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Research methods--quantitative, qualitative, and more: overview.

• Quantitative Research
• Qualitative Research
• Data Science Methods (Machine Learning, AI, Big Data)
• Text Mining and Computational Text Analysis
• Evidence Synthesis/Systematic Reviews
• Get Data, Get Help!

About Research Methods

This guide provides an overview of research methods, how to choose and use them, and supports and resources at UC Berkeley. 

As Patten and Newhart note in the book Understanding Research Methods , "Research methods are the building blocks of the scientific enterprise. They are the "how" for building systematic knowledge. The accumulation of knowledge through research is by its nature a collective endeavor. Each well-designed study provides evidence that may support, amend, refute, or deepen the understanding of existing knowledge...Decisions are important throughout the practice of research and are designed to help researchers collect evidence that includes the full spectrum of the phenomenon under study, to maintain logical rules, and to mitigate or account for possible sources of bias. In many ways, learning research methods is learning how to see and make these decisions."

The choice of methods varies by discipline, by the kind of phenomenon being studied and the data being used to study it, by the technology available, and more.  This guide is an introduction, but if you don't see what you need here, always contact your subject librarian, and/or take a look to see if there's a library research guide that will answer your question. 

Suggestions for changes and additions to this guide are welcome! 

START HERE: SAGE Research Methods

Without question, the most comprehensive resource available from the library is SAGE Research Methods.  HERE IS THE ONLINE GUIDE  to this one-stop shopping collection, and some helpful links are below:

• SAGE Research Methods
• Little Green Books  (Quantitative Methods)
• Little Blue Books  (Qualitative Methods)
• Dictionaries and Encyclopedias  
• Case studies of real research projects
• Sample datasets for hands-on practice
• Streaming video--see methods come to life
• Methodspace- -a community for researchers
• SAGE Research Methods Course Mapping

Library Data Services at UC Berkeley

Library Data Services Program and Digital Scholarship Services

The LDSP offers a variety of services and tools !  From this link, check out pages for each of the following topics:  discovering data, managing data, collecting data, GIS data, text data mining, publishing data, digital scholarship, open science, and the Research Data Management Program.

Be sure also to check out the visual guide to where to seek assistance on campus with any research question you may have!

Library GIS Services

Other Data Services at Berkeley

D-Lab Supports Berkeley faculty, staff, and graduate students with research in data intensive social science, including a wide range of training and workshop offerings Dryad Dryad is a simple self-service tool for researchers to use in publishing their datasets. It provides tools for the effective publication of and access to research data. Geospatial Innovation Facility (GIF) Provides leadership and training across a broad array of integrated mapping technologies on campu Research Data Management A UC Berkeley guide and consulting service for research data management issues

General Research Methods Resources

Here are some general resources for assistance:

• Assistance from ICPSR (must create an account to access): Getting Help with Data , and Resources for Students
• Wiley Stats Ref for background information on statistics topics
• Survey Documentation and Analysis (SDA) .  Program for easy web-based analysis of survey data.

Consultants

• D-Lab/Data Science Discovery Consultants Request help with your research project from peer consultants.
• Research data (RDM) consulting Meet with RDM consultants before designing the data security, storage, and sharing aspects of your qualitative project.
• Statistics Department Consulting Services A service in which advanced graduate students, under faculty supervision, are available to consult during specified hours in the Fall and Spring semesters.

Related Resourcex

• IRB / CPHS Qualitative research projects with human subjects often require that you go through an ethics review.
• OURS (Office of Undergraduate Research and Scholarships) OURS supports undergraduates who want to embark on research projects and assistantships. In particular, check out their "Getting Started in Research" workshops
• Sponsored Projects Sponsored projects works with researchers applying for major external grants.
• Next: Quantitative Research >>
• Last Updated: Apr 25, 2024 11:09 AM
• URL: https://guides.lib.berkeley.edu/researchmethods

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• Knowledge Base
• Methodology

Research Design | Step-by-Step Guide with Examples

Published on 5 May 2022 by Shona McCombes . Revised on 20 March 2023.

A research design is a strategy for answering your research question  using empirical data. Creating a research design means making decisions about:

• Your overall aims and approach
• The type of research design you’ll use
• Your sampling methods or criteria for selecting subjects
• Your data collection methods
• The procedures you’ll follow to collect data
• Your data analysis methods

A well-planned research design helps ensure that your methods match your research aims and that you use the right kind of analysis for your data.

Table of contents

Step 1: consider your aims and approach, step 2: choose a type of research design, step 3: identify your population and sampling method, step 4: choose your data collection methods, step 5: plan your data collection procedures, step 6: decide on your data analysis strategies, frequently asked questions.

• Introduction

Before you can start designing your research, you should already have a clear idea of the research question you want to investigate.

There are many different ways you could go about answering this question. Your research design choices should be driven by your aims and priorities – start by thinking carefully about what you want to achieve.

The first choice you need to make is whether you’ll take a qualitative or quantitative approach.

Qualitative research designs tend to be more flexible and inductive , allowing you to adjust your approach based on what you find throughout the research process.

Quantitative research designs tend to be more fixed and deductive , with variables and hypotheses clearly defined in advance of data collection.

It’s also possible to use a mixed methods design that integrates aspects of both approaches. By combining qualitative and quantitative insights, you can gain a more complete picture of the problem you’re studying and strengthen the credibility of your conclusions.

Practical and ethical considerations when designing research

As well as scientific considerations, you need to think practically when designing your research. If your research involves people or animals, you also need to consider research ethics .

• How much time do you have to collect data and write up the research?
• Will you be able to gain access to the data you need (e.g., by travelling to a specific location or contacting specific people)?
• Do you have the necessary research skills (e.g., statistical analysis or interview techniques)?
• Will you need ethical approval ?

At each stage of the research design process, make sure that your choices are practically feasible.

Prevent plagiarism, run a free check.

Within both qualitative and quantitative approaches, there are several types of research design to choose from. Each type provides a framework for the overall shape of your research.

Types of quantitative research designs

Quantitative designs can be split into four main types. Experimental and   quasi-experimental designs allow you to test cause-and-effect relationships, while descriptive and correlational designs allow you to measure variables and describe relationships between them.

With descriptive and correlational designs, you can get a clear picture of characteristics, trends, and relationships as they exist in the real world. However, you can’t draw conclusions about cause and effect (because correlation doesn’t imply causation ).

Experiments are the strongest way to test cause-and-effect relationships without the risk of other variables influencing the results. However, their controlled conditions may not always reflect how things work in the real world. They’re often also more difficult and expensive to implement.

Types of qualitative research designs

Qualitative designs are less strictly defined. This approach is about gaining a rich, detailed understanding of a specific context or phenomenon, and you can often be more creative and flexible in designing your research.

The table below shows some common types of qualitative design. They often have similar approaches in terms of data collection, but focus on different aspects when analysing the data.

Your research design should clearly define who or what your research will focus on, and how you’ll go about choosing your participants or subjects.

In research, a population is the entire group that you want to draw conclusions about, while a sample is the smaller group of individuals you’ll actually collect data from.

Defining the population

A population can be made up of anything you want to study – plants, animals, organisations, texts, countries, etc. In the social sciences, it most often refers to a group of people.

For example, will you focus on people from a specific demographic, region, or background? Are you interested in people with a certain job or medical condition, or users of a particular product?

The more precisely you define your population, the easier it will be to gather a representative sample.

Sampling methods

Even with a narrowly defined population, it’s rarely possible to collect data from every individual. Instead, you’ll collect data from a sample.

To select a sample, there are two main approaches: probability sampling and non-probability sampling . The sampling method you use affects how confidently you can generalise your results to the population as a whole.

Probability sampling is the most statistically valid option, but it’s often difficult to achieve unless you’re dealing with a very small and accessible population.

For practical reasons, many studies use non-probability sampling, but it’s important to be aware of the limitations and carefully consider potential biases. You should always make an effort to gather a sample that’s as representative as possible of the population.

Case selection in qualitative research

In some types of qualitative designs, sampling may not be relevant.

For example, in an ethnography or a case study, your aim is to deeply understand a specific context, not to generalise to a population. Instead of sampling, you may simply aim to collect as much data as possible about the context you are studying.

In these types of design, you still have to carefully consider your choice of case or community. You should have a clear rationale for why this particular case is suitable for answering your research question.

For example, you might choose a case study that reveals an unusual or neglected aspect of your research problem, or you might choose several very similar or very different cases in order to compare them.

Data collection methods are ways of directly measuring variables and gathering information. They allow you to gain first-hand knowledge and original insights into your research problem.

You can choose just one data collection method, or use several methods in the same study.

Survey methods

Surveys allow you to collect data about opinions, behaviours, experiences, and characteristics by asking people directly. There are two main survey methods to choose from: questionnaires and interviews.

Observation methods

Observations allow you to collect data unobtrusively, observing characteristics, behaviours, or social interactions without relying on self-reporting.

Observations may be conducted in real time, taking notes as you observe, or you might make audiovisual recordings for later analysis. They can be qualitative or quantitative.

Other methods of data collection

There are many other ways you might collect data depending on your field and topic.

If you’re not sure which methods will work best for your research design, try reading some papers in your field to see what data collection methods they used.

Secondary data

If you don’t have the time or resources to collect data from the population you’re interested in, you can also choose to use secondary data that other researchers already collected – for example, datasets from government surveys or previous studies on your topic.

With this raw data, you can do your own analysis to answer new research questions that weren’t addressed by the original study.

Using secondary data can expand the scope of your research, as you may be able to access much larger and more varied samples than you could collect yourself.

However, it also means you don’t have any control over which variables to measure or how to measure them, so the conclusions you can draw may be limited.

As well as deciding on your methods, you need to plan exactly how you’ll use these methods to collect data that’s consistent, accurate, and unbiased.

Planning systematic procedures is especially important in quantitative research, where you need to precisely define your variables and ensure your measurements are reliable and valid.

Operationalisation

Some variables, like height or age, are easily measured. But often you’ll be dealing with more abstract concepts, like satisfaction, anxiety, or competence. Operationalisation means turning these fuzzy ideas into measurable indicators.

If you’re using observations , which events or actions will you count?

If you’re using surveys , which questions will you ask and what range of responses will be offered?

You may also choose to use or adapt existing materials designed to measure the concept you’re interested in – for example, questionnaires or inventories whose reliability and validity has already been established.

Reliability and validity

Reliability means your results can be consistently reproduced , while validity means that you’re actually measuring the concept you’re interested in.

For valid and reliable results, your measurement materials should be thoroughly researched and carefully designed. Plan your procedures to make sure you carry out the same steps in the same way for each participant.

If you’re developing a new questionnaire or other instrument to measure a specific concept, running a pilot study allows you to check its validity and reliability in advance.

Sampling procedures

As well as choosing an appropriate sampling method, you need a concrete plan for how you’ll actually contact and recruit your selected sample.

That means making decisions about things like:

• How many participants do you need for an adequate sample size?
• What inclusion and exclusion criteria will you use to identify eligible participants?
• How will you contact your sample – by mail, online, by phone, or in person?

If you’re using a probability sampling method, it’s important that everyone who is randomly selected actually participates in the study. How will you ensure a high response rate?

If you’re using a non-probability method, how will you avoid bias and ensure a representative sample?

Data management

It’s also important to create a data management plan for organising and storing your data.

Will you need to transcribe interviews or perform data entry for observations? You should anonymise and safeguard any sensitive data, and make sure it’s backed up regularly.

Keeping your data well organised will save time when it comes to analysing them. It can also help other researchers validate and add to your findings.

On their own, raw data can’t answer your research question. The last step of designing your research is planning how you’ll analyse the data.

Quantitative data analysis

In quantitative research, you’ll most likely use some form of statistical analysis . With statistics, you can summarise your sample data, make estimates, and test hypotheses.

Using descriptive statistics , you can summarise your sample data in terms of:

• The distribution of the data (e.g., the frequency of each score on a test)
• The central tendency of the data (e.g., the mean to describe the average score)
• The variability of the data (e.g., the standard deviation to describe how spread out the scores are)

The specific calculations you can do depend on the level of measurement of your variables.

Using inferential statistics , you can:

• Make estimates about the population based on your sample data.
• Test hypotheses about a relationship between variables.

Regression and correlation tests look for associations between two or more variables, while comparison tests (such as t tests and ANOVAs ) look for differences in the outcomes of different groups.

Your choice of statistical test depends on various aspects of your research design, including the types of variables you’re dealing with and the distribution of your data.

Qualitative data analysis

In qualitative research, your data will usually be very dense with information and ideas. Instead of summing it up in numbers, you’ll need to comb through the data in detail, interpret its meanings, identify patterns, and extract the parts that are most relevant to your research question.

Two of the most common approaches to doing this are thematic analysis and discourse analysis .

There are many other ways of analysing qualitative data depending on the aims of your research. To get a sense of potential approaches, try reading some qualitative research papers in your field.

A sample is a subset of individuals from a larger population. Sampling means selecting the group that you will actually collect data from in your research.

For example, if you are researching the opinions of students in your university, you could survey a sample of 100 students.

Statistical sampling allows you to test a hypothesis about the characteristics of a population. There are various sampling methods you can use to ensure that your sample is representative of the population as a whole.

Operationalisation means turning abstract conceptual ideas into measurable observations.

For example, the concept of social anxiety isn’t directly observable, but it can be operationally defined in terms of self-rating scores, behavioural avoidance of crowded places, or physical anxiety symptoms in social situations.

Before collecting data , it’s important to consider how you will operationalise the variables that you want to measure.

The research methods you use depend on the type of data you need to answer your research question .

• If you want to measure something or test a hypothesis , use quantitative methods . If you want to explore ideas, thoughts, and meanings, use qualitative methods .
• If you want to analyse a large amount of readily available data, use secondary data. If you want data specific to your purposes with control over how they are generated, collect primary data.
• If you want to establish cause-and-effect relationships between variables , use experimental methods. If you want to understand the characteristics of a research subject, use descriptive methods.

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3 The research process

In Chapter 1, we saw that scientific research is the process of acquiring scientific knowledge using the scientific method. But how is such research conducted? This chapter delves into the process of scientific research, and the assumptions and outcomes of the research process.

Paradigms of social research

Our design and conduct of research is shaped by our mental models, or frames of reference that we use to organise our reasoning and observations. These mental models or frames (belief systems) are called paradigms . The word ‘paradigm’ was popularised by Thomas Kuhn (1962) [1] in his book The structure of scientific r evolutions , where he examined the history of the natural sciences to identify patterns of activities that shape the progress of science. Similar ideas are applicable to social sciences as well, where a social reality can be viewed by different people in different ways, which may constrain their thinking and reasoning about the observed phenomenon. For instance, conservatives and liberals tend to have very different perceptions of the role of government in people’s lives, and hence, have different opinions on how to solve social problems. Conservatives may believe that lowering taxes is the best way to stimulate a stagnant economy because it increases people’s disposable income and spending, which in turn expands business output and employment. In contrast, liberals may believe that governments should invest more directly in job creation programs such as public works and infrastructure projects, which will increase employment and people’s ability to consume and drive the economy. Likewise, Western societies place greater emphasis on individual rights, such as one’s right to privacy, right of free speech, and right to bear arms. In contrast, Asian societies tend to balance the rights of individuals against the rights of families, organisations, and the government, and therefore tend to be more communal and less individualistic in their policies. Such differences in perspective often lead Westerners to criticise Asian governments for being autocratic, while Asians criticise Western societies for being greedy, having high crime rates, and creating a ‘cult of the individual’. Our personal paradigms are like ‘coloured glasses’ that govern how we view the world and how we structure our thoughts about what we see in the world.

Paradigms are often hard to recognise, because they are implicit, assumed, and taken for granted. However, recognising these paradigms is key to making sense of and reconciling differences in people’s perceptions of the same social phenomenon. For instance, why do liberals believe that the best way to improve secondary education is to hire more teachers, while conservatives believe that privatising education (using such means as school vouchers) is more effective in achieving the same goal? Conservatives place more faith in competitive markets (i.e., in free competition between schools competing for education dollars), while liberals believe more in labour (i.e., in having more teachers and schools). Likewise, in social science research, to understand why a certain technology was successfully implemented in one organisation, but failed miserably in another, a researcher looking at the world through a ‘rational lens’ will look for rational explanations of the problem, such as inadequate technology or poor fit between technology and the task context where it is being utilised. Another researcher looking at the same problem through a ‘social lens’ may seek out social deficiencies such as inadequate user training or lack of management support. Those seeing it through a ‘political lens’ will look for instances of organisational politics that may subvert the technology implementation process. Hence, subconscious paradigms often constrain the concepts that researchers attempt to measure, their observations, and their subsequent interpretations of a phenomenon. However, given the complex nature of social phenomena, it is possible that all of the above paradigms are partially correct, and that a fuller understanding of the problem may require an understanding and application of multiple paradigms.

Two popular paradigms today among social science researchers are positivism and post-positivism. Positivism , based on the works of French philosopher Auguste Comte (1798–1857), was the dominant scientific paradigm until the mid-twentieth century. It holds that science or knowledge creation should be restricted to what can be observed and measured. Positivism tends to rely exclusively on theories that can be directly tested. Though positivism was originally an attempt to separate scientific inquiry from religion (where the precepts could not be objectively observed), positivism led to empiricism or a blind faith in observed data and a rejection of any attempt to extend or reason beyond observable facts. Since human thoughts and emotions could not be directly measured, they were not considered to be legitimate topics for scientific research. Frustrations with the strictly empirical nature of positivist philosophy led to the development of post-positivism (or postmodernism) during the mid-late twentieth century. Post-positivism argues that one can make reasonable inferences about a phenomenon by combining empirical observations with logical reasoning. Post-positivists view science as not certain but probabilistic (i.e., based on many contingencies), and often seek to explore these contingencies to understand social reality better. The post-positivist camp has further fragmented into subjectivists , who view the world as a subjective construction of our subjective minds rather than as an objective reality, and critical realists , who believe that there is an external reality that is independent of a person’s thinking but we can never know such reality with any degree of certainty.

Burrell and Morgan (1979), [2] in their seminal book Sociological p aradigms and organizational a nalysis , suggested that the way social science researchers view and study social phenomena is shaped by two fundamental sets of philosophical assumptions: ontology and epistemology. Ontology refers to our assumptions about how we see the world (e.g., does the world consist mostly of social order or constant change?). Epistemology refers to our assumptions about the best way to study the world (e.g., should we use an objective or subjective approach to study social reality?). Using these two sets of assumptions, we can categorise social science research as belonging to one of four categories (see Figure 3.1).

If researchers view the world as consisting mostly of social order (ontology) and hence seek to study patterns of ordered events or behaviours, and believe that the best way to study such a world is using an objective approach (epistemology) that is independent of the person conducting the observation or interpretation, such as by using standardised data collection tools like surveys, then they are adopting a paradigm of functionalism . However, if they believe that the best way to study social order is though the subjective interpretation of participants, such as by interviewing different participants and reconciling differences among their responses using their own subjective perspectives, then they are employing an interpretivism paradigm. If researchers believe that the world consists of radical change and seek to understand or enact change using an objectivist approach, then they are employing a radical structuralism paradigm. If they wish to understand social change using the subjective perspectives of the participants involved, then they are following a radical humanism paradigm.

To date, the majority of social science research has emulated the natural sciences, and followed the functionalist paradigm. Functionalists believe that social order or patterns can be understood in terms of their functional components, and therefore attempt to break down a problem into small components and studying one or more components in detail using objectivist techniques such as surveys and experimental research. However, with the emergence of post-positivist thinking, a small but growing number of social science researchers are attempting to understand social order using subjectivist techniques such as interviews and ethnographic studies. Radical humanism and radical structuralism continues to represent a negligible proportion of social science research, because scientists are primarily concerned with understanding generalisable patterns of behaviour, events, or phenomena, rather than idiosyncratic or changing events. Nevertheless, if you wish to study social change, such as why democratic movements are increasingly emerging in Middle Eastern countries, or why this movement was successful in Tunisia, took a longer path to success in Libya, and is still not successful in Syria, then perhaps radical humanism is the right approach for such a study. Social and organisational phenomena generally consist of elements of both order and change. For instance, organisational success depends on formalised business processes, work procedures, and job responsibilities, while being simultaneously constrained by a constantly changing mix of competitors, competing products, suppliers, and customer base in the business environment. Hence, a holistic and more complete understanding of social phenomena such as why some organisations are more successful than others, requires an appreciation and application of a multi-paradigmatic approach to research.

Overview of the research process

So how do our mental paradigms shape social science research? At its core, all scientific research is an iterative process of observation, rationalisation, and validation. In the observation phase, we observe a natural or social phenomenon, event, or behaviour that interests us. In the rationalisation phase, we try to make sense of the observed phenomenon, event, or behaviour by logically connecting the different pieces of the puzzle that we observe, which in some cases, may lead to the construction of a theory. Finally, in the validation phase, we test our theories using a scientific method through a process of data collection and analysis, and in doing so, possibly modify or extend our initial theory. However, research designs vary based on whether the researcher starts at observation and attempts to rationalise the observations (inductive research), or whether the researcher starts at an ex ante rationalisation or a theory and attempts to validate the theory (deductive research). Hence, the observation-rationalisation-validation cycle is very similar to the induction-deduction cycle of research discussed in Chapter 1.

Most traditional research tends to be deductive and functionalistic in nature. Figure 3.2 provides a schematic view of such a research project. This figure depicts a series of activities to be performed in functionalist research, categorised into three phases: exploration, research design, and research execution. Note that this generalised design is not a roadmap or flowchart for all research. It applies only to functionalistic research, and it can and should be modified to fit the needs of a specific project.

The first phase of research is exploration . This phase includes exploring and selecting research questions for further investigation, examining the published literature in the area of inquiry to understand the current state of knowledge in that area, and identifying theories that may help answer the research questions of interest.

The first step in the exploration phase is identifying one or more research questions dealing with a specific behaviour, event, or phenomena of interest. Research questions are specific questions about a behaviour, event, or phenomena of interest that you wish to seek answers for in your research. Examples include determining which factors motivate consumers to purchase goods and services online without knowing the vendors of these goods or services, how can we make high school students more creative, and why some people commit terrorist acts. Research questions can delve into issues of what, why, how, when, and so forth. More interesting research questions are those that appeal to a broader population (e.g., ‘how can firms innovate?’ is a more interesting research question than ‘how can Chinese firms innovate in the service-sector?’), address real and complex problems (in contrast to hypothetical or ‘toy’ problems), and where the answers are not obvious. Narrowly focused research questions (often with a binary yes/no answer) tend to be less useful and less interesting and less suited to capturing the subtle nuances of social phenomena. Uninteresting research questions generally lead to uninteresting and unpublishable research findings.

The next step is to conduct a literature review of the domain of interest. The purpose of a literature review is three-fold: one, to survey the current state of knowledge in the area of inquiry, two, to identify key authors, articles, theories, and findings in that area, and three, to identify gaps in knowledge in that research area. Literature review is commonly done today using computerised keyword searches in online databases. Keywords can be combined using Boolean operators such as ‘and’ and ‘or’ to narrow down or expand the search results. Once a shortlist of relevant articles is generated from the keyword search, the researcher must then manually browse through each article, or at least its abstract, to determine the suitability of that article for a detailed review. Literature reviews should be reasonably complete, and not restricted to a few journals, a few years, or a specific methodology. Reviewed articles may be summarised in the form of tables, and can be further structured using organising frameworks such as a concept matrix. A well-conducted literature review should indicate whether the initial research questions have already been addressed in the literature (which would obviate the need to study them again), whether there are newer or more interesting research questions available, and whether the original research questions should be modified or changed in light of the findings of the literature review. The review can also provide some intuitions or potential answers to the questions of interest and/or help identify theories that have previously been used to address similar questions.

Since functionalist (deductive) research involves theory-testing, the third step is to identify one or more theories can help address the desired research questions. While the literature review may uncover a wide range of concepts or constructs potentially related to the phenomenon of interest, a theory will help identify which of these constructs is logically relevant to the target phenomenon and how. Forgoing theories may result in measuring a wide range of less relevant, marginally relevant, or irrelevant constructs, while also minimising the chances of obtaining results that are meaningful and not by pure chance. In functionalist research, theories can be used as the logical basis for postulating hypotheses for empirical testing. Obviously, not all theories are well-suited for studying all social phenomena. Theories must be carefully selected based on their fit with the target problem and the extent to which their assumptions are consistent with that of the target problem. We will examine theories and the process of theorising in detail in the next chapter.

The next phase in the research process is research design . This process is concerned with creating a blueprint of the actions to take in order to satisfactorily answer the research questions identified in the exploration phase. This includes selecting a research method, operationalising constructs of interest, and devising an appropriate sampling strategy.

Operationalisation is the process of designing precise measures for abstract theoretical constructs. This is a major problem in social science research, given that many of the constructs, such as prejudice, alienation, and liberalism are hard to define, let alone measure accurately. Operationalisation starts with specifying an ‘operational definition’ (or ‘conceptualization’) of the constructs of interest. Next, the researcher can search the literature to see if there are existing pre-validated measures matching their operational definition that can be used directly or modified to measure their constructs of interest. If such measures are not available or if existing measures are poor or reflect a different conceptualisation than that intended by the researcher, new instruments may have to be designed for measuring those constructs. This means specifying exactly how exactly the desired construct will be measured (e.g., how many items, what items, and so forth). This can easily be a long and laborious process, with multiple rounds of pre-tests and modifications before the newly designed instrument can be accepted as ‘scientifically valid’. We will discuss operationalisation of constructs in a future chapter on measurement.

