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This article has a correction. Please see:

• Correction: How to appraise quantitative research - April 01, 2019

• Xabi Cathala 1 ,
• Calvin Moorley 2
• 1 Institute of Vocational Learning , School of Health and Social Care, London South Bank University , London , UK
• 2 Nursing Research and Diversity in Care , School of Health and Social Care, London South Bank University , London , UK
• Correspondence to Mr Xabi Cathala, Institute of Vocational Learning, School of Health and Social Care, London South Bank University London UK ; cathalax{at}lsbu.ac.uk and Dr Calvin Moorley, Nursing Research and Diversity in Care, School of Health and Social Care, London South Bank University, London SE1 0AA, UK; Moorleyc{at}lsbu.ac.uk

https://doi.org/10.1136/eb-2018-102996

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Introduction

Some nurses feel that they lack the necessary skills to read a research paper and to then decide if they should implement the findings into their practice. This is particularly the case when considering the results of quantitative research, which often contains the results of statistical testing. However, nurses have a professional responsibility to critique research to improve their practice, care and patient safety. 1  This article provides a step by step guide on how to critically appraise a quantitative paper.

Title, keywords and the authors

The authors’ names may not mean much, but knowing the following will be helpful:

Their position, for example, academic, researcher or healthcare practitioner.

Their qualification, both professional, for example, a nurse or physiotherapist and academic (eg, degree, masters, doctorate).

This can indicate how the research has been conducted and the authors’ competence on the subject. Basically, do you want to read a paper on quantum physics written by a plumber?

The abstract is a resume of the article and should contain:

Introduction.

Research question/hypothesis.

Methods including sample design, tests used and the statistical analysis (of course! Remember we love numbers).

Main findings.

Conclusion.

The subheadings in the abstract will vary depending on the journal. An abstract should not usually be more than 300 words but this varies depending on specific journal requirements. If the above information is contained in the abstract, it can give you an idea about whether the study is relevant to your area of practice. However, before deciding if the results of a research paper are relevant to your practice, it is important to review the overall quality of the article. This can only be done by reading and critically appraising the entire article.

The introduction

Example: the effect of paracetamol on levels of pain.

My hypothesis is that A has an effect on B, for example, paracetamol has an effect on levels of pain.

My null hypothesis is that A has no effect on B, for example, paracetamol has no effect on pain.

My study will test the null hypothesis and if the null hypothesis is validated then the hypothesis is false (A has no effect on B). This means paracetamol has no effect on the level of pain. If the null hypothesis is rejected then the hypothesis is true (A has an effect on B). This means that paracetamol has an effect on the level of pain.

Background/literature review

The literature review should include reference to recent and relevant research in the area. It should summarise what is already known about the topic and why the research study is needed and state what the study will contribute to new knowledge. 5 The literature review should be up to date, usually 5–8 years, but it will depend on the topic and sometimes it is acceptable to include older (seminal) studies.

Methodology

In quantitative studies, the data analysis varies between studies depending on the type of design used. For example, descriptive, correlative or experimental studies all vary. A descriptive study will describe the pattern of a topic related to one or more variable. 6 A correlational study examines the link (correlation) between two variables 7  and focuses on how a variable will react to a change of another variable. In experimental studies, the researchers manipulate variables looking at outcomes 8  and the sample is commonly assigned into different groups (known as randomisation) to determine the effect (causal) of a condition (independent variable) on a certain outcome. This is a common method used in clinical trials.

There should be sufficient detail provided in the methods section for you to replicate the study (should you want to). To enable you to do this, the following sections are normally included:

Overview and rationale for the methodology.

Participants or sample.

Data collection tools.

Methods of data analysis.

Ethical issues.

Data collection should be clearly explained and the article should discuss how this process was undertaken. Data collection should be systematic, objective, precise, repeatable, valid and reliable. Any tool (eg, a questionnaire) used for data collection should have been piloted (or pretested and/or adjusted) to ensure the quality, validity and reliability of the tool. 9 The participants (the sample) and any randomisation technique used should be identified. The sample size is central in quantitative research, as the findings should be able to be generalised for the wider population. 10 The data analysis can be done manually or more complex analyses performed using computer software sometimes with advice of a statistician. From this analysis, results like mode, mean, median, p value, CI and so on are always presented in a numerical format.

