospective cohort study used biennial national physicians’ survey data from 2012 to 2018. It targeted physicians who worked at RCDAs in 2012 and participated in all four surveys ( n = 510). The physicians were divided into two groups. One group consisted of physicians who worked continuously at the RCDA over the four study periods (retained physicians, n = 278), and the other included physicians who migrated to other institutions midway through the study period (migrated physicians, n = 232). We tracked the types of facilities where RCDA physicians worked from 2012 to 2018, also examined the factors associated with their migration.

Among physicians from RCDAs who migrated to other institutions ( n = 151) between 2012 and 2014, many migrated to hospitals ( n = 87/151, 57.6%), and some migrated to CHRA ( n = 35/87, 40.2%). Physicians in their 40s (Hazard ratio 0.32 [95% CI 0.19–0.55]), 50s (0.20 [0.11–0.35]), and over 60 years (0.33 [0.20–0.56]) were more likely to remain at RCDAs. Changes in their area of practice (1.82 [1.34–2.45]) and an increase in the number of board certifications held by physicians between 2012 and 2018 (1.50 [1.09–2.06]) were associated with migration.

Conclusions

Many migrating physicians choose to work at hospitals after migrating from RCDAs. It was seemed that the physician dispatch system between RCDA and CHRA has been a measure to secure physicians in rural areas. Young age, obtaining board certification, and changes in areas of practice were associated with physician migration from RCDAs.

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Introduction

Physicians are typically present in large numbers in urban areas. There is an urgent need to reduce the disparity in physician distribution across urban and rural areas and secure physicians in rural areas [ 1 , 2 , 3 ]. Many countries are trying to secure physicians in rural areas by providing incentives such as job placements and scholarships [ 4 , 5 , 6 ]. Moreover, only a few physicians continue to work in rural areas for a long time. So, strategies that retain physicians in rural areas must be implemented [ 7 , 8 ].

In Japan, each prefecture has formulated medical plans to ensure rural medical care [ 9 , 10 ]. These plans have established rural clinics designated for areas without physicians (RCDA, Hekichi-shinryojo in Japanese) [ 9 , 11 ]. RCDAs have been established in areas with a population of 1,000 or more, where residents live within approximately a 4 km radius of the central community and require more than 30 min to reach major medical institutions, even with ordinary transportation [ 9 , 11 ]. Japan does not have a gatekeeper system with primary care physicians [ 12 ], but patients typically visit a clinic first [ 13 ]. RCDAs are essential, as residents in these areas often find it difficult to visit other medical institutions. As of April 1, 2020, Japan had 1,113 RCDAs, but only 554 of these had regular physicians [ 14 ]. Moreover, 631 regular physicians were working at RCDAs [ 14 ]. Based on the medical plan, physicians are dispatched to RCDAs from core hospitals for rural areas (CHRA; Hekichi-iryo-kyoten-byoin in Japanese) [ 9 ]. CHRAs, designated by each prefecture, are required to send physicians to RCDAs to provide mobile medical care to rural residents [ 9 , 15 ]. Although a dispatch system for physicians exists, the strategies for recruiting physicians for RCDAs vary by prefecture, and physicians’ backgrounds vary widely [ 16 ]. For example, Jichi Medical University (JMU) was established by national and local governments to secure physicians for rural medical care, with their graduates receiving tuition exemption after completing a nine-year compulsory service period, including several years of rural service [ 17 ]. According to prefectural medical plans, these physicians can work in RCDAs during their mandatory service period. Physicians trained through scholarship programs from medical universities other than JMU can also fulfill their compulsory service in rural areas [ 6 ]. Physicians from medical educational institutions, including university hospitals, can be sent to RCDAs [ 18 ]. In other cases, the local government recruited physicians to the local RCDA.

Many RCDAs have limited medical resources, are located in rural areas, and are often staffed by solo practitioners [ 19 ]. Previous studies have reported that the factors that lead to the retention of physicians in rural areas are age, rural background, family or primary care physicians, multi-specialty rotation for postgraduate training, and administrative position [ 20 , 21 , 22 , 23 , 24 ]. These studies focused on physicians working in rural areas [ 20 , 21 , 22 , 23 ]. In this study, we focused on physicians in RCDAs, not just those in rural areas. They also played distinct roles in rural medical care. Understanding the retention and migration patterns of these physicians is essential when considering strategies for securing physicians in rural areas. This retrospective cohort study used data from national physician surveys conducted biennially from 2012 to 2018 to identify the actual migration patterns of physicians from RCDAs to other institutions and the differences in attributes between physicians who migrated and those who remained in RCDAs. We also explored factors associated with their retention and migration from RCDAs.