Simultaneously with operationalisation, the researcher must also decide what research method they wish to employ for collecting data to address their research questions of interest. Such methods may include quantitative methods such as experiments or survey research or qualitative methods such as case research or action research, or possibly a combination of both. If an experiment is desired, then what is the experimental design? If this is a survey, do you plan a mail survey, telephone survey, web survey, or a combination? For complex, uncertain, and multifaceted social phenomena, multi-method approaches may be more suitable, which may help leverage the unique strengths of each research method and generate insights that may not be obtained using a single method.

Researchers must also carefully choose the target population from which they wish to collect data, and a sampling strategy to select a sample from that population. For instance, should they survey individuals or firms or workgroups within firms? What types of individuals or firms do they wish to target? Sampling strategy is closely related to the unit of analysis in a research problem. While selecting a sample, reasonable care should be taken to avoid a biased sample (e.g., sample based on convenience) that may generate biased observations. Sampling is covered in depth in a later chapter.

At this stage, it is often a good idea to write a research proposal detailing all of the decisions made in the preceding stages of the research process and the rationale behind each decision. This multi-part proposal should address what research questions you wish to study and why, the prior state of knowledge in this area, theories you wish to employ along with hypotheses to be tested, how you intend to measure constructs, what research method is to be employed and why, and desired sampling strategy. Funding agencies typically require such a proposal in order to select the best proposals for funding. Even if funding is not sought for a research project, a proposal may serve as a useful vehicle for seeking feedback from other researchers and identifying potential problems with the research project (e.g., whether some important constructs were missing from the study) before starting data collection. This initial feedback is invaluable because it is often too late to correct critical problems after data is collected in a research study.

Having decided who to study (subjects), what to measure (concepts), and how to collect data (research method), the researcher is now ready to proceed to the research execution phase. This includes pilot testing the measurement instruments, data collection, and data analysis.

Pilot testing is an often overlooked but extremely important part of the research process. It helps detect potential problems in your research design and/or instrumentation (e.g., whether the questions asked are intelligible to the targeted sample), and to ensure that the measurement instruments used in the study are reliable and valid measures of the constructs of interest. The pilot sample is usually a small subset of the target population. After successful pilot testing, the researcher may then proceed with data collection using the sampled population. The data collected may be quantitative or qualitative, depending on the research method employed.

Following data collection, the data is analysed and interpreted for the purpose of drawing conclusions regarding the research questions of interest. Depending on the type of data collected (quantitative or qualitative), data analysis may be quantitative (e.g., employ statistical techniques such as regression or structural equation modelling) or qualitative (e.g., coding or content analysis).

The final phase of research involves preparing the final research report documenting the entire research process and its findings in the form of a research paper, dissertation, or monograph. This report should outline in detail all the choices made during the research process (e.g., theory used, constructs selected, measures used, research methods, sampling, etc.) and why, as well as the outcomes of each phase of the research process. The research process must be described in sufficient detail so as to allow other researchers to replicate your study, test the findings, or assess whether the inferences derived are scientifically acceptable. Of course, having a ready research proposal will greatly simplify and quicken the process of writing the finished report. Note that research is of no value unless the research process and outcomes are documented for future generations—such documentation is essential for the incremental progress of science.

Common mistakes in research

The research process is fraught with problems and pitfalls, and novice researchers often find, after investing substantial amounts of time and effort into a research project, that their research questions were not sufficiently answered, or that the findings were not interesting enough, or that the research was not of ‘acceptable’ scientific quality. Such problems typically result in research papers being rejected by journals. Some of the more frequent mistakes are described below.

Insufficiently motivated research questions. Often times, we choose our ‘pet’ problems that are interesting to us but not to the scientific community at large, i.e., it does not generate new knowledge or insight about the phenomenon being investigated. Because the research process involves a significant investment of time and effort on the researcher’s part, the researcher must be certain—and be able to convince others—that the research questions they seek to answer deal with real—and not hypothetical—problems that affect a substantial portion of a population and have not been adequately addressed in prior research.

Pursuing research fads. Another common mistake is pursuing ‘popular’ topics with limited shelf life. A typical example is studying technologies or practices that are popular today. Because research takes several years to complete and publish, it is possible that popular interest in these fads may die down by the time the research is completed and submitted for publication. A better strategy may be to study ‘timeless’ topics that have always persisted through the years.

Unresearchable problems. Some research problems may not be answered adequately based on observed evidence alone, or using currently accepted methods and procedures. Such problems are best avoided. However, some unresearchable, ambiguously defined problems may be modified or fine tuned into well-defined and useful researchable problems.

Favoured research methods. Many researchers have a tendency to recast a research problem so that it is amenable to their favourite research method (e.g., survey research). This is an unfortunate trend. Research methods should be chosen to best fit a research problem, and not the other way around.

Blind data mining. Some researchers have the tendency to collect data first (using instruments that are already available), and then figure out what to do with it. Note that data collection is only one step in a long and elaborate process of planning, designing, and executing research. In fact, a series of other activities are needed in a research process prior to data collection. If researchers jump into data collection without such elaborate planning, the data collected will likely be irrelevant, imperfect, or useless, and their data collection efforts may be entirely wasted. An abundance of data cannot make up for deficits in research planning and design, and particularly, for the lack of interesting research questions.

• Kuhn, T. (1962). The structure of scientific revolutions . Chicago: University of Chicago Press. ↵
• Burrell, G. & Morgan, G. (1979). Sociological paradigms and organisational analysis: elements of the sociology of corporate life . London: Heinemann Educational. ↵

Social Science Research: Principles, Methods and Practices (Revised edition) Copyright © 2019 by Anol Bhattacherjee is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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Types of Research – Explained with Examples

• By DiscoverPhDs
• October 2, 2020

Types of Research

Research is about using established methods to investigate a problem or question in detail with the aim of generating new knowledge about it.

It is a vital tool for scientific advancement because it allows researchers to prove or refute hypotheses based on clearly defined parameters, environments and assumptions. Due to this, it enables us to confidently contribute to knowledge as it allows research to be verified and replicated.

Knowing the types of research and what each of them focuses on will allow you to better plan your project, utilises the most appropriate methodologies and techniques and better communicate your findings to other researchers and supervisors.

Classification of Types of Research

There are various types of research that are classified according to their objective, depth of study, analysed data, time required to study the phenomenon and other factors. It’s important to note that a research project will not be limited to one type of research, but will likely use several.

According to its Purpose

Theoretical research.

Theoretical research, also referred to as pure or basic research, focuses on generating knowledge , regardless of its practical application. Here, data collection is used to generate new general concepts for a better understanding of a particular field or to answer a theoretical research question.

Results of this kind are usually oriented towards the formulation of theories and are usually based on documentary analysis, the development of mathematical formulas and the reflection of high-level researchers.

Applied Research

Here, the goal is to find strategies that can be used to address a specific research problem. Applied research draws on theory to generate practical scientific knowledge, and its use is very common in STEM fields such as engineering, computer science and medicine.

This type of research is subdivided into two types:

• Technological applied research : looks towards improving efficiency in a particular productive sector through the improvement of processes or machinery related to said productive processes.
• Scientific applied research : has predictive purposes. Through this type of research design, we can measure certain variables to predict behaviours useful to the goods and services sector, such as consumption patterns and viability of commercial projects.

According to your Depth of Scope

Exploratory research.

Exploratory research is used for the preliminary investigation of a subject that is not yet well understood or sufficiently researched. It serves to establish a frame of reference and a hypothesis from which an in-depth study can be developed that will enable conclusive results to be generated.

Because exploratory research is based on the study of little-studied phenomena, it relies less on theory and more on the collection of data to identify patterns that explain these phenomena.

Descriptive Research

The primary objective of descriptive research is to define the characteristics of a particular phenomenon without necessarily investigating the causes that produce it.

In this type of research, the researcher must take particular care not to intervene in the observed object or phenomenon, as its behaviour may change if an external factor is involved.

Explanatory Research

Explanatory research is the most common type of research method and is responsible for establishing cause-and-effect relationships that allow generalisations to be extended to similar realities. It is closely related to descriptive research, although it provides additional information about the observed object and its interactions with the environment.

Correlational Research

The purpose of this type of scientific research is to identify the relationship between two or more variables. A correlational study aims to determine whether a variable changes, how much the other elements of the observed system change.

According to the Type of Data Used

Qualitative research.

Qualitative methods are often used in the social sciences to collect, compare and interpret information, has a linguistic-semiotic basis and is used in techniques such as discourse analysis, interviews, surveys, records and participant observations.

In order to use statistical methods to validate their results, the observations collected must be evaluated numerically. Qualitative research, however, tends to be subjective, since not all data can be fully controlled. Therefore, this type of research design is better suited to extracting meaning from an event or phenomenon (the ‘why’) than its cause (the ‘how’).

Quantitative Research

Quantitative research study delves into a phenomena through quantitative data collection and using mathematical, statistical and computer-aided tools to measure them . This allows generalised conclusions to be projected over time.

According to the Degree of Manipulation of Variables

Experimental research.

It is about designing or replicating a phenomenon whose variables are manipulated under strictly controlled conditions in order to identify or discover its effect on another independent variable or object. The phenomenon to be studied is measured through study and control groups, and according to the guidelines of the scientific method.

Non-Experimental Research

Also known as an observational study, it focuses on the analysis of a phenomenon in its natural context. As such, the researcher does not intervene directly, but limits their involvement to measuring the variables required for the study. Due to its observational nature, it is often used in descriptive research.

Quasi-Experimental Research

It controls only some variables of the phenomenon under investigation and is therefore not entirely experimental. In this case, the study and the focus group cannot be randomly selected, but are chosen from existing groups or populations . This is to ensure the collected data is relevant and that the knowledge, perspectives and opinions of the population can be incorporated into the study.

According to the Type of Inference

Deductive investigation.

In this type of research, reality is explained by general laws that point to certain conclusions; conclusions are expected to be part of the premise of the research problem and considered correct if the premise is valid and the inductive method is applied correctly.

Inductive Research

In this type of research, knowledge is generated from an observation to achieve a generalisation. It is based on the collection of specific data to develop new theories.

Hypothetical-Deductive Investigation

It is based on observing reality to make a hypothesis, then use deduction to obtain a conclusion and finally verify or reject it through experience.

According to the Time in Which it is Carried Out

Longitudinal study (also referred to as diachronic research).

It is the monitoring of the same event, individual or group over a defined period of time. It aims to track changes in a number of variables and see how they evolve over time. It is often used in medical, psychological and social areas .

Cross-Sectional Study (also referred to as Synchronous Research)

Cross-sectional research design is used to observe phenomena, an individual or a group of research subjects at a given time.

According to The Sources of Information

Primary research.

This fundamental research type is defined by the fact that the data is collected directly from the source, that is, it consists of primary, first-hand information.

Secondary research

Unlike primary research, secondary research is developed with information from secondary sources, which are generally based on scientific literature and other documents compiled by another researcher.

According to How the Data is Obtained

Documentary (cabinet).

Documentary research, or secondary sources, is based on a systematic review of existing sources of information on a particular subject. This type of scientific research is commonly used when undertaking literature reviews or producing a case study.

Field research study involves the direct collection of information at the location where the observed phenomenon occurs.

From Laboratory

Laboratory research is carried out in a controlled environment in order to isolate a dependent variable and establish its relationship with other variables through scientific methods.

Mixed-Method: Documentary, Field and/or Laboratory

Mixed research methodologies combine results from both secondary (documentary) sources and primary sources through field or laboratory research.

There are various types of research that are classified by objective, depth of study, analysed data and the time required to study the phenomenon etc.

This article will answer common questions about the PhD synopsis, give guidance on how to write one, and provide my thoughts on samples.

Fieldwork can be essential for your PhD project. Use these tips to help maximise site productivity and reduce your research time by a few weeks.

Join thousands of other students and stay up to date with the latest PhD programmes, funding opportunities and advice.

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A well written figure legend will explain exactly what a figure means without having to refer to the main text. Our guide explains how to write one.

Scientific misconduct can be described as a deviation from the accepted standards of scientific research, study and publication ethics.

Dr Young gained his PhD in Neuroscience from the University of Cambridge. He is now a a Senior Lecturer at the University of Portsmouth, Deputy Director for the Institute of Biological and Biomedical Sciences and more!

Adam’s about to start his fifth year of PhD research at the University of Massachusetts Amherst, where he’s earning a doctorate in anthropology as an affiliated researcher with the University of Iceland’s medical school.

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• Research Process

Choosing the Right Research Methodology: A Guide for Researchers

• 3 minute read

Table of Contents

Choosing an optimal research methodology is crucial for the success of any research project. The methodology you select will determine the type of data you collect, how you collect it, and how you analyse it. Understanding the different types of research methods available along with their strengths and weaknesses, is thus imperative to make an informed decision.

Understanding different research methods:

There are several research methods available depending on the type of study you are conducting, i.e., whether it is laboratory-based, clinical, epidemiological, or survey based . Some common methodologies include qualitative research, quantitative research, experimental research, survey-based research, and action research. Each method can be opted for and modified, depending on the type of research hypotheses and objectives.

Qualitative vs quantitative research:

When deciding on a research methodology, one of the key factors to consider is whether your research will be qualitative or quantitative. Qualitative research is used to understand people’s experiences, concepts, thoughts, or behaviours . Quantitative research, on the contrary, deals with numbers, graphs, and charts, and is used to test or confirm hypotheses, assumptions, and theories. 

Qualitative research methodology:

Qualitative research is often used to examine issues that are not well understood, and to gather additional insights on these topics. Qualitative research methods include open-ended survey questions, observations of behaviours described through words, and reviews of literature that has explored similar theories and ideas. These methods are used to understand how language is used in real-world situations, identify common themes or overarching ideas, and describe and interpret various texts. Data analysis for qualitative research typically includes discourse analysis, thematic analysis, and textual analysis. 

Quantitative research methodology:

The goal of quantitative research is to test hypotheses, confirm assumptions and theories, and determine cause-and-effect relationships. Quantitative research methods include experiments, close-ended survey questions, and countable and numbered observations. Data analysis for quantitative research relies heavily on statistical methods.

Analysing qualitative vs quantitative data:

The methods used for data analysis also differ for qualitative and quantitative research. As mentioned earlier, quantitative data is generally analysed using statistical methods and does not leave much room for speculation. It is more structured and follows a predetermined plan. In quantitative research, the researcher starts with a hypothesis and uses statistical methods to test it. Contrarily, methods used for qualitative data analysis can identify patterns and themes within the data, rather than provide statistical measures of the data. It is an iterative process, where the researcher goes back and forth trying to gauge the larger implications of the data through different perspectives and revising the analysis if required.

When to use qualitative vs quantitative research:

The choice between qualitative and quantitative research will depend on the gap that the research project aims to address, and specific objectives of the study. If the goal is to establish facts about a subject or topic, quantitative research is an appropriate choice. However, if the goal is to understand people’s experiences or perspectives, qualitative research may be more suitable. 

Conclusion:

In conclusion, an understanding of the different research methods available, their applicability, advantages, and disadvantages is essential for making an informed decision on the best methodology for your project. If you need any additional guidance on which research methodology to opt for, you can head over to Elsevier Author Services (EAS). EAS experts will guide you throughout the process and help you choose the perfect methodology for your research goals.

Why is data validation important in research?

When Data Speak, Listen: Importance of Data Collection and Analysis Methods

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• USC Libraries
• Research Guides

Organizing Your Social Sciences Research Paper

• Types of Research Designs
• Purpose of Guide
• Design Flaws to Avoid
• Independent and Dependent Variables
• Glossary of Research Terms
• Reading Research Effectively
• Narrowing a Topic Idea
• Broadening a Topic Idea
• Extending the Timeliness of a Topic Idea
• Academic Writing Style
• Applying Critical Thinking
• Choosing a Title
• Making an Outline
• Paragraph Development
• Research Process Video Series
• Executive Summary
• The C.A.R.S. Model
• Background Information
• The Research Problem/Question
• Theoretical Framework
• Citation Tracking
• Content Alert Services
• Evaluating Sources
• Primary Sources
• Secondary Sources
• Tiertiary Sources
• Scholarly vs. Popular Publications
• Qualitative Methods
• Quantitative Methods
• Insiderness
• Using Non-Textual Elements
• Limitations of the Study
• Common Grammar Mistakes
• Writing Concisely
• Avoiding Plagiarism
• Footnotes or Endnotes?
• Further Readings
• Generative AI and Writing
• USC Libraries Tutorials and Other Guides
• Bibliography

Introduction

Before beginning your paper, you need to decide how you plan to design the study .

The research design refers to the overall strategy and analytical approach that you have chosen in order to integrate, in a coherent and logical way, the different components of the study, thus ensuring that the research problem will be thoroughly investigated. It constitutes the blueprint for the collection, measurement, and interpretation of information and data. Note that the research problem determines the type of design you choose, not the other way around!

De Vaus, D. A. Research Design in Social Research . London: SAGE, 2001; Trochim, William M.K. Research Methods Knowledge Base. 2006.

General Structure and Writing Style

The function of a research design is to ensure that the evidence obtained enables you to effectively address the research problem logically and as unambiguously as possible . In social sciences research, obtaining information relevant to the research problem generally entails specifying the type of evidence needed to test the underlying assumptions of a theory, to evaluate a program, or to accurately describe and assess meaning related to an observable phenomenon.

With this in mind, a common mistake made by researchers is that they begin their investigations before they have thought critically about what information is required to address the research problem. Without attending to these design issues beforehand, the overall research problem will not be adequately addressed and any conclusions drawn will run the risk of being weak and unconvincing. As a consequence, the overall validity of the study will be undermined.

The length and complexity of describing the research design in your paper can vary considerably, but any well-developed description will achieve the following :

• Identify the research problem clearly and justify its selection, particularly in relation to any valid alternative designs that could have been used,
• Review and synthesize previously published literature associated with the research problem,
• Clearly and explicitly specify hypotheses [i.e., research questions] central to the problem,
• Effectively describe the information and/or data which will be necessary for an adequate testing of the hypotheses and explain how such information and/or data will be obtained, and
• Describe the methods of analysis to be applied to the data in determining whether or not the hypotheses are true or false.

The research design is usually incorporated into the introduction of your paper . You can obtain an overall sense of what to do by reviewing studies that have utilized the same research design [e.g., using a case study approach]. This can help you develop an outline to follow for your own paper.

NOTE: Use the SAGE Research Methods Online and Cases and the SAGE Research Methods Videos databases to search for scholarly resources on how to apply specific research designs and methods . The Research Methods Online database contains links to more than 175,000 pages of SAGE publisher's book, journal, and reference content on quantitative, qualitative, and mixed research methodologies. Also included is a collection of case studies of social research projects that can be used to help you better understand abstract or complex methodological concepts. The Research Methods Videos database contains hours of tutorials, interviews, video case studies, and mini-documentaries covering the entire research process.

Creswell, John W. and J. David Creswell. Research Design: Qualitative, Quantitative, and Mixed Methods Approaches . 5th edition. Thousand Oaks, CA: Sage, 2018; De Vaus, D. A. Research Design in Social Research . London: SAGE, 2001; Gorard, Stephen. Research Design: Creating Robust Approaches for the Social Sciences . Thousand Oaks, CA: Sage, 2013; Leedy, Paul D. and Jeanne Ellis Ormrod. Practical Research: Planning and Design . Tenth edition. Boston, MA: Pearson, 2013; Vogt, W. Paul, Dianna C. Gardner, and Lynne M. Haeffele. When to Use What Research Design . New York: Guilford, 2012.

Action Research Design

Definition and Purpose

The essentials of action research design follow a characteristic cycle whereby initially an exploratory stance is adopted, where an understanding of a problem is developed and plans are made for some form of interventionary strategy. Then the intervention is carried out [the "action" in action research] during which time, pertinent observations are collected in various forms. The new interventional strategies are carried out, and this cyclic process repeats, continuing until a sufficient understanding of [or a valid implementation solution for] the problem is achieved. The protocol is iterative or cyclical in nature and is intended to foster deeper understanding of a given situation, starting with conceptualizing and particularizing the problem and moving through several interventions and evaluations.

What do these studies tell you ?

• This is a collaborative and adaptive research design that lends itself to use in work or community situations.
• Design focuses on pragmatic and solution-driven research outcomes rather than testing theories.
• When practitioners use action research, it has the potential to increase the amount they learn consciously from their experience; the action research cycle can be regarded as a learning cycle.
• Action research studies often have direct and obvious relevance to improving practice and advocating for change.
• There are no hidden controls or preemption of direction by the researcher.

What these studies don't tell you ?

• It is harder to do than conducting conventional research because the researcher takes on responsibilities of advocating for change as well as for researching the topic.
• Action research is much harder to write up because it is less likely that you can use a standard format to report your findings effectively [i.e., data is often in the form of stories or observation].
• Personal over-involvement of the researcher may bias research results.
• The cyclic nature of action research to achieve its twin outcomes of action [e.g. change] and research [e.g. understanding] is time-consuming and complex to conduct.
• Advocating for change usually requires buy-in from study participants.

Coghlan, David and Mary Brydon-Miller. The Sage Encyclopedia of Action Research . Thousand Oaks, CA:  Sage, 2014; Efron, Sara Efrat and Ruth Ravid. Action Research in Education: A Practical Guide . New York: Guilford, 2013; Gall, Meredith. Educational Research: An Introduction . Chapter 18, Action Research. 8th ed. Boston, MA: Pearson/Allyn and Bacon, 2007; Gorard, Stephen. Research Design: Creating Robust Approaches for the Social Sciences . Thousand Oaks, CA: Sage, 2013; Kemmis, Stephen and Robin McTaggart. “Participatory Action Research.” In Handbook of Qualitative Research . Norman Denzin and Yvonna S. Lincoln, eds. 2nd ed. (Thousand Oaks, CA: SAGE, 2000), pp. 567-605; McNiff, Jean. Writing and Doing Action Research . London: Sage, 2014; Reason, Peter and Hilary Bradbury. Handbook of Action Research: Participative Inquiry and Practice . Thousand Oaks, CA: SAGE, 2001.

Case Study Design

A case study is an in-depth study of a particular research problem rather than a sweeping statistical survey or comprehensive comparative inquiry. It is often used to narrow down a very broad field of research into one or a few easily researchable examples. The case study research design is also useful for testing whether a specific theory and model actually applies to phenomena in the real world. It is a useful design when not much is known about an issue or phenomenon.

• Approach excels at bringing us to an understanding of a complex issue through detailed contextual analysis of a limited number of events or conditions and their relationships.
• A researcher using a case study design can apply a variety of methodologies and rely on a variety of sources to investigate a research problem.
• Design can extend experience or add strength to what is already known through previous research.
• Social scientists, in particular, make wide use of this research design to examine contemporary real-life situations and provide the basis for the application of concepts and theories and the extension of methodologies.
• The design can provide detailed descriptions of specific and rare cases.
• A single or small number of cases offers little basis for establishing reliability or to generalize the findings to a wider population of people, places, or things.
• Intense exposure to the study of a case may bias a researcher's interpretation of the findings.
• Design does not facilitate assessment of cause and effect relationships.
• Vital information may be missing, making the case hard to interpret.
• The case may not be representative or typical of the larger problem being investigated.
• If the criteria for selecting a case is because it represents a very unusual or unique phenomenon or problem for study, then your interpretation of the findings can only apply to that particular case.

Case Studies. Writing@CSU. Colorado State University; Anastas, Jeane W. Research Design for Social Work and the Human Services . Chapter 4, Flexible Methods: Case Study Design. 2nd ed. New York: Columbia University Press, 1999; Gerring, John. “What Is a Case Study and What Is It Good for?” American Political Science Review 98 (May 2004): 341-354; Greenhalgh, Trisha, editor. Case Study Evaluation: Past, Present and Future Challenges . Bingley, UK: Emerald Group Publishing, 2015; Mills, Albert J. , Gabrielle Durepos, and Eiden Wiebe, editors. Encyclopedia of Case Study Research . Thousand Oaks, CA: SAGE Publications, 2010; Stake, Robert E. The Art of Case Study Research . Thousand Oaks, CA: SAGE, 1995; Yin, Robert K. Case Study Research: Design and Theory . Applied Social Research Methods Series, no. 5. 3rd ed. Thousand Oaks, CA: SAGE, 2003.

Causal Design

Causality studies may be thought of as understanding a phenomenon in terms of conditional statements in the form, “If X, then Y.” This type of research is used to measure what impact a specific change will have on existing norms and assumptions. Most social scientists seek causal explanations that reflect tests of hypotheses. Causal effect (nomothetic perspective) occurs when variation in one phenomenon, an independent variable, leads to or results, on average, in variation in another phenomenon, the dependent variable.

Conditions necessary for determining causality:

• Empirical association -- a valid conclusion is based on finding an association between the independent variable and the dependent variable.
• Appropriate time order -- to conclude that causation was involved, one must see that cases were exposed to variation in the independent variable before variation in the dependent variable.
• Nonspuriousness -- a relationship between two variables that is not due to variation in a third variable.
• Causality research designs assist researchers in understanding why the world works the way it does through the process of proving a causal link between variables and by the process of eliminating other possibilities.
• Replication is possible.
• There is greater confidence the study has internal validity due to the systematic subject selection and equity of groups being compared.
• Not all relationships are causal! The possibility always exists that, by sheer coincidence, two unrelated events appear to be related [e.g., Punxatawney Phil could accurately predict the duration of Winter for five consecutive years but, the fact remains, he's just a big, furry rodent].
• Conclusions about causal relationships are difficult to determine due to a variety of extraneous and confounding variables that exist in a social environment. This means causality can only be inferred, never proven.
• If two variables are correlated, the cause must come before the effect. However, even though two variables might be causally related, it can sometimes be difficult to determine which variable comes first and, therefore, to establish which variable is the actual cause and which is the  actual effect.

