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

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

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

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

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

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

Table of contents

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

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

Common uses of survey research include:

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

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

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

Populations

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

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

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

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

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

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

There are two main types of survey:

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

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

Questionnaires

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

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

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

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

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

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

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

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

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

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

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

Open-ended vs closed-ended questions

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

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

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

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

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

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

The content of the survey questions

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

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

Phrasing the survey questions

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

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

Ordering the survey questions

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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How to Write a Survey Paper: A stepwise Guide with Examples

How to Write a Survey Paper

Some of you may be wondering what a survey paper is. A survey paper contains the interpretation that has been drawn by the author after they have reviewed and analyzed various research papers that are centered on a specific topic. Those research papers should be already published.

Now that we have understood what a survey paper is, let us explore the various steps that have to be taken when coming up with a survey paper. As noted, a survey paper lists and analyzes the most recent research work in a particular area of study.

To write a good survey paper, you need to research the representative papers, come up with a title, a good abstract, and writing the introduction, the body, and conclusions that reflect the findings as well as the challenges of the study.

To do this, there is a challenge of research. As such, the first challenge is to find the most recent and appropriate research papers for the topic. The 9 steps below should be followed when writing a survey paper.

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Step 1: selecting the representative papers.

The first step when writing a survey paper is selecting the most relevant representative papers that are within the scope of your research and summarizing them effectively. As you will note, there can be a lot of research papers, and the space required to create a survey paper is limited.

During such, it can be challenging when trying to pick the key work within the scope of your study.

As an author of the survey paper, you will have to read the research papers’ abstracts and conclusions and pick the subset that captures your area of study.

To ensure that the selected research papers are appropriate or relevant, they should be recent, contain more citations, and be published in journals with a high reputation.

The research papers should not be less than 10.

Step 2: Coming up with an Appropriate Title

The second step is coming up with a captivating title that provides a clear summary of your paper’s contents. As such, the title should be clear and brief. To achieve this, the title should utilize active verbs rather than complex phrases that are based on nouns. 

A good title of your survey paper should contain between 10 and 12 words because a title with more words will divert the attention of the readers from the central point.

A longer title will also appear unfocused. Therefore, the title should have the keywords of your survey paper in such a way that it defines the study’s nature. 

Step 3: Creating an Abstract

Another important step to be taken when writing a survey paper is to create an abstract. The abstract acts as a summary of your survey paper.

It should provide a summary of the problem that has been investigated, the methods used, the results of the study, and the conclusion.

Abstracts summarize the most important contents of your survey paper in a single paragraph of between 200 and 300 words.

When creating an abstract, make sure that it contains or highlights the key points while convincing the readers or the target audience to continue reading the whole survey paper. Should always include an abstract in your survey paper.

Step 4: Listing Key Terms

While the keywords help the target audience or other researchers understand the field of the survey paper, the subfield, research issue, the topic, and so on, the main purpose of this section is to help readers or researchers locate your paper when they are doing searches on the topic.

Most of the databases, electronic search engines such as Google, and journal websites will utilize keywords when deciding whether to display the survey paper to interested readers and when this should be done.

With the proper keywords, your survey paper will be more searchable and it will be cited by more researchers because it can be easily located. 

Step 5: Writing the Introduction

The next step when writing a survey paper is to include a good introduction.

A good introduction paragraph will explain to the target readers how the research problem has been tackled by the research papers that you have included in your paper.

The introduction should arouse the readers’ interest in knowing more about the topic and the research domain. If they are interested, they will continue reading your survey paper.

Unlike the abstract, the introduction within a survey paper does not contain a very strict word limit. However, it should be concise because it introduces the paper’s topic, provides a broader context of the study, and gradually narrows the scope down to the research problem. 

Therefore, make sure that your introduction sets a scene and contextualizes your paper. It can begin with a historical narrative bringing the narrative to the present day and ending with a research question. Ensure that the very last sentence of your introduction is the thesis statement. 

Step 6: Providing the Approaches Used in the Survey Paper

This is a very important step in any survey paper. This is where you are required to provide the methodologies used to conduct your research or survey in a logical order.

You are required to logically move from one method to the next as you clearly define each approach at the beginning of every section.

To ensure that your readers are at par with you, you should share the motivation behind each methodology. This is achieved by giving a high-level summary of every approach and then narrowing it down to the specific approaches.

You should also demonstrate the applicability and the practicability of every approach used in the research, and the areas that need to be improved. You should graphically visualize at least one method used. 

Step 7: Writing About the Paper Surveys

This step should take the bulk of your survey paper because it is the point where you survey the papers you have selected. Here, you should decide what you are going to inform your readers about each research paper.

Therefore, it is important to first read the research papers in a manner that you can know what to inform your readers about them.

For each research paper, make sure that you tell your readers about their research direction. Also, ensure that you identify the algorithms or mathematical techniques the research papers rely on and whether they are application or theory papers. 

You should also state whether the selected research papers are an improvement on other works or they are a continuation of other works.

Then, state whether the research papers utilize simulations, theoretical proofs, real-life deployment, and so on. Finally, you should state the strengths and weaknesses of each research paper, authors’ claims, and assumptions. 

Step 8: Research Challenges

After surveying every research paper you have utilized, the next step is to state the challenges you encountered while conducting research.

When writing a survey paper, you will always face various challenges.

Such challenges can be finding the best or most appropriate research papers, comparing them to determine their strengths, and so on.

Other challenges can arise from the research papers themselves. This can include their delivery of results. Some research papers will contain confusing data. 

Step 9: Coming up with a Conclusion

Finally, the conclusion should answer the questions that have been raised by your survey paper’s objectives and goals.

Though it should be interesting and captivating, it should still be presented academically. It should be objective and offer a final say concerning the survey’s subject. 

The conclusion should synthesize the results by proving their interpretation, propose the course of action as per the results, and offer solutions to the issues that have been identified.

The reader should be capable of understanding the whole survey paper by reading the conclusion. Therefore, ensure that your conclusion synthesizes your paper. 

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Tips When Writing a Good Survey Paper

The first tip in writing a good survey paper is to select the most appropriate and latest research papers that will be used in the paper. This is a very important tip because the survey paper will be completely based on them. Old research papers will render your survey paper useless.

Research papers that are not within the scope of your research or topic will also render the survey paper useless.

The second tip is to make sure that you come up with a concise topic that will summarize what your paper is about.

It is also very important to follow the appropriate format of a survey paper.

The format, after you have written your title, should be abstract, key terms, introduction, approaches or methodologies, conducting surveys for every paper used, research challenges, and finally the conclusion.

Another important tip is to utilize more than 10 research papers for the survey. Then can be even more than 20 depending on the scope of your study. The more the research papers used in your survey paper, the more professional and credible it will appear. 

It should be noted that a good survey paper will utilize research papers that are recent (not more than 5 years) and have more academic sources.

To increase the credibility of your survey paper, the research papers used should come from reputable journal sources or publications. In our guide to writing good research papers , we explained more about references. Check it out.

Also, note that the process of writing a survey paper is much different from that of writing an issue paper or doing opinion essays . Therefore, each step needs to relate to the survey.

15 Examples of Topics for Writing a Survey Paper

• Advances in leaf image analysis for bacterial disease detection
• A survey on the impact of social media among youths in the united states
• A Survey on leaf image analysis for bacterial disease detection
• Recent trends in the electric cars manufacturing industry
• Recent trends in perinatal care: Exploring the major causes of perinatal mortality
• Leaf image analysis for bacterial disease detection
• Advances in curriculum-based education: A survey on educational trends in sub-Saharan Africa
• Recent trends in environmental awareness campaigns in low-income countries
• A survey on COVID-19 pandemic impact on the united states economy
• Recent trends in the immunization approach taken by third world countries after the second and third wave of COVID-19 disease
• Advances in semiconductor manufacturing for BMW electronic cars
• A survey on the impact of 5-G connectivity among SMEs in Britain
• Recent trends in the space race: A survey of how the founders of Virgin Atlantic, Tesla, and Amazon are competing to dominate space travel 
• Advances in care for pressure ulcers: A survey on the impact of frequent automated turning on older immobile patients in Germany
• A survey on the impact of geopolitics on peace within the Middle East 

Josh Jasen or JJ as we fondly call him, is a senior academic editor at Grade Bees in charge of the writing department. When not managing complex essays and academic writing tasks, Josh is busy advising students on how to pass assignments. In his spare time, he loves playing football or walking with his dog around the park.

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How to Write a Survey Paper: Brief Overview

Every student wishes there was a shortcut to learning about a subject. Writing a survey paper can be an effective tool for synthesizing and consolidating information on a particular topic to gain mastery over it.

There are several techniques and best practices for writing a successful survey paper. Our team is ready to guide you through the writing process and teach you how to write a paper that will benefit your academic and professional career.

What is a Survey Paper

A survey paper is a type of academic writing that aims to give readers a comprehensive understanding of the current state of research on a particular topic. By synthesizing and analyzing already existing research, a survey paper provides good shortcuts highlighting meaningful achievements and recent advances in the field and shows the gaps where further research might be needed.

The survey paper format includes an introduction that defines the scope of the research domain, followed by a thorough literature review section that summarizes and critiques existing research while showcasing areas for further research. A good survey paper must also provide an overview of commonly used methodologies, approaches, key terms, and recent trends in the field and a clear summary that synthesizes the main findings presented.

Our essay writing service team not only provides the best survey paper example but can also write a custom academic paper based on your specific requirements and needs.

How to Write a Survey Paper: Important Steps

If you have your head in your hands, wondering how to write a survey paper, you must be new here. Luckily, our team of experts got you! Below you will find the steps that will guide you to the best approach to writing a successful survey paper. No more worries about how to research a topic . Let's dive in!

Obviously, the first step is to choose a topic that is both interesting to you and relevant to a large audience. If you are struggling with topic selection, go for only the ones that have the most literature to compose a comprehensive research paper.

Once you have selected your topic, define the scope of your survey paper and the specific research questions that will guide your literature review. This will help you establish boundaries and ensure that your paper is focused and well-structured.

Next, start collecting existing research on your topic through various academic databases and literature reviews. Make sure you are up to date with recent discoveries and advances. Before selecting any work for the survey, make sure the database is credible. Determine what sources are considered trustworthy and reputable within the specific domain.

Continue survey paper writing by selecting the most relevant and significant research pieces to include in your literature overview. Make sure to methodically analyze each source and critically evaluate its relevance, rigor, validity, and contribution to the field.

At this point, you have already undertaken half of the job. Maybe even more since collecting and analyzing the literature is often the most challenging part of writing a survey paper. Now it's time to organize and structure your paper. Follow the well-established outline, give a thorough review, and compose compelling body paragraphs. Don't forget to include detailed methodology and highlight key findings and revolutionary ideas.

Finish off your writing with a powerful conclusion that not only summarizes the key arguments but also indicates future research directions.

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Survey Paper Outline

The following is a general outline of a survey paper.

• Introduction - with background information on the topic and research questions
• Literature Overview - including relevant research studies and their analysis
• Methodologies and Approaches - detailing the methods used to collect and analyze data in the literature overview
• Findings and Trends - summarizing the key findings and trends from the literature review
• Challenges and Gaps - highlighting the limitations of studies reviewed
• Future Research Direction - exploring future research opportunities and recommendations
• Conclusion - a summary of the research conducted and its significance, along with suggestions for further work in this area.
• References - a list of all the sources cited in the paper, including academic articles and reports.

You can always customize this outline to fit your paper's specific requirements, but none of the components can be eliminated. Our custom essay writer

Further, we can explore survey paper example formats to get a better understanding of what a well-written survey paper looks like. Our custom essay writer can assist in crafting a plagiarism-free essay tailored to meet your unique needs.