In Japan, the Ministry of Health, Labour and Welfare (MHLW) conducts a national survey titled “The Survey of Physicians, Dentists, and Pharmacists” (before 2016) or “The Statistics of Physicians, Dentists and Pharmacists” (since 2018), and according to the Medical Practitioners Act, every physician must declare their status every two years [ 25 , 26 , 27 , 28 ]. In this retrospective cohort study, we used the national survey guide, which was not specifically created for this study [ 25 , 26 , 27 , 28 ], analyzing data from four surveys conducted between 2012 and 2018. We sought permission from the MHLW to analyze parts of these surveys for research purposes, following procedures set out in the statistics act (approval dates: September 29, 2021, and November 15, 2021). The sample size for this study was determined by the number of respondents to the national survey. While the survey’s response rate has not been made public by the MHLW, it is estimated to be approximately 90% [ 29 ].

The survey data included registration number, sex, age, place of work, area of practice, and board certification status. All physicians provided their registration numbers, which were then anonymized by our research group by assigning unique identifiers. We established a cohort dataset using these numbers to track physicians during the study period. Exclusion criteria encompassed physicians who did not respond to questions regarding sex, age, place of work, or board certification status. Our study targeted physicians who worked at the RCDAs in 2012 and participated in all four surveys. First, we extracted data on the physicians registered in all four surveys from 2012 to 2018 ( n = 246,585). We excluded physicians who did not respond to survey questions about their place of work ( n = 2,479), resulting in a total of 244,106 physicians’ responses (80.5% of the 303,268 physicians who participated in the 2012 survey). Of these, none were missing data on sex, age, or board certification status. Next, the physicians were categorized according to their medical institutions. The institutions were categorized into clinics, medical education institutions (universities with medical schools or their affiliated institutions), hospitals (excluding hospitals affiliated with medical education institutions), healthcare facilities for older people requiring long-term care, other types of institutions, and others, according to the type of institution in the survey data.

Regarding the types of institutions in the survey data, RCDAs were included in the clinical classification, and CHRAs were included in the hospital classification. Classification of RCDAs and CHRAs was performed by creating and using a text reference program that matched the facility names in the physicians’ survey data with the RCDA names in the data published by the MHLW (as of April 1, 2020) [ 14 ]. Using this procedure, we estimated that 510 physicians worked at RCDAs in 2012, and the number of RCDAs in which these physicians worked was 442. It was considered a solo practice if an RCDA had only one registered physician. We then divided the data of physicians who worked in the RCDAs into two groups. One group consisted of physicians who worked at the RCDA throughout the four study periods (retained physicians, n = 278), and the other group included physicians who migrated to another type of institution midway through the study period (migrated physicians, n = 232). We then compared the physicians’ attributes. We also explored the factors associated with physician migration from RCDAs. Furthermore, we charted the types of facilities where RCDA physicians worked from 2012 to 2018.

The areas of practice and board certification were classified into three categories (internal medicine, surgery, and others), as shown in Table 1 , following a previous report [ 30 ]. The institutions that did not have an area of practice (e.g., health care facilities for older people requiring long-term care) and cases where the area of practice was unknown or remained unanswered in the survey were included in the “others” category (number of unknown responses or remained unanswered regarding area of practice: none in 2012; n = 22 in 2018). Since 2018, the MHLW has defined board certifications by general areas (Table 1 ) [ 31 ]. Before 2018, academic societies with boards and multiple board certifications in general fields were recognized [ 31 ]. Board certifications for psychiatry were not included in the 2012 survey, and laboratory medicine and general practice were not included in the statistics from 2012 to 2018. General practice was certified by the board of directors after the research period; therefore, there were no certified individuals during the research period. We compared physicians’ areas of practice categories in 2012 and 2018. If those categories were different, it was classified as “changes in area of practice.” We also compared the number of board certifications held by each physician in the general area in 2012 and 2018. The number of board certifications in general regions held by the physicians in 2012 and 2018 was classified as “increase,” “no change,” and “decrease.”

Additionally, we considered physicians who were not certified in the general area in 2012 but had at least one certification in the general area in 2018 as new board certification holders. The data were anonymized. If the number of physicians aggregated was under 10, the table marked it as “<10” to prevent individual identification.

