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• Survey Research | Definition, Examples & Methods

Survey Research | Definition, Examples & Methods

Published on August 20, 2019 by Shona McCombes . Revised on June 22, 2023.

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

• Determine who will participate in the survey
• Decide the type of survey (mail, online, or in-person)
• Design the survey questions and layout
• Distribute the survey
• Analyze 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: analyze the survey results, step 6: write up the survey results, other interesting articles, 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 in 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
• US college students
• Second-generation immigrants in the Netherlands
• Customers of a specific company aged 18-24
• British transgender women over the age of 50

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

Several common research biases can arise if your survey is not generalizable, particularly sampling bias and selection bias . The presence of these biases have serious repercussions for the validity of your results.

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 college student in the US. 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 generalize 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. Again, beware of various types of sampling bias as you design your sample, particularly self-selection bias , nonresponse bias , undercoverage bias , and survivorship bias .

There are two main types of survey:

• A questionnaire , where a list of questions is distributed by mail, 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 mail 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, and at risk for biases like self-selection bias .

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 analyze.
• The anonymity and accessibility of online surveys mean you have less control over who responds, which can lead to biases like self-selection bias .

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 mall 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 store’s weekday customers).
• The sample size will be smaller, so this method is less suitable for collecting data on broad populations and is at risk for sampling bias .

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 analyzes the results. But they are more commonly used to collect qualitative data : the interviewees’ full responses are transcribed and analyzed 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 analyzed 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. Avoid jargon or industry-specific terminology.

Survey questions are at risk for biases like social desirability bias , the Hawthorne effect , or demand characteristics . It’s critical to use language that respondents will easily understand, and avoid words with vague or ambiguous meanings. Make sure your questions are phrased neutrally, with no indication that you’d prefer a particular answer or emotion.

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.

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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 mail, online, or in person.

There are many methods of analyzing 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 clean 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 organizing them into categories or themes. You can also use more qualitative methods, such as thematic analysis , which is especially suitable for analyzing 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 analyzed 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 analyze it. In the results section, you summarize the key results from your analysis.

In the discussion and conclusion , you give your explanations and interpretations of these results, answer your research question, and reflect on the implications and limitations of the research.

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

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

Research bias

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

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

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

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

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 analyze your data.

The priorities of a research design can vary depending on the field, but you usually have to specify:

• Your research questions and/or hypotheses
• Your overall approach (e.g., qualitative or quantitative )
• The type of design you’re using (e.g., a survey , experiment , or case study )
• Your sampling methods or criteria for selecting subjects
• Your data collection methods (e.g., questionnaires , observations)
• Your data collection procedures (e.g., operationalization , timing and data management)
• Your data analysis methods (e.g., statistical tests  or thematic analysis )

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McCombes, S. (2023, June 22). Survey Research | Definition, Examples & Methods. Scribbr. Retrieved June 18, 2024, from https://www.scribbr.com/methodology/survey-research/

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• Knowledge Base
• Methodology
• 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.

Prevent plagiarism, run a free check.

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.

Cite this Scribbr article

If you want to cite this source, you can copy and paste the citation or click the ‘Cite this Scribbr article’ button to automatically add the citation to our free Reference Generator.

McCombes, S. (2022, October 10). Doing Survey Research | A Step-by-Step Guide & Examples. Scribbr. Retrieved 18 June 2024, from https://www.scribbr.co.uk/research-methods/surveys/

Is this article helpful?

Shona McCombes

Other students also liked, qualitative vs quantitative research | examples & methods, construct validity | definition, types, & examples, what is a likert scale | guide & examples.

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Article Contents

What is survey research, advantages and disadvantages of survey research, essential steps in survey research, research methods, designing the research tool, sample and sampling, data collection, data analysis.

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Good practice in the conduct and reporting of survey research

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KATE KELLEY, BELINDA CLARK, VIVIENNE BROWN, JOHN SITZIA, Good practice in the conduct and reporting of survey research, International Journal for Quality in Health Care , Volume 15, Issue 3, May 2003, Pages 261–266, https://doi.org/10.1093/intqhc/mzg031

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Survey research is sometimes regarded as an easy research approach. However, as with any other research approach and method, it is easy to conduct a survey of poor quality rather than one of high quality and real value. This paper provides a checklist of good practice in the conduct and reporting of survey research. Its purpose is to assist the novice researcher to produce survey work to a high standard, meaning a standard at which the results will be regarded as credible. The paper first provides an overview of the approach and then guides the reader step-by-step through the processes of data collection, data analysis, and reporting. It is not intended to provide a manual of how to conduct a survey, but rather to identify common pitfalls and oversights to be avoided by researchers if their work is to be valid and credible.