Survey Paper Format

Having a basic understanding of an outline for a survey paper is just the beginning. To excel in survey paper writing, it's important to become proficient in academic essay formatting techniques. Have the following as a rule of thumb: make sure each section relates to the others and that the flow of your paper is logical and readable.

Title - You need to come up with a clear and concise title that reflects the main objective of your research question.

Survey paper example title: 'The analysis of recommender systems in E-commerce.'

Abstract - Here, you should state the purpose of your research and summarize key findings in a brief paragraph. The abstract is a shortcut to the paper, so make sure it's informative.

Introduction - This section is a crucial element of an academic essay and should be intriguing and provide background information on the topic, feeding the readers' curiosity.

Literature with benefits and limitations - This section dives into the existing literature on the research question, including relevant studies and their analyses. When reviewing the literature, it is important to highlight both benefits and limitations of existing studies to identify gaps for future research.

Result analysis - In this section, you should present and analyze the results of your survey paper. Make sure to include statistical data, graphs, and charts to support your conclusions.

Conclusion - Just like in any other thesis writing, here you need to sum up the key findings of your survey paper. How it helped advance the research topic, what limitations need to be addressed, and important implications for future research.

Future Research Direction - You can either give this a separate section or include it in a conclusion, but you can never overlook the importance of a future research direction. Distinctly point out areas of limitations and suggest possible avenues for future research.

References - Finally, be sure to include a list of all the sources/references you've used in your research. Without a list of references, your work will lose all its credibility and can no longer be beneficial to other researchers.

Writing a Good Survey Paper: Helpful Tips

After mastering the basics of how to write a good survey paper, there are a few tips to keep in mind. They will help you advance your writing and ensure your survey paper stands out among others.

Select Only Relevant Literature

When conducting research, one can easily get carried away and start hoarding all available literature, which may not necessarily be relevant to your research question. Make sure to stay within the scope of your topic. Clearly articulate your research question, and then select only literature that directly addresses the research question. A few initial readings might not reveal the relevance, so you need a systematic review and filter of the literature that is directly related to the research question.

Use Various Sources and Be Up-to-Date

Our team suggests only using up-to-date material that was published within the last 5 years. Additional sources may be used if they contribute significantly to the research question, but it is important to prioritize current literature.

Use more than 10 research papers. Though narrowing your pool of references to only relevant literature is important, it's also crucial that you have a sufficient number of sources.

Rely on Reputable Sources

Writing a survey paper is a challenge. Don't forget that it is quality over quantity. Be sure to choose reputable sources that have been peer-reviewed and are recognized within your field of research. Having a large number of various research papers does not mean that your survey paper is of high quality.

Construct a Concise Research Question

Having a short and to-the-point research question not only helps the audience understand the direction of your paper but also helps you stay focused on a clear goal. With a clear research question, you will have an easier time selecting the relevant literature, avoiding unnecessary information, and maintaining the structure of your paper.

Use an Appropriate Format

The scholarly world appreciates when researchers follow a standard format when presenting their survey papers. Therefore, it is important to use a suitable and consistent format that adheres to the guidelines provided by your academic institution or field.

Our paper survey template offers a clear structure that can aid in organizing your thoughts and sources, as well as ensuring that you cover all the necessary components of a survey paper.

Don't forget to use appropriate heading, font, spacing, margins, and referencing style. If there is a strict word limit, be sure to adhere to it and use concise wording.

Use Logical Sequence

A survey paper is different from a regular research paper. Every element of the essay needs to relate to the research question and tie into the overall objective of the paper.

Writing research papers takes a lot of effort and attention to detail. You will have to revise, edit and proofread your work several times. If you are struggling with any aspect of the writing process, just say, ' Write my research paper for me ,' and our team of tireless writers will be happy to assist you.

Starting Point: Survey Paper Example Topics

Learning how to write a survey paper is important, but it is only one aspect of the process.

Now you need a powerful research question. To help get you started, we have compiled a list of survey paper example topics that may inspire you.

• Survey of Evolution and Challenges of Electronic Search Engines
• A Comprehensive Survey Paper on Machine Learning Algorithms
• Survey of Leaf Image Analysis for Plant Species Recognition
• Advances in Natural Language Processing for Sentiment Analysis
• Emerging Trends in Cybersecurity Threat Detection
• A Comprehensive Survey of Techniques in Big Data Analytics in Healthcare
• A Survey of Advances in Digital Art and Virtual Reality
• A Systematic Review of the Impact of Social Media Marketing Strategies on Consumer Behavior
• A Survey of AI Systems in Artistic Expression
• Exploring New Research Methods and Ethical Considerations in Anthropology
• Exploring Data-driven Approaches for Performance Analysis and Decision Making in Sports
• A Survey of Benefits of Optimizing Performance through Diet and Supplementation
• A Critical Review of Existing Research on The Impact of Climate Change on Biodiversity Conservation Strategies
• Investigating the Future of Blockchain Technology for Secure Data Sharing
• A Critical Review of the Literature on Mental Health and Innovation in the Workplace

Final Thoughts

Next time you are asked to write a survey paper, remember it is not just following an iterative process of gathering and summarizing existing research; it requires a deep understanding of the subject matter as well as critical analysis skills. Creative thinking and innovative approaches also play a key role in producing high-quality survey papers.

Our expert writers can help you navigate the complex process of writing a survey paper, from topic selection to data analysis and interpretation.

Finding It Difficult to Write a Survey Paper?

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Are you looking for advice on how to create an engaging and informative survey paper? This frequently asked questions (FAQ) section offers valuable responses to common inquiries that researchers frequently come across when writing a survey paper. Let's delve into it!

What is Survey Paper in Ph.D.?

What is the difference between survey paper and literature review paper, related articles.

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Survey Research: Definition, Examples and Methods

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

LEARN ABOUT: Behavioral Research

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

Survey Research Definition

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

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

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

LEARN ABOUT: Survey Sampling

Survey Research Methods

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

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

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

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

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

LEARN ABOUT: Survey Sample Sizes

The various non-probability sampling techniques are :

• Convenience sampling
• Snowball sampling
• Consecutive sampling
• Judgemental sampling
• Quota sampling

Process of implementing survey research methods:

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

LEARN ABOUT: System Usability Scale

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

LEARN ABOUT:  Testimonial Questions

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

Reasons to conduct survey research

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

LEARN ABOUT: Research Process Steps

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

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

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

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

Survey Research Scales

There are four main scales for the measurement of variables:

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

Benefits of survey research

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

Other benefits of survey research are:

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

Survey research design

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

There are five stages of survey research design:

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

Survey examples: 10 tips to design the perfect research survey

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

Below are 10 Tips To Design The Perfect Research Survey:

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

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

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

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Survey Research — Types, Methods and Example Questions

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

Table Content

Survey research.

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

What is survey research?

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

Why is survey research important?

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

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

Types of survey research

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

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

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

Survey research and data collection methods

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

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

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

Advantages and disadvantages of survey research

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

Advantages:

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

Disadvantages:

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

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

Limitations of survey research

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

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

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

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

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

•   Create surveys in 40+ languages
•   Unlimited number of users
•   Ready-to-go survey templates
•   So much more...

Survey research design

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

Approach and Strategy

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

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

9 Tips on Building the Perfect Survey Research Questionnaire

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

Survey research examples and questions

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

User Experience (UX)

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

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

• "On a scale of 1 to 10, how would you rate the ease of navigating our app?"
• "How often do you encounter difficulties while using our app?"
• "What features do you use most frequently in our app?"
• "What improvements would you suggest for our app?"
• "What features would you like to see in future updates?"

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

Psychology and Ethics in survey research

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

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

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

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

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

Survey research software

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

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

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

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

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

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

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

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A Comprehensive Guide to Survey Research Methodologies

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

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

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

What is Survey Research

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

Brief History of Survey Research

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

-       First Era (1930-1960)

-       Second Era (1960-1990)

-       Third Era (1990 onwards)

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

Survey Research Methods & Types

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

Surveys based on Objective

Exploratory survey research.

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

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

Predictive Survey Research

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

Descriptive Survey Research

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

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

Survey Research Types based on Concept Testing

Monadic concept testing.

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

Sequential Monadic Concept Testing

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

Based on Data Source

Primary data.

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

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

Secondary Data

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

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

Based on Research Method

Quantitative research.

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

Qualitative Research

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

Based on Deployment Method

Online surveys.

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

Paper or Print Surveys

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

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

Telephonic Surveys

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

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

One-on-one Surveys

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

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

Based on Distribution

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

Buy Survey Responses

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

Embedding Survey on a Website

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

Post the Survey on Social Media

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

Based on Frequency of Deployment

Cross-sectional studies.

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

Longitudinal Surveys

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

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

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

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

Retrospective Survey

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

Why Should You Conduct Research Surveys?

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

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

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

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

Common Uses of a Survey

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

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

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

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

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

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

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

6 Steps to Conduct Survey Research

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

Step 1: Objective of the Survey

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

Step 2: Number of Questions

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

Step 3: Language and Voice of Questions

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

Step 4: Type of Questions

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

Step 5: User Experience

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

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

Step 6: Survey Logic

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

How to Effectively Use Survey Research with Starlight Analytics

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

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

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

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

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Home » Survey Research – Types, Methods, Examples

Survey Research – Types, Methods, Examples

Table of Contents

Survey Research

Definition:

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

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

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

Survey Research Methods

Survey Research Methods are as follows:

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

Types of Survey Research

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

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

Types Based on Methodology

Based on Methodology Survey are divided into two Types:

Quantitative Survey Research

Qualitative survey research.

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

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

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

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

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

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

Data Analysis Methods

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

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

Applications of Survey Research

Here are some common applications of survey research:

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

Examples of Survey Research

Here are some real-time examples of survey research:

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

Survey Sample

Purpose of survey research.

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

Here are some common purposes of survey research:

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

When to use Survey Research

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

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

How to Conduct Survey Research

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

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

Advantages of Survey Research

There are several advantages to using survey research, including:

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

Limitations of Survey Research

Here are some of the main limitations of survey research:

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

Following is an example of a Survey Sample:

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

1. What is your age?

• A) Under 18
• G) 65 or older

2. What is your highest level of education completed?

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

3. What is your current employment status?

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

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

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

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

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

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

• A) Excellent
• E) Very poor

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

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

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

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

10. Any additional comments or suggestions?

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

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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Survey Research Design: Definition, How to Conduct a Survey & Examples

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Survey research is a quantitative research method that involves collecting data from a sample of individuals using standardized questionnaires or surveys. The goal of survey research is to measure the attitudes, opinions, behaviors, and characteristics of a target population. Surveys can be conducted through various means, including phone, mail, online, or in-person.

If your project involves live interaction with numerous people in order to obtain important data, you should know the basic rules of survey research beforehand. Today we’ll talk about this research type, review the step-by-step guide on how to do a survey research and try to understand main advantages and potential pitfalls. The following important questions will be discussed below:

• Purpose and techniques of information collection.
• Kinds of responses.
• Analysis techniques, assumptions, and conclusions.

Do you wish to learn best practices of survey conducting? Stay with our research paper service and get prepared for some serious reading!

What Is Survey Research: Definition

Let’s define the notion of survey research first. It revolves around surveys you conduct to retrieve certain data from your respondents. The latter is to be carefully selected from some population that for particular reasons possess the data necessary for your research. For example, they can be witnesses of some event that you should investigate. Surveys contain a set of predefined questions, closed- or open-ended. They can be sent to participants who would answer them and thus provide you with data for your research. There are many methods for organizing surveys and processing the obtained information.