Statistical analysis

Data were expressed as percentages if they were categorical variables or medians (interquartile range, IQR) if they were continuous variables. Categorical variables were analyzed using the chi-square or Fisher test and continuous variables using the Mann-Whitney test. When chi-square analysis revealed significant differences, residual analysis was performed. A multivariate Cox regression analysis was used to determine the factors associated with migration from RCDAs. The outcome was migration from the first RCDA. Exposures included the area of practice, board certification status, and solo practice. The covariates included in the multivariate Cox regression analysis were sex (male or female), age (categorized as 20s, 30s, 40s, 50s, and over 60), area of practice (categorized as internal medicine, surgery, or others), change in location of practice (“no change” or “change”), difference in the number of board certifications held by physicians in general areas between 2018 and 2012 (categorized as “no change”, “decreased”, or “increased”), and practice status (“group” or “solo practice”). This selection of covariates was determined by our research group based on factors that were significant at the P < 0.05 level in the comparison of the two groups, including sex and age. For the analysis, we used the forced entry method.

Additionally, since this study targeted physicians who participated throughout the study period, no physicians were lost to follow-up. We tracked the physicians for up to six years. Results are reported as adjusted hazard ratios (HR) with 95% confidence intervals (CI). IBM SPSS version 28.0 (IBM, Tokyo, Japan) was used for all the statistical analyses. The significance level was set at 5% for all analyses.

Migration of physicians from RCDAs

The migration of physicians working at the RCDAs in 2012 is shown via a flow chart in Fig. 1 . The number of physicians who did not migrate from RCDAs in each survey year was 359/510 (70.4%) in 2014, 300/359 (83.6%) in 2016, and 285/316 (90.2%) in 2018. When physicians from RCDAs migrated to other institutions ( n = 151) between 2012 and 2014, many migrated to hospitals ( n = 87, 57.6%); other hospitals ( n = 52, 34.4%), or CHRAs ( n = 35, 23.2%). Among the physicians who migrated in each survey year, the number of physicians who migrated to CHRAs was 35/151 (23.2%) in 2014 and 12/59 (20.3%) in 2016. The number of physicians in 2018 was not calculated because it < 10. Of the retained physicians, 25 (8.9%) were transferred between various RCDAs at least once.

Flow chart showing RCDA physicians’ migration patterns in 2012

Comparison between retained and migrated physicians

A comparison of the attributes of the retained and migrated physicians is shown in Table 2 . In 2012, the median age of RCDA physicians was 51 years (IQR 37–60). The median age in 2012 was significantly higher for retained physicians (54 [IQR 48–63]) than for migrated physicians (38 [IQR 31–56] years) ( P < 0.01; not stated in the table). In age distribution, a significantly higher proportion of retained physicians were in their 40s (retained physicians: 21.9% vs. migrated physicians: 14.2%), 50s (39.2% vs. 12.1%), and over 60 years (30.9% vs. 19.0%) compared to migrated physicians. The retained physicians had a significantly higher proportion of those who practiced internal medicine (88.5%) than the migrated physicians (82.3%). For the change in the number of board certifications held by physicians, the proportion of “no change” status was significantly higher among retained physicians (91.0%) than among the migrated physicians (67.2%). The retained physicians (4.7%) had a significantly lower proportion of “increase” in board certifications than migrated physicians (29.3%). The proportion of “new board certification holders” was significantly lower among retained physicians (4.3%) than among migrated physicians (28.4%). In descending order, the new board certification holders for the migrating physicians were internal medicine, surgery, pediatrics, orthopedics, and acute medicine. The percentage of physicians who changed their practice area was significantly lower among the retained physicians (5.8%) than among the migrated physicians (31.5%). Among the migrated physicians, the most common pattern of changing practice areas was from internal medicine to areas other than internal medicine and surgery for 50 physicians (68% of the 73 physicians changed their practice areas). The proportion of solo-practicing physicians was significantly higher among retained physicians (82.0%) than among migrated physicians (71.1%).

Factors associated with RCDA physicians’ retention and migration

Table 3 shows the factors associated with physician retention and migration at RCDAs. Physicians in their 40s (0.32 [0.19–0.55]), 50s (0.20 [0.11–0.35]), and over 60 years of age (0.33 [0.20–0.56]) showed a higher likelihood of staying in RCDAs. Conversely, increase in the number of board certifications (1.50 [1.09–2.06]) and changes in physicians’ areas of practice (1.82 [1.34–2.45]) were associated with a higher likelihood of migration.

Our study provides insights into the migration patterns among RCDA physicians and the factors associated with migration from RCDAs. Covering approximately 80% of regular physicians, estimated based on nationally published data on RCDA [ 14 ], our research depicts the migration situation within Japanese RCDAs. Furthermore, the results reveal previously undocumented destinations for these migrating physicians, providing deeper insights into the drivers of physician mobility [ 21 , 31 ].