Beach, Derek and Rasmus Brun Pedersen. Causal Case Study Methods: Foundations and Guidelines for Comparing, Matching, and Tracing . Ann Arbor, MI: University of Michigan Press, 2016; Bachman, Ronet. The Practice of Research in Criminology and Criminal Justice . Chapter 5, Causation and Research Designs. 3rd ed. Thousand Oaks, CA: Pine Forge Press, 2007; Brewer, Ernest W. and Jennifer Kubn. “Causal-Comparative Design.” In Encyclopedia of Research Design . Neil J. Salkind, editor. (Thousand Oaks, CA: Sage, 2010), pp. 125-132; Causal Research Design: Experimentation. Anonymous SlideShare Presentation; Gall, Meredith. Educational Research: An Introduction . Chapter 11, Nonexperimental Research: Correlational Designs. 8th ed. Boston, MA: Pearson/Allyn and Bacon, 2007; Trochim, William M.K. Research Methods Knowledge Base. 2006.

Cohort Design

Often used in the medical sciences, but also found in the applied social sciences, a cohort study generally refers to a study conducted over a period of time involving members of a population which the subject or representative member comes from, and who are united by some commonality or similarity. Using a quantitative framework, a cohort study makes note of statistical occurrence within a specialized subgroup, united by same or similar characteristics that are relevant to the research problem being investigated, rather than studying statistical occurrence within the general population. Using a qualitative framework, cohort studies generally gather data using methods of observation. Cohorts can be either "open" or "closed."

• Open Cohort Studies [dynamic populations, such as the population of Los Angeles] involve a population that is defined just by the state of being a part of the study in question (and being monitored for the outcome). Date of entry and exit from the study is individually defined, therefore, the size of the study population is not constant. In open cohort studies, researchers can only calculate rate based data, such as, incidence rates and variants thereof.
• Closed Cohort Studies [static populations, such as patients entered into a clinical trial] involve participants who enter into the study at one defining point in time and where it is presumed that no new participants can enter the cohort. Given this, the number of study participants remains constant (or can only decrease).
• The use of cohorts is often mandatory because a randomized control study may be unethical. For example, you cannot deliberately expose people to asbestos, you can only study its effects on those who have already been exposed. Research that measures risk factors often relies upon cohort designs.
• Because cohort studies measure potential causes before the outcome has occurred, they can demonstrate that these “causes” preceded the outcome, thereby avoiding the debate as to which is the cause and which is the effect.
• Cohort analysis is highly flexible and can provide insight into effects over time and related to a variety of different types of changes [e.g., social, cultural, political, economic, etc.].
• Either original data or secondary data can be used in this design.
• In cases where a comparative analysis of two cohorts is made [e.g., studying the effects of one group exposed to asbestos and one that has not], a researcher cannot control for all other factors that might differ between the two groups. These factors are known as confounding variables.
• Cohort studies can end up taking a long time to complete if the researcher must wait for the conditions of interest to develop within the group. This also increases the chance that key variables change during the course of the study, potentially impacting the validity of the findings.
• Due to the lack of randominization in the cohort design, its external validity is lower than that of study designs where the researcher randomly assigns participants.

Healy P, Devane D. “Methodological Considerations in Cohort Study Designs.” Nurse Researcher 18 (2011): 32-36; Glenn, Norval D, editor. Cohort Analysis . 2nd edition. Thousand Oaks, CA: Sage, 2005; Levin, Kate Ann. Study Design IV: Cohort Studies. Evidence-Based Dentistry 7 (2003): 51–52; Payne, Geoff. “Cohort Study.” In The SAGE Dictionary of Social Research Methods . Victor Jupp, editor. (Thousand Oaks, CA: Sage, 2006), pp. 31-33; Study Design 101. Himmelfarb Health Sciences Library. George Washington University, November 2011; Cohort Study. Wikipedia.

Cross-Sectional Design

Cross-sectional research designs have three distinctive features: no time dimension; a reliance on existing differences rather than change following intervention; and, groups are selected based on existing differences rather than random allocation. The cross-sectional design can only measure differences between or from among a variety of people, subjects, or phenomena rather than a process of change. As such, researchers using this design can only employ a relatively passive approach to making causal inferences based on findings.

• Cross-sectional studies provide a clear 'snapshot' of the outcome and the characteristics associated with it, at a specific point in time.
• Unlike an experimental design, where there is an active intervention by the researcher to produce and measure change or to create differences, cross-sectional designs focus on studying and drawing inferences from existing differences between people, subjects, or phenomena.
• Entails collecting data at and concerning one point in time. While longitudinal studies involve taking multiple measures over an extended period of time, cross-sectional research is focused on finding relationships between variables at one moment in time.
• Groups identified for study are purposely selected based upon existing differences in the sample rather than seeking random sampling.
• Cross-section studies are capable of using data from a large number of subjects and, unlike observational studies, is not geographically bound.
• Can estimate prevalence of an outcome of interest because the sample is usually taken from the whole population.
• Because cross-sectional designs generally use survey techniques to gather data, they are relatively inexpensive and take up little time to conduct.
• Finding people, subjects, or phenomena to study that are very similar except in one specific variable can be difficult.
• Results are static and time bound and, therefore, give no indication of a sequence of events or reveal historical or temporal contexts.
• Studies cannot be utilized to establish cause and effect relationships.
• This design only provides a snapshot of analysis so there is always the possibility that a study could have differing results if another time-frame had been chosen.
• There is no follow up to the findings.

Bethlehem, Jelke. "7: Cross-sectional Research." In Research Methodology in the Social, Behavioural and Life Sciences . Herman J Adèr and Gideon J Mellenbergh, editors. (London, England: Sage, 1999), pp. 110-43; Bourque, Linda B. “Cross-Sectional Design.” In  The SAGE Encyclopedia of Social Science Research Methods . Michael S. Lewis-Beck, Alan Bryman, and Tim Futing Liao. (Thousand Oaks, CA: 2004), pp. 230-231; Hall, John. “Cross-Sectional Survey Design.” In Encyclopedia of Survey Research Methods . Paul J. Lavrakas, ed. (Thousand Oaks, CA: Sage, 2008), pp. 173-174; Helen Barratt, Maria Kirwan. Cross-Sectional Studies: Design Application, Strengths and Weaknesses of Cross-Sectional Studies. Healthknowledge, 2009. Cross-Sectional Study. Wikipedia.

Descriptive Design

Descriptive research designs help provide answers to the questions of who, what, when, where, and how associated with a particular research problem; a descriptive study cannot conclusively ascertain answers to why. Descriptive research is used to obtain information concerning the current status of the phenomena and to describe "what exists" with respect to variables or conditions in a situation.

• The subject is being observed in a completely natural and unchanged natural environment. True experiments, whilst giving analyzable data, often adversely influence the normal behavior of the subject [a.k.a., the Heisenberg effect whereby measurements of certain systems cannot be made without affecting the systems].
• Descriptive research is often used as a pre-cursor to more quantitative research designs with the general overview giving some valuable pointers as to what variables are worth testing quantitatively.
• If the limitations are understood, they can be a useful tool in developing a more focused study.
• Descriptive studies can yield rich data that lead to important recommendations in practice.
• Appoach collects a large amount of data for detailed analysis.
• The results from a descriptive research cannot be used to discover a definitive answer or to disprove a hypothesis.
• Because descriptive designs often utilize observational methods [as opposed to quantitative methods], the results cannot be replicated.
• The descriptive function of research is heavily dependent on instrumentation for measurement and observation.

Anastas, Jeane W. Research Design for Social Work and the Human Services . Chapter 5, Flexible Methods: Descriptive Research. 2nd ed. New York: Columbia University Press, 1999; Given, Lisa M. "Descriptive Research." In Encyclopedia of Measurement and Statistics . Neil J. Salkind and Kristin Rasmussen, editors. (Thousand Oaks, CA: Sage, 2007), pp. 251-254; McNabb, Connie. Descriptive Research Methodologies. Powerpoint Presentation; Shuttleworth, Martyn. Descriptive Research Design, September 26, 2008; Erickson, G. Scott. "Descriptive Research Design." In New Methods of Market Research and Analysis . (Northampton, MA: Edward Elgar Publishing, 2017), pp. 51-77; Sahin, Sagufta, and Jayanta Mete. "A Brief Study on Descriptive Research: Its Nature and Application in Social Science." International Journal of Research and Analysis in Humanities 1 (2021): 11; K. Swatzell and P. Jennings. “Descriptive Research: The Nuts and Bolts.” Journal of the American Academy of Physician Assistants 20 (2007), pp. 55-56; Kane, E. Doing Your Own Research: Basic Descriptive Research in the Social Sciences and Humanities . London: Marion Boyars, 1985.

Experimental Design

A blueprint of the procedure that enables the researcher to maintain control over all factors that may affect the result of an experiment. In doing this, the researcher attempts to determine or predict what may occur. Experimental research is often used where there is time priority in a causal relationship (cause precedes effect), there is consistency in a causal relationship (a cause will always lead to the same effect), and the magnitude of the correlation is great. The classic experimental design specifies an experimental group and a control group. The independent variable is administered to the experimental group and not to the control group, and both groups are measured on the same dependent variable. Subsequent experimental designs have used more groups and more measurements over longer periods. True experiments must have control, randomization, and manipulation.

• Experimental research allows the researcher to control the situation. In so doing, it allows researchers to answer the question, “What causes something to occur?”
• Permits the researcher to identify cause and effect relationships between variables and to distinguish placebo effects from treatment effects.
• Experimental research designs support the ability to limit alternative explanations and to infer direct causal relationships in the study.
• Approach provides the highest level of evidence for single studies.
• The design is artificial, and results may not generalize well to the real world.
• The artificial settings of experiments may alter the behaviors or responses of participants.
• Experimental designs can be costly if special equipment or facilities are needed.
• Some research problems cannot be studied using an experiment because of ethical or technical reasons.
• Difficult to apply ethnographic and other qualitative methods to experimentally designed studies.

Anastas, Jeane W. Research Design for Social Work and the Human Services . Chapter 7, Flexible Methods: Experimental Research. 2nd ed. New York: Columbia University Press, 1999; Chapter 2: Research Design, Experimental Designs. School of Psychology, University of New England, 2000; Chow, Siu L. "Experimental Design." In Encyclopedia of Research Design . Neil J. Salkind, editor. (Thousand Oaks, CA: Sage, 2010), pp. 448-453; "Experimental Design." In Social Research Methods . Nicholas Walliman, editor. (London, England: Sage, 2006), pp, 101-110; Experimental Research. Research Methods by Dummies. Department of Psychology. California State University, Fresno, 2006; Kirk, Roger E. Experimental Design: Procedures for the Behavioral Sciences . 4th edition. Thousand Oaks, CA: Sage, 2013; Trochim, William M.K. Experimental Design. Research Methods Knowledge Base. 2006; Rasool, Shafqat. Experimental Research. Slideshare presentation.

Exploratory Design

An exploratory design is conducted about a research problem when there are few or no earlier studies to refer to or rely upon to predict an outcome . The focus is on gaining insights and familiarity for later investigation or undertaken when research problems are in a preliminary stage of investigation. Exploratory designs are often used to establish an understanding of how best to proceed in studying an issue or what methodology would effectively apply to gathering information about the issue.

The goals of exploratory research are intended to produce the following possible insights:

• Familiarity with basic details, settings, and concerns.
• Well grounded picture of the situation being developed.
• Generation of new ideas and assumptions.
• Development of tentative theories or hypotheses.
• Determination about whether a study is feasible in the future.
• Issues get refined for more systematic investigation and formulation of new research questions.
• Direction for future research and techniques get developed.
• Design is a useful approach for gaining background information on a particular topic.
• Exploratory research is flexible and can address research questions of all types (what, why, how).
• Provides an opportunity to define new terms and clarify existing concepts.
• Exploratory research is often used to generate formal hypotheses and develop more precise research problems.
• In the policy arena or applied to practice, exploratory studies help establish research priorities and where resources should be allocated.
• Exploratory research generally utilizes small sample sizes and, thus, findings are typically not generalizable to the population at large.
• The exploratory nature of the research inhibits an ability to make definitive conclusions about the findings. They provide insight but not definitive conclusions.
• The research process underpinning exploratory studies is flexible but often unstructured, leading to only tentative results that have limited value to decision-makers.
• Design lacks rigorous standards applied to methods of data gathering and analysis because one of the areas for exploration could be to determine what method or methodologies could best fit the research problem.

Cuthill, Michael. “Exploratory Research: Citizen Participation, Local Government, and Sustainable Development in Australia.” Sustainable Development 10 (2002): 79-89; Streb, Christoph K. "Exploratory Case Study." In Encyclopedia of Case Study Research . Albert J. Mills, Gabrielle Durepos and Eiden Wiebe, editors. (Thousand Oaks, CA: Sage, 2010), pp. 372-374; Taylor, P. J., G. Catalano, and D.R.F. Walker. “Exploratory Analysis of the World City Network.” Urban Studies 39 (December 2002): 2377-2394; Exploratory Research. Wikipedia.

Field Research Design

Sometimes referred to as ethnography or participant observation, designs around field research encompass a variety of interpretative procedures [e.g., observation and interviews] rooted in qualitative approaches to studying people individually or in groups while inhabiting their natural environment as opposed to using survey instruments or other forms of impersonal methods of data gathering. Information acquired from observational research takes the form of “ field notes ” that involves documenting what the researcher actually sees and hears while in the field. Findings do not consist of conclusive statements derived from numbers and statistics because field research involves analysis of words and observations of behavior. Conclusions, therefore, are developed from an interpretation of findings that reveal overriding themes, concepts, and ideas. More information can be found HERE .

• Field research is often necessary to fill gaps in understanding the research problem applied to local conditions or to specific groups of people that cannot be ascertained from existing data.
• The research helps contextualize already known information about a research problem, thereby facilitating ways to assess the origins, scope, and scale of a problem and to gage the causes, consequences, and means to resolve an issue based on deliberate interaction with people in their natural inhabited spaces.
• Enables the researcher to corroborate or confirm data by gathering additional information that supports or refutes findings reported in prior studies of the topic.
• Because the researcher in embedded in the field, they are better able to make observations or ask questions that reflect the specific cultural context of the setting being investigated.
• Observing the local reality offers the opportunity to gain new perspectives or obtain unique data that challenges existing theoretical propositions or long-standing assumptions found in the literature.

What these studies don't tell you

• A field research study requires extensive time and resources to carry out the multiple steps involved with preparing for the gathering of information, including for example, examining background information about the study site, obtaining permission to access the study site, and building trust and rapport with subjects.
• Requires a commitment to staying engaged in the field to ensure that you can adequately document events and behaviors as they unfold.
• The unpredictable nature of fieldwork means that researchers can never fully control the process of data gathering. They must maintain a flexible approach to studying the setting because events and circumstances can change quickly or unexpectedly.
• Findings can be difficult to interpret and verify without access to documents and other source materials that help to enhance the credibility of information obtained from the field  [i.e., the act of triangulating the data].
• Linking the research problem to the selection of study participants inhabiting their natural environment is critical. However, this specificity limits the ability to generalize findings to different situations or in other contexts or to infer courses of action applied to other settings or groups of people.
• The reporting of findings must take into account how the researcher themselves may have inadvertently affected respondents and their behaviors.

Historical Design

The purpose of a historical research design is to collect, verify, and synthesize evidence from the past to establish facts that defend or refute a hypothesis. It uses secondary sources and a variety of primary documentary evidence, such as, diaries, official records, reports, archives, and non-textual information [maps, pictures, audio and visual recordings]. The limitation is that the sources must be both authentic and valid.

• The historical research design is unobtrusive; the act of research does not affect the results of the study.
• The historical approach is well suited for trend analysis.
• Historical records can add important contextual background required to more fully understand and interpret a research problem.
• There is often no possibility of researcher-subject interaction that could affect the findings.
• Historical sources can be used over and over to study different research problems or to replicate a previous study.
• The ability to fulfill the aims of your research are directly related to the amount and quality of documentation available to understand the research problem.
• Since historical research relies on data from the past, there is no way to manipulate it to control for contemporary contexts.
• Interpreting historical sources can be very time consuming.
• The sources of historical materials must be archived consistently to ensure access. This may especially challenging for digital or online-only sources.
• Original authors bring their own perspectives and biases to the interpretation of past events and these biases are more difficult to ascertain in historical resources.
• Due to the lack of control over external variables, historical research is very weak with regard to the demands of internal validity.
• It is rare that the entirety of historical documentation needed to fully address a research problem is available for interpretation, therefore, gaps need to be acknowledged.

Howell, Martha C. and Walter Prevenier. From Reliable Sources: An Introduction to Historical Methods . Ithaca, NY: Cornell University Press, 2001; Lundy, Karen Saucier. "Historical Research." In The Sage Encyclopedia of Qualitative Research Methods . Lisa M. Given, editor. (Thousand Oaks, CA: Sage, 2008), pp. 396-400; Marius, Richard. and Melvin E. Page. A Short Guide to Writing about History . 9th edition. Boston, MA: Pearson, 2015; Savitt, Ronald. “Historical Research in Marketing.” Journal of Marketing 44 (Autumn, 1980): 52-58;  Gall, Meredith. Educational Research: An Introduction . Chapter 16, Historical Research. 8th ed. Boston, MA: Pearson/Allyn and Bacon, 2007.

Longitudinal Design

A longitudinal study follows the same sample over time and makes repeated observations. For example, with longitudinal surveys, the same group of people is interviewed at regular intervals, enabling researchers to track changes over time and to relate them to variables that might explain why the changes occur. Longitudinal research designs describe patterns of change and help establish the direction and magnitude of causal relationships. Measurements are taken on each variable over two or more distinct time periods. This allows the researcher to measure change in variables over time. It is a type of observational study sometimes referred to as a panel study.

• Longitudinal data facilitate the analysis of the duration of a particular phenomenon.
• Enables survey researchers to get close to the kinds of causal explanations usually attainable only with experiments.
• The design permits the measurement of differences or change in a variable from one period to another [i.e., the description of patterns of change over time].
• Longitudinal studies facilitate the prediction of future outcomes based upon earlier factors.
• The data collection method may change over time.
• Maintaining the integrity of the original sample can be difficult over an extended period of time.
• It can be difficult to show more than one variable at a time.
• This design often needs qualitative research data to explain fluctuations in the results.
• A longitudinal research design assumes present trends will continue unchanged.
• It can take a long period of time to gather results.
• There is a need to have a large sample size and accurate sampling to reach representativness.

Anastas, Jeane W. Research Design for Social Work and the Human Services . Chapter 6, Flexible Methods: Relational and Longitudinal Research. 2nd ed. New York: Columbia University Press, 1999; Forgues, Bernard, and Isabelle Vandangeon-Derumez. "Longitudinal Analyses." In Doing Management Research . Raymond-Alain Thiétart and Samantha Wauchope, editors. (London, England: Sage, 2001), pp. 332-351; Kalaian, Sema A. and Rafa M. Kasim. "Longitudinal Studies." In Encyclopedia of Survey Research Methods . Paul J. Lavrakas, ed. (Thousand Oaks, CA: Sage, 2008), pp. 440-441; Menard, Scott, editor. Longitudinal Research . Thousand Oaks, CA: Sage, 2002; Ployhart, Robert E. and Robert J. Vandenberg. "Longitudinal Research: The Theory, Design, and Analysis of Change.” Journal of Management 36 (January 2010): 94-120; Longitudinal Study. Wikipedia.

Meta-Analysis Design

Meta-analysis is an analytical methodology designed to systematically evaluate and summarize the results from a number of individual studies, thereby, increasing the overall sample size and the ability of the researcher to study effects of interest. The purpose is to not simply summarize existing knowledge, but to develop a new understanding of a research problem using synoptic reasoning. The main objectives of meta-analysis include analyzing differences in the results among studies and increasing the precision by which effects are estimated. A well-designed meta-analysis depends upon strict adherence to the criteria used for selecting studies and the availability of information in each study to properly analyze their findings. Lack of information can severely limit the type of analyzes and conclusions that can be reached. In addition, the more dissimilarity there is in the results among individual studies [heterogeneity], the more difficult it is to justify interpretations that govern a valid synopsis of results. A meta-analysis needs to fulfill the following requirements to ensure the validity of your findings:

• Clearly defined description of objectives, including precise definitions of the variables and outcomes that are being evaluated;
• A well-reasoned and well-documented justification for identification and selection of the studies;
• Assessment and explicit acknowledgment of any researcher bias in the identification and selection of those studies;
• Description and evaluation of the degree of heterogeneity among the sample size of studies reviewed; and,
• Justification of the techniques used to evaluate the studies.
• Can be an effective strategy for determining gaps in the literature.
• Provides a means of reviewing research published about a particular topic over an extended period of time and from a variety of sources.
• Is useful in clarifying what policy or programmatic actions can be justified on the basis of analyzing research results from multiple studies.
• Provides a method for overcoming small sample sizes in individual studies that previously may have had little relationship to each other.
• Can be used to generate new hypotheses or highlight research problems for future studies.
• Small violations in defining the criteria used for content analysis can lead to difficult to interpret and/or meaningless findings.
• A large sample size can yield reliable, but not necessarily valid, results.
• A lack of uniformity regarding, for example, the type of literature reviewed, how methods are applied, and how findings are measured within the sample of studies you are analyzing, can make the process of synthesis difficult to perform.
• Depending on the sample size, the process of reviewing and synthesizing multiple studies can be very time consuming.

Beck, Lewis W. "The Synoptic Method." The Journal of Philosophy 36 (1939): 337-345; Cooper, Harris, Larry V. Hedges, and Jeffrey C. Valentine, eds. The Handbook of Research Synthesis and Meta-Analysis . 2nd edition. New York: Russell Sage Foundation, 2009; Guzzo, Richard A., Susan E. Jackson and Raymond A. Katzell. “Meta-Analysis Analysis.” In Research in Organizational Behavior , Volume 9. (Greenwich, CT: JAI Press, 1987), pp 407-442; Lipsey, Mark W. and David B. Wilson. Practical Meta-Analysis . Thousand Oaks, CA: Sage Publications, 2001; Study Design 101. Meta-Analysis. The Himmelfarb Health Sciences Library, George Washington University; Timulak, Ladislav. “Qualitative Meta-Analysis.” In The SAGE Handbook of Qualitative Data Analysis . Uwe Flick, editor. (Los Angeles, CA: Sage, 2013), pp. 481-495; Walker, Esteban, Adrian V. Hernandez, and Micheal W. Kattan. "Meta-Analysis: It's Strengths and Limitations." Cleveland Clinic Journal of Medicine 75 (June 2008): 431-439.

Mixed-Method Design

• Narrative and non-textual information can add meaning to numeric data, while numeric data can add precision to narrative and non-textual information.
• Can utilize existing data while at the same time generating and testing a grounded theory approach to describe and explain the phenomenon under study.
• A broader, more complex research problem can be investigated because the researcher is not constrained by using only one method.
• The strengths of one method can be used to overcome the inherent weaknesses of another method.
• Can provide stronger, more robust evidence to support a conclusion or set of recommendations.
• May generate new knowledge new insights or uncover hidden insights, patterns, or relationships that a single methodological approach might not reveal.
• Produces more complete knowledge and understanding of the research problem that can be used to increase the generalizability of findings applied to theory or practice.
• A researcher must be proficient in understanding how to apply multiple methods to investigating a research problem as well as be proficient in optimizing how to design a study that coherently melds them together.
• Can increase the likelihood of conflicting results or ambiguous findings that inhibit drawing a valid conclusion or setting forth a recommended course of action [e.g., sample interview responses do not support existing statistical data].
• Because the research design can be very complex, reporting the findings requires a well-organized narrative, clear writing style, and precise word choice.
• Design invites collaboration among experts. However, merging different investigative approaches and writing styles requires more attention to the overall research process than studies conducted using only one methodological paradigm.
• Concurrent merging of quantitative and qualitative research requires greater attention to having adequate sample sizes, using comparable samples, and applying a consistent unit of analysis. For sequential designs where one phase of qualitative research builds on the quantitative phase or vice versa, decisions about what results from the first phase to use in the next phase, the choice of samples and estimating reasonable sample sizes for both phases, and the interpretation of results from both phases can be difficult.
• Due to multiple forms of data being collected and analyzed, this design requires extensive time and resources to carry out the multiple steps involved in data gathering and interpretation.

Burch, Patricia and Carolyn J. Heinrich. Mixed Methods for Policy Research and Program Evaluation . Thousand Oaks, CA: Sage, 2016; Creswell, John w. et al. Best Practices for Mixed Methods Research in the Health Sciences . Bethesda, MD: Office of Behavioral and Social Sciences Research, National Institutes of Health, 2010Creswell, John W. Research Design: Qualitative, Quantitative, and Mixed Methods Approaches . 4th edition. Thousand Oaks, CA: Sage Publications, 2014; Domínguez, Silvia, editor. Mixed Methods Social Networks Research . Cambridge, UK: Cambridge University Press, 2014; Hesse-Biber, Sharlene Nagy. Mixed Methods Research: Merging Theory with Practice . New York: Guilford Press, 2010; Niglas, Katrin. “How the Novice Researcher Can Make Sense of Mixed Methods Designs.” International Journal of Multiple Research Approaches 3 (2009): 34-46; Onwuegbuzie, Anthony J. and Nancy L. Leech. “Linking Research Questions to Mixed Methods Data Analysis Procedures.” The Qualitative Report 11 (September 2006): 474-498; Tashakorri, Abbas and John W. Creswell. “The New Era of Mixed Methods.” Journal of Mixed Methods Research 1 (January 2007): 3-7; Zhanga, Wanqing. “Mixed Methods Application in Health Intervention Research: A Multiple Case Study.” International Journal of Multiple Research Approaches 8 (2014): 24-35 .