The author(s) should present the results clearly. These may be presented in graphs, charts or tables alongside some text. You should perform your own critique of the data analysis process; just because a paper has been published, it does not mean it is perfect. Your findings may be different from the author’s. Through critical analysis the reader may find an error in the study process that authors have not seen or highlighted. These errors can change the study result or change a study you thought was strong to weak. To help you critique a quantitative research paper, some guidance on understanding statistical terminology is provided in  table 1 .

• View inline

Some basic guidance for understanding statistics

Quantitative studies examine the relationship between variables, and the p value illustrates this objectively.  11  If the p value is less than 0.05, the null hypothesis is rejected and the hypothesis is accepted and the study will say there is a significant difference. If the p value is more than 0.05, the null hypothesis is accepted then the hypothesis is rejected. The study will say there is no significant difference. As a general rule, a p value of less than 0.05 means, the hypothesis is accepted and if it is more than 0.05 the hypothesis is rejected.

The CI is a number between 0 and 1 or is written as a per cent, demonstrating the level of confidence the reader can have in the result. 12  The CI is calculated by subtracting the p value to 1 (1–p). If there is a p value of 0.05, the CI will be 1–0.05=0.95=95%. A CI over 95% means, we can be confident the result is statistically significant. A CI below 95% means, the result is not statistically significant. The p values and CI highlight the confidence and robustness of a result.

Discussion, recommendations and conclusion

The final section of the paper is where the authors discuss their results and link them to other literature in the area (some of which may have been included in the literature review at the start of the paper). This reminds the reader of what is already known, what the study has found and what new information it adds. The discussion should demonstrate how the authors interpreted their results and how they contribute to new knowledge in the area. Implications for practice and future research should also be highlighted in this section of the paper.

A few other areas you may find helpful are:

Limitations of the study.

Conflicts of interest.

Table 2 provides a useful tool to help you apply the learning in this paper to the critiquing of quantitative research papers.

Quantitative paper appraisal checklist

• 1. ↵ Nursing and Midwifery Council , 2015 . The code: standard of conduct, performance and ethics for nurses and midwives https://www.nmc.org.uk/globalassets/sitedocuments/nmc-publications/nmc-code.pdf ( accessed 21.8.18 ).
• Gerrish K ,
• Moorley C ,
• Tunariu A , et al
• Shorten A ,

Competing interests None declared.

Patient consent Not required.

Provenance and peer review Commissioned; internally peer reviewed.

Correction notice This article has been updated since its original publication to update p values from 0.5 to 0.05 throughout.

Linked Articles

• Miscellaneous Correction: How to appraise quantitative research BMJ Publishing Group Ltd and RCN Publishing Company Ltd Evidence-Based Nursing 2019; 22 62-62 Published Online First: 31 Jan 2019. doi: 10.1136/eb-2018-102996corr1

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Conducting an article critique for a quantitative research study: perspectives for doctoral students and other novice readers

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Authors Vance DE   , Talley M , Azuero A , Pearce PF , Christian BJ

Received 29 January 2013

Accepted for publication 12 March 2013

Published 22 April 2013 Volume 2013:3 Pages 67—75

DOI https://doi.org/10.2147/NRR.S43374

Checked for plagiarism Yes

Review by Single anonymous peer review

Peer reviewer comments 2

David E Vance, 1 Michele Talley, 1 Andres Azuero, 1 Patricia F Pearce, 2 Becky J Christian 1 1 School of Nursing, University of Alabama at Birmingham, Birmingham, AL, USA; 2 Loyola University School of Nursing, New Orleans, LA, USA Abstract: The ability to critically evaluate the merits of a quantitative design research article is a necessary skill for practitioners and researchers of all disciplines, including nursing, in order to judge the integrity and usefulness of the evidence and conclusions made in an article. In general, this skill is automatic for many practitioners and researchers who already possess a good working knowledge of research methodology, including: hypothesis development, sampling techniques, study design, testing procedures and instrumentation, data collection and data management, statistics, and interpretation of findings. For graduate students and junior faculty who have yet to master these skills, completing a formally written article critique can be a useful process to hone such skills. However, a fundamental knowledge of research methods is still needed in order to be successful. Because there are few published examples of critique examples, this article provides the practical points of conducting a formally written quantitative research article critique while providing a brief example to demonstrate the principles and form. Keywords: quantitative article critique, statistics, methodology, graduate students

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Critical Appraisal for Health Students

• Critical Appraisal of a quantitative paper
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Appraisal of a Quantitative paper: Top tips

• Introduction

Critical appraisal of a quantitative paper (RCT)

This guide, aimed at health students, provides basic level support for appraising quantitative research papers. It's designed for students who have already attended lectures on critical appraisal. One framework for appraising quantitative research (based on reliability, internal and external validity) is provided and there is an opportunity to practise the technique on a sample article.