Our study showed that some of physicians from the RCDAs were transferred to CHRAs. Approximately 20% of the physicians who migrated from RCDAs were transferred to CHRAs. When a CHRA sends physicians to an RCDA, the number of times a physician is dispatched is standardized (at least 12 times per year), although regulations regarding the dispatch period are not specific [ 15 ]. Furthermore, it is up to each RCDA to request hospitals to send physicians. Our results suggest that the transfer of physicians between CHRAs and clinics was recognized at a specific rate and that there were some physicians whose dispatch period was a few years. The physician dispatch system between the RCDA and the CHRA seemed to be a useful measure to secure physicians in rural areas.

Previous studies have shown that young age is associated with migration from rural areas [ 20 , 21 ]. These findings are consistent with those of the present study. In addition, our findings suggest that one of the reasons for younger physicians’ migration is associated with the timing of acquiring their board certification. In our study, many physicians migrated to hospitals after their tenure at RCDAs, following which they acquired board certifications. Typically, early-career physicians undergo training at designated hospitals to obtain board certification [ 22 , 32 , 33 , 34 ]; therefore it is common for young physicians to migrate from RCDAs to hospitals for this purpose. Another reason for migration could be that JMU graduates and other scholarship-trained physicians must practice in rural areas for approximately 3–5 years as a compulsory service [ 17 ]. These young physicians work in RCDAs to fulfill their mandatory service obligations. Furthermore, factors related to social environments, such as the educational needs of their children may also influence the migration decisions of these physicians [ 35 ].

Our results can be beneficial in developing strategies to retain physicians in rural clinics that support rural medical care, not only in Japan but also worldwide [ 36 ]. Physicians under 40 years of age working in rural areas are more likely to migrate to urban areas or other areas [ 37 , 38 ]. Young physicians may find acquiring board certifications more critical than extending their time in RCDAs. In designing the careers of young physicians, it may be essential to determine whether the timing of compulsory service in rural areas before or after acquiring board certification impacts retention. Further research is required to assess the impact of physicians’ work experience with RCDAs on their subsequent practice locations and career trajectories. Beyond long-term retention strategies, policymakers should consider implementing a rotation mechanism for physicians to ensure adequate coverage in RCDAs. Recently, a career development program for scholarship-trained physicians in Japan was introduced; this program is anticipated to provide ongoing support and planned placements for these physicians in rural settings, including RCDAs, while also facilitating career advancement opportunities such as their prospect of board certification while serving in rural areas [ 39 ]. Establishing a clear career progression for physicians in RCDAs could alleviate young physicians’ concerns about potential delays in obtaining board certification owing to RCDA postings, thereby leading to a smoother rotation of physicians within RCDAs.

The proportion of physicians who changed from their area of practice in internal medicine to areas other than internal medicine and surgery was higher among migrated physicians. Physicians in areas of practice other than internal medicine and surgery (e.g., radiology, anesthesiology, and acute medicine) have a tendency to work in urban areas [ 40 ]. Our results also showed that physicians not specializing in internal medicine were required to provide internal medicine care at RCDAs. Owing to the shortage of physicians in RCDAs, there may have been cases in which physicians’ board certifications and their actual practice areas differed.

Limitations

Our study has several limitations. First, the reasons physicians work in RCDAs and their migration needed clarification. Future research, possibly incorporating interviews or surveys that directly inquire about reasons for migration, such as the pursuit of certifications, is necessary. Second, because the statistical survey was conducted every two years, transfers made in less than two years were unknown. Therefore, the actual number of physicians who migrated could be higher than reported, as the survey may have included physicians who migrated from RCDAs and subsequently returned within two years. Third, the year of the national survey differed from the year of public data collection for the RCDAs. The RCDAs identified in this study may have included clinics not designated as RCDAs at the time of the national survey and may have excluded clinics that lost their designation post-survey. Fourth, the non-respondents likely included physicians working in RCDAs, potentially leading to an underestimation of the number of RCDA physicians in this study. However, the numbers of RCDAs and regular physicians have not changed substantially in recent years (RCDAs, n = 1,126; regular physicians in RCDAs, n = 653, as of April 2023) [ 41 ]. Despite these limitations, our results are considered to adequately represent the actual situation of RCDAs in Japan.

Many physicians choose to work at hospitals after migrating from RCDAs. The physician dispatch system between RCDAs and CHRAs seemed to be a measure for securing doctors in rural areas. Young age, board certification, and changes in areas of practice were associated with physicians’ migration from the RCDA. The results suggest that younger physicians initially worked in RCDAs and subsequently migrated to hospitals with intention of acquiring board certification in their chosen specialties. Further research is required to understand the effects of physicians’ work experience with RCDAs on their subsequent practice locations and careers.