Observational Design

This type of research design draws a conclusion by comparing subjects against a control group, in cases where the researcher has no control over the experiment. There are two general types of observational designs. In direct observations, people know that you are watching them. Unobtrusive measures involve any method for studying behavior where individuals do not know they are being observed. An observational study allows a useful insight into a phenomenon and avoids the ethical and practical difficulties of setting up a large and cumbersome research project.

• Observational studies are usually flexible and do not necessarily need to be structured around a hypothesis about what you expect to observe [data is emergent rather than pre-existing].
• The researcher is able to collect in-depth information about a particular behavior.
• Can reveal interrelationships among multifaceted dimensions of group interactions.
• You can generalize your results to real life situations.
• Observational research is useful for discovering what variables may be important before applying other methods like experiments.
• Observation research designs account for the complexity of group behaviors.
• Reliability of data is low because seeing behaviors occur over and over again may be a time consuming task and are difficult to replicate.
• In observational research, findings may only reflect a unique sample population and, thus, cannot be generalized to other groups.
• There can be problems with bias as the researcher may only "see what they want to see."
• There is no possibility to determine "cause and effect" relationships since nothing is manipulated.
• Sources or subjects may not all be equally credible.
• Any group that is knowingly studied is altered to some degree by the presence of the researcher, therefore, potentially skewing any data collected.

Atkinson, Paul and Martyn Hammersley. “Ethnography and Participant Observation.” In Handbook of Qualitative Research . Norman K. Denzin and Yvonna S. Lincoln, eds. (Thousand Oaks, CA: Sage, 1994), pp. 248-261; Observational Research. Research Methods by Dummies. Department of Psychology. California State University, Fresno, 2006; Patton Michael Quinn. Qualitiative Research and Evaluation Methods . Chapter 6, Fieldwork Strategies and Observational Methods. 3rd ed. Thousand Oaks, CA: Sage, 2002; Payne, Geoff and Judy Payne. "Observation." In Key Concepts in Social Research . The SAGE Key Concepts series. (London, England: Sage, 2004), pp. 158-162; Rosenbaum, Paul R. Design of Observational Studies . New York: Springer, 2010;Williams, J. Patrick. "Nonparticipant Observation." In The Sage Encyclopedia of Qualitative Research Methods . Lisa M. Given, editor.(Thousand Oaks, CA: Sage, 2008), pp. 562-563.

Philosophical Design

Understood more as an broad approach to examining a research problem than a methodological design, philosophical analysis and argumentation is intended to challenge deeply embedded, often intractable, assumptions underpinning an area of study. This approach uses the tools of argumentation derived from philosophical traditions, concepts, models, and theories to critically explore and challenge, for example, the relevance of logic and evidence in academic debates, to analyze arguments about fundamental issues, or to discuss the root of existing discourse about a research problem. These overarching tools of analysis can be framed in three ways:

• Ontology -- the study that describes the nature of reality; for example, what is real and what is not, what is fundamental and what is derivative?
• Epistemology -- the study that explores the nature of knowledge; for example, by what means does knowledge and understanding depend upon and how can we be certain of what we know?
• Axiology -- the study of values; for example, what values does an individual or group hold and why? How are values related to interest, desire, will, experience, and means-to-end? And, what is the difference between a matter of fact and a matter of value?
• Can provide a basis for applying ethical decision-making to practice.
• Functions as a means of gaining greater self-understanding and self-knowledge about the purposes of research.
• Brings clarity to general guiding practices and principles of an individual or group.
• Philosophy informs methodology.
• Refine concepts and theories that are invoked in relatively unreflective modes of thought and discourse.
• Beyond methodology, philosophy also informs critical thinking about epistemology and the structure of reality (metaphysics).
• Offers clarity and definition to the practical and theoretical uses of terms, concepts, and ideas.
• Limited application to specific research problems [answering the "So What?" question in social science research].
• Analysis can be abstract, argumentative, and limited in its practical application to real-life issues.
• While a philosophical analysis may render problematic that which was once simple or taken-for-granted, the writing can be dense and subject to unnecessary jargon, overstatement, and/or excessive quotation and documentation.
• There are limitations in the use of metaphor as a vehicle of philosophical analysis.
• There can be analytical difficulties in moving from philosophy to advocacy and between abstract thought and application to the phenomenal world.

Burton, Dawn. "Part I, Philosophy of the Social Sciences." In Research Training for Social Scientists . (London, England: Sage, 2000), pp. 1-5; Chapter 4, Research Methodology and Design. Unisa Institutional Repository (UnisaIR), University of South Africa; Jarvie, Ian C., and Jesús Zamora-Bonilla, editors. The SAGE Handbook of the Philosophy of Social Sciences . London: Sage, 2011; Labaree, Robert V. and Ross Scimeca. “The Philosophical Problem of Truth in Librarianship.” The Library Quarterly 78 (January 2008): 43-70; Maykut, Pamela S. Beginning Qualitative Research: A Philosophic and Practical Guide . Washington, DC: Falmer Press, 1994; McLaughlin, Hugh. "The Philosophy of Social Research." In Understanding Social Work Research . 2nd edition. (London: SAGE Publications Ltd., 2012), pp. 24-47; Stanford Encyclopedia of Philosophy . Metaphysics Research Lab, CSLI, Stanford University, 2013.

Sequential Design

• The researcher has a limitless option when it comes to sample size and the sampling schedule.
• Due to the repetitive nature of this research design, minor changes and adjustments can be done during the initial parts of the study to correct and hone the research method.
• This is a useful design for exploratory studies.
• There is very little effort on the part of the researcher when performing this technique. It is generally not expensive, time consuming, or workforce intensive.
• Because the study is conducted serially, the results of one sample are known before the next sample is taken and analyzed. This provides opportunities for continuous improvement of sampling and methods of analysis.
• The sampling method is not representative of the entire population. The only possibility of approaching representativeness is when the researcher chooses to use a very large sample size significant enough to represent a significant portion of the entire population. In this case, moving on to study a second or more specific sample can be difficult.
• The design cannot be used to create conclusions and interpretations that pertain to an entire population because the sampling technique is not randomized. Generalizability from findings is, therefore, limited.
• Difficult to account for and interpret variation from one sample to another over time, particularly when using qualitative methods of data collection.

Betensky, Rebecca. Harvard University, Course Lecture Note slides; Bovaird, James A. and Kevin A. Kupzyk. "Sequential Design." In Encyclopedia of Research Design . Neil J. Salkind, editor. (Thousand Oaks, CA: Sage, 2010), pp. 1347-1352; Cresswell, John W. Et al. “Advanced Mixed-Methods Research Designs.” In Handbook of Mixed Methods in Social and Behavioral Research . Abbas Tashakkori and Charles Teddle, eds. (Thousand Oaks, CA: Sage, 2003), pp. 209-240; Henry, Gary T. "Sequential Sampling." In The SAGE Encyclopedia of Social Science Research Methods . Michael S. Lewis-Beck, Alan Bryman and Tim Futing Liao, editors. (Thousand Oaks, CA: Sage, 2004), pp. 1027-1028; Nataliya V. Ivankova. “Using Mixed-Methods Sequential Explanatory Design: From Theory to Practice.” Field Methods 18 (February 2006): 3-20; Bovaird, James A. and Kevin A. Kupzyk. “Sequential Design.” In Encyclopedia of Research Design . Neil J. Salkind, ed. Thousand Oaks, CA: Sage, 2010; Sequential Analysis. Wikipedia.

Systematic Review

• A systematic review synthesizes the findings of multiple studies related to each other by incorporating strategies of analysis and interpretation intended to reduce biases and random errors.
• The application of critical exploration, evaluation, and synthesis methods separates insignificant, unsound, or redundant research from the most salient and relevant studies worthy of reflection.
• They can be use to identify, justify, and refine hypotheses, recognize and avoid hidden problems in prior studies, and explain data inconsistencies and conflicts in data.
• Systematic reviews can be used to help policy makers formulate evidence-based guidelines and regulations.
• The use of strict, explicit, and pre-determined methods of synthesis, when applied appropriately, provide reliable estimates about the effects of interventions, evaluations, and effects related to the overarching research problem investigated by each study under review.
• Systematic reviews illuminate where knowledge or thorough understanding of a research problem is lacking and, therefore, can then be used to guide future research.
• The accepted inclusion of unpublished studies [i.e., grey literature] ensures the broadest possible way to analyze and interpret research on a topic.
• Results of the synthesis can be generalized and the findings extrapolated into the general population with more validity than most other types of studies .
• Systematic reviews do not create new knowledge per se; they are a method for synthesizing existing studies about a research problem in order to gain new insights and determine gaps in the literature.
• The way researchers have carried out their investigations [e.g., the period of time covered, number of participants, sources of data analyzed, etc.] can make it difficult to effectively synthesize studies.
• The inclusion of unpublished studies can introduce bias into the review because they may not have undergone a rigorous peer-review process prior to publication. Examples may include conference presentations or proceedings, publications from government agencies, white papers, working papers, and internal documents from organizations, and doctoral dissertations and Master's theses.

Denyer, David and David Tranfield. "Producing a Systematic Review." In The Sage Handbook of Organizational Research Methods .  David A. Buchanan and Alan Bryman, editors. ( Thousand Oaks, CA: Sage Publications, 2009), pp. 671-689; Foster, Margaret J. and Sarah T. Jewell, editors. Assembling the Pieces of a Systematic Review: A Guide for Librarians . Lanham, MD: Rowman and Littlefield, 2017; Gough, David, Sandy Oliver, James Thomas, editors. Introduction to Systematic Reviews . 2nd edition. Los Angeles, CA: Sage Publications, 2017; Gopalakrishnan, S. and P. Ganeshkumar. “Systematic Reviews and Meta-analysis: Understanding the Best Evidence in Primary Healthcare.” Journal of Family Medicine and Primary Care 2 (2013): 9-14; Gough, David, James Thomas, and Sandy Oliver. "Clarifying Differences between Review Designs and Methods." Systematic Reviews 1 (2012): 1-9; Khan, Khalid S., Regina Kunz, Jos Kleijnen, and Gerd Antes. “Five Steps to Conducting a Systematic Review.” Journal of the Royal Society of Medicine 96 (2003): 118-121; Mulrow, C. D. “Systematic Reviews: Rationale for Systematic Reviews.” BMJ 309:597 (September 1994); O'Dwyer, Linda C., and Q. Eileen Wafford. "Addressing Challenges with Systematic Review Teams through Effective Communication: A Case Report." Journal of the Medical Library Association 109 (October 2021): 643-647; Okoli, Chitu, and Kira Schabram. "A Guide to Conducting a Systematic Literature Review of Information Systems Research."  Sprouts: Working Papers on Information Systems 10 (2010); Siddaway, Andy P., Alex M. Wood, and Larry V. Hedges. "How to Do a Systematic Review: A Best Practice Guide for Conducting and Reporting Narrative Reviews, Meta-analyses, and Meta-syntheses." Annual Review of Psychology 70 (2019): 747-770; Torgerson, Carole J. “Publication Bias: The Achilles’ Heel of Systematic Reviews?” British Journal of Educational Studies 54 (March 2006): 89-102; Torgerson, Carole. Systematic Reviews . New York: Continuum, 2003.

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Home Market Research

What is Research: Definition, Methods, Types & Examples

The search for knowledge is closely linked to the object of study; that is, to the reconstruction of the facts that will provide an explanation to an observed event and that at first sight can be considered as a problem. It is very human to seek answers and satisfy our curiosity. Let’s talk about research.

Content Index

What is Research?

What are the characteristics of research.

• Comparative analysis chart

Qualitative methods

Quantitative methods, 8 tips for conducting accurate research.

Research is the careful consideration of study regarding a particular concern or research problem using scientific methods. According to the American sociologist Earl Robert Babbie, “research is a systematic inquiry to describe, explain, predict, and control the observed phenomenon. It involves inductive and deductive methods.”

Inductive methods analyze an observed event, while deductive methods verify the observed event. Inductive approaches are associated with qualitative research , and deductive methods are more commonly associated with quantitative analysis .

Research is conducted with a purpose to:

• Identify potential and new customers
• Understand existing customers
• Set pragmatic goals
• Develop productive market strategies
• Address business challenges
• Put together a business expansion plan
• Identify new business opportunities
• Good research follows a systematic approach to capture accurate data. Researchers need to practice ethics and a code of conduct while making observations or drawing conclusions.
• The analysis is based on logical reasoning and involves both inductive and deductive methods.
• Real-time data and knowledge is derived from actual observations in natural settings.
• There is an in-depth analysis of all data collected so that there are no anomalies associated with it.
• It creates a path for generating new questions. Existing data helps create more research opportunities.
• It is analytical and uses all the available data so that there is no ambiguity in inference.
• Accuracy is one of the most critical aspects of research. The information must be accurate and correct. For example, laboratories provide a controlled environment to collect data. Accuracy is measured in the instruments used, the calibrations of instruments or tools, and the experiment’s final result.

What is the purpose of research?

There are three main purposes:

• Exploratory: As the name suggests, researchers conduct exploratory studies to explore a group of questions. The answers and analytics may not offer a conclusion to the perceived problem. It is undertaken to handle new problem areas that haven’t been explored before. This exploratory data analysis process lays the foundation for more conclusive data collection and analysis.

LEARN ABOUT: Descriptive Analysis

• Descriptive: It focuses on expanding knowledge on current issues through a process of data collection. Descriptive research describe the behavior of a sample population. Only one variable is required to conduct the study. The three primary purposes of descriptive studies are describing, explaining, and validating the findings. For example, a study conducted to know if top-level management leaders in the 21st century possess the moral right to receive a considerable sum of money from the company profit.

LEARN ABOUT: Best Data Collection Tools

• Explanatory: Causal research or explanatory research is conducted to understand the impact of specific changes in existing standard procedures. Running experiments is the most popular form. For example, a study that is conducted to understand the effect of rebranding on customer loyalty.

Here is a comparative analysis chart for a better understanding:

It begins by asking the right questions and choosing an appropriate method to investigate the problem. After collecting answers to your questions, you can analyze the findings or observations to draw reasonable conclusions.

When it comes to customers and market studies, the more thorough your questions, the better the analysis. You get essential insights into brand perception and product needs by thoroughly collecting customer data through surveys and questionnaires . You can use this data to make smart decisions about your marketing strategies to position your business effectively.

To make sense of your study and get insights faster, it helps to use a research repository as a single source of truth in your organization and manage your research data in one centralized data repository .

Types of research methods and Examples

Research methods are broadly classified as Qualitative and Quantitative .

Both methods have distinctive properties and data collection methods .

Qualitative research is a method that collects data using conversational methods, usually open-ended questions . The responses collected are essentially non-numerical. This method helps a researcher understand what participants think and why they think in a particular way.

Types of qualitative methods include:

• One-to-one Interview
• Focus Groups
• Ethnographic studies
• Text Analysis

Quantitative methods deal with numbers and measurable forms . It uses a systematic way of investigating events or data. It answers questions to justify relationships with measurable variables to either explain, predict, or control a phenomenon.

Types of quantitative methods include:

• Survey research
• Descriptive research
• Correlational research

LEARN MORE: Descriptive Research vs Correlational Research

Remember, it is only valuable and useful when it is valid, accurate, and reliable. Incorrect results can lead to customer churn and a decrease in sales.

It is essential to ensure that your data is:

• Valid – founded, logical, rigorous, and impartial.
• Accurate – free of errors and including required details.
• Reliable – other people who investigate in the same way can produce similar results.
• Timely – current and collected within an appropriate time frame.
• Complete – includes all the data you need to support your business decisions.

Gather insights

• Identify the main trends and issues, opportunities, and problems you observe. Write a sentence describing each one.
• Keep track of the frequency with which each of the main findings appears.
• Make a list of your findings from the most common to the least common.
• Evaluate a list of the strengths, weaknesses, opportunities, and threats identified in a SWOT analysis .
• Prepare conclusions and recommendations about your study.
• Act on your strategies
• Look for gaps in the information, and consider doing additional inquiry if necessary
• Plan to review the results and consider efficient methods to analyze and interpret results.

Review your goals before making any conclusions about your study. Remember how the process you have completed and the data you have gathered help answer your questions. Ask yourself if what your analysis revealed facilitates the identification of your conclusions and recommendations.

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Research Process: 8 Steps in Research Process

The research process starts with identifying a research problem and conducting a literature review to understand the context. The researcher sets research questions, objectives, and hypotheses based on the research problem.

A research study design is formed to select a sample size and collect data after processing and analyzing the collected data and the research findings presented in a research report.

What is the Research Process?

There are a variety of approaches to research in any field of investigation, irrespective of whether it is applied research or basic research. Each research study will be unique in some ways because of the particular time, setting, environment, and place it is being undertaken.

Nevertheless, all research endeavors share a common goal of furthering our understanding of the problem, and thus, all traverse through certain primary stages, forming a process called the research process.

Understanding the research process is necessary to effectively carry out research and sequence the stages inherent in the process.

How Research Process Work?

Eight steps research process is, in essence, part and parcel of a research proposal. It is an outline of the commitment that you intend to follow in executing a research study.

A close examination of the above stages reveals that each of these stages, by and large, is dependent upon the others.

One cannot analyze data (step 7) unless he has collected data (step 6). One cannot write a report (step 8) unless he has collected and analyzed data (step 7).

Research then is a system of interdependent related stages. Violation of this sequence can cause irreparable harm to the study.

It is also true that several alternatives are available to the researcher during each stage stated above. A research process can be compared with a route map.

The map analogy is useful for the researcher because several alternatives exist at each stage of the research process.

Choosing the best alternative in terms of time constraints, money, and human resources in our research decision is our primary goal.

Before explaining the stages of the research process, we explain the term ‘iterative’ appearing within the oval-shaped diagram at the center of the schematic diagram.

The key to a successful research project ultimately lies in iteration: the process of returning again and again to the identification of the research problems, methodology, data collection, etc., which leads to new ideas, revisions, and improvements.

By discussing the research project with advisers and peers, one will often find that new research questions need to be added, variables to be omitted, added or redefined, and other changes to be made. As a proposed study is examined and reexamined from different perspectives, it may begin to transform and take a different shape.

This is expected and is an essential component of a good research study.

Besides, examining study methods and data collected from different viewpoints is important to ensure a comprehensive approach to the research question.

In conclusion, there is seldom any single strategy or formula for developing a successful research study, but it is essential to realize that the research process is cyclical and iterative.

What is the primary purpose of the research process?

The research process aims to identify a research problem, understand its context through a literature review, set research questions and objectives, design a research study, select a sample, collect data, analyze the data, and present the findings in a research report.

Why is the research design important in the research process?

The research design is the blueprint for fulfilling objectives and answering research questions. It specifies the methods and procedures for collecting, processing, and analyzing data, ensuring the study is structured and systematic.

8 Steps of Research Process

Identifying the research problem.

The first and foremost task in the entire process of scientific research is to identify a research problem .

A well-identified problem will lead the researcher to accomplish all-important phases of the research process, from setting objectives to selecting the research methodology .

But the core question is: whether all problems require research.

We have countless problems around us, but all we encounter do not qualify as research problems; thus, these do not need to be researched.

Keeping this point in mind, we must draw a line between research and non-research problems.

Intuitively, researchable problems are those that have a possibility of thorough verification investigation, which can be effected through the analysis and collection of data. In contrast, the non-research problems do not need to go through these processes.

Researchers need to identify both;

Non-Research Problems

Statement of the problem, justifying the problem, analyzing the problem.

A non-research problem does not require any research to arrive at a solution. Intuitively, a non-researchable problem consists of vague details and cannot be resolved through research.

It is a managerial or built-in problem that may be solved at the administrative or management level. The answer to any question raised in a non-research setting is almost always obvious.

The cholera outbreak, for example, following a severe flood, is a common phenomenon in many communities. The reason for this is known. It is thus not a research problem.

Similarly, the reasons for the sudden rise in prices of many essential commodities following the announcement of the budget by the Finance Minister need no investigation. Hence it is not a problem that needs research.

How is a research problem different from a non-research problem?

A research problem is a perceived difficulty that requires thorough verification and investigation through data analysis and collection. In contrast, a non-research problem does not require research for a solution, as the answer is often obvious or already known.

Non-Research Problems Examples

A recent survey in town- A found that 1000 women were continuous users of contraceptive pills.

But last month’s service statistics indicate that none of these women were using contraceptive pills (Fisher et al. 1991:4).

The discrepancy is that ‘all 1000 women should have been using a pill, but none is doing so. The question is: why the discrepancy exists?

Well, the fact is, a monsoon flood has prevented all new supplies of pills from reaching town- A, and all old supplies have been exhausted. Thus, although the problem situation exists, the reason for the problem is already known.

Therefore, assuming all the facts are correct, there is no reason to research the factors associated with pill discontinuation among women. This is, thus, a non-research problem.

A pilot survey by University students revealed that in Rural Town-A, the goiter prevalence among school children is as high as 80%, while in the neighboring Rural Town-A, it is only 30%. Why is a discrepancy?

Upon inquiry, it was seen that some three years back, UNICEF launched a lipiodol injection program in the neighboring Rural Town-A.

This attempt acted as a preventive measure against the goiter. The reason for the discrepancy is known; hence, we do not consider the problem a research problem.

A hospital treated a large number of cholera cases with penicillin, but the treatment with penicillin was not found to be effective. Do we need research to know the reason?

Here again, there is one single reason that Vibrio cholera is not sensitive to penicillin; therefore, this is not the drug of choice for this disease.

In this case, too, as the reasons are known, it is unwise to undertake any study to find out why penicillin does not improve the condition of cholera patients. This is also a non-research problem.

In the tea marketing system, buying and selling tea starts with bidders. Blenders purchase open tea from the bidders. Over the years, marketing cost has been the highest for bidders and the lowest for blenders. What makes this difference?

The bidders pay exorbitantly higher transport costs, which constitute about 30% of their total cost.

Blenders have significantly fewer marketing functions involving transportation, so their marketing cost remains minimal.

Hence no research is needed to identify the factors that make this difference.

Here are some of the problems we frequently encounter, which may well be considered non-research problems:

• Rises in the price of warm clothes during winter;
• Preferring admission to public universities over private universities;
• Crisis of accommodations in sea resorts during summer
• Traffic jams in the city street after office hours;
• High sales in department stores after an offer of a discount.

Research Problem

In contrast to a non-research problem, a research problem is of primary concern to a researcher.

A research problem is a perceived difficulty, a feeling of discomfort, or a discrepancy between a common belief and reality.

As noted by Fisher et al. (1993), a problem will qualify as a potential research problem when the following three conditions exist:

• There should be a perceived discrepancy between “what it is” and “what it should have been.” This implies that there should be a difference between “what exists” and the “ideal or planned situation”;
• A question about “why” the discrepancy exists. This implies that the reason(s) for this discrepancy is unclear to the researcher (so that it makes sense to develop a research question); and
• There should be at least two possible answers or solutions to the questions or problems.

The third point is important. If there is only one possible and plausible answer to the question about the discrepancy, then a research situation does not exist.

It is a non-research problem that can be tackled at the managerial or administrative level.

Research Problem Examples

Research problem – example #1.

While visiting a rural area, the UNICEF team observed that some villages have female school attendance rates as high as 75%, while some have as low as 10%, although all villages should have a nearly equal attendance rate. What factors are associated with this discrepancy?

We may enumerate several reasons for this:

• Villages differ in their socio-economic background.
• In some villages, the Muslim population constitutes a large proportion of the total population. Religion might play a vital role.
• Schools are far away from some villages. The distance thus may make this difference.

Because there is more than one answer to the problem, it is considered a research problem, and a study can be undertaken to find a solution.

Research Problem – Example #2

The Government has been making all-out efforts to ensure a regular flow of credit in rural areas at a concession rate through liberal lending policy and establishing many bank branches in rural areas.

Knowledgeable sources indicate that expected development in rural areas has not yet been achieved, mainly because of improper credit utilization.

More than one reason is suspected for such misuse or misdirection.

These include, among others:

• Diversion of credit money to some unproductive sectors
• Transfer of credit money to other people like money lenders, who exploit the rural people with this money
• Lack of knowledge of proper utilization of the credit.

Here too, reasons for misuse of loans are more than one. We thus consider this problem as a researchable problem.

Research Problem – Example #3

Let’s look at a new headline: Stock Exchange observes the steepest ever fall in stock prices: several injured as retail investors clash with police, vehicles ransacked .

Investors’ demonstration, protest and clash with police pause a problem. Still, it is certainly not a research problem since there is only one known reason for the problem: Stock Exchange experiences the steepest fall in stock prices. But what causes this unprecedented fall in the share market?

Experts felt that no single reason could be attributed to the problem. It is a mix of several factors and is a research problem. The following were assumed to be some of the possible reasons:

• The merchant banking system;
• Liquidity shortage because of the hike in the rate of cash reserve requirement (CRR);
• IMF’s warnings and prescriptions on the commercial banks’ exposure to the stock market;
• Increase in supply of new shares;
• Manipulation of share prices;
• Lack of knowledge of the investors on the company’s fundamentals.

The choice of a research problem is not as easy as it appears. The researchers generally guide it;

• own intellectual orientation,
• level of training,
• experience,
• knowledge on the subject matter, and
• intellectual curiosity.

Theoretical and practical considerations also play a vital role in choosing a research problem. Societal needs also guide in choosing a research problem.

Once we have chosen a research problem, a few more related steps must be followed before a decision is taken to undertake a research study.

These include, among others, the following:

• Statement of the problem.
• Justifying the problem.
• Analyzing the problem.