Please note this framework is for appraising one particular type of quantitative research a Randomised Controlled Trial (RCT) which is defined as 

a trial in which participants are randomly assigned to one of two or more groups: the experimental group or groups receive the intervention or interventions being tested; the comparison group (control group) receive usual care or no treatment or a placebo.  The groups are then followed up to see if there are any differences between the results.  This helps in assessing the effectiveness of the intervention.(CASP, 2020)

Support materials

• Framework for reading quantitative papers (RCTs)
• Critical appraisal of a quantitative paper PowerPoint

To practise following this framework for critically appraising a quantitative article, please look at the following article:

Marrero, D.G.  et al  (2016) 'Comparison of commercial and self-initiated weight loss programs in people with prediabetes: a randomized control trial',  AJPH Research , 106(5), pp. 949-956.

Critical Appraisal of a quantitative paper (RCT): practical example

• Internal Validity
• External Validity
• Reliability Measurement Tool

How to use this practical example 

Using the framework, you can have a go at appraising a quantitative paper - we are going to look at the following article:

Marrero, d.g.  et al  (2016) 'comparison of commercial and self-initiated weight loss programs in people with prediabetes: a randomized control trial',  ajph research , 106(5), pp. 949-956.,            step 1.  take a quick look at the article, step 2.  click on the internal validity tab above - there are questions to help you appraise the article, read the questions and look for the answers in the article. , step 3.   click on each question and our answers will appear., step 4.    repeat with the other aspects of external validity and reliability. , questioning the internal validity:, randomisation : how were participants allocated to each group did a randomisation process taken place, comparability of groups: how similar were the groups eg age, sex, ethnicity – is this made clear, blinding (none, single, double or triple): who was not aware of which group a patient was in (eg nobody, only patient, patient and clinician, patient, clinician and researcher) was it feasible for more blinding to have taken place , equal treatment of groups: were both groups treated in the same way , attrition : what percentage of participants dropped out did this adversely affect one group has this been evaluated, overall internal validity: does the research measure what it is supposed to be measuring, questioning the external validity:, attrition: was everyone accounted for at the end of the study was any attempt made to contact drop-outs, sampling approach: how was the sample selected was it based on probability or non-probability what was the approach (eg simple random, convenience) was this an appropriate approach, sample size (power calculation): how many participants was a sample size calculation performed did the study pass, exclusion/ inclusion criteria: were the criteria set out clearly were they based on recognised diagnostic criteria, what is the overall external validity can the results be applied to the wider population, questioning the reliability (measurement tool) internal validity:, internal consistency reliability (cronbach’s alpha). has a cronbach’s alpha score of 0.7 or above been included, test re-test reliability correlation. was the test repeated more than once were the same results received has a correlation coefficient been reported is it above 0.7 , validity of measurement tool. is it an established tool if not what has been done to check if it is reliable pilot study expert panel literature review criterion validity (test against other tools): has a criterion validity comparison been carried out was the score above 0.7, what is the overall reliability how consistent are the measurements , overall validity and reliability:, overall how valid and reliable is the paper.

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The ability to critically evaluate the merits of a quantitative design research article is a necessary skill for practitioners and researchers of all disciplines, including nursing, in order to judge the integrity and usefulness of the evidence and conclusions made in an article. In general, this skill is automatic for many practitioners and researchers who already possess a good working knowledge of research methodology, including: hypothesis development, sampling techniques, study design, testing procedures and instrumentation, data collection and data management, statistics, and interpretation of findings. For graduate students and junior faculty who have yet to master these skills, completing a formally written article critique can be a useful process to hone such skills. However, a fundamental knowledge of research methods is still needed in order to be successful. Because there are few published examples of critique examples, this article provides the practical points of conducting a formally written quantitative research article critique while providing a brief example to demonstrate the principles and form.