Data availability

The data that support the findings of this study are available from the Ministry of Health, Labour and Welfare with restrictions to apply the others under license for the current study and are not publicly available. The data are not shared.

Abbreviations

confidence interval

Core hospitals for rural areas

Interquartile range

Hazard ratio

Jichi Medical University

Ministry of Health, Labour and Welfare

rural clinics designated for areas without physicians

Matsumoto M, Inoue K, Bowman R, Noguchi S, Toyokawa S, Kajii E. Geographical distributions of physicians in Japan and US: impact of the healthcare system on physician dispersal pattern. Health Policy. 2010;96:255–61.

Article PubMed Google Scholar

Tanihara S, Kobayashi Y, Une H, Kawachi I. Urbanization and physician maldistribution: a longitudinal study in Japan. BMC Health Serv Res. 2011;11:260. https://doi.org/10.1186/1472-6963-11-260 .

Article PubMed PubMed Central Google Scholar

Strasser R. Rural health around the world: challenges and solutions. Fam Pract. 2003;20:457–63.

Frehywot S, Mullan F, Payne PW, Ross H. Compulsory service programmes for recruiting health workers in remote and rural areas: do they work? Bull World Health Organ. 2010;88:364–70.

Matsumoto M, Kashima S, Owaki T, Iguchi S, Inoue K, Tazuma S, et al. Geographic distribution of regional quota program graduates of Japanese medical schools: a nationwide cohort study. Acad Med. 2019;94:1244–52.

Yoshida S, Matsumoto M, Kashima S, Owaki T, Iguchi S, Inoue K, et al. Emigration of regional quota graduates of Japanese medical schools to non-designated prefectures: a prospective nationwide cohort study. BMJ Open. 2019;9:e029335.

Matsumoto M, Okayama M, Kajii E. Rural doctors’ satisfaction in Japan: a nationwide survey. Aust J Rural Health. 2004;12:40–8.

PubMed Google Scholar

Goodfellow A, Ulloa JG, Dowling PT, Talamantes E, Chheda S, Bone C, et al. Predictors of primary care physician practice location in underserved urban or rural areas in the United States: a systematic literature review. Acad Med. 2016;91:1313–21.

Ministry of Health, Labour and Welfare. Measures for health and medical services in rural areas. 2001. https://www.mhlw.go.jp/web/t_doc?dataId=00ta6714&dataType=1&pageNo=1 . Accessed 25 Jan 2024.

Ministry of Health. LaW. Regional Health Care Plans. 2020. https://www.mhlw.go.jp/content/000622486.pdf . Accessed 25 Jan 2024.

Teraura H, Kotani K, Sato E, Koike S. The attributes of physicians assigned to rural clinics designated for areas without physicians in Japan. Tohoku J Exp Med. 2023;261:273–81.

Kaneko M, Matsushima M. Current trends in Japanese health care: establishing a system for board-certificated GPs. Br J Gen Pract. 2017;67:29.

Fukui T, Rahman M, Ohde S, Hoshino E, Kimura T, Urayama KY, et al. Reassessing the ecology of medical care in Japan. J Community Health. 2017;42:935–41.

Ministry of Health, Labour and Welfare. About rural medical care. 2020. https://www.mhlw.go.jp/stf/newpage_20900.html . Accessed 17 Nov 2021.

Ministry of Health, Labour and Welfare. Regarding medical systems related to diseases, business and home medical care. 2017. https://www.mhlw.go.jp/content/000846518.pdf . Accessed 25 Jan 2024.

Jichi Medical School. The White Paper on Community Healthcare. Tochigi: Jichi Medical School; 2002.

Google Scholar

Matsumoto M, Matsuyama Y, Kashima S, Koike S, Okazaki Y, Kotani K, et al. Education policies to increase rural physicians in Japan: a nationwide cohort study. Hum Resour Health. 2021;19:102.

Hara K, Kunisawa S, Sasaki N, Imanaka Y. Examining changes in the equity of physician distribution in Japan: a specialty-specific longitudinal study. BMJ Open. 2018;8:e018538.

Kuroda K, Kuroda M, Ohta R. Sources of anxiety in young rural physicians working alone on remote islands: a qualitative study. J Gen Fam Med. 2022;23:128–32.

Matsumoto M, Okayama M, Inoue K, Kajii E. Factors associated with rural doctors’ intention to continue a rural career: a survey of 3072 doctors in Japan. Aust J Rural Health. 2005;13:219–25.

Saijo Y, Yoshioka E, Sato Y, Kunori Y. Factors related to Japanese internal medicine doctors’ retention or migration to rural areas: a nationwide retrospective cohort study. Environ Health Prev Med. 2023;28:14.