A detailed exposition of these issues is undertaken in chapter ten while discussing the proposal development.

A clear and well-defined problem statement is considered the foundation for developing the research proposal.

It enables the researcher to systematically point out why the proposed research on the problem should be undertaken and what he hopes to achieve with the study’s findings.

A well-defined statement of the problem will lead the researcher to formulate the research objectives, understand the background of the study, and choose a proper research methodology.

Once the problem situation has been identified and clearly stated, it is important to justify the importance of the problem.

In justifying the problems, we ask such questions as why the problem of the study is important, how large and widespread the problem is, and whether others can be convinced about the importance of the problem and the like.

Answers to the above questions should be reviewed and presented in one or two paragraphs that justify the importance of the problem.

As a first step in analyzing the problem, critical attention should be given to accommodate the viewpoints of the managers, users, and researchers to the problem through threadbare discussions.

The next step is identifying the factors that may have contributed to the perceived problems.

Issues of Research Problem Identification

There are several ways to identify, define, and analyze a problem, obtain insights, and get a clearer idea about these issues. Exploratory research is one of the ways of accomplishing this.

The purpose of the exploratory research process is to progressively narrow the scope of the topic and transform the undefined problems into defined ones, incorporating specific research objectives.

The exploratory study entails a few basic strategies for gaining insights into the problem. It is accomplished through such efforts as:

Pilot Survey

A pilot survey collects proxy data from the ultimate subjects of the study to serve as a guide for the large study. A pilot study generates primary data, usually for qualitative analysis.

This characteristic distinguishes a pilot survey from secondary data analysis, which gathers background information.

Case Studies

Case studies are quite helpful in diagnosing a problem and paving the way to defining the problem. It investigates one or a few situations identical to the researcher’s problem.

Focus Group Interviews

Focus group interviews, an unstructured free-flowing interview with a small group of people, may also be conducted to understand and define a research problem .

Experience Survey

Experience survey is another strategy to deal with the problem of identifying and defining the research problem.

It is an exploratory research endeavor in which individuals knowledgeable and experienced in a particular research problem are intimately consulted to understand the problem.

These persons are sometimes known as key informants, and an interview with them is popularly known as the Key Informant Interview (KII).

Reviewing of Literature

A review of relevant literature is an integral part of the research process. It enables the researcher to formulate his problem in terms of the specific aspects of the general area of his interest that has not been researched so far.

Such a review provides exposure to a larger body of knowledge and equips him with enhanced knowledge to efficiently follow the research process.

Through a proper review of the literature, the researcher may develop the coherence between the results of his study and those of the others.

A review of previous documents on similar or related phenomena is essential even for beginning researchers.

Ignoring the existing literature may lead to wasted effort on the part of the researchers.

Why spend time merely repeating what other investigators have already done?

Suppose the researcher is aware of earlier studies of his topic or related topics . In that case, he will be in a much better position to assess his work’s significance and convince others that it is important.

A confident and expert researcher is more crucial in questioning the others’ methodology, the choice of the data, and the quality of the inferences drawn from the study results.

In sum, we enumerate the following arguments in favor of reviewing the literature:

• It avoids duplication of the work that has been done in the recent past.
• It helps the researcher discover what others have learned and reported on the problem.
• It enables the researcher to become familiar with the methodology followed by others.
• It allows the researcher to understand what concepts and theories are relevant to his area of investigation.
• It helps the researcher to understand if there are any significant controversies, contradictions, and inconsistencies in the findings.
• It allows the researcher to understand if there are any unanswered research questions.
• It might help the researcher to develop an analytical framework.
• It will help the researcher consider including variables in his research that he might not have thought about.

Why is reviewing literature crucial in the research process?

Reviewing literature helps avoid duplicating previous work, discovers what others have learned about the problem, familiarizes the researcher with relevant concepts and theories, and ensures a comprehensive approach to the research question.

What is the significance of reviewing literature in the research process?

Reviewing relevant literature helps formulate the problem, understand the background of the study, choose a proper research methodology, and develop coherence between the study’s results and previous findings.

Setting Research Questions, Objectives, and Hypotheses

After discovering and defining the research problem, researchers should make a formal statement of the problem leading to research objectives .

An objective will precisely say what should be researched, delineate the type of information that should be collected, and provide a framework for the scope of the study. A well-formulated, testable research hypothesis is the best expression of a research objective.

A hypothesis is an unproven statement or proposition that can be refuted or supported by empirical data. Hypothetical statements assert a possible answer to a research question.

Step #4: Choosing the Study Design

The research design is the blueprint or framework for fulfilling objectives and answering research questions .

It is a master plan specifying the methods and procedures for collecting, processing, and analyzing the collected data. There are four basic research designs that a researcher can use to conduct their study;

• experiment,
• secondary data study, and
• observational study.

The type of research design to be chosen from among the above four methods depends primarily on four factors:

• The type of problem
• The objectives of the study,
• The existing state of knowledge about the problem that is being studied, and
• The resources are available for the study.

Deciding on the Sample Design

Sampling is an important and separate step in the research process. The basic idea of sampling is that it involves any procedure that uses a relatively small number of items or portions (called a sample) of a universe (called population) to conclude the whole population.

It contrasts with the process of complete enumeration, in which every member of the population is included.

Such a complete enumeration is referred to as a census.

A population is the total collection of elements we wish to make some inference or generalization.

A sample is a part of the population, carefully selected to represent that population. If certain statistical procedures are followed in selecting the sample, it should have the same characteristics as the population. These procedures are embedded in the sample design.

Sample design refers to the methods followed in selecting a sample from the population and the estimating technique vis-a-vis the formula for computing the sample statistics.

The fundamental question is, then, how to select a sample.

To answer this question, we must have acquaintance with the sampling methods.

These methods are basically of two types;

• probability sampling , and
• non-probability sampling .

Probability sampling ensures every unit has a known nonzero probability of selection within the target population.

If there is no feasible alternative, a non-probability sampling method may be employed.

The basis of such selection is entirely dependent on the researcher’s discretion. This approach is called judgment sampling, convenience sampling, accidental sampling, and purposive sampling.

The most widely used probability sampling methods are simple random sampling , stratified random sampling , cluster sampling , and systematic sampling . They have been classified by their representation basis and unit selection techniques.

Two other variations of the sampling methods that are in great use are multistage sampling and probability proportional to size (PPS) sampling .

Multistage sampling is most commonly used in drawing samples from very large and diverse populations.

The PPS sampling is a variation of multistage sampling in which the probability of selecting a cluster is proportional to its size, and an equal number of elements are sampled within each cluster.

Collecting Data From The Research Sample

Data gathering may range from simple observation to a large-scale survey in any defined population. There are many ways to collect data. The approach selected depends on the objectives of the study, the research design, and the availability of time, money, and personnel.

With the variation in the type of data (qualitative or quantitative) to be collected, the method of data collection also varies .

The most common means for collecting quantitative data is the structured interview .

Studies that obtain data by interviewing respondents are called surveys. Data can also be collected by using self-administered questionnaires . Telephone interviewing is another way in which data may be collected .

Other means of data collection include secondary sources, such as the census, vital registration records, official documents, previous surveys, etc.

Qualitative data are collected mainly through in-depth interviews, focus group discussions , Key Informant Interview ( KII), and observational studies.

Process and Analyze the Collected Research Data

Data processing generally begins with the editing and coding of data . Data are edited to ensure consistency across respondents and to locate omissions if any.

In survey data, editing reduces errors in the recording, improves legibility, and clarifies unclear and inappropriate responses. In addition to editing, the data also need coding.

Because it is impractical to place raw data into a report, alphanumeric codes are used to reduce the responses to a more manageable form for storage and future processing.

This coding process facilitates the processing of the data. The personal computer offers an excellent opportunity for data editing and coding processes.

Data analysis usually involves reducing accumulated data to a manageable size, developing summaries, searching for patterns, and applying statistical techniques for understanding and interpreting the findings in light of the research questions.

Further, based on his analysis, the researcher determines if his findings are consistent with the formulated hypotheses and theories.

The techniques used in analyzing data may range from simple graphical techniques to very complex multivariate analyses depending on the study’s objectives, the research design employed, and the nature of the data collected.

As in the case of data collection methods, an analytical technique appropriate in one situation may not be suitable for another.

Writing Research Report – Developing Research Proposal, Writing Report, Disseminating and Utilizing Results

The entire task of a research study is accumulated in a document called a proposal or research proposal.

A research proposal is a work plan, prospectus, outline, offer, and a statement of intent or commitment from an individual researcher or an organization to produce a product or render a service to a potential client or sponsor .

The proposal will be prepared to keep the sequence presented in the research process. The proposal tells us what, how, where, and to whom it will be done.

It must also show the benefit of doing it. It always includes an explanation of the purpose of the study (the research objectives) or a definition of the problem.

It systematically outlines the particular research methodology and details the procedures utilized at each stage of the research process.

The end goal of a scientific study is to interpret the results and draw conclusions.

To this end, it is necessary to prepare a report and transmit the findings and recommendations to administrators, policymakers, and program managers to make a decision.

There are various research reports: term papers, dissertations, journal articles , papers for presentation at professional conferences and seminars, books, thesis, and so on. The results of a research investigation prepared in any form are of little utility if they are not communicated to others.

The primary purpose of a dissemination strategy is to identify the most effective media channels to reach different audience groups with study findings most relevant to their needs.

The dissemination may be made through a conference, a seminar, a report, or an oral or poster presentation.

The style and organization of the report will differ according to the target audience, the occasion, and the purpose of the research. Reports should be developed from the client’s perspective.

A report is an excellent means that helps to establish the researcher’s credibility. At a bare minimum, a research report should contain sections on:

• An executive summary;
• Background of the problem;
• Literature review;
• Methodology;
• Discussion;
• Conclusions and
• Recommendations.

The study results can also be disseminated through peer-reviewed journals published by academic institutions and reputed publishers both at home and abroad. The report should be properly evaluated .

These journals have their format and editorial policies. The contributors can submit their manuscripts adhering to the policies and format for possible publication of their papers.

There are now ample opportunities for researchers to publish their work online.

The researchers have conducted many interesting studies without affecting actual settings. Ideally, the concluding step of a scientific study is to plan for its utilization in the real world.

Although researchers are often not in a position to implement a plan for utilizing research findings, they can contribute by including in their research reports a few recommendations regarding how the study results could be utilized for policy formulation and program intervention.

Why is the dissemination of research findings important?

Dissemination of research findings is crucial because the results of a research investigation have little utility if not communicated to others. Dissemination ensures that the findings reach relevant stakeholders, policymakers, and program managers to inform decisions.

How should a research report be structured?

A research report should contain sections on an executive summary, background of the problem, literature review, methodology, findings, discussion, conclusions, and recommendations.

Why is it essential to consider the target audience when preparing a research report?

The style and organization of a research report should differ based on the target audience, occasion, and research purpose. Tailoring the report to the audience ensures that the findings are communicated effectively and are relevant to their needs.

Research Methods In Psychology

Saul Mcleod, PhD

Editor-in-Chief for Simply Psychology

BSc (Hons) Psychology, MRes, PhD, University of Manchester

Saul Mcleod, PhD., is a qualified psychology teacher with over 18 years of experience in further and higher education. He has been published in peer-reviewed journals, including the Journal of Clinical Psychology.

Learn about our Editorial Process

Olivia Guy-Evans, MSc

Associate Editor for Simply Psychology

BSc (Hons) Psychology, MSc Psychology of Education

Olivia Guy-Evans is a writer and associate editor for Simply Psychology. She has previously worked in healthcare and educational sectors.

Research methods in psychology are systematic procedures used to observe, describe, predict, and explain behavior and mental processes. They include experiments, surveys, case studies, and naturalistic observations, ensuring data collection is objective and reliable to understand and explain psychological phenomena.

Hypotheses are statements about the prediction of the results, that can be verified or disproved by some investigation.

There are four types of hypotheses :

• Null Hypotheses (H0 ) – these predict that no difference will be found in the results between the conditions. Typically these are written ‘There will be no difference…’
• Alternative Hypotheses (Ha or H1) – these predict that there will be a significant difference in the results between the two conditions. This is also known as the experimental hypothesis.
• One-tailed (directional) hypotheses – these state the specific direction the researcher expects the results to move in, e.g. higher, lower, more, less. In a correlation study, the predicted direction of the correlation can be either positive or negative.
• Two-tailed (non-directional) hypotheses – these state that a difference will be found between the conditions of the independent variable but does not state the direction of a difference or relationship. Typically these are always written ‘There will be a difference ….’

All research has an alternative hypothesis (either a one-tailed or two-tailed) and a corresponding null hypothesis.

Once the research is conducted and results are found, psychologists must accept one hypothesis and reject the other. 

So, if a difference is found, the Psychologist would accept the alternative hypothesis and reject the null.  The opposite applies if no difference is found.

Sampling techniques

Sampling is the process of selecting a representative group from the population under study.

A sample is the participants you select from a target population (the group you are interested in) to make generalizations about.

Representative means the extent to which a sample mirrors a researcher’s target population and reflects its characteristics.

Generalisability means the extent to which their findings can be applied to the larger population of which their sample was a part.

• Volunteer sample : where participants pick themselves through newspaper adverts, noticeboards or online.
• Opportunity sampling : also known as convenience sampling , uses people who are available at the time the study is carried out and willing to take part. It is based on convenience.
• Random sampling : when every person in the target population has an equal chance of being selected. An example of random sampling would be picking names out of a hat.
• Systematic sampling : when a system is used to select participants. Picking every Nth person from all possible participants. N = the number of people in the research population / the number of people needed for the sample.
• Stratified sampling : when you identify the subgroups and select participants in proportion to their occurrences.
• Snowball sampling : when researchers find a few participants, and then ask them to find participants themselves and so on.
• Quota sampling : when researchers will be told to ensure the sample fits certain quotas, for example they might be told to find 90 participants, with 30 of them being unemployed.

Experiments always have an independent and dependent variable .

• The independent variable is the one the experimenter manipulates (the thing that changes between the conditions the participants are placed into). It is assumed to have a direct effect on the dependent variable.
• The dependent variable is the thing being measured, or the results of the experiment.

Operationalization of variables means making them measurable/quantifiable. We must use operationalization to ensure that variables are in a form that can be easily tested.

For instance, we can’t really measure ‘happiness’, but we can measure how many times a person smiles within a two-hour period. 

By operationalizing variables, we make it easy for someone else to replicate our research. Remember, this is important because we can check if our findings are reliable.

Extraneous variables are all variables which are not independent variable but could affect the results of the experiment.

It can be a natural characteristic of the participant, such as intelligence levels, gender, or age for example, or it could be a situational feature of the environment such as lighting or noise.

Demand characteristics are a type of extraneous variable that occurs if the participants work out the aims of the research study, they may begin to behave in a certain way.

For example, in Milgram’s research , critics argued that participants worked out that the shocks were not real and they administered them as they thought this was what was required of them. 

Extraneous variables must be controlled so that they do not affect (confound) the results.

Randomly allocating participants to their conditions or using a matched pairs experimental design can help to reduce participant variables. 

Situational variables are controlled by using standardized procedures, ensuring every participant in a given condition is treated in the same way

Experimental Design

Experimental design refers to how participants are allocated to each condition of the independent variable, such as a control or experimental group.

• Independent design ( between-groups design ): each participant is selected for only one group. With the independent design, the most common way of deciding which participants go into which group is by means of randomization. 
• Matched participants design : each participant is selected for only one group, but the participants in the two groups are matched for some relevant factor or factors (e.g. ability; sex; age).
• Repeated measures design ( within groups) : each participant appears in both groups, so that there are exactly the same participants in each group.
• The main problem with the repeated measures design is that there may well be order effects. Their experiences during the experiment may change the participants in various ways.
• They may perform better when they appear in the second group because they have gained useful information about the experiment or about the task. On the other hand, they may perform less well on the second occasion because of tiredness or boredom.
• Counterbalancing is the best way of preventing order effects from disrupting the findings of an experiment, and involves ensuring that each condition is equally likely to be used first and second by the participants.

If we wish to compare two groups with respect to a given independent variable, it is essential to make sure that the two groups do not differ in any other important way. 

Experimental Methods

All experimental methods involve an iv (independent variable) and dv (dependent variable)..

• Field experiments are conducted in the everyday (natural) environment of the participants. The experimenter still manipulates the IV, but in a real-life setting. It may be possible to control extraneous variables, though such control is more difficult than in a lab experiment.
• Natural experiments are when a naturally occurring IV is investigated that isn’t deliberately manipulated, it exists anyway. Participants are not randomly allocated, and the natural event may only occur rarely.

Case studies are in-depth investigations of a person, group, event, or community. It uses information from a range of sources, such as from the person concerned and also from their family and friends.

Many techniques may be used such as interviews, psychological tests, observations and experiments. Case studies are generally longitudinal: in other words, they follow the individual or group over an extended period of time. 

Case studies are widely used in psychology and among the best-known ones carried out were by Sigmund Freud . He conducted very detailed investigations into the private lives of his patients in an attempt to both understand and help them overcome their illnesses.

Case studies provide rich qualitative data and have high levels of ecological validity. However, it is difficult to generalize from individual cases as each one has unique characteristics.

Correlational Studies

Correlation means association; it is a measure of the extent to which two variables are related. One of the variables can be regarded as the predictor variable with the other one as the outcome variable.

Correlational studies typically involve obtaining two different measures from a group of participants, and then assessing the degree of association between the measures. 

The predictor variable can be seen as occurring before the outcome variable in some sense. It is called the predictor variable, because it forms the basis for predicting the value of the outcome variable.

Relationships between variables can be displayed on a graph or as a numerical score called a correlation coefficient.

• If an increase in one variable tends to be associated with an increase in the other, then this is known as a positive correlation .
• If an increase in one variable tends to be associated with a decrease in the other, then this is known as a negative correlation .
• A zero correlation occurs when there is no relationship between variables.

After looking at the scattergraph, if we want to be sure that a significant relationship does exist between the two variables, a statistical test of correlation can be conducted, such as Spearman’s rho.

The test will give us a score, called a correlation coefficient . This is a value between 0 and 1, and the closer to 1 the score is, the stronger the relationship between the variables. This value can be both positive e.g. 0.63, or negative -0.63.

A correlation between variables, however, does not automatically mean that the change in one variable is the cause of the change in the values of the other variable. A correlation only shows if there is a relationship between variables.

Correlation does not always prove causation, as a third variable may be involved. 

Interview Methods

Interviews are commonly divided into two types: structured and unstructured.

A fixed, predetermined set of questions is put to every participant in the same order and in the same way. 

Responses are recorded on a questionnaire, and the researcher presets the order and wording of questions, and sometimes the range of alternative answers.

The interviewer stays within their role and maintains social distance from the interviewee.

There are no set questions, and the participant can raise whatever topics he/she feels are relevant and ask them in their own way. Questions are posed about participants’ answers to the subject

Unstructured interviews are most useful in qualitative research to analyze attitudes and values.

Though they rarely provide a valid basis for generalization, their main advantage is that they enable the researcher to probe social actors’ subjective point of view. 

Questionnaire Method

Questionnaires can be thought of as a kind of written interview. They can be carried out face to face, by telephone, or post.

The choice of questions is important because of the need to avoid bias or ambiguity in the questions, ‘leading’ the respondent or causing offense.

• Open questions are designed to encourage a full, meaningful answer using the subject’s own knowledge and feelings. They provide insights into feelings, opinions, and understanding. Example: “How do you feel about that situation?”
• Closed questions can be answered with a simple “yes” or “no” or specific information, limiting the depth of response. They are useful for gathering specific facts or confirming details. Example: “Do you feel anxious in crowds?”

Its other practical advantages are that it is cheaper than face-to-face interviews and can be used to contact many respondents scattered over a wide area relatively quickly.

Observations

There are different types of observation methods :

• Covert observation is where the researcher doesn’t tell the participants they are being observed until after the study is complete. There could be ethical problems or deception and consent with this particular observation method.
• Overt observation is where a researcher tells the participants they are being observed and what they are being observed for.
• Controlled : behavior is observed under controlled laboratory conditions (e.g., Bandura’s Bobo doll study).
• Natural : Here, spontaneous behavior is recorded in a natural setting.
• Participant : Here, the observer has direct contact with the group of people they are observing. The researcher becomes a member of the group they are researching.  
• Non-participant (aka “fly on the wall): The researcher does not have direct contact with the people being observed. The observation of participants’ behavior is from a distance

Pilot Study

A pilot  study is a small scale preliminary study conducted in order to evaluate the feasibility of the key s teps in a future, full-scale project.

A pilot study is an initial run-through of the procedures to be used in an investigation; it involves selecting a few people and trying out the study on them. It is possible to save time, and in some cases, money, by identifying any flaws in the procedures designed by the researcher.

A pilot study can help the researcher spot any ambiguities (i.e. unusual things) or confusion in the information given to participants or problems with the task devised.

Sometimes the task is too hard, and the researcher may get a floor effect, because none of the participants can score at all or can complete the task – all performances are low.

The opposite effect is a ceiling effect, when the task is so easy that all achieve virtually full marks or top performances and are “hitting the ceiling”.

Research Design

In cross-sectional research , a researcher compares multiple segments of the population at the same time

Sometimes, we want to see how people change over time, as in studies of human development and lifespan. Longitudinal research is a research design in which data-gathering is administered repeatedly over an extended period of time.

In cohort studies , the participants must share a common factor or characteristic such as age, demographic, or occupation. A cohort study is a type of longitudinal study in which researchers monitor and observe a chosen population over an extended period.

Triangulation means using more than one research method to improve the study’s validity.

Reliability

Reliability is a measure of consistency, if a particular measurement is repeated and the same result is obtained then it is described as being reliable.

• Test-retest reliability :  assessing the same person on two different occasions which shows the extent to which the test produces the same answers.
• Inter-observer reliability : the extent to which there is an agreement between two or more observers.

Meta-Analysis

A meta-analysis is a systematic review that involves identifying an aim and then searching for research studies that have addressed similar aims/hypotheses.

This is done by looking through various databases, and then decisions are made about what studies are to be included/excluded.

Strengths: Increases the conclusions’ validity as they’re based on a wider range.

Weaknesses: Research designs in studies can vary, so they are not truly comparable.

Peer Review

A researcher submits an article to a journal. The choice of the journal may be determined by the journal’s audience or prestige.

The journal selects two or more appropriate experts (psychologists working in a similar field) to peer review the article without payment. The peer reviewers assess: the methods and designs used, originality of the findings, the validity of the original research findings and its content, structure and language.

Feedback from the reviewer determines whether the article is accepted. The article may be: Accepted as it is, accepted with revisions, sent back to the author to revise and re-submit or rejected without the possibility of submission.

The editor makes the final decision whether to accept or reject the research report based on the reviewers comments/ recommendations.

Peer review is important because it prevent faulty data from entering the public domain, it provides a way of checking the validity of findings and the quality of the methodology and is used to assess the research rating of university departments.

Peer reviews may be an ideal, whereas in practice there are lots of problems. For example, it slows publication down and may prevent unusual, new work being published. Some reviewers might use it as an opportunity to prevent competing researchers from publishing work.

Some people doubt whether peer review can really prevent the publication of fraudulent research.

The advent of the internet means that a lot of research and academic comment is being published without official peer reviews than before, though systems are evolving on the internet where everyone really has a chance to offer their opinions and police the quality of research.

Types of Data

• Quantitative data is numerical data e.g. reaction time or number of mistakes. It represents how much or how long, how many there are of something. A tally of behavioral categories and closed questions in a questionnaire collect quantitative data.
• Qualitative data is virtually any type of information that can be observed and recorded that is not numerical in nature and can be in the form of written or verbal communication. Open questions in questionnaires and accounts from observational studies collect qualitative data.
• Primary data is first-hand data collected for the purpose of the investigation.
• Secondary data is information that has been collected by someone other than the person who is conducting the research e.g. taken from journals, books or articles.

Validity means how well a piece of research actually measures what it sets out to, or how well it reflects the reality it claims to represent.

Validity is whether the observed effect is genuine and represents what is actually out there in the world.

• Concurrent validity is the extent to which a psychological measure relates to an existing similar measure and obtains close results. For example, a new intelligence test compared to an established test.
• Face validity : does the test measure what it’s supposed to measure ‘on the face of it’. This is done by ‘eyeballing’ the measuring or by passing it to an expert to check.
• Ecological validit y is the extent to which findings from a research study can be generalized to other settings / real life.
• Temporal validity is the extent to which findings from a research study can be generalized to other historical times.

Features of Science

• Paradigm – A set of shared assumptions and agreed methods within a scientific discipline.
• Paradigm shift – The result of the scientific revolution: a significant change in the dominant unifying theory within a scientific discipline.
• Objectivity – When all sources of personal bias are minimised so not to distort or influence the research process.
• Empirical method – Scientific approaches that are based on the gathering of evidence through direct observation and experience.
• Replicability – The extent to which scientific procedures and findings can be repeated by other researchers.
• Falsifiability – The principle that a theory cannot be considered scientific unless it admits the possibility of being proved untrue.

Statistical Testing

A significant result is one where there is a low probability that chance factors were responsible for any observed difference, correlation, or association in the variables tested.

If our test is significant, we can reject our null hypothesis and accept our alternative hypothesis.

If our test is not significant, we can accept our null hypothesis and reject our alternative hypothesis. A null hypothesis is a statement of no effect.

In Psychology, we use p < 0.05 (as it strikes a balance between making a type I and II error) but p < 0.01 is used in tests that could cause harm like introducing a new drug.

A type I error is when the null hypothesis is rejected when it should have been accepted (happens when a lenient significance level is used, an error of optimism).

A type II error is when the null hypothesis is accepted when it should have been rejected (happens when a stringent significance level is used, an error of pessimism).