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Week 3 Assignment - Critiquing Quantitative or Qualitative Research

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Qualitative vs quantitative research.

13 min read You’ll use both quantitative and qualitative research methods to gather survey data. What are they exactly, and how can you best use them to gain the most accurate insights?

What is qualitative research?

Qualitative research  is all about  language, expression, body language and other forms of human communication . That covers words, meanings and understanding. Qualitative research is used to describe WHY. Why do people  feel  the way they do, why do they  act  in a certain way, what  opinions  do they have and what  motivates  them?

Qualitative data is used to understand phenomena – things that happen, situations that exist, and most importantly the meanings associated with them. It can help add a ‘why’ element to factual, objective data.

Qualitative research gives breadth, depth and context to questions, although its linguistic subtleties and subjectivity can mean that results are trickier to analyse than quantitative data.

This qualitative data is called  unstructured data by researchers. This is because it has not traditionally had the type of structure that can be processed by computers, until today. It has, until recently at least, been exclusively accessible to human brains. And although our brains are highly sophisticated, they have limited processing power. What can help analyse this structured data to assist computers and the human brain?

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What is quantitative research?

Quantitative data refers to numerical information. Quantitative research gathers information that can be counted, measured, or rated numerically – AKA quantitative data. Scores, measurements, financial records, temperature charts and receipts or ledgers are all examples of quantitative data.

Quantitative data is often structured data, because it follows a consistent, predictable pattern that computers and calculating devices are able to process with ease. Humans can process it too, although we are now able to pass it over to machines to process on our behalf. This is partly what has made quantitative data so important historically, and why quantitative data – sometimes called ‘hard data’ – has dominated over qualitative data in fields like business, finance and economics.

It’s easy to ‘crunch the numbers’ of quantitative data and produce results visually in graphs, tables and on data analysis dashboards. Thanks to today’s abundance and accessibility of processing power, combined with our ability to store huge amounts of information, quantitative data has fuelled the Big Data phenomenon, putting quantitative methods and vast amounts of quantitative data at our fingertips.

As we’ve indicated, quantitative and qualitative data are entirely different and mutually exclusive categories. Here are a few of the differences between them.

1. Data collection

Data collection methods for quantitative data and qualitative data vary, but there are also some places where they overlap.

2. Data analysis

Quantitative data suits statistical analysis techniques like linear regression, T-tests and ANOVA. These are quite easy to automate, and large quantities of quantitative data can be analyzed quickly.

Analyzing qualitative data needs a higher degree of human judgement, since unlike quantitative data, non numerical data of a subjective nature has certain characteristics that inferential statistics can’t perceive. Working at a human scale has historically meant that qualitative data is lower in volume – although it can be richer in insights.

3. Strengths and weaknesses

When weighing up qualitative vs quantitative research, it’s largely a matter of choosing the method appropriate to your research goals. If you’re in the position of having to choose one method over another, it’s worth knowing the strengths and limitations of each, so that you know what to expect from your results.

Qualitative vs quantitative – the role of research questions

How do you know whether you need qualitative or quantitative research techniques? By finding out what kind of data you’re going to be collecting.

You’ll do this as you develop your research question, one of the first steps to any research program. It’s a single sentence that sums up the purpose of your research, who you’re going to gather data from, and what results you’re looking for.

As you formulate your question, you’ll get a sense of the sort of answer you’re working towards, and whether it will be expressed in numerical data or qualitative data.

For example, your research question might be “How often does a poor customer experience cause shoppers to abandon their shopping carts?” – this is a quantitative topic, as you’re looking for numerical values.

Or it might be “What is the emotional impact of a poor customer experience on regular customers in our supermarket?” This is a qualitative topic, concerned with thoughts and feelings and answered in personal, subjective ways that vary between respondents.

Here’s how to evaluate your research question and decide which method to use:

• Qualitative research:

Use this if your goal is to  understand  something – experiences, problems, ideas.

For example, you may want to understand how poor experiences in a supermarket make your customers feel. You might carry out this research through focus groups or in depth interviews (IDI’s). For a larger scale research method you could start  by surveying supermarket loyalty card holders, asking open text questions, like “How would you describe your experience today?” or “What could be improved about your experience?” This research will provide context and understanding that quantitative research will not.