Inoue K, Matsumoto M, Toyokawa S, Kobayashi Y. Transition of physician distribution (1980–2002) in Japan and factors predicting future rural practice. Rural Remote Health. 2009;9:1070.

Pathman DE, Steiner BD, Jones BD, Konrad TR. Preparing and retaining rural physicians through medical education. Acad Med. 1999;74:810–20.

Article CAS PubMed Google Scholar

Burnett WH, Mark DH, Midtling JE, Zellner BB. Primary care physicians in underserved areas. Family physicians dominate. West J Med. 1995;163:532–6.

CAS PubMed PubMed Central Google Scholar

Ministry of Health, Labour and Welfare. Survey of physicians, dentists and pharmacists 2012. 2012. https://www.mhlw.go.jp/english/database/db-hss/dl/spdp_2012.pdf . Accessed 10 Jun 2024.

Ministry of Health, Labour and Welfare. Survey of physicians, dentists and pharmacists 2014. 2014. https://www.mhlw.go.jp/english/database/db-hss/dl/spdp_2014.pdf . Accessed 10 Jun 2024.

Ministry of Health, Labour and Welfare. Survey of physicians, dentists and pharmacists 2016. 2016. https://www.mhlw.go.jp/english/database/db-hss/dl/spdp_2016.pdf . Accessed 10 Jun 2024.

Ministry of Health, Labour and Welfare. Statistics of physicians, dentists and pharmacists 2018. 2018. https://www.mhlw.go.jp/english/database/db-hss/dl/spdp_2018.pdf . Accessed 10 Jun 2024.

Shimada N, Kondo T. Ishi-Shikaishi-Yakuzaishi Chosa no kohyo data wo shiyou shita todokede ritsu no suikei [estimation of actual report rates using data from the survey of physicians, dentists, and pharmacists] Nihon Koshu Eisei Zasshi. [Jpn J Public Health]. 2004;51:117–32.

Ministry of Health, Labour and Welfare. Clinical training instructor questionnaire survey results. 2020. https://www.mhlw.go.jp/content/001000359.pdf . Accessed 25 Jan 2024.

Koike S, Matsumoto M, Kawaguchi H, Ide H, Atarashi H, Kotani K, et al. Board certification and urban-rural migration of physicians in Japan. BMC Health Serv Res. 2018;18:615.

Saito H, Tanimoto T, Kami M, Suzuki Y, Morita T, Morita M, et al. New physician specialty training system impact on distribution of trainees in Japan. Public Health. 2020;182:143–50.

Inoue K, Matsumoto M. Japan’s new postgraduate medical training system. Clin Teach. 2004;1:38–40.

Article Google Scholar

Koike S, Ide H, Yasunaga H, Kodama T, Matsumoto S, Imamura T. Postgraduate training and career choices: an analysis of the National Physicians Survey in Japan. Med Educ. 2010;44:289–97.

Parlier AB, Galvin SL, Thach S, Kruidenier D, Fagan EB. The road to rural primary care: a narrative review of factors that help develop, recruit, and retain rural primary care physicians. Acad Med. 2018;93:130–40.

Mohammadiaghdam N, Doshmangir L, Babaie J, Khabiri R, Ponnet K. Determining factors in the retention of physicians in rural and underdeveloped areas: a systematic review. BMC Fam Pract. 2020;21:216.

Vanasse A, Ricketts TC, Courteau J, Orzanco MG, Randolph R, Asghari S. Long term regional migration patterns of physicians over the course of their active practice careers. Rural Remote Health. 2007;7:812.

McGrail MR, Humphreys JS. Geographical mobility of general practitioners in rural Australia. Med J Aust. 2015;203:92–6.

Koike S, Okazaki K, Tokinobu A, Matsumoto M, Kotani K, Kataoka H. Factors associated with regional retention of physicians: a cross-sectional online survey of medical students and graduates in Japan. Hum Resour Health. 2023;21:85.

Matsumoto M, Inoue K, Bowman R, Kajii E. Self-employment, specialty choice, and geographical distribution of physicians in Japan: a comparison with the United States. Health Policy. 2010;96:239–44.

Ministry of Health, Labour and Welfare. Current status of rural medical care. 2023. https://www.mhlw.go.jp/content/10800000/001218845.xlsx . Accessed 10 Jul 2024.

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Acknowledgements

We thank Dr. Eiji Satoh (Professor, Department of Architecture and Urban Design, School of Regional Design, Utsunomiya University) for assistance in creating a program for the classification of institutions and the classification of institutions in the survey data.