Purpose of Survey Research Design

Purpose of survey research is to collect proper data and thus get insights for your research. You should pick participants with relatable experience. It should be done in order to get relevant information from them. Questions in your survey should be formulated in a way that allows getting as much useful data as possible. The format of a survey should be adjusted to the situation. It will ensure your respondents will be ready to give their answers. It can be a questionnaire sent over email or questions asked during a phone call.

Surveys Research Methods

Which survey research method to choose? Let’s review the most popular approaches and when to use them. There are two critical factors that define how a survey will be conducted

• Tool to send questions
• online: using web forms or email questionnaires.
• phone: reaching out to respondents individually. Sometimes using an automated service.
• face-to-face: interviewing respondents in the real world. This makes room for more in-depth questions.
• Time to conduct research
• short-term periods.
• long-term periods.

Let’s explore the time-related methods in detail.

Cross-Sectional Survey Design Research

The first type is cross sectional survey research. Design of this survey type includes collecting various insights from an audience within a specific short time period. It is used for descriptive analysis of a subject. The purpose is to provide quick conclusions or assumptions. Which is why this approach relies on fast data gathering and processing techniques.  Such surveys are typically implemented in sectors such as retail, education, healthcare etc, where the situation tends to change fast. So it is important to obtain operational results as soon as possible.

Longitudinal Survey Research

Let’s talk about survey research designs . Planning a design beforehand is crucial. It is crucial in case you are pressed on time or have a limited budget. Collecting information using a properly designed survey research is typically more effective and productive compared with a casually conducted study.  Preparation of a survey design includes the following major steps:

• Understand the aim of your research. So that you can better plan the entire path of a survey and avoid obvious issues.
• Pick a good sample from a population. Ensure precision of the results by selecting members who could provide useful insights and opinions.
• Review available research methods. Decide about the one most suitable for your specific case.
• Prepare a questionnaire. Selection of questions would directly affect the quality of your longitudinal analysis . So make sure to pick good questions. Also, avoid unnecessary ones to save time and counter possible errors.
• Analyze results and make conclusions.

Advantages of Survey Research

As a rule, survey research involves getting data from people with first-hand knowledge about the research subject. Therefore, when formulated properly, survey questions should provide some unique insights and thus describe the subject better. Other benefits of this approach include:

• Minimum investment. Online and automated call services require very low investment per respondent.
• Versatile sources. Data can be collected by numerous means, allowing more flexibility.
• Reliable for respondents. Anonymous surveys are secure. Respondents are more likely to answer honestly if they understand it will be confidential.

Types of Survey Research

Let’s review the main types of surveys. It is important to know about most popular templates. So that you wouldn’t have to develop your own ones from scratch for your specific case. Such studies are usually categorized by the following aspects:

• Objectives.
• Data source.
• Methodology.

We’ll examine each of these aspects below, focusing on areas where certain types are used. 

Types of Survey Research Depending on Objective

Depending on your objective and the specifics of the subject’s context, the following survey research types can be used:

• Predictive This approach foresees asking questions that automatically predict the best possible response options based on how they are formulated. As a result, it is often easier for respondents to provide their answers as they already have helpful suggestions.
• Exploratory This approach is focused more on the discovery of new ideas and insights rather than collecting statistically accurate information. The results can be difficult to categorize and analyze. But this approach is very useful for finding a general direction for further research.
• Descriptive This approach helps to define and describe your respondents' opinions or behavior more precisely. By predefining certain categories and designing survey questions, you obtain statistical data. This descriptive research approach is often used at later research stages. It is used in order to better understand the meaning of insights obtained at the beginning.

Types of Survey Research Depending on Data Source

The following research survey types can be defined based on which sources you obtain the data from:

• Primary In this case, you collect information directly from the original source, e.g., learn about a natural disaster from a survivor. You aren’t using any intermediary instances. And, as a result, don't get any information twisted or lost on its way. This is the way to obtain the most valid and trustworthy results. But at the same time, it is often not so easy to access such sources.
• Secondary This involves collecting data from existing research on the same subject that has been published. Such information is easier to access. But at the same time, it is usually too general and not tailored for your specific needs.

Types of Survey Research Depending on Methodology

Finally, let’s review survey research methodologies based on the format of retrieved and processed data. They can be:

• Quantitative An approach that focuses on gathering numeric or measurable data from respondents. This provides enough material for statistical analysis. And then leads to some meaningful conclusions. Collection of such data requires properly designed surveys that include numeric options. It is important to take precautions to ensure that the data you’ve gathered is valid.
• Qualitative Such surveys rely on opinions, impressions, reflections, and typical reactions of target groups. They should include open-ended questions to allow respondents to give detailed answers. It allows providing information that they consider most relevant. Qualitative research is used to understand, explain or evaluate some ideas or tendencies.

It is essential to differentiate these two kinds of research. That's why we prepared a special blog, which is about quantitative vs qualitative research .

How to Conduct a Survey Research: Main Steps

Now let’s find out how to do a survey step by step. Regardless of methods you use to design and conduct your survey, there are general guidelines that should be followed. The path is quite straightforward: 

• Assess your goals and options for accessing necessary groups.
• Formulate each question in a way that helps you obtain the most valuable data.
• Plan and execute the distribution of the questions.
• Process the results.

Let’s take a closer look at all these stages.

Step 1. Create a Clear Survey Research Question

Each survey research question should add some potential value to your expected results. Before formulating your questionnaire, it is better to invest some time analyzing your target populations. This will allow you to form proper samples of respondents. Big enough to get some insights from them but not too big at the same time. A good way to prepare questions is by constructing case studies for your subject. Analyzing case study examples in detail will help you understand which information about them is necessary.

Step 2. Choose a Type of Survey Research

As we’ve already learned, there are several different types of survey research. Starting with a close analysis of your subject, goals and available sources will help you understand which kinds of questions are to be distributed.  As a researcher, you’ll also need to analyze the features of the selected group of respondents. Pick a type that makes it easier to reach out to them. For example, if you should question a group of elderly people, online forms wouldn’t be efficient compared with interviews.

Step 3. Distribute the Questionnaire for Your Survey Research

The next step of survey research is the most decisive one. Now you should execute the plan you’ve created earlier. And then conduct the questioning of the entire group that was selected. If this is a group assignment, ask your colleagues or peers for help. Especially if you should deal with a big group of respondents. It is important to stick to the initial scenario but leave some room for improvisation in case there are difficulties with reaching out to respondents. After you collect all necessary responses, this data can be processed and analyzed.

Step 4. Analyze the Results of Your Research Survey

The data obtained during the survey research should be processed. So that you can use it for making assumptions and conclusions. If it is qualitative, you should conduct a thematic analysis to find important ideas and insights that could confirm your theories or expand your knowledge of the subject. Quantitative data can be analyzed manually or with the help of some program. Its purpose is to extract dependencies and trends from it to confirm or refute existing assumptions.

Step 5. Save the Results of Your Survey Research

The final step is to compose a survey research paper in order to get your results ordered. This way none of them would be lost especially if you save some copies of the paper. Depending on your assignment and on which stage you are at, it can be a dissertation, a thesis or even an illustrative essay where you explain the subject to your audience.  Each survey you’ve conducted must get a special section in your paper where you explain your methods and describe your results.

Survey Research Example

We have got a few research survey examples in case you would need some real world cases to illustrate the guidelines and tips provided above. Below is a sample research case with population and the purposes of researchers defined.

Survey Research: Key Takeaways

Today, we have explored the research survey notion and reviewed the main features of this research activity and its usage in the social sciences topics . Important techniques and tips have been reviewed. A step by step guide for conducting such studies has also been provided.

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Example of survey research design The Newtown Youth Initiative will conduct a qualitative survey to develop a program to mitigate alcohol consumption by adolescent citizens of Newtown. Previously, cultural anthropology research was performed for studying mental constructs to understand young people's expectations from alcohol and their views on specific cultural values. Based on its results, a survey was designed to measure expectancies, cultural orientation among the adolescent population. A secure web page has been developed to conduct this survey and ensure anonymity of respondents. The Newtown Youth Initiative will partner with schools to share the link to this page with students and engage them to participate. Statistical analysis of differences in expectancies and cultural orientation between drinkers and non-drinkers will be performed using the data from this survey.

Frequently Asked Questions About Survey Research

1. what is a market research survey.

A market research survey can help a company understand several aspects of their target market. It typically involves picking focus groups of customers and asking them questions in order to learn about demand for specific products or services and understand whether it grows. Such feedback would be crucial for a company’s development. It can help it to plan its further strategic steps.

2. How does survey research differ from experimental research methods?

The main difference between experiment and survey research is that the latter means field research, while experiments are typically performed in laboratory conditions. When conducting surveys, researchers don’t have full control on the process and should adapt to the specific traits of their target groups in order to obtain answers from them. Besides, results of a study might be harder to quantify and turn into statistical values.

4. What is the difference between survey research and descriptive research?

The purpose of descriptive studies is to explain what the subject is and which features it has. Survey research may include descriptive information but is not limited by that. Typically it goes beyond descriptive statistics and includes qualitative research or advanced statistical methods used to draw inferences, find dependencies or build trends. On the other hand, descriptive methods don’t necessarily include questioning respondents, obtaining information from other sources.

3. What is good sample size for a survey?

It always depends on a specific case and researcher’s goals. However, there are some general guidelines and best practices for this activity. Good maximum sample size is usually around 10% of the population, as long as this does not exceed 1000 people. In any case, you should be mindful of your time and budget limitations when planning your actions. In case you’ve got a team to help you, it might be possible to process more data.

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Designing, Conducting, and Reporting Survey Studies: A Primer for Researchers

Olena zimba.

1 Department of Clinical Rheumatology and Immunology, University Hospital in Krakow, Krakow, Poland.

2 National Institute of Geriatrics, Rheumatology and Rehabilitation, Warsaw, Poland.

3 Department of Internal Medicine N2, Danylo Halytsky Lviv National Medical University, Lviv, Ukraine.

Armen Yuri Gasparyan

4 Departments of Rheumatology and Research and Development, Dudley Group NHS Foundation Trust (Teaching Trust of the University of Birmingham, UK), Russells Hall Hospital, Dudley, UK.

Survey studies have become instrumental in contributing to the evidence accumulation in rapidly developing medical disciplines such as medical education, public health, and nursing. The global medical community has seen an upsurge of surveys covering the experience and perceptions of health specialists, patients, and public representatives in the peri-pandemic coronavirus disease 2019 period. Currently, surveys can play a central role in increasing research activities in non-mainstream science countries where limited research funding and other barriers hinder science growth. Planning surveys starts with overviewing related reviews and other publications which may help to design questionnaires with comprehensive coverage of all related points. The validity and reliability of questionnaires rely on input from experts and potential responders who may suggest pertinent revisions to prepare forms with attractive designs, easily understandable questions, and correctly ordered points that appeal to target respondents. Currently available numerous online platforms such as Google Forms and Survey Monkey enable moderating online surveys and collecting responses from a large number of responders. Online surveys benefit from disseminating questionnaires via social media and other online platforms which facilitate the survey internationalization and participation of large groups of responders. Survey reporting can be arranged in line with related recommendations and reporting standards all of which have their strengths and limitations. The current article overviews available recommendations and presents pointers on designing, conducting, and reporting surveys.