• Quantitative research:

Use this if your goal is to  test or confirm  a hypothesis, or to study cause and effect relationships. For example, you want to find out what percentage of your returning customers are happy with the customer experience at your store. You can collect data to answer this via a survey.

For example, you could recruit 1,000 loyalty card holders as participants, asking them, “On a scale of 1-5, how happy are you with our store?” You can then make simple mathematical calculations to find the average score. The larger sample size will help make sure your results aren’t skewed by anomalous data or outliers, so you can draw conclusions with confidence.

Qualitative and quantitative research combined?

Do you always have to choose between qualitative or quantitative data?

In some cases you can get the best of both worlds by combining both quantitative and qualitative data.You could use pre quantitative data to understand the landscape of your research. Here you can gain  insights around a topic  and propose a  hypothesis.  Then adopt a quantitative research method to test it out. Here you’ll discover where to focus your survey appropriately or to pre-test your survey, to ensure your questions are understood as you intended. Finally, using a round of qualitative research methods to bring your insights and story to life. This mixed methods approach is becoming increasingly popular with businesses who are looking for in depth insights.

For example, in the supermarket scenario we’ve described, you could start out with a qualitative data collection phase where you use focus groups and conduct interviews with customers. You might find suggestions in your qualitative data that customers would like to be able to buy children’s clothes in the store.

In response, the supermarket might pilot a children’s clothing range. Targeted  quantitative  research could then reveal whether or not those stores selling children’s clothes achieve higher  customer satisfaction  scores  and a  rise in profits  for clothing.

Together, qualitative and quantitative data, combined with statistical analysis, have provided important insights about customer experience, and have proven the effectiveness of a solution to business problems.

Qualitative vs quantitative question types

As we’ve noted, surveys are one of the data collection methods suitable for both quantitative and qualitative research. Depending on the types of questions you choose to include, you can generate qualitative and quantitative data. Here we have summarized some of the survey question types you can use for each purpose.

Qualitative data survey questions

There are fewer survey  question  options for collecting qualitative data, since they all essentially do the same thing – provide the respondent with space to enter information in their own words. Qualitative research is not typically done with surveys alone, and researchers may use a mix of qualitative methods. As well as a survey, they might conduct in depth interviews, use observational studies or hold focus groups.

Open text ‘Other’ box (can be used with multiple choice questions)

Text box (space for short written answer)

Essay box (space for longer, more detailed written answers)

Quantitative data survey questions

These questions will yield quantitative data – i.e. a numerical value.

Net Promoter Score (NPS)

Likert Scale

Radio buttons (respondents choose just one option)

Check boxes (respondents can choose multiple options)

Sliding scale

Star rating

Analysing data (quantitative or qualitative) using technology

We are currently at an exciting point in the history of qualitative analysis. Digital analysis and other methods that were formerly exclusively used for  quantitative data  are now used for interpreting non numerical data too.

Artificial intelligence programs can now be used to analyse open text, and turn qualitative data into structured and semi structured quantitative data that relates to qualitative data topics such as emotion and sentiment, opinion and experience.

Research that in the past would have meant qualitative researchers conducting time-intensive studies using analysis methods like thematic analysis can now be done in a very short space of time. This not only saves time and money, but opens up qualitative data analysis to a much wider range of businesses and organisations.

The most advanced tools can even be used for real-time statistical analysis, forecasting and prediction, making them a powerful asset for businesses.

Qualitative or quantitative – which is better for data analysis?

Historically, quantitative data was much easier to analyse than qualitative data. But as we’ve seen, modern technology is helping qualitative analysis to catch up, making it quicker and less labor-intensive than before.

That means the choice between qualitative and quantitative studies no longer needs to factor in ease of analysis, provided you have the right tools at your disposal. With an integrated platform like Qualtrics, which incorporates data collection, data cleaning, data coding and a powerful suite of analysis tools for both qualitative and quantitative data, you have a wide range of options at your fingertips.

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Related resources

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MASTER OF COMMUNICATION MANAGEMENT ONLINE

4 Research Methods for Audience Analysis

November 15, 2023

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Before communications professionals such as technical writers, public relations specialists, and others within the field launch a campaign or strategy, they often need to assess the target audience to make sure that all information provided is appropriate, appealing, and at the correct level.