Ethical Issues

• Informed consent is when participants are able to make an informed judgment about whether to take part. It causes them to guess the aims of the study and change their behavior.
• To deal with it, we can gain presumptive consent or ask them to formally indicate their agreement to participate but it may invalidate the purpose of the study and it is not guaranteed that the participants would understand.
• Deception should only be used when it is approved by an ethics committee, as it involves deliberately misleading or withholding information. Participants should be fully debriefed after the study but debriefing can’t turn the clock back.
• All participants should be informed at the beginning that they have the right to withdraw if they ever feel distressed or uncomfortable.
• It causes bias as the ones that stayed are obedient and some may not withdraw as they may have been given incentives or feel like they’re spoiling the study. Researchers can offer the right to withdraw data after participation.
• Participants should all have protection from harm . The researcher should avoid risks greater than those experienced in everyday life and they should stop the study if any harm is suspected. However, the harm may not be apparent at the time of the study.
• Confidentiality concerns the communication of personal information. The researchers should not record any names but use numbers or false names though it may not be possible as it is sometimes possible to work out who the researchers were.

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Types of Fat

Unsaturated fats

Unsaturated fats, which are liquid at room temperature, are considered beneficial fats because they can improve blood cholesterol levels, ease inflammation, stabilize heart rhythms, and play a number of other beneficial roles. Unsaturated fats are predominantly found in foods from plants, such as vegetable oils, nuts, and seeds.

There are two types of “good” unsaturated fats:

1. Monounsaturated fats are found in high concentrations in:

• Olive, peanut, and canola oils
• Nuts such as almonds, hazelnuts, and pecans
• Seeds such as pumpkin and sesame seeds

2. Polyunsaturated fats are found in high concentrations in

• Sunflower, corn, soybean, and flaxseed oils
• Canola oil – though higher in monounsaturated fat, it’s also a good source of polyunsaturated fat.

Omega-3 fats are an important  type of polyunsaturated fat. The body can’t make these, so they must come from food.

• An excellent way to get omega-3 fats is by eating fish 2-3 times a week.
• Good plant sources of omega-3 fats include flax seeds, walnuts, and canola or soybean oil.
• Higher blood omega-3 fats are associated with lower risk of premature death among older adults, according to a study by HSPH faculty.
• Read more about omega-3 fats in our Ask the Expert with Dr. Frank Sacks.

Most people don’t eat enough healthful unsaturated fats. The American Heart Association suggests that 8-10 percent of daily calories should come from polyunsaturated fats, and there is evidence that eating more polyunsaturated fat—up to 15 percent of daily calories—in place of saturated fat can lower heart disease risk. ( 7 )

• Dutch researchers conducted an analysis of 60 trials that examined the effects of carbohydrates and various fats on blood lipid levels. In trials in which polyunsaturated and monounsaturated fats were eaten in place of carbohydrates, these good fats decreased levels of harmful LDL and increased protective HDL. ( 8 )
• More recently, a randomized trial known as the Optimal Macronutrient Intake Trial for Heart Health (OmniHeart) showed that replacing a carbohydrate-rich diet with one rich in unsaturated fat, predominantly monounsaturated fats, lowers blood pressure, improves lipid levels, and reduces the estimated cardiovascular risk. ( 9 )

Finding Foods with Healthy Fats   is a handy visual guide to help you determine which fats are beneficial, and which are harmful.

Saturated Fats

All foods containing fat have a mix of specific types of fats. Even healthy foods like chicken and nuts have small amounts of saturated fat, though much less than the amounts found in beef, cheese, and ice cream. Saturated fat is mainly found in animal foods, but a few plant foods are also high in saturated fats, such as coconut, coconut oil , palm oil, and palm kernel oil.

• The Dietary Guidelines for Americans recommends getting less than 10 percent of calories each day from saturated fat. ( 10 )
• The American Heart Association goes even further, recommending limiting saturated fat to no more than 7 percent of calories. ( 11 )
• Cutting back on saturated fat will likely have no benefit, however, if people replace saturated fat with refined carbohydrates. Eating refined carbohydrates in place of saturated fat does lower “bad” LDL cholesterol, but it also lowers the “good” HDL cholesterol and increases triglycerides. The net effect is as bad for the heart as eating too much saturated fat.

In the United States, the biggest sources of saturated fat ( 12 ) in the diet are

• Pizza and cheese
• Whole and reduced fat milk, butter and dairy desserts
• Meat products (sausage, bacon, beef, hamburgers)
• Cookies and other grain-based desserts
• A variety of mixed fast food dishes

Though decades of dietary advice ( 13 , 14 ) suggested saturated fat was harmful, in recent years that idea has begun to evolve. Several studies suggest that eating diets high in saturated fat do not raise the risk of heart disease, with one report analyzing the findings of 21 studies that followed 350,000 people for up to 23 years.

• Investigators looked at the relationship between saturated fat intake and coronary heart disease (CHD), stroke, and cardiovascular disease (CVD). Their controversial conclusion: “There is insufficient evidence from prospective epidemiologic studies to conclude that dietary saturated fat is associated with an increased risk of CHD, stroke, or CVD.”( 13 )
• A well-publicized 2014 study questioned the link between saturated fat and heart disease, but HSPH nutrition experts determined the paper to be seriously misleading . In order to set the record straight, Harvard School of Public Health convened a panel of nutrition experts and held a teach-in, “ Saturated or not: Does type of fat matter? “

The overarching message is that cutting back on saturated fat can be good for health if people replace saturated fat with good fats , especially, polyunsaturated fats. ( 1 , 15 , 22 ) Eating good fats in place of saturated fat lowers the “bad” LDL cholesterol, and it improves the ratio of total cholesterol to “good” HDL cholesterol, lowering the risk of heart disease.

Eating good fats in place of saturated fat can also help prevent insulin resistance, a precursor to diabetes. ( 16 ) So while saturated fat may not be as harmful as once thought, evidence clearly shows that unsaturated fat remains the healthiest type of fat.

*Values expressed as percent of total fat; data are from analyses at Harvard School of Public Health Lipid Laboratory and U.S.D.A. publications.

Trans fatty acids, more commonly called trans fats, are made by heating liquid vegetable oils in the presence of hydrogen gas and a catalyst, a process called hydrogenation.

• Partially hydrogenating vegetable oils makes them more stable and less likely to become rancid. This process also converts the oil into a solid, which makes them function as margarine or shortening.
• Partially hydrogenated oils can withstand repeated heating without breaking down, making them ideal for frying fast foods.
• For these reasons, partially hydrogenated oils became a mainstay in restaurants and the food industry – for frying, baked goods, and processed snack foods and margarine.

Partially hydrogenated oil is not the only source of trans fats in our diets. Trans fats are also naturally found in beef fat and dairy fat in small amounts.

Trans fats are the worst type of fat for the heart, blood vessels, and rest of the body because they:

• Raise bad LDL and lower good HDL
• Create inflammation, ( 18 ) – a reaction related to immunity – which has been implicated in heart disease, stroke, diabetes, and other chronic conditions
• Contribute to insulin resistance ( 16 )
• Can have harmful health effects even in small amounts – for each additional 2 percent of calories from trans fat consumed daily, the risk of coronary heart disease increases by 23 percent.

The long road to phasing-out artificial trans fats

7. Mozaffarian, D., R. Micha, and S. Wallace, Effects on coronary heart disease of increasing polyunsaturated fat in place of saturated fat: a systematic review and meta-analysis of randomized controlled trials. PLoS Med , 2010. 7(3): p. e1000252.

8. Mensink, R.P., et al., Effects of dietary fatty acids and carbohydrates on the ratio of serum total to HDL cholesterol and on serum lipids and apolipoproteins: a meta-analysis of 60 controlled trials. Am J Clin Nutr , 2003. 77(5): p. 1146-55.

9. Appel, L.J., et al., Effects of protein, monounsaturated fat, and carbohydrate intake on blood pressure and serum lipids: results of the OmniHeart randomized trial. JAMA , 2005. 294(19): p. 2455-64.

10. U.S. Department of Agriculture, U.S.D.o.H.a.H.S., Washington, D.C.: U.S. Government Printing Office. Dietary Guidelines for Americans, 2010, 2010.

11. Lichtenstein, A.H., et al., Diet and lifestyle recommendations revision 2006: a scientific statement from the American Heart Association Nutrition Committee. Circulation , 2006. 114(1): p. 82-96.

12. Institute, N.C., Risk Factor Monitoring and Methods: Table 1. Top Food Sources of Saturated Fat among U.S. Population, 2005–2006. NHANES.

13. Siri-Tarino, P.W., et al., Meta-analysis of prospective cohort studies evaluating the association of saturated fat with cardiovascular disease. Am J Clin Nutr , 2010. 91(3): p. 535-46.

14. Micha, R. and D. Mozaffarian, Saturated fat and cardiometabolic risk factors, coronary heart disease, stroke, and diabetes: a fresh look at the evidence. Lipids , 2010. 45(10): p. 893-905.

15. Astrup, A., et al., The role of reducing intakes of saturated fat in the prevention of cardiovascular disease: where does the evidence stand in 2010? Am J Clin Nutr , 2011. 93(4): p. 684-8.

16. Riserus, U., W.C. Willett, and F.B. Hu, Dietary fats and prevention of type 2 diabetes. Prog Lipid Res , 2009. 48(1): p. 44-51.

18. Mozaffarian, D., et al., Dietary intake of trans fatty acids and systemic inflammation in women. Am J Clin Nutr, 2004. 79(4): p. 606-12.

22. Farvid MS, Ding M, Pan A, Sun Q, Chiuve SE, Steffen LM, Willett WC, Hu FB. Dietary Linoleic Acid and Risk of Coronary Heart Disease: A Systematic Review and Meta-Analysis of Prospective Cohort Studies. Circulation, 2014.

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• Open access
• Published: 29 May 2024

The implementation of person-centred plans in the community-care sector: a qualitative study of organizations in Ontario, Canada

• Samina Idrees 1 ,
• Gillian Young 1 ,
• Brian Dunne 2 ,
• Donnie Antony 2 ,
• Leslie Meredith 1 &
• Maria Mathews 1  

BMC Health Services Research volume  24 , Article number:  680 ( 2024 ) Cite this article

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Metrics details

Person-centred planning refers to a model of care in which programs and services are developed in collaboration with persons receiving care (i.e., persons-supported) and tailored to their unique needs and goals. In recent decades, governments around the world have enacted policies requiring community-care agencies to adopt an individualized or person-centred approach to service delivery. Although regional mandates provide a framework for directing care, it is unclear how this guidance is implemented in practice given the diversity and range of organizations within the sector. This study aims to address a gap in the literature by describing how person-centred care plans are implemented in community-care organizations.

We conducted semi-structured interviews with administrators from community-care organizations in Ontario, Canada. We asked participants about their organization’s approach to developing and updating person-centred care plans, including relevant supports and barriers. We analyzed the data thematically using a pragmatic, qualitative, descriptive approach.

We interviewed administrators from 12 community-care organizations. We identified three overarching categories or processes related to organizational characteristics and person-centred planning: (1) organizational context, (2) organizational culture, and (3) the design and delivery of person-centred care plans. The context of care and the types of services offered by the organization were directly informed by the needs and characteristics of the population served. The culture of the organization (e.g., their values, attitudes and beliefs surrounding persons-supported) was a key influence in the development and implementation of person-centred care plans. Participants described the person-centred planning process as being iterative and collaborative, involving initial and continued consultations with persons-supported and their close family and friends, while also citing implementation challenges in cases where persons had difficulty communicating, and in cases where they preferred not to have a formal plan in place.

Conclusions

The person-centred planning process is largely informed by organizational context and culture. There are ongoing challenges in the implementation of person-centred care plans, highlighting a gap between policy and practice and suggesting a need for comprehensive guidance and enhanced adaptability in current regulations. Policymakers, administrators, and service providers can leverage these insights to refine policies, advocating for inclusive, flexible approaches that better align with diverse community needs.

Peer Review reports

The community-care sector facilitates the coordination and administration of in-home and community-based health and social services. Community-care services include supports for independent living, residential services, complex medical care, and community-participation services to support personal and professional goals (e.g., education, employment, and recreation-based supports) [ 1 ]. There is substantial heterogeneity in the clinical and demographic characteristics of the community-care population, including individuals with physical and developmental disabilities, and complex medical needs [ 2 ]. We refer to the individuals served by these organizations as ‘persons-supported’ in line with person-first language conventions [ 3 , 4 ].

In recent decades, governments across the world have enacted policies requiring community-care agencies to adopt an individualized or person-centred approach to service delivery [ 5 , 6 , 7 , 8 ]. Person-centred care encompasses a broad framework designed to direct care delivery, as opposed to a singular standardized process. In the context of community-care, person-centred planning refers to a model of care provision in which programs and services are developed in collaboration with persons-supported and tailored to their unique needs and desired outcomes [ 9 , 10 ].

In Ontario, Canada, community-care services are funded by the Ministry of Health (MOH) and the Ministry of Children, Community and Social Services (MCCSS). Service agreements between these ministries and individual agencies can be complex and contingent on different factors including compliance with a number of regulatory items and policies [ 7 , 11 ]. MOH provides funding for health-based services including in-home physiotherapy, respiratory therapy, and personal support services, among several others. MOH funds Home and Community Care Support Services (HCCSS), a network of organizations responsible for coordinating the delivery of in-home and community-based care in the province. MCCSS funds social service agencies including those providing community participation and residential support for people with intellectual and developmental disabilities (IDDs).

Several tools and resources have been developed to aid organizations in providing person-centred care and organizations may differ in their use of these tools and their specific approach. Although regional mandates provide a framework for directing care delivery, it is unclear how this guidance is implemented in practice given the diversity and range of organizations within the sector. In addition, as noted by a recent scoping review, there is limited literature on the implementation process and impact of person-centred planning on individual outcomes [ 12 ]. Using a pragmatic, qualitative, descriptive approach [ 13 ], we outline how community-care organizations enact a person-centred approach to care and the factors that shape their enactment. By describing existing practices in the context of the community-care sector, we aim to provide insight on how to optimize care delivery to improve outcomes and inform current policy. This study is part of a larger, multi-methods project examining the implementation of person-centred care plans in the community-care sector. This project encompasses qualitative interviews with representatives from different community-care organizations, as well as staff and persons-supported at a partner community-care organization. This paper focuses on analyzing data from interviews with representatives from different community-care organizations.

We conducted semi-structured interviews with administrators from community-care organizations in Southwestern Ontario (roughly the Ontario Health West Region) between October 2022 and January 2023. We included community-care organizations funded by MOH or MCCSS. We excluded organizations that did not provide services in Southwestern Ontario. We identified eligible organizations and participants by searching online databases, including community resource lists, as well as through consultation with members of the research team.

We used maximum variation sampling [ 14 ], to recruit participants from organizations with a wide range of characteristics including location (i.e., urban, rural), organization type (i.e., for-profit, not-for-profit), and types of services provided (e.g., residential, recreation, transportation, etc.) We contacted eligible organizations via email, providing them with study information and inviting them to participate. We recruited until the data reached saturation, defined as the point at which there was sufficient data to enable rigorous analysis [ 14 , 15 ].

In each interview, we asked participants about their organization’s approach to developing and updating individual service agreements or person-centred care plans, and the supports and barriers (e.g., organizational, funding, staffing, etc.) that facilitate or hinder the implementation of these plans (Supplementary Material 1 : Interview Guide). We also collected information on relevant participant and organizational characteristics, including participant gender, position, years of experience, organization location, type (i.e., for-profit, not-for-profit), services offered, years in operation, and client load. The interviews were approximately one hour in length and conducted virtually via Zoom (Zoom Video Communications Inc.) or by telephone. The interviews were audio-recorded and transcribed verbatim. Interviewer field notes were also used in data analysis.

We analyzed the data thematically [ 16 ]. The coding process followed a collaborative and multi-step approach. Initially, three members of the research team independently reviewed and coded a selection of transcripts to identify key ideas and patterns in the data, and form a preliminary coding template. We then met to consolidate individual coding efforts. We compared coding of each transcript, resolving conflicts through discussion and consensus. In coding subsequent transcripts and through a series of meetings, we worked together to finalize the codebook to reflect more analytic codes. We used the finalized template to code all interview transcripts in NVivo (QSR International), a software designed to facilitate qualitative data analysis. We refined the codebook on an as-needed basis by incorporating novel insights gleaned from the coding of additional transcripts, reflecting the iterative nature of the analysis.

We increased the robustness of our methodology by pre-testing interview questions, documenting interview and transcription protocols, using experienced interviewers, and confirming meaning with participants in interviews [ 14 , 15 , 16 ]. We kept detailed records of interviews, field notes, and drafts of the coding template. We made efforts to identify negative cases and provided rich descriptions and illustrative quotes [ 17 ]. We included individuals directly involved in the administration of community-care services on our research team. These individuals provided important context and feedback at each stage of the research process.

This study was approved by the research ethics board at Western University. We obtained informed consent from participants prior to the onset of interviews. We maintained confidentiality through secure storage of interview data (e.g., audio recordings), password-protection of sensitive documents, and the de-identification of transcripts.

Positionality

The authors represent a multidisciplinary team of researchers, clinicians, and community-care leaders. The community-care leaders and clinicians on our team provided key practical expertise to inform the development of interview questions and the analysis of study findings.

We interviewed administrators across 12 community-care organizations in Southwestern Ontario. The sample included representatives from seven organizations that received funding from MCCSS, three organizations that received funding from MOH, and two organizations that received funding from both MCCSS and MOH (Table  1 ). Eleven organizations were not-for-profit, one was a for-profit agency. The organizations provided care in rural ( n =  3), urban ( n =  4), or both rural and urban populations ( n =  5). Seven of the 12 participants were women, nine had been working with their organization for more than 11 years, and all had been working in the community-care sector for more than 12 years (Table  2 ).

We identified three key categories or processes relating to organizational characteristics and their impact on the design and delivery of person-centred care plans: (1) organizational context, (2) organizational culture, and (3) the development and implementation of person-centred care plans.

Organizational context

Organizational context refers to the characteristics of persons-supported, and the nature of services provided. Organizational context accounts for the considerable heterogeneity across organizations in the community-care sector and their approach to person-centred care plans.

Populations served

The majority of organizations included in the study supported individuals with IDDs: “all of the people have been identified as having a developmental disability. That’s part of the eligibility criteria for any funded developmental service in Ontario.” [P10]. Participants described how eligibility was ascertained through the referral process: “ the DSO [Developmental Services Ontario] figures all of that out and then refers them to us .” [P08]. These descriptions highlighted a common access point for publicly-funded adult developmental services in the province. Accordingly, these organizations were primarily funded by MCCSS. Other organizations focused on medically complex individuals including those with acquired brain injuries or those unable to access out-patient services due to physical disabilities: “the typical reason for referral is going to be around a physical impairment… But, with this medically complex population, you’re often seeing comorbidities where there may be some cognitive impairment, early dementia.” [P04]. In these organizations, eligibility and referral were usually coordinated by HCCSS. These insights highlighted the diverse characteristics of community-care populations, emphasizing the need to consider both physical and cognitive health challenges in care provision approaches.

Services offered

The characteristics of persons-supported informed the context of care and the type of services offered by the organization. The different dimensions of services offered within this sector include social and medical care, short and long-term care provision, in-home and community-care, and full and part-time care.

Nature of care: social vs. medical

Many organizations serving individuals with IDDs employed a holistic, psychosocial model of care, designed to support all areas of an individual’s life including supports for independent-living, and community-based education, employment, and recreation services to support personal and professional goals: “we support people in their homes, so residential supports. We also support people in the community, to be a part of the community, participate in the community and also to work in the community.” [P06]. These descriptions reflect a comprehensive approach to care, aiming to address needs within and beyond residential settings to promote active participation within the broader community. In contrast, some organizations followed a biomedical model of care, designed to support specific health needs: “We provide all five therapies… physiotherapy, occupational therapy, speech, social work, and nutrition. In some locations we provide visiting nursing, at some locations shift nursing. We have some clinic-nursing… and we provide personal support and home-making services in a number of locations as well.” [P04]. These organizations adopted a more clinically-focused approach to care. In either instance, the care model and the nature of services offered were largely determined by an organization’s mandate including which gaps they aimed to fill within the community. Many organizations described providing a mixture of social and medical care for individuals with complex needs. However, the implementation of care plans could be impacted by the lack of integration between social and medical care sectors, as some participants spoke to the importance of “[integrating] all of the different healthcare sector services… [including] acute care and public health and home and community care and primary care, and mental health and addictions.” [P04].

Duration of care: short-term vs. long-term

The duration of care also varied based on the needs of persons-supported. Organizations serving individuals with IDDs usually offered support across the lifespan: “We support adults with developmental disabilities and we support them from 18 [years] up until the end of their life.” [P06]. Some organizations provided temporary supports aimed at addressing specific health needs: “For therapies – these are all short-term interventions and typically they’re very specific and focused on certain goals. And so, you may get a referral for physiotherapy that is authorized for three visits or five visits” [P04], or crisis situations (e.g., homelessness): “Our services are then brought in to help provide some level of support, guidance, stabilization resource, and once essentially sustainability and positive outcomes are achieved—then our services are immediately withdrawn.” [P12]. One organization employed a model of care with two service streams, an initial rehabilitation stream that was intended to be short-term and an ongoing service stream for individuals requiring continuing support.

In-home vs. community-based care

Many organizations provided in-home care and community-based supports, where residential supports were designed to help individuals lead independent lives, and community-based supports encouraged participation in community activities to further inclusion and address personal and professional goals. One participant spoke about the range of services offered in the home and community:

“There’s probably two big categories of [services we offer]: community support services—so that includes things like adult day programs, assisted living, meals on wheels, transportation, friendly visiting … and things like blood pressure clinics, exercise programs… and then on the other side we do home care services. In the home care basket, we provide personal support, and we also provide social work support.” [P05].

Likewise, another participant spoke in further detail on the types of services that allow individuals to live independently within their homes, or in community-based residential settings (e.g., long-term care facilities):

“We provide accommodation supports to about 100 people living in our community—which means that we will provide support to them in their own homes. So, anywhere from an hour a week to 24 hours a day. And that service can include things from personal care to home management to money management, cooking, cleaning, and being out and about in communities—so community participation. We also provide supports for about 50 people living in long-term care facilities and that is all community participation support. So, minus the last 2 and a half years because of the pandemic, what that means is that a person living in a long-term care facility with a developmental disability can have our support to get out and about for 2 or 3 hours a week, on average.” [P10].

Full-time vs. part-time support

The person-supported’s needs also determined whether they would receive care within their homes and if they would be supported on a full-time (i.e., 24 h a day, 7 days a week) or part-time basis:

“ It really does range from that intensive 24- hour/7 day a week support, which we actually do provide that level of intense support in the family home, if that’s needed. And then, all the way through to just occasional advocacy support and phone check-in.” [P01].

Organizational Culture

Organizational culture was described as a key influence in the development and implementation of person-centred care plans. The culture of the organization includes their perceptions, attitudes and beliefs surrounding persons-supported; their model of care provision; as well as their willingness to evolve and adapt service provision to optimize care delivery.

Perceptions, attitudes, and beliefs regarding persons-supported

Participants described their organization’s view of persons-supported, with many organizations adopting an inclusionary framework where persons-supported were afforded the same rights and dignities as others in the community. This organizational philosophy was described as being deeply intertwined with an organization’s approach to personalizing programs and services:

“…an organization needs to be able to listen to the people who are receiving the service… and support them, to learn more, figure out, articulate, whatever it is, the service or the supports that they need in order to get and move forward with their life.” [P10].

The focus on the person-supported, their needs, likes, and dislikes, was echoed across organizations, with an emphasis on the impact of “culture and trying to embed for each person who delivers service the importance of understanding the individual.” [P05]. Participants also described their organization’s approach to allowing persons-supported to take risks, make mistakes, and live life on their own terms:

“You have to go and venture out and take some [risks]… We try to exercise that philosophy - people with disabilities should have the same rights and responsibilities as other people in the community. Whether that’s birthing or education, getting a job, having a house they can be proud of, accessing community supports, whether that be [a] library or community centre, or service club, whatever that is.” [P03].

Model of care provision

The model of care provision was heavily influenced by the organization’s values and philosophy. Several organizations employed a flexible model of care where supports were developed around the needs, preferences, and desired outcomes of the person-supported:

“…if we don’t offer [the program they want], we certainly build it. Honestly, most of our programs were either created or built by someone coming to us [and] saying ‘I want to do this with my life,’ or …‘my son would like to do art.’” [P02].

Although there were similarities in models across the different organizations, one participant noted that flexibility can be limited in the congregate care setting as staff must tend to the needs of a group as opposed to an individual:

“Our typical plan of operation outside of the congregate setting is we design services around the needs of the person. We don’t ask them to fit into what we need, we build services for what they need. Within the congregate care setting, we have a specific set of rules and regulations for safety and well-being of the other people that are here.” [P11].

Evolving service orientation

In organizations serving individuals with IDDs, many described shifting from program-based services to more individualized and community-based supports: “The goal was always to get people involved in their community and build in some of those natural supports … [we] are looking to support people in their own communities based on their individual plans.” [P07]. One participant described this model as a person-directed approach as opposed to person-centred, citing the limitations of program-based services in meeting individual needs:

“[Persons-supported] couldn’t [do] what they wanted because they were part of a bigger group. We would listen to the bigger group, but if one person didn’t want to go bowling … we couldn’t support them because everybody had to go bowling.” [P06].