Survey research is common in studies of health and health services, although its roots lie in the social surveys conducted in Victorian Britain by social reformers to collect information on poverty and working class life (e.g. Charles Booth [ 1 ] and Joseph Rowntree [ 2 ]), and indeed survey research remains most used in applied social research. The term ‘survey’ is used in a variety of ways, but generally refers to the selection of a relatively large sample of people from a pre-determined population (the ‘population of interest’; this is the wider group of people in whom the researcher is interested in a particular study), followed by the collection of a relatively small amount of data from those individuals. The researcher therefore uses information from a sample of individuals to make some inference about the wider population.

Data are collected in a standardized form. This is usually, but not necessarily, done by means of a questionnaire or interview. Surveys are designed to provide a ‘snapshot of how things are at a specific time’ [ 3 ]. There is no attempt to control conditions or manipulate variables; surveys do not allocate participants into groups or vary the treatment they receive. Surveys are well suited to descriptive studies, but can also be used to explore aspects of a situation, or to seek explanation and provide data for testing hypotheses. It is important to recognize that ‘the survey approach is a research strategy, not a research method’ [ 3 ]. As with any research approach, a choice of methods is available and the one most appropriate to the individual project should be used. This paper will discuss the most popular methods employed in survey research, with an emphasis upon difficulties commonly encountered when using these methods.

Descriptive research

Descriptive research is a most basic type of enquiry that aims to observe (gather information on) certain phenomena, typically at a single point in time: the ‘cross-sectional’ survey. The aim is to examine a situation by describing important factors associated with that situation, such as demographic, socio-economic, and health characteristics, events, behaviours, attitudes, experiences, and knowledge. Descriptive studies are used to estimate specific parameters in a population (e.g. the prevalence of infant breast feeding) and to describe associations (e.g. the association between infant breast feeding and maternal age).

Analytical studies

Analytical studies go beyond simple description; their intention is to illuminate a specific problem through focused data analysis, typically by looking at the effect of one set of variables upon another set. These are longitudinal studies, in which data are collected at more than one point in time with the aim of illuminating the direction of observed associations. Data may be collected from the same sample on each occasion (cohort or panel studies) or from a different sample at each point in time (trend studies).

Evaluation research

This form of research collects data to ascertain the effects of a planned change.

Advantages:

The research produces data based on real-world observations (empirical data).

The breadth of coverage of many people or events means that it is more likely than some other approaches to obtain data based on a representative sample, and can therefore be generalizable to a population.

Surveys can produce a large amount of data in a short time for a fairly low cost. Researchers can therefore set a finite time-span for a project, which can assist in planning and delivering end results.

Disadvantages:

The significance of the data can become neglected if the researcher focuses too much on the range of coverage to the exclusion of an adequate account of the implications of those data for relevant issues, problems, or theories.

The data that are produced are likely to lack details or depth on the topic being investigated.

Securing a high response rate to a survey can be hard to control, particularly when it is carried out by post, but is also difficult when the survey is carried out face-to-face or over the telephone.

Research question

Good research has the characteristic that its purpose is to address a single clear and explicit research question; conversely, the end product of a study that aims to answer a number of diverse questions is often weak. Weakest of all, however, are those studies that have no research question at all and whose design simply is to collect a wide range of data and then to ‘trawl’ the data looking for ‘interesting’ or ‘significant’ associations. This is a trap novice researchers in particular fall into. Therefore, in developing a research question, the following aspects should be considered [ 4 ]:

Be knowledgeable about the area you wish to research.

Widen the base of your experience, explore related areas, and talk to other researchers and practitioners in the field you are surveying.

Consider using techniques for enhancing creativity, for example brainstorming ideas.

Avoid the pitfalls of: allowing a decision regarding methods to decide the questions to be asked; posing research questions that cannot be answered; asking questions that have already been answered satisfactorily.

The survey approach can employ a range of methods to answer the research question. Common survey methods include postal questionnaires, face-to-face interviews, and telephone interviews.

Postal questionnaires

This method involves sending questionnaires to a large sample of people covering a wide geographical area. Postal questionnaires are usually received ‘cold’, without any previous contact between researcher and respondent. The response rate for this type of method is usually low, ∼20%, depending on the content and length of the questionnaire. As response rates are low, a large sample is required when using postal questionnaires, for two main reasons: first, to ensure that the demographic profile of survey respondents reflects that of the survey population; and secondly, to provide a sufficiently large data set for analysis.

Face-to-face interviews

Face-to-face interviews involve the researcher approaching respondents personally, either in the street or by calling at people’s homes. The researcher then asks the respondent a series of questions and notes their responses. The response rate is often higher than that of postal questionnaires as the researcher has the opportunity to sell the research to a potential respondent. Face-to-face interviewing is a more costly and time-consuming method than the postal survey, however the researcher can select the sample of respondents in order to balance the demographic profile of the sample.