The audience, also referred to as the end-user, will be the recipient of any items produced and shared, so it's crucial to make sure that all communications are targeted towards that group. In order to achieve this goal, many communications professionals will use research methods for audience analysis. As you work toward your master's in communications , it’s important to cultivate skills like these now that can help you at work later.

There are several commonly used methods; each offers its own insights into your target audience. Read on for four examples:

Primary Research

The first step when beginning audience analysis is gathering as much information as possible. If you have preconceived notions or ideas about your audience, avoid them and focus on the actual research performed instead. You should eliminate any information that has already been found by other researchers as part of your primary research phase, since this will allow you to start from scratch. You might choose to use qualitative or quantitative research methods during this process, but all information should come from your own work and findings.

Qualitative Research

Qualitative research focuses on the feelings and opinions of a consumer or member of the target audience. When performing this type of research, you should try to get into and understand the mindset of a customer to see which areas of the product or campaign are most appealing and which areas are lacking. Examples include interviews and focus groups.

Face-to-face or telephone interviews can provide a lot of insight into your target audience. This method of research can fall into either qualitative or quantitative, although most believe that it provides more information in the former category. An interview involves interaction between a single respondent and the moderator, or person asking the questions.

However, an interview doesn't have to follow a prescribed layout and format with a list of questions and time for answers. Instead, some researchers choose to make the interview process more comfortable and informal by simply engaging in a conversation with audience members. When conducting interviews, ask open-ended questions that allow for detailed responses instead of just "yes" or "no."

Focus Groups

One of the most common methods of qualitative research is hosting a focus group. In this method, you will organize a group of people and share information about your product or service, campaign and marketing ideas, and development. As the participants of the focus group view the information presented, you can gauge their reactions through body language, facial expressions, and actual feedback that they provide. Hosting focus groups in virtual settings is becoming more popular, thanks to technological advancements, but doing so can make it harder to see facial expressions and read body language.

When bringing people together to participate in a focus group, it's important to make sure that all participants have something in common. You might choose to divide groups by age, gender, or other factors. When you split them into more targeted groups, you can get more information that will help you better understand your audience . Most focus group hosts offer some type of compensation for participation, such as a free product, gift card, voucher, coupon, or even cash.

Quantitative Research

Quantitative research typically focuses on statistics and hard facts instead of opinions and feelings. For a better understanding of your audience, it's helpful to use methods that fall under this category when conducting both primary and secondary research. Examples of quantitative research include social media analytics, surveys/questionnaires, and trials with experimentation.

Social Media Analytics

In today's online world, social media is a critical area when researching your audience. Companies can reach millions of people with a single post, something that was never previously within reach. But simply sharing posts without following up on how they are performing is a waste of time and resources. Analytics are built into most social media platforms and allow users to view how many people viewed a post, as well as any interaction with the content, such as clicks and responses.

Using the information provided can help your company learn what type of content resonates with your target audience. By viewing what they choose to interact with, you can then create additional content that complements those topics. New jobs are popping up across the country , and they require experience in and an understanding of social media analytics.

Surveys and Questionnaires

Surveys and questionnaires are old-school methods of quantitative research that still work. Whether you conduct a follow-up survey by phone or email or slip a flyer into the bag of every customer who visits your store, you can get information from real buyers or users of your product. Using this information can help you improve the product or service as well as customer service techniques and the overall customer experience.

Secondary Research

Secondary research involves reviewing information presented from other sources. If your company has conducted primary research on other products or service, you might use that data for developing and improving new products and services. Some businesses also rely on external sources to present data.

If you're simply relying on the internet for market research, it may be time to reevaluate your strategy. The online world is certainly useful as a starting point but should not be the only method by which you conduct research. Talking to your customers and understanding their unique perspectives is critical to improving the way you speak to them and market your products. Keep in mind that it would be a mistake to rely on just one research method instead of employing several different ones.

If you are interested in understanding and working in market research for audience analysis, you may want to consider your advanced education options. The online Masters in Communication Management , offered by the Annenberg School for Communication and Journalism, includes courses that focus on research methods and how to improve audience engagement through understanding their thoughts and feelings.

Sources https://www.cleverism.com/market-research-techniques-primary-secondary/ https://www.entrepreneur.com/article/270131 http://study.com/academy/lesson/informal-and-formal-methods-of-audience-analysis.html http://study.com/academy/lesson/gathering-information-for-audience-analysis-research-observation.html

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