The focus on individualized support could potentially lead to increased inclusion for persons-supported in their communities:

“… people go to Tim Horton’s, and if they go every day at 9 they probably, eventually will meet other people that go at 9 o’clock and maybe strike up a conversation and get to know somebody and join a table … and meet people in the community.” [P02].

By creating routines centred on individual preferences, the person-supported becomes a part of a community with shared interests and values.

Person-centred care plans

Community-care organizations enacted a person-centred approach by creating person-centred care plans for each person-supported. Although all participants said their organization provided person-centred services, there was considerable variation in the specific processes for developing, implementing, and updating care plans.

Developing a person-centred care plan

The development of a care plan includes assessment, consultation, and prioritization. The initial development of the care plan usually involved an assessment of an individual’s needs and goals. Participants described agency-specific assessment processes that often incorporated information from service referrals: “ In addition to the material we get from the DSO [Disability Services Ontario] we facilitate the delivery of an intake package specifically for our services. And that intake package helps to further understand the nature and needs of an individual.” [P12]. Agency-specific assessment processes differed by the nature of services provided and the characteristics of the population. However, most organizations included assessments of “not only physical functioning capabilities, but also cognitive.” [P01]. Assessment also included an appraisal of the suitability of the organization’s services. In instances where persons-supported were seeking residential placements or independent-living support, organizations assessed their ability to carry out the activities of daily living:

“[Our internal assessment] is an overview of all areas of their life. From, ‘do they need assistance with baking, cooking, groceries, cleaning, laundry? Is there going to be day program opportunities included in that residential request for placement? What the medical needs are?’” [P02].

In contrast, the person-supported’s community-based activities were primarily informed by their interests and desired outcomes: “We talk about what kinds of goals they want to work on. What kind of outcomes we’re looking for…” [P06].

The development of the care plan also included a consultation phase, involving conversations with the person-supported, their family members, and potentially external care providers: “We would use the application information, we’d use the supports intensity scale, but we’d also spend time with the person and their connections, their family and friends, in their home to figure out what are the kinds of things that this person needs assistance with.” [P10]. Participants described the person-supported’s view as taking precedence in these meetings: “We definitely include the family or [alternate] decision-maker in that plan, but the person-supported ultimately has the final stamp of approval.” [P08]. Many participants also acknowledged the difficulty of identifying and incorporating the person-supported’s view in cases where opinions clash and the person-supported has difficulty communicating and/or is non-verbal: “Some of the people we support are very good at expressing what they want. Some people are not. Some of our staff are really strong in expressing what they support. …And some of the family members are very strong. So you have to be very careful that the [person-supported] is not being lost in the middle of it.” [P06].

Participants also noted that some persons-supported preferred not to have a care plan:

“Some of the people say ‘I hate [the plans] I don’t want to do them’…. we look at it in a different way then. We’ll use graphic art, we’ll use video, we’ll think outside the box to get them to somehow—because at the end of the day when we’re audited by MCCSS every [person-supported] either has to have [a plan]… or there has to be [an approval of] why it wasn’t completed.” [P02].

Plan development may also include a prioritization process, particularly in cases where resources are limited. A person-supported’s goals could be prioritized using different schemas. One participant noted that “the support coordinator takes the cue from the person-supported - … what they’ve identified as ‘have to have’ and ‘nice to have’. … because the ‘have to haves’ are prioritized.” [P09]. Likewise, the person-supported’s preference could also be identified through “[an] exercise, called ‘what’s important for and what’s important to .’” [P06]. This model, based on a Helen Sanderson approach [ 18 ], was described as being helpful in highlighting what is important to the person-supported, as opposed to what others (i.e., friends, family, staff, etc.) feel is important for them.

Several organizations updated care plans throughout the year, to document progress towards goals, adapt to changing needs and plan for future goals: “We revisit the plan periodically through the year. And if they say the goal is done, we may set another goal.” [P06]. Organizations may also change plans to adapt to the person-supported’s changing health status or personal capacity.

Implementing a person-centred care plan

The implementation of care plans differed based on the nature of services provided by the organization. The delivery of health-based or personal support services often involved matching the length and intensity of care with the individual’s needs and capacity:

“Sometimes that is a long time, sometimes it’s a short time, sometimes it’s an intervention that’s needed for a bit, and then the person is able to function.” [P05].

In contrast, the delivery of community-based services involved matching activities and staff by interests: “[if] a person-supported wants to go out and be involved in the music community, then we pull the staff pool in and match them up according to interest.” [P06].

Broad personal goals were broken down into smaller, specific activities. For example, one participant described their organization’s plan in helping a person-supported achieve his professional goal of securing employment:

“[The person-supported] said ‘Okay, I want a job.’ So for three weeks he was matched up with a facilitator. They came up with an action plan in terms of how to get a job, what kind of job he’s looking for, where he wants to go, where he wants to apply, how to conduct an interview. And after three weeks he got a job.” [P09].

Organizations that provided residential services focused on developing independent-living skills. One participant described their organization’s plan to empowering persons-supported by allowing them to make their own financial decisions:

“If one month they’re looking after their own finances, and they’ve overspent. Well, maybe we help them out with a grocery card or something and say ‘okay, next month how are you going to do this?’ [The person-supported may say], ‘well, maybe I’ll put so much money aside each week rather than doing a big grocery shop the first week and not having enough money left at the end of the month.’” [P03].

The participant noted that “a tremendous amount of learning [happens] when a person is allowed to [take] risks and make their own decisions.” [P03].

Likewise, participants representing organizations that provided residential services described tailoring care to the persons-supported’s sleeping schedule and daily routine:

“We develop a plan and tweak it as we go. With [the person-supported] coming to the home, what worked well was, we found that he wanted to sleep in, so we adjusted the [staff] time. We took a look at his [medication] times in the morning… and [changed] his [medication] times. We found that he wanted to sleep [until] later in the day, so he would get up at 10 o’clock, so then instead of having breakfast, lunch, and supper he would just have a bigger brunch. Just really tailoring the plan around the person-supported, and it’s worked out well.” [P08].

These examples highlight how organizational context and culture influence how organizations operationalize person-centred care plans; the same individual may experience different approaches to care and engage in different activities depending on the organization they receive services from.

In this paper, we described key elements of the person-centred planning process across different community-care organizations in Southwestern Ontario. We also identified that the context and culture of an organization play a central role in informing the process by which services are personalized to an individual’s needs. These findings shed light on the diversity of factors that influence the implementation of person-centred care plans and the degree to which organizations are able to address medical and social needs in an integrated fashion. They also inform future evaluations of person and system-related outcomes of person-centred planning.

There are regulations around individualizing services delivered by community-care organizations, whereby care providers must allow persons-supported to participate in the development and evaluation of their care plans. HCCSS or MOH-funded services are largely focused on in-home rehabilitation or medical care. In contrast, MCCSS-funded organizations often focus on developing independent living skills or promoting community participation, thus highlighting the role of the funding agency in determining organizational context as well as the nature of services and personalization of care plans.

We also identified organizational culture as a key influence in the person-centred planning process. In previous reports, organizational culture, and specifically the way in which staff perceive and view persons-supported and their decision-making capabilities can impact the effective delivery of person-centred care [ 19 ]. Staff support, including their commitment to persons-supported and the person-centred process, has been regarded as one of the most powerful predictors of positive outcomes and goal attainment in the developmental services sector [ 20 , 21 ]. Moreover, in order to be successful, commitment to this process should extend across all levels of the organization, be fully integrated into organizational service delivery, and be reflected in organizational philosophy, values and views of persons-supported [ 22 , 23 , 24 ].

MCCSS mandates that agencies serving individuals with IDDs develop an individual service plan (ISP) for each person-supported, one “that address[es] the person’s goals, preferences and needs.” [ 7 ]. We reference ISPs as person-centred care plans, as is in line with the view of participants in interviews. There are a series of checklists designed to measure compliance with these policies, and the process is iterative, with mandated annual reviews of care plans and active participation by the person-supported [ 25 ]. In our study, the agencies funded by MCCSS adhered to the general framework outlined by these regulations and informed service delivery accordingly. However, participants also described areas for improvement with respect to the implementation of these policies in practice. These policies, while well-intentioned, may imply a one-size-fits-all approach and appear more as an administrative exercise as opposed to a meaningful endeavor designed to optimize care. Participants spoke about individuals who preferred not to have an ISP, and how that in and of itself is a person-centred approach, respecting the person’s wishes. Additionally, we heard about how the goal-setting process may not be realistic as it can be perceived as unnatural to have goals at each point in one’s life. Moreover, participants noted challenges in implementing person-centred care in shared residential settings (e.g., group homes) or in cases where persons-supported had difficulty communicating.

Prior research indicates that individuals living in semi-independent settings fare better across several quality-of-life measures relative to individuals living in group homes, including decreased social dissatisfaction, increased community participation, increased participation in activities of daily living, and increased empowerment [ 26 ]. Furthermore, a recent study by İsvan et al. (2023) found that individuals living in the community (e.g., own home, family home, or foster home) exhibit greater autonomy in making everyday and life decisions, and greater satisfaction with their inclusion in the community [ 27 ]. These findings may be indicative of a reduced focus on person-centred care plan development and implementation in congregate care settings, where limited staff capacity can make it difficult to tend to the needs of everyone in the home. However, poor outcomes may also be explained by potentially more complex health challenges or more severe disability in persons-supported living in congregate care settings. The challenges described in our study are consistent with calls to improve the quality of care provided in residential group home settings [ 28 , 29 ].

In line with our findings, previous literature also describes challenges in implementing person-centred planning for individuals who have difficulty communicating or are non-verbal [ 19 , 30 , 31 , 32 ]. Communication has also been identified as a barrier to patient-centred care for adults with IDDs in healthcare settings [ 33 , 34 ]. Other reports have identified a need for increased training and awareness of diverse communication styles (including careful observation of non-verbal cues) to aid staff in including persons-supported in the development of care plans [ 35 , 36 , 37 ]. Importantly, these methods take substantial time which is often limited, and compounded by staffing shortages that are widespread across the sector [ 38 ]. Similar barriers were identified in interviews with staff and persons-supported at a partner community-care agency within our larger project [ 39 ]; other papers from the project examine strategies used by the organization to overcome these barriers.

Limitations

The findings from this study should be interpreted in the context of the following limitations. There is a risk for social desirability bias, whereby participants may feel pressure to present their care plan process in a more positive light due to societal norms and expectations [ 40 ]. Additionally, the experiences and views of community-care organizations may vary by region and organization type (i.e., for-profit vs. not-for-profit). In this study, we limited participation to agencies providing services in Southwestern Ontario and we were only able to interview one for-profit agency, despite concerted recruitment efforts. Consequently, we may not have fully captured how financial pressures, or different contextual and cultural components of an organization impact their implementation of care plans.

The person-centred planning process in community-care organizations is largely informed by the characteristics of the population served and the nature of services offered (i.e., organizational context). This process usually involves initial and continued consultations with persons-supported to tailor plans to their specific needs and desired outcomes. There are ongoing challenges in the implementation of person-centred planning, including a need for increased adaptability and clarity in current regulations. In some areas, there may be benefit to incorporating nuance in the application of policies (e.g., in cases where a person-supported does not want to have a formal plan in place). In other areas, it may be helpful to have increased guidance on how to optimize care delivery to improve outcomes (e.g., in cases where a person-supported has difficulty communicating, or is residing in a group home). Policymakers, administrators, and service providers can leverage these insights to refine policies, advocating for inclusive, flexible approaches that better align with diverse community needs.

Data availability

The datasets generated and analyzed in the current study are not publicly available to maintain participant confidentiality, however access may be granted by the corresponding author upon reasonable request.

Abbreviations

Acquired Brain Injury

Disability Services Ontario

Home and Community Care Support Services

Intellectual and Developmental Disabilities

Individual Service Plan

Ministry of Children, Community and Social Services

Ministry of Health

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Acknowledgements

The authors thank Ruth Armstrong, from PHSS - Medical & Complex Care in Community, for her valuable feedback and support throughout the research process.

This research was funded by the Canadian Institutes of Health Research. The funding agency had no role in the conceptualization, design, data collection, analysis, decision to publish, or preparation of the manuscript.

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S.I. conducted the interviews, developed the coding template, coded the data, thematically analyzed the data, and prepared the manuscript. G.Y. helped develop the coding template, and reviewed and approved the final manuscript. B.D. and D.A. helped conceptualize the study, aided in the interpretation and analysis of study findings, and reviewed and approved the final manuscript. L.M. coordinated research activities, aided in the interpretation and analysis of study findings, and reviewed and approved the final manuscript. M.M. conceptualized the study, supervised its implementation, and was a major contributor in reviewing and editing the manuscript. All authors have read and approved the final manuscript.

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Idrees, S., Young, G., Dunne, B. et al. The implementation of person-centred plans in the community-care sector: a qualitative study of organizations in Ontario, Canada. BMC Health Serv Res 24 , 680 (2024). https://doi.org/10.1186/s12913-024-11089-7

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Ryan Pollyea joined Virginia Tech’s “Curious Conversations”  to talk about geologic carbon sequestration, which is the process of permanently storing carbon dioxide thousands of feet below the Earth’s surface. Pollyea explained what types of rock this is currently known to work with, the efforts he and his colleagues are taking to expand this to other geologic regions, and the potential impact that could have for the environment and economics.

About Pollyea

Pollyea is an associate professor in the Department of Geosciences and an affiliate faculty member of the Department of Mining and Minerals Engineering as well as the Virginia Center for Coal and Energy Research . His research interests are at the intersection of geofluids and energy resources, including geologic carbon dioxide sequestration, hydrothermal fluid systems, and fluid-triggered earthquakes.

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Some geologic formations, such as sandstone, are known to be capable of storing carbon dioxide, but Pollyea and his colleagues are exploring storing it in other types of geology, such as limestone formations and fold-and-thrust belts.

Understanding the geology of these underground formations is critical to potential carbon dioxide storage and a major challenge due to the areas being so far out of sight.

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One of the most confusing aspects for patients with type 2 diabetes mellitus is that they have high fasting glucose levels. This is because in these insulin-resistant patients, glucose production by the liver is triggered, a process that is still full of questions for the scientific community. Now, a review article published in the journal Trends in Endocrinology & Metabolism presents a comprehensive overview of the most important advances in understanding this mechanism. It also helps to identify new drug targets in the fight against type 2 diabetes mellitus, which the World Health Organization (WHO) considers one of the pandemics of the 21 st century.

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In patients, the glucose synthesis pathway in the liver (gluconeogenesis) is hyperactivated, a process that can be controlled by drugs such as metformin. "Recently, new factors involved in the control of hepatic gluconeogenesis have been identified. For example, a study by our group revealed that growth differentiation factor (GDF15) reduces the levels of proteins involved in hepatic gluconeogenesis," says Professor Manuel Vázquez-Carrera, from the UB's Department of Pharmacology, Toxicology and Therapeutic Chemistry.

To make progress in the fight against this pathology, it will also be necessary to further study pathways such as TGF-β, which is involved in the progression of metabolic dysfunction-associated fatty liver disease (MASLD), a very prevalent pathology that often coexists with type 2 diabetes mellitus. "TGF-β plays a very relevant role in the progression of liver fibrosis and has become one of the most important factors that may contribute to increased hepatic gluconeogenesis and, therefore, to type 2 diabetes mellitus. Therefore, studying the involvement of the TGF-β pathway in the regulation of hepatic gluconeogenesis could help to achieve better glycaemic control," stresses Vázquez-Carrera.

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"Today there are several molecules -- TGF-β, TOX3, TOX4, etc. -- that could be considered therapeutic targets for designing future strategies to improve patients' well-being. Their efficacy and safety will determine their therapeutic success. We cannot lose sight of the fact that controlling the overactivation of hepatic gluconeogenesis in type 2 diabetes mellitus has an additional difficulty: it is a key pathway for making glucose available in fasting situations, it is finely modulated by numerous factors and this makes regulation difficult," he adds.

Interestingly, other factors involved in the control of gluconeogenesis have also been identified in patients hospitalised with COVID-19 who showed high glucose levels. "Hyperglycaemia was very prevalent in patients hospitalised with COVID-19, which seems to be related to the ability of SARS-CoV-2 to induce the activity of proteins involved in hepatic gluconeogenesis," the expert notes.

The mechanisms of action of metformin, the most commonly prescribed drug for the treatment of type 2 diabetes, which reduces hepatic gluconeogenesis, are still not fully understood. It has now been discovered that the drug decreases gluconeogenesis via inhibition of complex IV of the mitochondrial electron transport chain. This is a mechanism independent of the classical effects known until now through activation of the AMPK protein, a sensor of the cell's energy metabolism.

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In addition, metformin can also reduce gluconeogenesis through its effects on the gut, leading to changes that ultimately attenuate hepatic glucose production in the liver. "Thus, metformin increases glucose uptake and utilisation in the gut, and generates metabolites capable of inhibiting gluconeogenesis when they reach the liver via the portal vein. Finally, metformin also stimulates the secretion of GLP-1 in the intestine, a hepatic gluconeogenesis inhibitory peptide that contributes to its anti-diabetic effect," he explains.

For now, the team led by Vázquez-Carrera continues its research work to decipher the mechanisms by which GDF15 could regulate hepatic gluconeogenesis. "In parallel, we want to design new molecules that increase circulating GDF15 levels. If we have potent inducers of GDF15, we could improve glycaemia in people with type 2 diabetes mellitus by reducing hepatic gluconeogenesis, but also by other actions of this cytokine," concludes the researcher.

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• Emma Barroso, Javier Jurado-Aguilar, Walter Wahli, Xavier Palomer, Manuel Vázquez-Carrera. Increased hepatic gluconeogenesis and type 2 diabetes mellitus . Trends in Endocrinology & Metabolism , 2024; DOI: 10.1016/j.tem.2024.05.006

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Experience and training needs of nurses in military hospital on emergency rescue at high altitude: a qualitative meta-synthesis

• Ruixuan Zhao 1 ,
• Shijie Fang 1 ,
• Dongwen Li 2 &
• Cheng Zhang 3  

BMC Nursing volume  23 , Article number:  370 ( 2024 ) Cite this article

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Metrics details

Nurses play an important role in the treatment of war wounds on the plateau, and they face multiple challenges and a variety of needs in their caregiving process. This study aimed to systematically integrate and evaluate qualitative research data to understand the altitude emergency rescue experience and training needs of nurses in military hospitals and provide them with targeted assistance.

We critically assessed the study using the Joanna Briggs Institute Critical Assessment Checklist for Qualitative Research. Extraction, summarization and meta-synthesis of qualitative data. Cochrane Library, PubMed, Embase, FMRS, CINAHL, PsycINFO, Chinese National Knowledge Infrastructure (CNKI), Wanfang Database (CECDB), VIP Database, and China Biomedical Database (CBM) were searched for relevant studies published from the establishment of the database to May 2023. Additionally, we conducted a manual search of the references of the identified studies. Registered on the PROSPERO database (CRD42024537104).

A total of 17 studies, including 428 participants, were included, and 139 research results were extracted, summarized into 10 new categories, and formed 3 meta-themes. Meta-theme 1: mental state of military nurses during deployment. Meta-theme 2: the experience of military nurses during deployment. Meta-theme 3: training needs for emergency care.

Conclusions

Emergency rescue of high-altitude war injuries is a challenging process. Leaders should pay full attention to the feelings and needs of military nurses during the first aid process and provide them with appropriate support.

Peer Review reports

Introduction

The plateau area has the characteristics of high altitude, cold all the year round, many ice peaks and snow mountains, and hypoxia [ 1 ]. These characteristics pose major obstacles to both military operations and non-military operations and at the same time, due to the complex terrain and inconvenient transportation, the detection, handling, treatment, and evacuation of the wounded become very difficult. These special natural environments put forward higher requirements for medical rescue [ 2 , 3 ]. As an important part of military or non-military missions, military nurses play an important role in emergency rescue [ 4 ]. There has been a long history of military nurses engaging in war, military operations and humanitarian missions, they are required to provide not only routine health care during peacetime, but also medical services during conflict or humanitarian assistance in response to disasters, public emergencies and epidemics [ 5 , 6 ]. The rescue process is arduous, and nurses may face great challenges. When they are at high altitude environment, they are prone to hypoxia, frostbite, sunburn, fall, blindness, etc., and may be accompanied by high altitude pulmonary edema and high-altitude coma. In war and non-war military operations, military nurses are required to care for a variety of trauma patients, including burns, traumatic amputations, shock, bleeding, penetrating injuries, spinal cord injuries, head injuries, crush injuries, radiation injuries, chemical injuries, infectious diseases, and more. This has higher requirements for the physical, psychological and professional knowledge of military nurses [ 4 , 7 , 8 ].

To provide better care for the wounded and respond to various emergency situations, military nurses must continuously improve their competence. In addition, according to the literature [ 4 , 6 , 9 ], the demand of military nurses for emergency rescue training is gradually increasing, with nurses with deployment experience reporting limited first aid proficiency and a lack of practical training, and related qualitative studies are also increasing, but a single qualitative research result is difficult to fully and accurately reflect the needs of military nurses. Therefore, this study uses a meta-synthesis approach to analyze and summarize such studies the to understand experience and training needs of nurses in military hospitals with altitude war injury emergency rescue, to provide reference for formulating altitude emergency rescue training strategies, and better meet their needs and provide them with appropriate support.

Study design

The Joanna Briggs Institute(JBI)methodology for systematic reviews of qualitative evidence [ 10 ] guided this systematic review and qualitative meta-synthesis. We used the PROSPERO to identify published or ongoing research relevant to the topic and registered for this review(CRD42024537104). In addition, we report our findings by the Enhancing Transparency in Reporting the Synthesis of Qualitative Research (ENTREQ) Statement [ 11 ].

Search strategy

We performed systematic searches in Cochrane Library, PubMed, Embase, FMRS, CINAHL, PsycINFO, Chinese National Knowledge Infrastructure (CNKI), Wanfang Database (CECDB), VIP Database, and China Biomedical Database (CBM). The retrieval time limit was from the establishment of the database to May 2023. The following search terms were used in different combinations: plateau, qualitative study, Emergency rescue, train, Military nurses, education, disaster, public health emergency, rescue, army, War readiness, war. Additionally, we conducted a manual search of the references to the identified studies to find additional eligible articles.

Inclusion and exclusion criteria

Articles that satisfied the following criteria were included in the qualitative synthesis: 1)study population(P): military nurses; 2)phenomenon of interest(I): highland or mountain emergency rescue or emergency rescue experiences, experiences and training needs; 3)context(Co): military nurse emergency rescue process or training process; 4)type of study: qualitative research, including phenomenological, descriptive qualitative research, rooted theory, ethnography, etc.

The exclusion criteria were as follows: 1)duplicate literature, literature with unavailable full text or incomplete data, literature with substandard quality (The JBI qualitative research critical assessment is graded C); 2)literature not in English; 3) secondary research.

Article filtering and quality assessment

Literature screening was done independently by 2 researchers following strict inclusion and exclusion criteria, and they independently assessed the quality of the included literature using the JBI Manual for Systematic reviews of qualitative evidence [ 10 ]. The guideline has 10 evaluation items, each items uses “yes”, “no”, and “not provided” as evaluation indicators. In this study, literature quality is divided into A, B and C. A represents that the literature meets all the above evaluation indicators, B represents that the literature partially meets, and C represents that it does not meet all the above evaluation indicators. During the article selection and quality evaluation process, disagreements were settled with discussion or with a third author’s assistance.

Data extraction

Data management was enabled by the reference management program Endnote 20. Data extraction consists of two researchers reading the content contained in the study independently to extract relevant and useful information, cross-reviewed, and when any disagreement was discussion to resolve it with a third experienced researcher. The relevant content of each study was extracted using a standardized data extraction tool from the Joanna Briggs Institute Qualitative Assessment and Review (JBI-QARI), the JBI-QARI qualitative criteria are: (1) unequivocal (U)—refers to findings that are a matter of fact, beyond a reasonable doubt; (2) credible (C)—refers to findings that are plausible interpretations of the primary data within the theoretical framework; (3) unsupported (Un)—relates to findings that are unsupported by the data [ 12 ]. The researchers extracted data according to the above criteria. Data extraction included author, country, objective, study population, research Methodology, and main results.

Data synthesis

This data extraction was carried out and checked independently by 2 researchers, and when disagreements were encountered, a third researcher was asked and consensus was reached on the results. We used Thomas and Hardens’ three stage thematic synthesis approach [ 13 ]: (1) coding the text; (2) developing descriptive themes; (3) generating analytical themes. First, two researchers independently coded the results based on text content and meaning; then, researchers looked for similarities and differences between the textual data, and classify the meaning of the original dataset; finally, the categories were evaluated repeatedly to identify similarities and obtain synthesized results.

Study characteristics

A total of 1070 articles were searched, we found two additional articles by checking the references of articles, and the exclusion of duplicate publications yielded 783 articles. After reading the titles and abstracts, 708 articles were excluded. After reading the remaining 75 articles 58 articles were excluded, including 52 articles with content mismatches, 3 articles studied population errors and full text information could not be obtained for 3 articles, Finally, 17 studies [ 7 , 9 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 ] were identified for inclusion in this analysis. The results of the search are shown in the PRISMA flowchart in Fig.  1 . The 17 included studies were published between 2005 and 2023, of which 16 were qualitative studies [ 7 , 9 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 28 ] and one were mixed-methods studies [ 27 ]. A total of 428 participants, involved 6 countries, including China (2 study [ 7 , 27 ]), USA (6 studies [ 9 , 15 , 17 , 20 , 21 , 22 ]), Sweden (2 studies [ 14 ]), Iran (3studies [ 19 , 24 , 25 ]), Israel (1 study [ 28 ]), Korean (2 studies [ 23 , 26 ]), and British (1 study [ 18 ]). The characteristics of the included literature are shown in Table  1 .