INTRODUCTION

Surveys are increasingly popular research studies that are aimed at collecting and analyzing opinions of diverse subject groups at certain periods. Initially and predominantly employed for applied social science research, 1 surveys have maintained their social dimension and transformed into indispensable tools for analyzing knowledge, perceptions, prevalence of clinical conditions, and practices in the medical sciences. 2 In rapidly developing disciplines with social dimensions such as medical education, public health, and nursing, online surveys have become essential for monitoring and auditing healthcare and education services 3 , 4 and generating new hypotheses and research questions. 5 In non-mainstream science countries with uninterrupted Internet access, online surveys have also been praised as useful studies for increasing research activities. 6

In 2016, the Medical Subject Headings (MeSH) vocabulary of the US National Library of Medicine introduced "surveys and questionnaires" as a structured keyword, defining survey studies as "collections of data obtained from voluntary subjects" ( https://www.ncbi.nlm.nih.gov/mesh/?term=surveys+and+questionnaires ). Such studies are instrumental in the absence of evidence from randomized controlled trials, systematic reviews, and cohort studies. Tagging survey reports with this MeSH term is advisable for increasing the retrieval of relevant documents while searching through Medline, Scopus, and other global databases.

Surveys are relatively easy to conduct by distributing web-based and non-web-based questionnaires to large groups of potential responders. The ease of conduct primarily depends on the way of approaching potential respondents. Face-to-face interviews, regular postmails, e-mails, phone calls, and social media posts can be employed to reach numerous potential respondents. Digitization and social media popularization have improved the distribution of questionnaires, expanded respondents' engagement, facilitated swift data processing, and globalization of survey studies. 7

SURVEY REPORTING GUIDANCE

Despite the ease of survey studies and their importance for maintaining research activities across academic disciplines, their methodological quality, reproducibility, and implications vary widely. The deficiencies in designing and reporting are the main reason for the inefficiency of some surveys. For instance, systematic analyses of survey methodologies in nephrology, transfusion medicine, and radiology have indicated that less than one-third of related reports provide valid and reliable data. 8 , 9 , 10 Additionally, no discussions of respondents' representativeness, reasons for nonresponse, and generalizability of the results have been pinpointed as drawbacks of some survey reports. The revealed deficiencies have justified the need for survey designing and data processing in line with reporting recommendations, including those listed on the EQUATOR Network website ( https://www.equator-network.org/ ).

Arguably, survey studies lack discipline-specific and globally-acceptable reporting guidance. The diversity of surveyed subjects and populations is perhaps the main confounder. Although most questionnaires contain socio-demographic questions, there are no reporting guidelines specifically tailored to comprehensively inquire specialists across different academic disciplines, patients, and public representatives.

The EQUATOR Network platform currently lists some widely promoted documents with statements on conducting and reporting web-based and non-web-based surveys ( Table 1 ). 11 , 12 , 13 , 14 The oldest published recommendation guides on postal, face-to-face, and telephone interviews. 1 One of its critical points highlights the need to formulate a clear and explicit question/objective to run a focused survey and to design questionnaires with respondent-friendly layout and content. 1 The Checklist for Reporting Results of Internet E-Surveys (CHERRIES) is the most-used document for reporting online surveys. 11 The CHERRIES checklist included points on ensuring the reliability of online surveys and avoiding manipulations with multiple entries by the same users. 11 A specific set of recommendations, listed by the EQUATOR Network, is available for specialists who plan web-based and non-web-based surveys of knowledge, attitude, and practice in clinical medicine. 12 These recommendations help design valid questionnaires, survey representative subjects with clinical knowledge, and complete transparent reporting of the obtained results. 12

COVID-19 = coronavirus disease 2019.

From January 2018 to December 2019, three rounds of surveying experts with interest in surveys and questionnaires allowed reaching consensus on a set of points for reporting web-based and non-web-based surveys. 13 The Consensus-Based Checklist for Reporting of Survey Studies included a rating of 19 items of survey reports, from titles to acknowledgments. 13 Finally, rapid recommendations on online surveys amid the coronavirus disease 2019 (COVID-19) pandemic were published to guide the authors on how to choose social media and other online platforms for disseminating questionnaires and targeting representative groups of respondents. 14

Adhering to a combination of these recommendations is advisable to minimize the limitations of each document and increase the transparency of survey reports. For cross-sectional analyses of large sample sizes, additionally consulting the STROBE standard of the EQUATOR Network may further improve the accuracy of reporting respondents' inclusion and exclusion criteria. In fact, there are examples of online survey reports adhering to both CHERRIES and STROBE recommendations. 15 , 16

ETHICS CONSIDERATIONS

Although health research authorities in some countries lack mandates for full ethics review of survey studies, obtaining formal review protocols or ethics waivers is advisable for most surveys involving respondents from more than one country. And following country-based regulations and ethical norms of research are therefore mandatory. 14 , 17

Full ethics review or exemption procedures are important steps for planning and conducting ethically sound surveys. Given the non-interventional origin and absence of immediate health risks for participants, ethics committees may approve survey protocols without a full ethics review. 18 A full ethics review is however required when the informational and psychological harms of surveys increase the risk. 18 Informational harms may result from unauthorized access to respondents' personal data and stigmatization of respondents with leaked information about social diseases. Psychological harms may include anxiety, depression, and exacerbation of underlying psychiatric diseases.

Survey questionnaires submitted for evaluation should indicate how informed consent is obtained from respondents. 13 Additionally, information about confidentiality, anonymity, questionnaire delivery modes, compensations, and mechanisms preventing unauthorized access to questionnaires should be provided. 13 , 14 Ethical considerations and validation are especially important in studies involving vulnerable and marginalized subjects with diminished autonomy and poor social status due to dementia, substance abuse, inappropriate sexual behavior, and certain infections. 18 , 19 , 20 Precautions should be taken to avoid confidentiality breaches and bot activities when surveying via insecure online platforms. 21

Monetary compensation helps attract respondents to fill out lengthy questionnaires. However, such incentives may create mechanisms deceiving the system by surveyees with a primary interest in compensation. 22 Ethics review protocols may include points on recording online responders' IP addresses and blocking duplicate submissions from the same Internet locations. 22 IP addresses are viewed as personal information in the EU, but not in the US. Notably, IP identification may deter some potential responders in the EU. 21

PATIENT KNOWLEDGE AND PERCEPTION SURVEYS

The design of patient knowledge and perception surveys is insufficiently defined and poorly explored. Although such surveys are aimed at consistently covering research questions on clinical presentation, prevention, and treatment, more emphasis is now placed on psychometric aspects of designing related questionnaires. 23 , 24 , 25 Targeting responsive patient groups to collect reliable answers is yet another challenge that can be addressed by distributing questionnaires to patients with good knowledge of their diseases, particularly those registering with university-affiliated clinics and representing patient associations. 26 , 27 , 28

The structure of questionnaires may differ for surveys of patient groups with various age-dependent health issues. Care should be taken when children are targeted since they often report a variety of modifiable conditions such as anxiety and depression, musculoskeletal problems, and pain, affecting their quality of life. 29 Likewise, gender and age differences should be considered in questionnaires addressing the quality of life in association with mental health and social status. 30 Questionnaires for older adults may benefit from including questions about social support and assistance in the context of caring for aging diseases. 31 Finally, addressing the needs of digital technologies and home-care applications may help to ensure the completeness of questionnaires for older adults with sedentary lifestyles and mobility disabilities. 32 , 33

SOCIAL MEDIA FOR QUESTIONNAIRE DISTRIBUTION

The widespread use of social media has made it easier to distribute questionnaires to a large number of potential responders. Employing popular platforms such as Twitter and Facebook has become particularly useful for conducting nationwide surveys on awareness and concerns about global health and pandemic issues. 34 , 35 When various social media platforms are simultaneously employed, participants' sociodemographic factors such as gender, age, and level of education may confound the study results. 36 Knowing targeted groups' preferred online networking and communication sites may better direct the questionnaire distribution. 37 , 38 , 39

Preliminary evidence suggests that distributing survey links via social-media accounts of individual users and organized e-groups with interest in specific health issues may increase their engagement and correctness of responses. 40 , 41

Since surveys employing social media are publicly accessible, related questionnaires should be professionally edited to easily inquire target populations, avoid sensitive and disturbing points, and ensure privacy and confidentiality. 42 , 43 Although counting e-post views is feasible, response rates of social-media distributed questionnaires are practically impossible to record. The latter is an inherent limitation of such surveys.

SURVEY SAMPLING

Establishing connections with target populations and diversifying questionnaire dissemination may increase the rigor of current surveys which are abundantly administered. 44 Sample sizes depend on various factors, including the chosen topic, aim, and sampling strategy (random or non-random). 12 Some topics such as COVID-19 and global health may easily attract the attention of large respondent groups motivated to answer a variety of questionnaire questions. In the beginning of the pandemic, most surveys employed non-random (non-probability) sampling strategies which resulted in analyses of numerous responses without response rate calculations. These qualitative research studies were mainly aimed to analyze opinions of specialists and patients exposed to COVID-19 to develop rapid guidelines and initiate clinical trials.

Outside the pandemic, and beyond hot topics, there is a growing trend of low response rates and inadequate representation of target populations. 45 Such a trend makes it difficult to design and conduct random (probability) surveys. Subsequently, hypotheses of current online surveys often omit points on randomization and sample size calculation, ending up with qualitative analyses and pilot studies. In fact, convenience (non-random or non-probability) sampling can be particularly suitable for previously unexplored and emerging topics when overviewing literature cannot help estimate optimal samples and entirely new questionnaires should be designed and tested. The limitations of convenience sampling minimize the generalizability of the conclusions since the sample representativeness is uncertain. 45

Researchers often employ 'snowball' sampling techniques with initial surveyees forwarding the questionnaires to other interested respondents, thereby maximizing the sample size. Another common technique for obtaining more responses relies on generating regular social media reminders and resending e-mails to interested individuals and groups. Such tactics can increase the study duration but cannot exclude the participation bias and non-response.

Purposive or targeted sampling is perhaps the most precise technique when knowing the target population size and respondents' readiness to correctly fill the questionnaires and ensure an exact estimate of response rate, close to 100%. 46

DESIGNING QUESTIONNAIRES

Correctness, confidentiality, privacy, and anonymity are critical points of inquiry in questionnaires. 47 Correctly worded and convincingly presented survey invitations with consenting options and reassurances of secure data processing may increase response rates and ensure the validity of responses. 47 Online surveys are believed to be more advantageous than offline inquiries for ensuring anonymity and privacy, particularly for targeting socially marginalized and stigmatized subjects. Online study design is indeed optimal for collecting more responses in surveys of sex- and gender-related and otherwise sensitive topics.

Performing comprehensive literature reviews, consultations with subject experts, and Delphi exercises may all help to specify survey objectives, identify questionnaire domains, and formulate pertinent questions. Literature searches are required for in-depth topic coverage and identification of previously published relevant surveys. By analyzing previous questionnaire characteristics, modifications can be made to designing new self-administered surveys. The justification of new studies should correctly acknowledge similar published reports to avoid redundancies.

The initial part of a questionnaire usually includes a short introduction/preamble/cover letter that specifies the objectives, target respondents, potential benefits and risks, and moderators' contact details for further inquiries. This part may motivate potential respondents to consent and answer questions. The specifics, volume, and format of other parts are dependent on revisions in response to pretesting and pilot testing. 48 The pretesting usually involves co-authors and other contributors, colleagues with the subject interest while the pilot testing usually involves 5-10 target respondents who are well familiar with the subject and can swiftly complete the questionnaires. The guidance obtained at the pretesting and pilot testing allows editing, shortening, or expanding questionnaire sections. Although guidance on questionnaire length and question numbers is scarce, some experts empirically consider 5 domains with 5 questions in each as optimal. 12 Lengthy questionnaires may be biased due to respondents' fatigue and inability to answer numerous and complicated questions. 46

Questionnaire revisions are aimed at ensuring the validity and consistency of questions, implying the appeal to relevant responders and accurate covering of all essential points. 45 Valid questionnaires enable reliable and reproducible survey studies that end up with the same responses to variably worded and located questions. 45

Various combinations of open-ended and close-ended questions are advisable to comprehensively cover all pertinent points and enable easy and quick completion of questionnaires. Open-ended questions are usually included in small numbers since these require more time to respond. 46 Also, the interpretation and analysis of responses to open-ended questions hardly contribute to generating robust qualitative data. 49 Close-ended questions with single and multiple-choice answers constitute the main part of a questionnaire, with single answers easier to analyze and report. Questions with single answers can be presented as 3 or more Likert scales (e.g., yes/no/do not know).