This study was conducted with the support of the Ministry of Health, Labour and Welfare Science Research Grants (20IA1001 and 21IA1004).

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Hiroyuki Teraura & Kazuhiko Kotani

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HT conceived the study, performed the analysis, and drafted the manuscript. KK and SK interpreted the data and revised the manuscript. KK and SK supervised the study. All the authors have read and approved the final version.

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Correspondence to Kazuhiko Kotani .

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The Jichi Medical University Bioethics Committee for Medical Research approved this study (21–067). This study was conducted following the “Ethical Guidelines for Medical and Biological Research Involving Human Subjects” (Ministry of Education, Culture, Sports, Science and Technology, Ministry of Health, Labour and Welfare, and Ministry of Economy, Trade and Industry. 2021), and study participants’ consent requirement was waived because it was a secondary data analysis of a government survey. The MHLW approved access to the survey data.

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Teraura, H., Kotani, K. & Koike, S. Physician retention and migration in rural clinics designated for areas without physicians in Japan: descriptive epidemiological study using the national physicians’ survey. BMC Health Serv Res 24 , 1049 (2024). https://doi.org/10.1186/s12913-024-11446-6

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Received : 05 June 2024

Accepted : 16 August 2024

Published : 11 September 2024

DOI : https://doi.org/10.1186/s12913-024-11446-6

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Survey Research
Market research survey: A type of survey research that collects data on consumer preferences, behaviors, or attitudes, often used in market research or product development. Public opinion survey: A type of survey research that measures the attitudes, beliefs, or opinions of a population on a specific issue or topic, often used in political or ...
Survey Research: Definition, Types & Methods
Descriptive research is the most common and conclusive form of survey research due to its quantitative nature. Unlike exploratory research methods, descriptive research utilizes pre-planned, structured surveys with closed-ended questions. It's also deductive, meaning that the survey structure and questions are determined beforehand based on existing theories or areas of inquiry.
Survey Research
Survey research means collecting information about a group of people by asking them questions and analyzing the results. To conduct an effective survey, follow these six steps: Determine who will participate in the survey. Decide the type of survey (mail, online, or in-person) Design the survey questions and layout.
Types of surveys with examples
1. Online surveys: One of the most popular types is an online survey. With technology advancing many folds with each passing day, an online survey is becoming more popular. This survey consists of survey questions that can be easily deployed to the respondents online via email, or they can access the survey if they have an internet connection.
Survey Research: Definition, Examples & Methods
But survey research needs careful planning and execution to get the results you want. So if you're thinking about using surveys to carry out research, read on. Get started with our free survey maker tool. Types of survey research. Calling these methods 'survey research' slightly underplays the complexity of this type of information gathering.
Survey Research: Definition, Examples and Methods
Survey Research Definition. Survey Research is defined as the process of conducting research using surveys that researchers send to survey respondents. The data collected from surveys is then statistically analyzed to draw meaningful research conclusions. In the 21st century, every organization's eager to understand what their customers think ...
Survey Research: Types, Examples & Methods
Types of Survey Research Based on Data Source. Secondary Data; Survey research can be designed to collect and process secondary data. Secondary data is a type of data that has been collected from primary sources in the past and is readily available for use. It is the type of data that is already existing.
A Comprehensive Guide to Survey Research Methodologies
In this article, we will discuss what survey research is, its brief history, types, common uses, benefits, and the step-by-step process of designing a survey. What is Survey Research A survey is a research method that is used to collect data from a group of respondents in order to gain insights and information regarding a particular subject.
Doing Survey Research
Survey research means collecting information about a group of people by asking them questions and analysing the results. To conduct an effective survey, follow these six steps: Determine who will participate in the survey. Decide the type of survey (mail, online, or in-person) Design the survey questions and layout. Distribute the survey.
10 Different Types of Survey Methods + Pros & Cons
"What are the types of surveys I should use," you ask? Here's a look at the 18 types of survey methods researchers use today. 1. Interviews. Also known as in-person surveys or household surveys, this used to be one of the most popular types of survey to conduct. Researchers like them because they involve getting face-to-face with individuals.
Types of Surveys: All You Need to Know About Survey Research Methods
Tl; dr; Choose the right survey method: Your method should always align with your research objectives, target audience, budget, time constraints, and the type of data needed.; Pick distribution channels: You can embed surveys in email and use them in-product, as website pop-ups, or in a mobile app.There are also plenty of offline types of surveys. Each has its advantages and is suitable for ...
Understanding and Evaluating Survey Research