Quality assessment of studies

The included studies were evaluated separately by two trained researchers using the JBI Qualitative Research quality Evaluation criteria, who then participated in the discussion together. When disagreements arose, the help of a third researcher was sought and the final results were unanimously approved by the researchers. All literature included in this study was either A or B grade, which three studies were quality rating of A and 13 studies with a B. Table  2 presents the results of the critical appraisal of the 17 studies.

PRISMA flowchart and literature selection results

Results of synthesis

This study uses the method of aggregative integration [ 12 ] to integrate the results, that is, to further organize and summarize the meaning of the collected results, so as to make the results more convincing, targeted and general. Researchers in understanding the various qualitative research philosophy and methodology of the premise, through repeated reading, analysis and interpretation of each research results, are summarized, integration, form a new category and form integrated results. Finally extracted the results of 17 studies [ 7 , 9 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 ], which were summarized into 10 new categories and formed 3 meta-themes. The categories are presented below with supporting subcategories and illustrative quotes from the original studies.

Theme 1: Mental state of military nurses during deployment

Feeling down.

Military nurses are often frustrated by complex battlefield environments or natural disasters. For example, some nurses may be frustrated by the lack of equipment or supplies, or despair that they cannot save the lives of the wounded; They were frustrated that they could not do more for the wounded. Other nurses were depressed about life after witnessing the brutality of war.

“I am afraid of the battlefield situation on the plateau, and do not understand the local dialect, I do not know how to carry out the rescue work, and I am worried that I have not done anything, dragging everyone down.” [ 7 ]. “You are going to be frustrated at the lack of resources”; “you are going to see young people slaughtered more or less and feel hopelessness at not being able to save their lives.’’ [ 14 ]. “Nurses reported frustration at the time it took for patients to arrive, the extent of injuries, and that they could not do more to save some patients.” [ 9 ].

Emotion management

During deployment, nurses use a variety of methods to vent their emotions and keep them positive. Such as, taking a shower, keeping a journal, talking to others, Mutual acceptance and respect. By adopting positive coping measures, they enable themselves to be competent in their caring role and increase their belief in caring.

“After each surgery I went to take a shower, pouring out my heart in tears, washing myself changing to a clean uniform, then going back like a new person” [ 28 ]. “I’ve had some depression on and off since I came back from Vietnam. If I kept a journal maybe I could get a better handle on some of the things that happened to me over there” [ 15 ]. “Confide in you colleagues and don’t hold things in…I think that’s what kept us going real well” [ 15 ].

Sense of responsibility

It is crucially important for a nurse to understand the mission, policies, and procedures of the armed forces and the part one is asked to play as a military nurse. They need to understand that the purpose of the military is to support, protect, and defend a country’s national security interests. Performing military missions will enable them to serve a greater purpose in life. As both soldiers as well as nurses, based on the sense of responsibility to make them in a state of crisis to protect and serve the people, which make them proud. Military nurses also have an inspiring role to play by example.

“We worked together in the implementation of emergency rescue support tasks, filled with positive energy and a sense of honor, and strengthened our sense of mission” [ 7 ]. “To be something of a father-figure, to give the soldiers a feeling of safety. Keep your eye on your men so that they know they will be looked after if anything happens” [ 14 ].

Theme 2: the experience of military nurses during deployment

There are three main types of “chaos” here: Natural disasters and wars make the environment chaotic; the environment of disaster or war often makes the rescue work of nurses full of uncertainty, which leads to confusion in the team; chaos in the role of nurses during deployment.

“You get over there, [combat] it [the chaos] becomes real, bullets are flying, we’re being mortared … all these injuries, people with broken bones, blown off arms, burns … [In disasters, initially] “It was pure chaos, triage was going on, treatment was going on, people [were] everywhere, lying on the conveyor belt, in wheelchairs, tons of elderly, some had no clothing, it was just a sea of people that you could not see through” [ 22 ]. “One of our biggest challenges in critical situations is ambiguity or confusion in roles. These programs help us to clarify different roles in critical situations” [ 24 ].

Unique environment

This is different from the usual environment, its “Unique” is manifested as: the uncertainty of the war zone; patients with complex injuries, such as explosion injuries, penetrating injuries; lack of resources and poor health care; and the special natural environment at high-altitudes.

“We did not know what to expect in a war zone” [ 28 ]. “I usually have the habit of taking a bath every day, the most difficult to adapt to the field toilet and bathing, bathing like a market, the toilet is very simple, what flying animals can appear, often the toilet has not yet waited, it is necessary to gather training” [ 7 ]. “The biggest headache for me was the sweltering heat of the tent during the day and the shivering cold at night” [ 7 ].

Team support

Team support is important. Maintaining a cohesive team relationship can not only improve the efficiency of casualty rescue, but also provide psychological support to each other. During deployment, the team helps and supports each other, and they are like a family. In addition, successful teams need strong leadership to ensure that the task is completed smoothly.

“We were working in harmony, with collaboration between us. In this way, we could overcome this difficult and stressful time” [ 28 ]. “The chief nurse knew her people. She knew the nurses. She had a feel for what was going on in the unit and she knew who and when she could pull them, and where the staff needed to be to get the job done to cut down on the confusion ” [ 9 ].

The need for specialized skills

Due to the special nature of war trauma, medical personnel lack knowledge and experience in its cause mechanism and operation principle. Other nurses noted their lack of experience in military nursing because they had not been deployed before. Therefore, according to the study, military nurses need to improve their professional skills before deployment.

“I have not systematically received the training of the professional theoretical knowledge of war injury rescue, and I have a sense of panic about the lack of professional knowledge when facing the practical rescue” [ 7 ].

Training needs for emergency care

Psychological training needs.

Military nursing is different from traditional nursing in terms of military obligations and requirements. Firstly, nurses need to cultivate military values, responsibility, patriotism, and a sense of sacrifice. Second, in a battlefield or disaster environment, military nurses face a variety of scenarios, so it requires them to develop a positive mindset. Finally, they need to keep their confidence and overcome their fear.

“I think professional education should begin with enforcement in mind, and it is necessary for nurses to cultivate a spirit of sacrifice and patriotism.” [ 27 ]. “Be secure in yourself and in your professional abilities and limitations. Be realistic in your expectations. You have to cope with the reality and deal with it, even though it is very, very hard” [ 15 ].

Military training content needs

Nurses play an increasingly important role in military missions and are often deployed to different missions, such as humanitarian operations, natural disasters and public health emergencies. Therefore, it is necessary that they have the relevant knowledge, skills and abilities. And they suggest that it is best to train them in local customs and languages before deployment. The special nature of military medicine, they have a lot to learn in the military, including combat and trauma care areas; Chemical, biological, radiological or nuclear (CBRN) preparation/reaction, such as Combat Casualty Care Course, Emergency War Surgery Course, or Trauma Nursing Core Course, etc. In addition, in the plateau region, they also learn medical care under extreme conditions.

“I think the emergency response capacity should be enforced, such as when we run into public health emergencies and natural disasters; s” [ 27 ]. “Now, I think we are dealing with these cultural aspects in all our operational readiness courses” [ 15 ]. “Fluid resuscitation on plains and plateaus is different; thus, we also need to learn medical care and nursing skills for extreme environments” [ 27 ].

Training methods needs

Mixed training methods should be adopted in teaching. Among them, practice, scenario simulation and distance learning are effective training methods, for example, they participated in training exercises in a field training environment or simulation laboratory. At the same time, they should not forget that teamwork training is also important in training.

“I think scenario simulation is a good way, because theory lectures are too boring and we need to put theory into practice” [ 27 ]. “When participating in professional education, trainees should take part in exercise to avoid only talking on paper” [ 27 ]. “We had teamwork training during that education program, and I was impressed with this activity, which provided training on team cohesion” [ 27 ]. “Tabletop exercises were unrealistic and less helpful. We did not practice for a mass casualty.” [ 9 ].

This systematic review and comprehensive study discussed the experience and training needs of nurses in military hospital in altitude first aid. The findings of the review have shown that military nurses faced a lot of physical and emotional stress during deployment. These stressors came from lack of professional ability, inadequate professional preparation, chaotic battlefield environment and extreme natural environment and similar. Military nurses found reasonable ways to cope with stress in a variety of military Settings. They receive training to improve professional competence and self-efficacy, while external support from care managers and colleagues also plays a vital role. However, more strategies are needed to enhance this effect.

The comprehensive quality of the individual (including physical and psychological quality) has a crucial impact on the rescue mission of military nurses [ 8 ]. For rescue in various environments(aircraft carriers, hospital ships, evacuation aircraft, plateaus, hypoxia, cold, desert, Gobi, high humidity, low pressure, jungle, and other area), rescuers need to have good physical fitness, positive and optimistic psychological quality and self-adjustment ability, in order to maximize their own knowledge and skills of high quality play out [ 29 ]. However, the findings of this review [ 7 , 9 , 16 , 17 ] indicate that military nurses may experience altitude sickness, fatigue, nausea, and even acute pulmonary edema when faced with a cold, oxygen-deprived altitude environment; faced with many casualties, they feel depressed, helpless, sad and even depressed. Therefore, military nurses should pay attention to physical training, enhance physical quality, to resist and adapt to extreme environment; nursing managers accurately their psychological state, timely guidance, tracking comfort. The findings of this review also suggest strengthening teamwork and support, which can help nurses support each other during periods of loneliness and provide quality care to wounded patients [ 6 , 7 , 22 , 24 ]. Bonnie et al [ 30 ]. also suggests trying to change thinking and manage emotions by changing feelings and reframing experiences.

Knowledge and technology are the fundamental prerequisites for military nurses to accomplish rescue operations [ 31 ]. This review found that knowledge and skills were mentioned more frequently, indicating that knowledge and skills were the most concerned skills of nurses participating in deployment, and rich knowledge storage and skilled nursing skills are crucial to the first aid of the wounded. Other studies have also drawn a similar conclusion. For example, Harris [ 32 ] found that one unique aspect of clinical expertise in the context of military nursing is clinical diversity, and military nurses should not specialize in just one specialty, but should have multidisciplinary nursing knowledge and skills. Formulating a scientific and effective training program is helpful to improve the ability of military nurses. Caporiccio et al [ 33 ]. found continuing professional education (CPE) is widely recognized by nurses who learn the latest knowledge and skills through CPE, which has become the primary source for maintaining their competencies and ensuring better outcomes worldwide. The training including trauma care, combat knowledge, field nursing, the cultural customs and languages of the deployment place, chemical, biological, radiological or nuclear (CBRN) preparation/reaction(such as Combat Casualty Care Course, Emergency War Surgery Course, or Trauma Nursing Core Course, etc.) [ 8 , 9 , 14 , 15 , 27 ]. Learning barriers have family and work factors, trainees often did not want to attend training because they are worried about their children or heavy work, the learning environment is also an important factor, and the positive learning atmosphere organized by the staff can make the trainees full of passion for learning [ 34 ]. In addition, appropriate training methods have a positive effect on improving nurses’ professional skills. The main methods include practice, scene simulation and distance learning. And leaders should pay attention to teamwork training among medical staff [ 9 , 27 , 35 ]. Overall, making scientific training programs and creating a good learning atmosphere are helpful to improve the knowledge and technology of military nurses.

Competency is the key to affect the rescue mission of military nurses [ 31 ]. Competency is an important invisible feature for military nurses to complete rescue tasks, and is the driving force for other skills to play. Military nurses need to have the ability of organization and management, nursing risk prediction, nursing decision making, emergency handling and so on when performing rescue tasks [ 29 , 36 ]. These are essential conditions for successful treatment. Some studies have shown that team members from different majors simulate operation and rescue tasks in non-task environments, which can effectively prevent the repetition of wrong behaviors by improving leadership, communication skills, teamwork, etc [ 24 , 37 ]. Good communication and teamwork can also reduce the occurrence of adverse events during rescue [ 24 ]. Decisive decision-making ability becomes the key to winning survival time, and good emergency response ability can often avoid further damage [ 4 , 29 , 38 ]. Therefore, military nurses with good comprehensive ability can achieve the rescue effect of both efficiency and quality. Through simulation-based training, military nurses can improve their personal knowledge, skills, abilities, thinking and team ability [ 4 ]. Such as high-fidelity simulation could improve emergency management capabilities, team leadership, and basic nursing skills [ 39 ]; human patient simulators could improve their cognitive thinking and critical thinking skills [ 40 ]; hyper-realistic immersive training could improve the performance of multidisciplinary medical team members and facilitate effective collaboration between members and teams [ 41 ]. We found that military nurses are more willing to improve their ability through practice [ 27 ]. Consequently, it is suggested that the management should expand the practical training mode and combine various simulated training with simulated extreme environment to enhance the comprehensive ability and adaptability of military nurses to special environment.

Strengths and limitations

The advantage of this study is that we not only searched medical databases but supplemented this with manual searches to ensure that studies were fully retrieved. Secondly, we conducted quality control, data extraction, and study quality assessment. Finally, the study is largely reflective of the dilemmas and needs of military nurse and is of great significance to military emergency care. However, there are some limitations to this study. Although the search strategy was thorough, some articles may have been missed, such as the gray literature. And the lack of detailed discussion on the potential influence of the researchers on some of the research studies suggests a possible bias of the findings of original studies.

This qualitative systematic review reviews the experience of military nurses during deployment and analyzes the feelings, experiences, and needs of military nurses during military duty. In contrast, there is less research on emergency rescue operations in extreme environments such as high altitudes, which should be the focus of future exploratory research. Qualitative research in this area should address the lack of mental, physical, and professional preparedness of deployers by understanding the experiences of those with deployment experience in extreme environments. In the future, managers should design diversified, personalized training programs and training methods that are suitable for the deployment of military nurses in a variety of environments.

Data availability

Data used to support the findings of this study are available from the corresponding author upon request.

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This systematic review is supported by the military medical research project of General Hospital of Western Theater Command (2019ZY08).

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Ruixuan Zhao wrote the main manuscript text; Ruixuan Zhao, Shijie Fang and Dongwen Li Collectioned and analysis the data.; Ruixuan Zhao, Shijie Fang and Cheng Zhang were involved in data synthesis; Dongwen Li had a writing review; Ruixuan Zhao and Dongwen Li prepared Fig. 1 and Table 1, and 2; Ruixuan Zhao, Shijie Fang, Cheng Zhang, and Dongwen Li prepared additional file 1 – 4 ; All authors reviewed the manuscript.

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Zhao, R., Fang, S., Li, D. et al. Experience and training needs of nurses in military hospital on emergency rescue at high altitude: a qualitative meta-synthesis. BMC Nurs 23 , 370 (2024). https://doi.org/10.1186/s12912-024-02029-1

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Home » Research Methodology – Types, Examples and writing Guide

Research Methodology – Types, Examples and writing Guide

Table of Contents

Research Methodology

Definition:

Research Methodology refers to the systematic and scientific approach used to conduct research, investigate problems, and gather data and information for a specific purpose. It involves the techniques and procedures used to identify, collect , analyze , and interpret data to answer research questions or solve research problems . Moreover, They are philosophical and theoretical frameworks that guide the research process.

Structure of Research Methodology

Research methodology formats can vary depending on the specific requirements of the research project, but the following is a basic example of a structure for a research methodology section:

I. Introduction

• Provide an overview of the research problem and the need for a research methodology section
• Outline the main research questions and objectives

II. Research Design

• Explain the research design chosen and why it is appropriate for the research question(s) and objectives
• Discuss any alternative research designs considered and why they were not chosen
• Describe the research setting and participants (if applicable)

III. Data Collection Methods

• Describe the methods used to collect data (e.g., surveys, interviews, observations)
• Explain how the data collection methods were chosen and why they are appropriate for the research question(s) and objectives
• Detail any procedures or instruments used for data collection

IV. Data Analysis Methods

• Describe the methods used to analyze the data (e.g., statistical analysis, content analysis )
• Explain how the data analysis methods were chosen and why they are appropriate for the research question(s) and objectives
• Detail any procedures or software used for data analysis

V. Ethical Considerations

• Discuss any ethical issues that may arise from the research and how they were addressed
• Explain how informed consent was obtained (if applicable)
• Detail any measures taken to ensure confidentiality and anonymity

VI. Limitations

• Identify any potential limitations of the research methodology and how they may impact the results and conclusions

VII. Conclusion

• Summarize the key aspects of the research methodology section
• Explain how the research methodology addresses the research question(s) and objectives

Research Methodology Types

Types of Research Methodology are as follows:

Quantitative Research Methodology

This is a research methodology that involves the collection and analysis of numerical data using statistical methods. This type of research is often used to study cause-and-effect relationships and to make predictions.

Qualitative Research Methodology

This is a research methodology that involves the collection and analysis of non-numerical data such as words, images, and observations. This type of research is often used to explore complex phenomena, to gain an in-depth understanding of a particular topic, and to generate hypotheses.

Mixed-Methods Research Methodology

This is a research methodology that combines elements of both quantitative and qualitative research. This approach can be particularly useful for studies that aim to explore complex phenomena and to provide a more comprehensive understanding of a particular topic.

Case Study Research Methodology

This is a research methodology that involves in-depth examination of a single case or a small number of cases. Case studies are often used in psychology, sociology, and anthropology to gain a detailed understanding of a particular individual or group.

Action Research Methodology

This is a research methodology that involves a collaborative process between researchers and practitioners to identify and solve real-world problems. Action research is often used in education, healthcare, and social work.

Experimental Research Methodology

This is a research methodology that involves the manipulation of one or more independent variables to observe their effects on a dependent variable. Experimental research is often used to study cause-and-effect relationships and to make predictions.

Survey Research Methodology

This is a research methodology that involves the collection of data from a sample of individuals using questionnaires or interviews. Survey research is often used to study attitudes, opinions, and behaviors.

Grounded Theory Research Methodology

This is a research methodology that involves the development of theories based on the data collected during the research process. Grounded theory is often used in sociology and anthropology to generate theories about social phenomena.

Research Methodology Example

An Example of Research Methodology could be the following:

Research Methodology for Investigating the Effectiveness of Cognitive Behavioral Therapy in Reducing Symptoms of Depression in Adults

Introduction:

The aim of this research is to investigate the effectiveness of cognitive-behavioral therapy (CBT) in reducing symptoms of depression in adults. To achieve this objective, a randomized controlled trial (RCT) will be conducted using a mixed-methods approach.

Research Design:

The study will follow a pre-test and post-test design with two groups: an experimental group receiving CBT and a control group receiving no intervention. The study will also include a qualitative component, in which semi-structured interviews will be conducted with a subset of participants to explore their experiences of receiving CBT.

Participants:

Participants will be recruited from community mental health clinics in the local area. The sample will consist of 100 adults aged 18-65 years old who meet the diagnostic criteria for major depressive disorder. Participants will be randomly assigned to either the experimental group or the control group.

Intervention :

The experimental group will receive 12 weekly sessions of CBT, each lasting 60 minutes. The intervention will be delivered by licensed mental health professionals who have been trained in CBT. The control group will receive no intervention during the study period.

Data Collection:

Quantitative data will be collected through the use of standardized measures such as the Beck Depression Inventory-II (BDI-II) and the Generalized Anxiety Disorder-7 (GAD-7). Data will be collected at baseline, immediately after the intervention, and at a 3-month follow-up. Qualitative data will be collected through semi-structured interviews with a subset of participants from the experimental group. The interviews will be conducted at the end of the intervention period, and will explore participants’ experiences of receiving CBT.

Data Analysis:

Quantitative data will be analyzed using descriptive statistics, t-tests, and mixed-model analyses of variance (ANOVA) to assess the effectiveness of the intervention. Qualitative data will be analyzed using thematic analysis to identify common themes and patterns in participants’ experiences of receiving CBT.

Ethical Considerations:

This study will comply with ethical guidelines for research involving human subjects. Participants will provide informed consent before participating in the study, and their privacy and confidentiality will be protected throughout the study. Any adverse events or reactions will be reported and managed appropriately.

Data Management:

All data collected will be kept confidential and stored securely using password-protected databases. Identifying information will be removed from qualitative data transcripts to ensure participants’ anonymity.

Limitations:

One potential limitation of this study is that it only focuses on one type of psychotherapy, CBT, and may not generalize to other types of therapy or interventions. Another limitation is that the study will only include participants from community mental health clinics, which may not be representative of the general population.

Conclusion:

This research aims to investigate the effectiveness of CBT in reducing symptoms of depression in adults. By using a randomized controlled trial and a mixed-methods approach, the study will provide valuable insights into the mechanisms underlying the relationship between CBT and depression. The results of this study will have important implications for the development of effective treatments for depression in clinical settings.

How to Write Research Methodology

Writing a research methodology involves explaining the methods and techniques you used to conduct research, collect data, and analyze results. It’s an essential section of any research paper or thesis, as it helps readers understand the validity and reliability of your findings. Here are the steps to write a research methodology:

• Start by explaining your research question: Begin the methodology section by restating your research question and explaining why it’s important. This helps readers understand the purpose of your research and the rationale behind your methods.
• Describe your research design: Explain the overall approach you used to conduct research. This could be a qualitative or quantitative research design, experimental or non-experimental, case study or survey, etc. Discuss the advantages and limitations of the chosen design.
• Discuss your sample: Describe the participants or subjects you included in your study. Include details such as their demographics, sampling method, sample size, and any exclusion criteria used.
• Describe your data collection methods : Explain how you collected data from your participants. This could include surveys, interviews, observations, questionnaires, or experiments. Include details on how you obtained informed consent, how you administered the tools, and how you minimized the risk of bias.
• Explain your data analysis techniques: Describe the methods you used to analyze the data you collected. This could include statistical analysis, content analysis, thematic analysis, or discourse analysis. Explain how you dealt with missing data, outliers, and any other issues that arose during the analysis.
• Discuss the validity and reliability of your research : Explain how you ensured the validity and reliability of your study. This could include measures such as triangulation, member checking, peer review, or inter-coder reliability.
• Acknowledge any limitations of your research: Discuss any limitations of your study, including any potential threats to validity or generalizability. This helps readers understand the scope of your findings and how they might apply to other contexts.
• Provide a summary: End the methodology section by summarizing the methods and techniques you used to conduct your research. This provides a clear overview of your research methodology and helps readers understand the process you followed to arrive at your findings.

When to Write Research Methodology

Research methodology is typically written after the research proposal has been approved and before the actual research is conducted. It should be written prior to data collection and analysis, as it provides a clear roadmap for the research project.

The research methodology is an important section of any research paper or thesis, as it describes the methods and procedures that will be used to conduct the research. It should include details about the research design, data collection methods, data analysis techniques, and any ethical considerations.

The methodology should be written in a clear and concise manner, and it should be based on established research practices and standards. It is important to provide enough detail so that the reader can understand how the research was conducted and evaluate the validity of the results.

Applications of Research Methodology

Here are some of the applications of research methodology:

• To identify the research problem: Research methodology is used to identify the research problem, which is the first step in conducting any research.
• To design the research: Research methodology helps in designing the research by selecting the appropriate research method, research design, and sampling technique.
• To collect data: Research methodology provides a systematic approach to collect data from primary and secondary sources.
• To analyze data: Research methodology helps in analyzing the collected data using various statistical and non-statistical techniques.
• To test hypotheses: Research methodology provides a framework for testing hypotheses and drawing conclusions based on the analysis of data.
• To generalize findings: Research methodology helps in generalizing the findings of the research to the target population.
• To develop theories : Research methodology is used to develop new theories and modify existing theories based on the findings of the research.
• To evaluate programs and policies : Research methodology is used to evaluate the effectiveness of programs and policies by collecting data and analyzing it.
• To improve decision-making: Research methodology helps in making informed decisions by providing reliable and valid data.

Purpose of Research Methodology

Research methodology serves several important purposes, including:

• To guide the research process: Research methodology provides a systematic framework for conducting research. It helps researchers to plan their research, define their research questions, and select appropriate methods and techniques for collecting and analyzing data.
• To ensure research quality: Research methodology helps researchers to ensure that their research is rigorous, reliable, and valid. It provides guidelines for minimizing bias and error in data collection and analysis, and for ensuring that research findings are accurate and trustworthy.
• To replicate research: Research methodology provides a clear and detailed account of the research process, making it possible for other researchers to replicate the study and verify its findings.
• To advance knowledge: Research methodology enables researchers to generate new knowledge and to contribute to the body of knowledge in their field. It provides a means for testing hypotheses, exploring new ideas, and discovering new insights.
• To inform decision-making: Research methodology provides evidence-based information that can inform policy and decision-making in a variety of fields, including medicine, public health, education, and business.

Advantages of Research Methodology

Research methodology has several advantages that make it a valuable tool for conducting research in various fields. Here are some of the key advantages of research methodology:

• Systematic and structured approach : Research methodology provides a systematic and structured approach to conducting research, which ensures that the research is conducted in a rigorous and comprehensive manner.
• Objectivity : Research methodology aims to ensure objectivity in the research process, which means that the research findings are based on evidence and not influenced by personal bias or subjective opinions.
• Replicability : Research methodology ensures that research can be replicated by other researchers, which is essential for validating research findings and ensuring their accuracy.
• Reliability : Research methodology aims to ensure that the research findings are reliable, which means that they are consistent and can be depended upon.
• Validity : Research methodology ensures that the research findings are valid, which means that they accurately reflect the research question or hypothesis being tested.
• Efficiency : Research methodology provides a structured and efficient way of conducting research, which helps to save time and resources.
• Flexibility : Research methodology allows researchers to choose the most appropriate research methods and techniques based on the research question, data availability, and other relevant factors.
• Scope for innovation: Research methodology provides scope for innovation and creativity in designing research studies and developing new research techniques.

Research Methodology Vs Research Methods

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