Avoiding too simplistic (yes/no) questions and replacing them with Likert-scale items may increase the robustness of questionnaire analyses. 50 Additionally, constructing easily understandable questions, excluding merged items with two or more points, and moving sophisticated questions to the beginning of a questionnaire may add to the quality and feasibility of the study. 50

Survey studies are increasingly conducted by health professionals to swiftly explore opinions on a wide range of topics by diverse groups of specialists, patients, and public representatives. Arguably, quality surveys with generalizable results can be instrumental for guiding health practitioners in times of crises such as the COVID-19 pandemic when clinical trials, systematic reviews, and other evidence-based reports are scarcely available or absent. Online surveys can be particularly valuable for collecting and analyzing specialist, patient, and other subjects' responses in non-mainstream science countries where top evidence-based studies are scarce commodities and research funding is limited. Accumulated expertise in drafting quality questionnaires and conducting robust surveys is valuable for producing new data and generating new hypotheses and research questions.

The main advantages of surveys are related to the ease of conducting such studies with limited or no research funding. The digitization and social media advances have further contributed to the ease of surveying and growing global interest toward surveys among health professionals. Some of the disadvantages of current surveys are perhaps those related to imperfections of digital platforms for disseminating questionnaires and analysing responses.

Although some survey reporting standards and recommendations are available, none of these comprehensively cover all items of questionnaires and steps in surveying. None of the survey reporting standards is based on summarizing guidance of a large number of contributors involved in related research projects. As such, presenting the current guidance with a list of items for survey reports ( Table 2 ) may help better design and publish related articles.

Disclosure: The authors have no potential conflicts of interest to disclose.

Author Contributions:

• Conceptualization: Zimba O.
• Formal analysis: Zimba O, Gasparyan AY.
• Writing - original draft: Zimba O.
• Writing - review & editing: Zimba O, Gasparyan AY.

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Open Access

Peer-reviewed

Research Article

A Survey of U.S Adults’ Opinions about Conduct of a Nationwide Precision Medicine Initiative® Cohort Study of Genes and Environment

Contributed equally to this work with: David J. Kaufman, Rebecca Baker, Lauren C. Milner, Kathy L. Hudson

* E-mail: [email protected]

Affiliation National Human Genome Research Institute, Division of Genomics and Society, National Institutes of Health, Rockville, MD, United States of America

Affiliation National Institutes of Health, Office of the Director, Bethesda, MD, United States of America

• David J. Kaufman, 
• Rebecca Baker, 
• Lauren C. Milner, 
• Stephanie Devaney, 
• Kathy L. Hudson

• Published: August 17, 2016
• https://doi.org/10.1371/journal.pone.0160461
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A survey of a population-based sample of U.S adults was conducted to measure their attitudes about, and inform the design of the Precision Medicine Initiative’s planned national cohort study.

An online survey was conducted by GfK between May and June of 2015. The influence of different consent models on willingness to share data was examined by randomizing participants to one of eight consent scenarios.

Of 4,777 people invited to take the survey, 2,706 responded and 2,601 (54% response rate) provided valid responses. Most respondents (79%) supported the proposed study, and 54% said they would definitely or probably participate if asked. Support for and willingness to participate in the study varied little among demographic groups; younger respondents, LGBT respondents, and those with more years of education were significantly more likely to take part if asked. The most important study incentive that the survey asked about was learning about one’s own health information. Willingness to share data and samples under broad, study-by-study, menu and dynamic consent models was similar when a statement about transparency was included in the consent scenarios. Respondents were generally interested in taking part in several governance functions of the cohort study.

Conclusions

A large majority of the U.S. adults who responded to the survey supported a large national cohort study. Levels of support for the study and willingness to participate were both consistent across most demographic groups. The opportunity to learn health information about one’s self from the study appears to be a strong motivation to participate.

Citation: Kaufman DJ, Baker R, Milner LC, Devaney S, Hudson KL (2016) A Survey of U.S Adults’ Opinions about Conduct of a Nationwide Precision Medicine Initiative® Cohort Study of Genes and Environment. PLoS ONE 11(8): e0160461. https://doi.org/10.1371/journal.pone.0160461

Editor: Alejandro Raul Hernandez Montoya, Universidad Veracruzana, MEXICO

Received: January 18, 2016; Accepted: July 19, 2016; Published: August 17, 2016

This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.

Data Availability: With respect to our ability to share the data, the ethos of the Precision Medicine Initiative is to share data openly. However, in this instance, the survey data used in the paper were collected under a contractual agreement with the survey research company GfK. GfK carries out the survey on a sample drawn from a large population-based sample that GfK recruits and maintains. GfK has an ethical and contractual obligation to protect the privacy of its panel members and their households. To this end GfK passes these obligations on to its clients. We are bound ethically and legally not to share respondent identifiers, or data that could be linked to the larger dataset we possess that would allow for the identification of respondents or households. Requests for collaborations to examine aggregate analyses of these data are welcome and can be sent to [email protected] .

Funding: The Foundation for National Institutes of Health directly paid for GfK to field the survey. The authors themselves received no specific funding for the work. FNIH did not participate in data collection, analysis, decisions to publish or preparation of the manuscript. They were involved in discussions about the logistics of study design but did not influence survey content.

Competing interests: During the study and at the time of publication, DK worked at the National Institutes of Health (NIH) which is sponsoring and developing the PMI cohort study. He was not involved in those efforts. During the study and at the time of publication, KH, RB, and LM worked at the NIH which is sponsoring and developing the PMI cohort study, and were directly involved in development of the PMI cohort study. SD worked at the NIH at the time the survey was developed where she worked directly on development of the PMI study. At the time of publication, she worked at the White House where she was involved in some aspects of developing the PMI study. This does not alter the authors' adherence to all PLOS ONE policies on data sharing and materials.

Introduction

Precision medicine is an emerging approach to disease prevention, diagnosis and treatment that takes into account differences between individuals. While not new, to date it has only been applied to certain conditions. The Precision Medicine Initiative® (PMI) plans to build a comprehensive scientific knowledge base to implement precision medicine on a larger scale by launching a national cohort study of a million or more Americans [ 1 ]. The national cohort study will aim to foster open, responsible data sharing, maintain participant privacy, and build on strong partnerships between researchers and participants [ 2 ].

Prospective cohort studies using biospecimens are a common approach taken to examine the effects and interactions of genes, environment, and lifestyle [ 3 – 7 ]. Although they are labor-, time-, and capital-intensive [ 8 ], these studies can provide the statistical power needed to detect small biological effects on disease [ 9 – 10 ]. Both public [ 3 , 5 , 11 , 12 ] and private [ 4 , 6 , 7 ] cohort studies and biobanks have been created, and genetic analyses have been incorporated into existing cohort studies as genotyping and computational tools become more accessible [ 11 , 13 , 14 ].

The Precision Medicine Initiative® aims to expand on these efforts to engage a wider group who would volunteer a standardized set of health information that can be shared broadly with qualified researchers. Cohort volunteers would share their information and biological specimens for genomic and other analyses. Genomic information would be combined with clinical data from electronic health records, lifestyle data, and data measured through mobile health devices, for use by a broad range of researchers. Participants would have access to information about cohort-fueled research findings, as well as some individual research results.

The National Institutes of Health (NIH) along with other federal agencies has begun to design and execute this large prospective study as part of the White House’s Precision Medicine Initiative® [ 1 , 2 , 10 ]. During the initial planning process for this PMI Cohort Program, NIH engaged a wide variety of expertise through four public workshops on issues of design and vision for the cohort [ 15 – 18 ], and two Requests for Information [ 19 , 20 ].

At a July, 2015 workshop on participant engagement and health equity a broad range of experts discussed the role of participant engagement in the design and conduct of an inclusive PMI cohort [ 17 ]. The discussions, which focused on building and sustaining public trust, actively engaging participants, and enlisting participants to set research priorities and directly collect study data informed the strategic design of the PMI cohort [ 21 ].

The workshop concluded that continued engagement of a broad range of stakeholders will be needed to plan, carry out and sustain the PMI cohort program. As part of this larger public engagement effort, a survey of U. S. adults was conducted to measure support for such a study, to measure acceptability of various design features, and to identify and prioritize public concerns.

Materials and Methods

Survey methods.

A 44-question online survey, determined by the NIH Office of Human Subjects Research to be exempt from human subjects review (Exemption #12889), collected U.S. adults’ opinions about a national cohort study. Formal consent was not obtained both because the study was judged as exempt, and because completion of the survey is taken as a form of consent to participate.

The survey was not intended to collect psychometric data and thus did not rely on validated psychometric scales. However, to examine changes over time in public support for and hypothetical willingness to take part in a large U.S. cohort study, exact wording from two previous surveys was used for some questions.[ 22 – 24 ] Some questions came from a related survey of biobank participants under development at the time by the NIH-funded Electronic Medical Records and Genomics (or eMERGE) consortia [ 25 ]. Response choices consisted of pre-defined options. Most of these question choices were developed based on findings of focus groups conducted as part of prior studies [ 22 – 24 ].

The survey addressed support for and willingness to take part in the cohort study, specific aspects of participation, study oversight including participant involvement in governance, and the return of information to participants. Respondents were first shown a description of the cohort study. ( S1 Appendix ) At the end of the description, respondents were told that participants in the cohort study “might get access to the information collected about their health”.

Respondents were then asked several questions about their support for the concept and willingness to take part if they were asked. ( S2 Appendix contains exact wording of all of the questions analyzed here.) Respondents were also shown one of eight different scenarios, selected at random, describing study consent and data sharing and asked whether they would “consent to share your samples and information with researchers in this manner”. The eight scenarios varied with respect to two factors: the structure of consent (broad, study by study, menu, or dynamic consent) and the presence or absence of a statement that cohort study participants would “have access to a website where you would be able to see what studies are going on, which studies are using your information, and what each study has learned.” The exact wording of all eight versions of consent is found in S3 Appendix .

A pilot survey (n = 30) fielded between May 5 and May 7, 2015 evaluated the instrument length and logic. Median completion time for the pilot was 23 minutes; the instrument was shortened to 20 minutes. The final instrument was translated into Spanish for use by respondents who preferred it. The translation was back-translated and certified.

Sample selection and online survey administration was managed by the online survey firm GfK. The survey sample was drawn from GfK’s KnowledgePanel, which is itself a probability-based pool of approximately 55,000 people designed to be representative of the U.S. population.

Individuals can become GfK panelists only after being randomly selected by GfK; no one can volunteer to be a member. GfK selects people using probability-based sampling of addresses from the U.S. Postal Service’s Delivery Sequence File, which includes 97% of residential U.S. households. Excluded from eligibility are those in residential care settings, institutionalized and incarcerated people, and homeless individuals. Individuals residing at randomly sampled addresses are invited to join KnowledgePanel through a series of mailings in English and Spanish; non-responders are phoned when a telephone number can be matched to the sampled address.

For those who agree to be part of the GfK panel, but do not have Internet access, GfK provides at no cost a laptop and Internet connection. GfK also optimized the survey for administration via smartphone or tablet. When GfK enrolls participants into its panel, each panel participant answers demographic questions which are banked and periodically updated by GfK. GfK can then provide data on common demographics for each of its participants, allowing surveys to reduce burden by not asking these questions. Data in this paper on participants’ self-reported race and ethnic group, age, education, gender, sexual orientation or gender identity, household income, and residence in a metropolitan statistical area were all measured by GfK prior to this survey.