Survey research is defined as "the collection of information from a sample of individuals through their responses to questions" (Check & Schutt, 2012, p. 160). This type of research allows for a variety of methods to recruit participants, collect data, and utilize various methods of instrumentation. Survey research can use quantitative research ...
Survey Research
Types of survey research. Survey research is like an artist's palette, offering a variety of types to suit your unique research needs. Each type paints a different picture, giving us fascinating insights into the world around us. Cross-Sectional Surveys: Capture a snapshot of a population at a specific moment in time.
Survey Research: Definition, Methods, Examples, and More
Types of Survey Research Methods & Data Collection Methods. In the world of survey research a range of methods each offer unique advantages tailored to a researcher or businesses specific research goals. Email Surveys. Email surveys represent a modern approach to data collection, utilizing email addresses stored on client databases to ...
A quick guide to survey research
Medical research questionnaires or surveys are vital tools used to gather information on individual perspectives in a large cohort. Within the medical realm, there are three main types of survey: epidemiological surveys, surveys on attitudes to a health service or intervention and questionnaires assessing knowledge on a particular issue or topic. 1
7 Types of Survey Research Methods & When to Use Them
7. Kiosk surveys. The final and more niche option for gathering survey feedback is by using a kiosk survey. This is a survey on a computer screen located in physical locations such as offices, stores, lobbies, and hospitals. Kiosk survey research gathers instant feedback for a product or service.
Types of market research surveys
Panel surveys use a pre-selected group of people as the sample, so that the research can be carried out quickly. It presents a happy medium between the speed and quality of research data. Survey tools for your survey method. Based on the type of survey method you choose, here are the types of tools you need and can use for each: Online surveys
Survey Research: Definition, Types & Methods
Descriptive research is the most common and conclusive form of survey research due to its quantitative nature. Unlike exploratory research methods, descriptive research utilises pre-planned, structured surveys with closed-ended questions. It's also deductive, meaning that the survey structure and questions are determined beforehand based on existing theories or areas of enquiry.
Understanding the 3 Main Types of Survey Research ...
Descriptive Research. The first main type of survey research is descriptive research. This type is centered on describing, as its name suggests, a topic of study. This can be a population, an occurrence or a phenomenon. Descriptive research is often the first type of research applied around a research issue, because it paints a picture of a ...
Questionnaire Design
Questionnaires vs. surveys. A survey is a research method where you collect and analyze data from a group of people. A questionnaire is a specific tool or instrument for collecting the data.. Designing a questionnaire means creating valid and reliable questions that address your research objectives, placing them in a useful order, and selecting an appropriate method for administration.
Data Collection: Methods, Types, Examples and Tools
This data type is collected firsthand and specific to the researcher's current study. Common methods include surveys, interviews, observations, and experiments. For instance, a company may survey to understand customer satisfaction, or a researcher might use interviews to gather detailed opinions on a new product. Advantages
One Curve Doesn't Fit All
The reason is our new friend, the B&K Type 5128-B. The B&K Type 5128-B. ... Our sample was a bit small for proper statistics to be made on these considerations, but we had a simple survey. While we don't draw any concrete conclusions on these aspects, it didn't make any significant differences in preferences in our experiment, except that women ...
Classification of lakebed geologic substrate in autonomously collected
Mapping benthic habitats with bathymetric, acoustic, and spectral data requires georeferenced ground-truth information about habitat types and characteristics. New technologies like autonomous underwater vehicles (AUVs) collect tens of thousands of images per mission making image-based ground truthing particularly attractive. Two types of machine learning (ML) models, random forest (RF) and deep n
The drop in worry about crime and its gender gap: Trends in England and
Using data from the Crime Survey for England and Wales, this research explores trends in worry about crime and its gender gap between 1998 and 2019/20. Worry about different types of crime follows a downwards trajectory, with worries about car-related crimes showing the strongest decline.
Range maps and waterbody occupancy data for 1158 freshwater ...
Number of macroinvertebrate genera detected at each National Aquatic Resource Surveys (NARS) sampling site across all sampling dates. We used all benthic macroinvertebrate data from the National ...
Physician retention and migration in rural clinics designated for areas
Regarding the types of institutions in the survey data, RCDAs were included in the clinical classification, and CHRAs were included in the hospital classification. ... Future research, possibly incorporating interviews or surveys that directly inquire about reasons for migration, such as the pursuit of certifications, is necessary. Second ...

Survey Research – Types, Methods, Examples

Survey Research

Survey Research Methods

Types of Survey Research

Types Based on Methodology

Quantitative Survey Research

Data Analysis Methods

Applications of Survey Research

Examples of Survey Research

Survey Sample

When to use Survey Research

How to Conduct Survey Research

Advantages of Survey Research

Limitations of Survey Research

About the author

Muhammad Hassan

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