GfK attempts to address sources of survey error including sampling error, non-coverage and non-response due to panel recruitment methods and panel attrition by using demographic post-stratification weights based on demographics of the U.S. Current Population Survey (CPS) as the benchmark. Once the data are collected, post-stratification weights are constructed so that the study data can be adjusted for the study’s sample design and for survey nonresponse[ 26 ].

This series of methods has resulted in GfK survey samples that compare favorably to other gold standard methods designed to generate population-based samples [ 27 ]. During the field period for this survey, GfK first drew a random sample of 3,271 U.S. adults from their Web-enabled panel of approximately 55,000 U.S. residents. This included Hispanics and black non-Hispanics. In order to meet oversampling goals of 500 in these two groups, three additional random samples were drawn, including one of 665 Black non-Hispanic adults and two additional samples of 541 and 320 Hispanic adults. GfK contacted each of these 4,777 individuals via email to invite them to take part in this survey. Non-respondents received up to four email reminders from GfK.

The survey was fielded online between May 28, 2015 and June 9, 2015. Participants received the equivalent of $2 for their time. After survey data were collected, information previously collected by GfK on panel members’ demographics was added to the dataset.

Analysis Methods

Data were cleaned and analyzed using SPSS software [ 28 ]. Respondents who skipped more than one-third of the questions, or who completed the survey in less than one quarter of the median survey time were excluded from analyses.

Support for the study and willingness to participate were measured using 4-point Likert scales; two binary variables were created for analysis from these scales. Demographic variables were analyzed using the categories as shown in Table 1 . Two sets of multiple logistic regressions were conducted. ( Table 2 ) Support for the study and willingness to participate were the dependent variables. In these models, race and ethnic group were treated as a single categorical variable using dummy variables, and treating white non-Hispanics as the reference group. Education, household income and age were each modeled as ordinal variables using the categories shown in Tables 1 and 2 . Respondents who identified as lesbian, gay, bisexual or transgender (LGBT) were analyzed together as a single group.

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(n = 2,601).

https://doi.org/10.1371/journal.pone.0160461.t001

Each multiple logistic regression included independent covariates for gender, self-identified race and ethnic group, survey language (among Hispanics only), age, household income, educational attainment, residence within or outside a metropolitan statistical area, and identification as either lesbian, gay, bisexual or transgender. For purposes of the analysis, race and ethnicity was treated as a categorical variable, using dummy variables for black non-Hispanics, Hispanics, and other non-white, non-Hispanics. Education, household income, and age were each treated as 4-level variables using the categories shown below. To examine whether there were differences among Hispanics who took the survey in Spanish and English, separate regressions were conducted using Hispanic respondents’ data only, adjusting for all of the variables below except for race and ethnic group.

https://doi.org/10.1371/journal.pone.0160461.t002

The multiple logistic regressions examined demographic factors associated with support and participation. Analyses that included the entire sample were weighted to 2014 U.S. Census demographic benchmarks. To examine whether Hispanics who took the survey in English differed from those who took it in Spanish with respect to support and willingness to participate, separate regressions were carried out using only Hispanic respondents’ data, adjusting for the covariates in Table 1 except for race and ethnic group. Analyses within or between different races and ethnic groups used an alternate set of weights calculated for these oversampled groups.

In total, 4,777 people were contacted by GfK via email and invited to take the survey, and 2,706 provided at least some responses, for an overall response rate of 56.6%. Overall response rates were 62.2% (2,036 of 3,271) in the general population sample, 345/665 or 51.9%, in the Black-non-Hispanic oversample and 325/841 or 38.6% in the Hispanic oversample. It should be noted that 320 Hispanic cases in the oversample were invited to respond on June 5, 2015 and the survey was closed on June 9, 2015. Members of this oversample received fewer email reminders to take part and had a shorter field period to participate, which could account for some but not all of the lower completion rate in the Hispanic oversample.

Responses from 105 people (3.9%) were excluded from analysis because they skipped more than one-third of the questions or completed the survey in less than 6 minutes, leaving a valid response rate of 2,601/4,777 or 54%. The excluded people did not differ demographically from those retained in the analysis. The margin of error on opinion estimates based on the sample of 2,601 is +/- 1.9%.

Demographic characteristics of the surveyed population are found in Table 1 . After weighting the sample, people with less than twelve years of education were still somewhat underrepresented compared to census data. This should be considered where differences in opinions exist across education groups.

General Support for the Cohort Study

Immediately after viewing the description of the cohort study, participants were asked ‘Based on the description you just read, do you think this study should be done?’ Seventy-nine percent said the study definitely (22%) or probably (57%) should be done, while 21% said probably not (16%) or definitely not (5%).

Similar levels of support were observed across most demographic groups ( Table 2 ). A multiple logistic regression treating support for the cohort study as a binary independent variable showed that, adjusting for the other factors in Table 1 , no significant differences in support were observed between genders, age groups, races or ethnic groups, or between Hispanics who took the survey in Spanish and English. Fewer years of education (p<0.0001), lower household income (p = 0.04), and residence outside of metropolitan statistical areas (a proxy for rural residence, p = 0.03) were independently associated with lower levels of support for the study. However, in all but one of the demographic categories examined (0–11 years of education), 70% or more said they supported the study.

Stated Willingness to Participate in the Cohort Study if Asked

The question ‘Would you participate in the cohort study if you were asked?’ was also posed at the survey’s start. Prior to this question, the only possible personal benefit of participating that was mentioned was that cohort participants “might get access to the information collected about their health.” A majority of participants (54%) said they definitely (14%) or probably (40%) would participate if asked, while the rest said they probably (30%) or definitely (16%) would not take part. Willingness to participate did not vary considerably between demographic groups ( Table 2 ). Majorities (>50%) in most groups said they would participate if asked, and in each group, at least 1 in 9 people said they would definitely take part. A second multiple logistic regression treated willingness to participate as a binary independent variable. Adjusting for the other factors in Table 1 , increasing years of education (p<0.0001) and younger age (p<0.0001) were independently associated with increased likelihood of willingness to participate. Compared to white non-Hispanics, Hispanic respondents were more likely to say they would participate (59% vs 53%, adjusted p = 0.009). As a group, respondents who identified as lesbian, gay, bisexual or transgender were significantly more likely to say they would participate if asked (p = 0.01).

One in four respondents said that they supported the idea of the study, but also said they would not participate if they were asked. People who supported the study but would not participate if asked were more than twice as likely as those who would participate to agree that the study “would take too much of my time” (77% vs 30%), and were less likely than those who would take part to agree with the statement “I trust the study to protect my privacy” (51% vs. 81% respectively).

The survey was not designed to educate people about precision medicine or biomedical research. However it was hypothesized that thinking about some of the attitudinal questions in the survey could influence respondents’ opinions about taking part in the study. To test this hypothesis, near the end of the survey, respondents were asked again “Now that you have had a chance to think about the study, would you participate in the study if you were asked?” Overall, responses were fairly similar to the earlier question– 56% said they would definitely (15%) or probably (41%) take part if asked; 25% said they probably would not participate and 19% said they definitely would not. Seven in ten (70%) did not change their answer from the beginning to the end of the survey. However, 15% had grown more positive about participating by the end of the survey, and 15% had grown more negative. Some demographic differences were observed in shifts from the beginning of the survey to the end. For example, fewer people who took the survey in Spanish (61% vs 55%) said they would take part at the end of the survey, while more people with some college (55% vs 60%) or a bachelor’s degree (60% vs 64%) were willing to take part at the end of the survey.

Respondents were also asked about specific things they would be willing to do as study participants. Among all respondents, one in seven (14%) said they would participate for their lifetime, and an additional 11% said they would take part for at least ten years. Among people who said they would definitely or probably participate if asked, 42% said they would take part for at least ten years. However, only one in four of the Black non-Hispanics and Hispanics who were willing to take part said they would do so for at least ten years.

All respondents, including those who said they would not participate, were asked to “[i]magine you were considering participating in the study”, and then asked about their willingness to provide various types of data and samples. Nearly three quarters of respondents (73%) said that if they were participating they would be willing to provide the study with a blood sample. Higher fractions said they would provide urine, hair, and saliva samples (75%), data from an activity tracker (i.e. Fitbit) (75%), genetic information (76%), a family medical history (77%), soil and water samples from home (83%), and data on lifestyle, diet and exercise (84%). Among those with a social media account (n = 1,641) only 43% responded that they would share their social media information with the study.

In each demographic group listed in Table 1 , at least 9% of people (one in eleven) said they would definitely participate, would take part for at least ten years, and would provide the study with a blood sample.

In the sample, 87% owned either a smart phone (62%) or a cell phone (25%). Three-quarters of these phone users responded that if they “were texted or prompted on your cell phone to answer a question from the study, or measure your pulse”, they would be willing to respond at least once a week. A majority (59%) said they would respond at least once a day, and 28% would be willing to respond at least twice a day.

Incentives for participation

Respondents were asked about the importance of six different incentives in their decision about whether or not to participate. The most important incentive was “learning information about my health”, listed as either somewhat or very important by 90% of people, including at least 85% of people in each group in Table 1 . Receiving payment for their time (80%) and getting health care (77%) were important to more people than receiving free internet connections (56%), activity trackers (55%) or smartphones and data plans (52%). However, the technology incentives were of more interest to younger respondents, those with lower household incomes, and those with fewer years of education.

Respondents said they would be interested in a wide variety of information that the study might return to them ( Fig 1 ). Three in four would be interested in “lab results” (examples given were cholesterol and blood sugar) as well as genetic results. Slightly fewer (68%) said they would like a copy of their medical record. Six in ten (60%) said they would be interested in receiving information about other research studies related to their health.

Respondents’ interest in different types of information the study could return to participants.

https://doi.org/10.1371/journal.pone.0160461.g001

Consent and Sharing of Data and Samples

As described above, respondents were randomly selected to view one of eight consent scenarios and asked “would you consent to share your samples and information with researchers in this manner”. There were four models of consent: broad, study-by-study, menu, and dynamic consent. The exact wording of the four consent scenarios is found in S3 Appendix . Two versions of these four scenarios were presented; four where the consent description stood alone, and four where the consent option was followed by this sentence: “You would (also) have access to a website where you would be able to see what studies are going on, which studies are using your information, and what each study has learned.”

When the consent models were displayed alone, similar fractions of respondents said they would share samples and data under the study-by-study (72%), menu (75%), and dynamic consent models (73%) ( Fig 2 ) while 64% would share with the study under the broad consent model. However, when the consent scenarios were accompanied by the statement about a website that displays how samples and data are being used, there was essentially no difference in support for the four consent models.

Willingness to share samples and information under different consent models.

https://doi.org/10.1371/journal.pone.0160461.g002

When asked about allowing different categories of researchers to use their samples and information, people were most likely to say they would share with researchers at the NIH (79%) and U.S. academic researchers (71%). There was more reluctance to share with “pharmaceutical or drug company researchers” (52%) or “other government researchers” (44%). The category “other government researchers” may be overly broad and non-specific; for example, had the survey named researchers at specific health-related agencies, responses may have differed. Consistent with two prior surveys, people were least willing to share with university researchers in other countries (39%) [ 23 , 24 ].

In a separate question, 43% of people agreed that if their personal information was removed first, they would be willing to have their “information and research results available on the Internet to anyone”.

Involvement of Participants in Design and Conduct of the Study

To create a cohort study that addresses health related questions that are relevant to the lives of participants, study designers are embracing new models of participants as partners in research. Several questions addressed respondents’ interest in this area. A large majority (76%) agreed with the statement “research participants and researchers should be equal partners in the study”.

Fig 3 shows that between 34% and 62% of respondents said that participants should be involved in various phases of the study. Important to the most respondents was participant involvement in three governance tasks—deciding what kinds of research are appropriate, deciding what to do with study results, and deciding what research questions to answer. Between 35% and 45% said they would like to be involved themselves in those three aspects of the study.

Aspects of the study that participants should be involved in generally, and aspects the respondent themselves would want to be involved in.

https://doi.org/10.1371/journal.pone.0160461.g003

One in four people said that including research participants in planning and running the study would increase their willingness to participate, including 18% of those people who said earlier in the survey that they would not take part if asked. Another 17% said it would make them less willing to take part if participants were included, and 58% said it would not affect their decision.

The Precision Medicine Initiative® cohort program been engaging and partnering with participant representatives prior to the launch of the study, and plans to actively continue this work with cohort study participants. This survey reflects an early effort to understand the views and preferences of potential participants toward the PMI cohort program. Findings from this survey were incorporated into the final report that the Precision Medicine Initiative Working Group made to the National Institutes of Health, and are reflected in recommendations about how the cohort study might be designed.[ 21 ] As such, the survey represents one of several early efforts to engage the public in order to inform whether and how the PMI cohort study might move forward.

Across most demographic groups this survey found consistent levels of support for and willingness to participate in the PMI cohort study as it was described. The overall support (79%) and willingness to take part (54%) observed are comparable to measures in previous public surveys conducted using nationwide GfK samples in 2008 and 2012, which found overall support for a large nationwide biobank at 84% and 83% respectively, and willingness to participate if asked at 60% and 56% respectively [ 23 , 25 ]. Support in this study could be lower than that measured in earlier surveys in part due to the explicitly stated association with the NIH (and thus the federal government) in this survey, as well as high profile privacy breaches associated with the federal government and health providers in the six months prior to the survey [ 29 , 30 ]. Differences in levels of support and willingness to participate might also result from this survey’s mention of smartphones and activity trackers to collect data, especially among older respondents, who had more concern about the privacy of electronic media (data not shown). This study’s estimates of overall support and willingness to participate are also biased slightly upward, since people with fewer years of education, who were underrepresented in the sample compared to U.S. demographics, were less likely to support the study and participate. However, extrapolating support and willingness observed in each category of education to U.S. census frequencies of the education categories suggests the magnitude of inflation from this source is less than 1% in both figures.

The findings suggest that certain groups including older Americans and those with lower socioeconomic status may require additional engagement if they are to take part. However the survey findings do not support the idea that people from communities that have historically been understudied in research are not interested in participating in this cohort. In contrast, in each demographic group in Table 1 , at least one in eleven people (9%) said they would definitely participate if asked, would donate blood, and would take part for at least ten years. The willingness to take part observed here is only the foundation for efforts needed to engage, recruit and retain people in traditionally underrepresented groups. Researchers likely must work as part of communities that have been underrepresented, if those communities are going to feel and be a part of the study. [ 17 ] To this end, scientists may consider adopting language and policies that bond researchers and potential participants together todesign and govern the study [ 17 , 31 ].

Thirty percent of survey respondents shifted their opinions about their willingness to take part in the study from the beginning to the end of the survey. This suggests that considering some of the potential risks and benefits of participation may inform and influence people’s decision to take part. Engagement before and during study recruitment may help people make better informed decisions about participation.

The observation that receipt of health information was the most important incentive was consistent with results of a 2008 nationwide survey [ 23 ]. Maximizing information shared with research participants will be a key challenge of the PMI. Survey respondents expressed interest in a wide range of information, including but not limited to genetic information. Laboratory measurements such as blood sugar were seen as equally interesting. The return of information may also benefit research, encouraging participants to stay engaged and enrolled, and to take part in other research studies based on their results.

There was considerable enthusiasm among respondents about participant involvement in different phases of the study. Between 19% and 45% said they themselves would take part in various study related functions. The tasks of greatest interest to the most people were governance-related. Developing “participants as equal partners” may not drastically improve enrollment. However it may establish the kind of study identity and enthusiasm that others have cited as one key to the success of this effort [ 16 – 18 , 21 ].

NIH researchers were found to be trusted with the data and samples to be collected. If the NIH serves as a leader in the PMI cohort, it must be prepared to understand and meet those expectations. For example, if PMI cohort data are shared with foreign academics, study leaders may need to address negative attitudes about such sharing, perhaps by engaging the public to understand their reservations, and explaining how the sharing benefits U.S. medicine and research.

Limitations

It is very important to note that the results of this survey were not meant to, and do not accurately predict what portion of American adults would take part in the PMI cohort study if they were asked. First, although half of respondents said they would take part in PMI if asked, only 54% of the sample contacted for this survey agreed to participate. Second, respondents in this survey are members of the GfK panel; they may be more favorably inclined toward research participation than the general population. This limitation is inherent in most studies of attitudes about taking part in biomedical research, since people must be willing to take part in a survey study like this one to collect such data. On the other hand, the bias may not be particularly strong since sharing opinions on a survey is likely to be a smaller, lower risk commitment than sharing ones’ biospecimens and medical data. Third, people’s stated willingness to take part in a hypothetical study will not correlate perfectly with actual behaviors. The PMI study should not be expected to enjoy a 54% success rate in its recruitment based on these data. Given the limitations of the survey, the data likely provide valid estimates of support for the study as well as the relative willingness of different groups to participate, the relative importance of different incentives, and the relative acceptability of different consent models.

Supporting Information

S1 appendix. text used to describe the pmi cohort study in the survey..

https://doi.org/10.1371/journal.pone.0160461.s001

S2 Appendix. Exact wording of survey questions used in this manuscript.

https://doi.org/10.1371/journal.pone.0160461.s002

S3 Appendix. Wording used to describe eight consent scenarios in the survey.

https://doi.org/10.1371/journal.pone.0160461.s003

Acknowledgments

The authors wish to thank the Foundation for the National Institutes of Health, which funded this survey. The authors would also like to thank Vence Bonham, Laura Rodriguez, Alex Lee and the members of the Consent, Education, Regulation and Consultation Working Group of the eMERGE research consortium for their contributions to the survey and manuscript development.

Author Contributions

• Conceived and designed the experiments: DK RB LM SD KH.
• Performed the experiments: DK RB LM SD KH.
• Analyzed the data: DK RB.
• Wrote the paper: DK RB LM SD KH.
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Sample Survey Methods Research Paper

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A survey consists of a number of operations or steps of survey design. The ultimate goal of the survey is to generate estimates of population parameters, based on observations of (a sample of) the units that comprise the population. The design steps can be viewed as a chain of links.

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The steps can be labeled in the following way: (a) Research objectives are defined, i.e., the subject-matter problem is translated into a statistical problem. Researchers must define the target population they want to study and the concepts they wish to measure. Indicators (variables) of the concepts are chosen and eventually, questions are formulated. Problems in this first step usually result in relevance errors, see Hox (1997). (b) A frame of the population is developed. The frame could be a list of population units, a map, or even a set of random numbers that could be used to access a population of individuals with telephones. Coverage errors result when frame units do not completely correspond with population units. (See Groves 1989.) (c) The mode of administrating the survey is chosen. The suitable survey mode depends on budget constraints, topic, and the type of measurement that is being considered. Common modes include face-to-face interviews, telephone interviews, diaries, and administrative records. New modes related to the Internet have recently entered the scene, see Lyberg and Kasprzyk (1991) and Dillman (2000). (d) The questionnaire is developed. For each survey construct, one or more survey questions are developed. Questionnaire development is complicated since the perception of questions varies among respondents and is sensitive to a number of cognitive phenomena. Effects that are treated in the literature include: question wording, question order, order between response alternatives, context, navigational principles, and the influence of interviewers. Many large survey organizations emphasize this step and have created cognitive laboratories to improve their questionnaire work, see Sudman et al. (1996) and Forsyth and Lessler (1991). (e) The sampling design specifies the sampling unit, the method for randomly selecting the sample from the frame, and the sample size. The choice depends on the assumed population variability and the costs of sampling different units, see Sarndal et al. (1992). (f) Data are collected, i.e., observations or measurements are made of the sampled units. Typically both random and systematic errors occur at this stage, see de Leeuw and Collins (1997). (g) Data are processed. This step is needed to make estimation and tabulation possible, given that only raw data exist. The processing includes editing activities where data consistency and completeness are controlled, entry of data (data capture), and coding of variables, see Lyberg and Kasprzyk(1997).

All design steps are interdependent. A decision regarding one step has an impact on other steps. Thus, several iterations of the above steps of the design process may be necessary before the final design is determined. There follows details of the survey process.

1. Populations And Population Parameters

A population is a set of units. For example, a population might be the inhabitants of a country, the households in a city, or the companies in a sector of industry. The ‘units of study’ are the units used as a basis of the analysis, for example individuals, households, or companies. The ‘target population’ is that particular part of the population about which inference is desired. The ‘study variables’ are the values of the units studied, for example the age of an individual, the disposable income of a household, or the number of employees in a company. The ‘population parameters’ are characteristics of the population, summarizing features of the population, for example the average disposable income for households in a population. Most often interest centers on finding the population parameters for specific subsets of the population such as geographical regions or age groups. The subsets are called ‘domains of study.’

2. Sampling Units, Frames, And Probability Samples

Frequently, statements about some population parameters are problematic because of a lack of time and funding necessary for surveying all units in the population. Instead we have to draw a sample, a subset of the population, and base conclusions on that sample. High quality conclusions concerning the parameter values require care when designing the sample. Assessing the quality of the conclusions made can be accomplished by using a probability sampling design, which is a design such that all units in the population is given a known probability of being included in the sample. Given that knowledge, it is possible to produce estimates of the parameters that are unbiased and of high precision. Moreover it is also possible to estimate the precision of the estimates based on the sample. This is usually in contrast to nonprobability sampling designs where, strictly speaking, the statistical properties of the estimators are unknown unless one is willing to accept distribution assumptions for the variables under study in combination with the sampling design.

Probability sampling requires a frame of sampling units. The units of study in the population can be of different types, such as individuals, households, or companies. Even if the analysis is intended to be based on these units it is often practical or even necessary to group the population units into units that are better suited for sampling. The reason for this can be that, due to imperfect frames, there is no register of the units of study and therefore the units cannot be selected directly. Instead, groups of units can be selected, for example, villages or city blocks, and interviews are conducted with the people in the villages or blocks. Here the sampling unit consists of a cluster of units of study. In many countries, the demarcation of the clusters are based on geographical units identified through areas on maps. Often the clusters are formed to be a suitable workload for an interviewer or enumerator and are called the enumeration area. The enumeration areas are often formed and updated in population censuses. In countries where the telecommunication system is well developed, interviews are often done by telephone. The sampling unit in this case is the cluster of individuals, i.e., the household members that have access to the same telephone.

The frame can take different shapes. For example, a list of N students at a university complete with names and addresses is a frame of students. In this case the sampling units and the units of study are the same. This makes it easy to select a sample of n students by numbering the students from 1 to N and generating n random numbers in a computer. Then we select the students that have the same number as the realized random numbers. Note that in doing so we deliberately introduce randomization through the random number generation. This is in contrast to methods that do not use randomization techniques but act as if data are independent identically distributed random variables regardless of how the data was obtained.

Often, the sampling units are not the same as the study units. If, for example, the units of study are individuals in a country and the target population consists of all individuals living in the country at a specific date, there is seldom a list or data file that contains the individuals. Also the cost of making such a list would be prohibitive.

Using a sequence of frames containing a sequence of sampling units of decreasing sizes can improve this situation. For example, if there exists a list of villages in the country, then this is a frame of primary sampling units. From a sample of villages, a list of all households within the villages selected can be made. This is a frame of secondary sampling units. Note that there is a need for making the list of households only for the villages selected. Using this list, some of the households may be selected for interviews. Thus, a sequence of frames containing a sequence of sampling units has been constructed in a way that permits selection of a probability sample of units of study without enumerating all the individuals in the country. The existence of, or the possibility of, creating reliable frames is a prerequisite for making efficient sampling designs. Often the frame situation will govern the sampling procedure. Ideally the frame should cover the target population and only that population. It should provide the information necessary for contacting the units of study such as names, addresses, telephone numbers, or the like. If there is auxiliary information about the units, it is very practical if it is included in the frame. Auxiliary information is useful for constructing efficient sampling designs. A specific type of frame is used in ‘Random Digit Dialing’ (RDD). When telephone numbers are selected, a common technique is to select numbers by generating them at random in a computer. The frame is the set of numbers that could be generated in the computer. The selection probability of the cluster is proportional to the number of telephones to which the household members have access.

3. Sampling Methods And Estimators

The overall goal is to be able to make (high) quality estimates of the parameters as cheaply as possible. This is implemented using a ‘sampling strategy,’ i.e., a combination of sampling design (a certain combination of sampling methods) and an ‘estimator,’ which is as efficient as possible, i.e., gives the highest precision for a given cost. There exists a variety of sampling methods that can be applied in different situations depending on the circumstances. The most frequently employed sampling methods are:

(a) Simple Random Sampling (SRS). Every unit in the population is given an equal chance of being included in the sample.

(b) Systematic Sampling. Every kth unit in the frame is included in the sample, starting from a randomly selected starting point. The sampling step k is chosen so that the sample has a predetermined size.

(c) Stratified Sampling. The units are grouped together in homogenous groups (strata) and then sampled, for example, using SRS within each group. Stratified sampling is used either for efficiency reasons or to ensure a certain sample size in some domains of study, such as geographical regions or specific age groups. It is necessary to know the values of a stratification variable in advance to be able to create the strata. Stratification is efficient if the stratification variable is related to the variables under study. If the number of units that are being selected within each stratum is proportional to the number of units in the stratum, then this is called proportional allocation. Usually this will give fairly efficient estimates. It can be improved upon using optimal allocation, which requires knowledge of the variability of the study variables or correlated variables within each stratum. In many cases the improvement is small compared to proportional stratification.

(d) Unequal Probability Sampling. This is a method, which can be employed either for efficiency reasons or for sheer necessity. Often the probability of selecting a cluster of units is (or is made to be) proportional to the number of units in the cluster. This is called selecting with probability proportional to size (PPS), with size in this case equal to the number of units. The measure of size can vary. The efficiency of the estimator will increase if the measure of size is related to the study variables.

(e) Multistage Sampling. This is a technique, which is typically used in connection with frame problems.

The above-mentioned sampling methods can be combined to produce good sampling designs. For example, the following is an example of a ‘master sample design’ that is used in some countries. Suppose that the object is to conduct a series of sample surveys concerning employment status, living conditions, and household expenditures. Also suppose that based on a previous census there exist enumeration areas (EAs) for the country, which are reasonably well updated so that approximations of the population sizes are available for each EA. Suppose that it is deemed appropriate to stratify the EAs according to geographical regions both because the government wants these regions as domains of study and because there is reason to believe that the consumption pattern is different within each region. Thus, the stratification of the EAs would serve both purposes, namely controlling the sample sizes for domains of study and presumably being more efficient than SRS. A number of EAs are selected within each stratum. The number of EAs to be selected is chosen to be proportional to the aggregated population figures in the regions according to the most recent census. The EAs are the primary sampling units. If the EAs vary a lot in size it could be efficient to select the EAs with PPS; otherwise SRS could be used.

The EAs so selected, constitute the master sample of primary sampling units that will be kept the same for a number of years. The actual number of years will depend on the migration rate within the regions. From this master sample a number of households are selected each time a new survey is to be conducted. When selecting the households, it is possible to make a new updating of the EAs, i.e., to make a new list of the households living in the area and then select with systematic sampling or SRS a number of households to be interviewed. The households are the secondary sampling units. Often the sampling fractions in the second stage are determined in such a way that the resulting inflation factor for the households is the same. This is called a ‘self-weighting design.’ In principle, a self-weighting design makes it possible to calculate the estimates and the precision of the estimates without a computer.

4. Estimators, Auxiliary Information, And Sample Weights

To each sampling design there corresponds at least one estimator, which is a function of the sample data used for making statements about the parameters. The form of the estimator depends on the sampling design used and also on whether auxiliary information is included in the function. In survey sampling, some auxiliary information is almost always available, i.e., values of concomitant variables known for all units in the population. If this information is correlated to the study variables, it can be used to increase the efficiency of the sampling strategy either by incorporating the information in the sampling method, as in stratification, or in the probability of including the unit in the sample as in PPS, or in adjusting the estimator. A very general form of an estimator is the so-called generalized regression estimator (Cassel et al. 1976), which for estimating the population total takes the form

where x denotes the values of the auxiliary variable, T x the known value of the population total of x, β is the regression coefficient estimated from the sample be- tween x and the study variable y and

is the so-called Horvitz–Thompson estimator of X, and α i the inclusion probability of unit i. The function t y is the estimator of the unknown value of the parameter. The motivation for using this estimator is based on the conviction that the study variable and the auxiliary variable are linearly related. Thus, this can be seen as one example of the use of models in survey sampling. If the inclusion probabilities are the same for all units, i.e., if α i = (n/N ), then the Horvitz– Thompson estimator becomes the expanded sample mean, which is an unbiased estimator of the population total under the SRS scheme if the expectation is taken with respect to the design properties.

The sample weights are the inflation factors used in the estimator for inflating the sample data. They are usually a function of the inverted values of the inclusion probabilities. In the Horvitz–Thompson estimator, the sample weights are N(α i n) −1 . For the sample mean, the sample weights become N/n. As was noted earlier, to each sampling design, there exists an estimator that is natural, i.e., it is unbiased in the design sense. For example, in the case of multistage probability sampling, the sampling weights are functions of the different selection probabilities in each selection step. If the selection probabilities are carefully selected they may form a weight, which is constant for all units in the sample, and the value taken by the estimator can be calculated simply by summing the values of the units in the sample and multiplying the sum by the constant. This is called a ‘self-weighted estimator’ (and design). This technique was important before the breakthrough of the personal computer, because it saved a lot of manual labor but with today’s powerful PCs, it has lost its merits. The generalized regression estimator can be rewritten in the form:

where w i are the sample weights pertinent to unit i for this estimator. The ‘calibration estimator’ is the form of the regression estimator where the sample weights have been adjusted so that t x = T x . This adjustment causes a small systematic error, which decreases when the sample size increases.

5. Assessing The Quality Of The Estimates—Precision

The quality of the statements depend among other things on the precision of the estimates. Probability sampling supports measurement of the sampling error, since a randomly selected subset of the population is a basis for the estimates. The calculation takes into consideration the randomization induced by the sampling design. Because the design might be complex, the calculation of the precision might be different from what is traditionally used in statistics. For example the variance of the sample mean y s for estimating the population mean y under SRS with replacement is S 2 /n where S 2 is the population variance, where

and n is the sample size. This formula is similar to that used in traditional statistical analysis. However for the Horvitz–Thompson estimator, the variance is:

where α ij is the joint inclusion probability of units i and j. As can be seen, the calculation of the variance becomes complicated for complicated sampling de-signs, having a large number of selection stages and also unequal selection probabilities in each step. This complexity becomes even more pronounced when estimating population parameters in subgroups where the means are ratios of random variables. However some shortcut methods have been developed: ultimate cluster techniques, Taylor series, jack-knifing, and replications, see Wolter (1985). It is also evident from the formula for the variance that the variance of the Horvitz–Thompson estimator depends on the relation between the values of the study variable y and the inclusion probability α. If the inclusion probability can be made to be approximately proportional to the values of the study variable, then the variance becomes small. That is one reason why much emphasis is put on the existence of auxiliary information in survey sampling. However, as was shown by Godambe (1955) there does not exist a uniformly minimum variance unbiased estimator in survey sampling when inference is restricted to design-based inference.

6. Assessing The Quality Of The Estimates—Total Survey Error

The total survey error can be measured by the mean squared error (MSE), which is the sum of the variance and the squared bias of the estimate. Regular formulas for error estimation do not take all MSE components into account but rather the precision components mentioned above. Basically, a variance formula includes random variation induced by the sampling procedure and the random response variation. Components such as correlated variances induced by interviewers, coders, editors, and others have to be estimated separately and added to the sampling and response variance. The same goes for systematic errors that contribute to the bias. They have to be estimated separately and added, so that a proper estimate of MSE can be obtained.

Often the survey quality is visualized by a confidence interval, based on the estimated precision. Obviously such an interval might be too short because it has not taken the total error into account. Some of the sources of correlated variances and biases can be traced to:

(a) respondents who might have a tendency to, for instance, under-report socially undesirable behaviors;

(b) interviewers who might systematically reformulate certain questions and do so in an interviewer- specific fashion;

(c) respondents who do not participate because they cannot be contacted or they refuse;

(d) incomplete frames resulting in, e.g., undercoverage; and

(e) coders who might introduce biased measurements if they tend to erroneously code certain variable descriptions.

There are of course many other possibilities for error to occur in the estimates. There are basically two ways of assessing the quality of estimates: (a) The components of MSE can be estimated—this is a costly and time-consuming operation and (b) by a modeling approach—it might be possible to include, e.g., non- response errors and coverage errors in the assessment formulas. This method’s success depends on the realism of the modeling of the error mechanisms involved.

One should bear in mind, however, that for each survey step there are methods designed to keep the errors small. Systematic use of such known dependable methods decreases the need for evaluation studies or heavy reliance on modeling.

Bibliography:

• Cassel C M, Sarndal C E, Wretman J H 1976 Some results on generalized difference and generalized regression estimation for finite populations. Biometrika 63: 615–20
• De Leeuw E, Collins M 1997 Data collection methods and survey quality: An overview. In: Lyberg L et al. (eds.) Survey Measurement and Process Quality. Wiley, New York
• Dillman D 2000 Mail and Internet Surveys. Wiley, New York
• Godambe V P 1955 A unified theory of sampling from finite populations. Journal of Royal Statistical Society, Series B 17: 269–78
• Groves R 1989 Survey Errors and Survey Costs. Wiley
• Forsyth B, Lessler J 1991 Cognitive laboratory methods: A taxomomy. In: Biemer P et al. (eds.) Measurement Errors in Surveys. Wiley, New York
• Hox J 1997 From theoretical concept to survey question. In: Lyberg L et al. (eds.) Survey Measurement and Process Quality. Wiley, New York, pp. 47–70
• Lyberg L, Kasprzyk D 1991 Data collection methods and measurement error: An overview. In: Biemer P et al. (eds.) Measurement Errors in Surveys. Wiley
• Lyberg L, Kasprzyk D 1997 Some aspects of post-survey processing. In: Lyberg L et al. (eds.) Survey Measurement and Process Quality. Wiley
• Sarndal C E, Swensson B, Wretman J 1992 Model Assisted Survey Sampling. Springer-Verlag, New York
• Sudman S, Bradburn N, Schwarz N 1996 Thinking About Answers: The Application of Cognitive Processes to Survey Methodology. Jossey-Bass, San Francisco
• Wolter K 1985 Introduction to Variance Estimation. SpringerVerlag

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