Telephone interviews

Telephone surveys, like face-to-face interviews, allow a two-way interaction between researcher and respondent. Telephone surveys are quicker and cheaper than face-to-face interviewing. Whilst resulting in a higher response rate than postal surveys, telephone surveys often attract a higher level of refusals than face-to-face interviews as people feel less inhibited about refusing to take part when approached over the telephone.

Whether using a postal questionnaire or interview method, the questions asked have to be carefully planned and piloted. The design, wording, form, and order of questions can affect the type of responses obtained, and careful design is needed to minimize bias in results. When designing a questionnaire or question route for interviewing, the following issues should be considered: (1) planning the content of a research tool; (2) questionnaire layout; (3) interview questions; (4) piloting; and (5) covering letter.

Planning the content of a research tool

The topics of interest should be carefully planned and relate clearly to the research question. It is often useful to involve experts in the field, colleagues, and members of the target population in question design in order to ensure the validity of the coverage of questions included in the tool (content validity).

Researchers should conduct a literature search to identify existing, psychometrically tested questionnaires. A well designed research tool is simple, appropriate for the intended use, acceptable to respondents, and should include a clear and interpretable scoring system. A research tool must also demonstrate the psychometric properties of reliability (consistency from one measurement to the next), validity (accurate measurement of the concept), and, if a longitudinal study, responsiveness to change [ 5 ]. The development of research tools, such as attitude scales, is a lengthy and costly process. It is important that researchers recognize that the development of the research tool is equal in importance—and deserves equal attention—to data collection. If a research instrument has not undergone a robust process of development and testing, the credibility of the research findings themselves may legitimately be called into question and may even be completely disregarded. Surveys of patient satisfaction and similar are commonly weak in this respect; one review found that only 6% of patient satisfaction studies used an instrument that had undergone even rudimentary testing [ 6 ]. Researchers who are unable or unwilling to undertake this process are strongly advised to consider adopting an existing, robust research tool.

Questionnaire layout

Questionnaires used in survey research should be clear and well presented. The use of capital (upper case) letters only should be avoided, as this format is hard to read. Questions should be numbered and clearly grouped by subject. Clear instructions should be given and headings included to make the questionnaire easier to follow.

The researcher must think about the form of the questions, avoiding ‘double-barrelled’ questions (two or more questions in one, e.g. ‘How satisfied were you with your personal nurse and the nurses in general?’), questions containing double negatives, and leading or ambiguous questions. Questions may be open (where the respondent composes the reply) or closed (where pre-coded response options are available, e.g. multiple-choice questions). Closed questions with pre-coded response options are most suitable for topics where the possible responses are known. Closed questions are quick to administer and can be easily coded and analysed. Open questions should be used where possible replies are unknown or too numerous to pre-code. Open questions are more demanding for respondents but if well answered can provide useful insight into a topic. Open questions, however, can be time consuming to administer and difficult to analyse. Whether using open or closed questions, researchers should plan clearly how answers will be analysed.

Interview questions

Open questions are used more frequently in unstructured interviews, whereas closed questions typically appear in structured interview schedules. A structured interview is like a questionnaire that is administered face to face with the respondent. When designing the questions for a structured interview, the researcher should consider the points highlighted above regarding questionnaires. The interviewer should have a standardized list of questions, each respondent being asked the same questions in the same order. If closed questions are used the interviewer should also have a range of pre-coded responses available.

If carrying out a semi-structured interview, the researcher should have a clear, well thought out set of questions; however, the questions may take an open form and the researcher may vary the order in which topics are considered.

A research tool should be tested on a pilot sample of members of the target population. This process will allow the researcher to identify whether respondents understand the questions and instructions, and whether the meaning of questions is the same for all respondents. Where closed questions are used, piloting will highlight whether sufficient response categories are available, and whether any questions are systematically missed by respondents.

When conducting a pilot, the same procedure as as that to be used in the main survey should be followed; this will highlight potential problems such as poor response.

Covering letter

All participants should be given a covering letter including information such as the organization behind the study, including the contact name and address of the researcher, details of how and why the respondent was selected, the aims of the study, any potential benefits or harm resulting from the study, and what will happen to the information provided. The covering letter should both encourage the respondent to participate in the study and also meet the requirements of informed consent (see below).

The concept of sample is intrinsic to survey research. Usually, it is impractical and uneconomical to collect data from every single person in a given population; a sample of the population has to be selected [ 7 ]. This is illustrated in the following hypothetical example. A hospital wants to conduct a satisfaction survey of the 1000 patients discharged in the previous month; however, as it is too costly to survey each patient, a sample has to be selected. In this example, the researcher will have a list of the population members to be surveyed (sampling frame). It is important to ensure that this list is both up-to date and has been obtained from a reliable source.

The method by which the sample is selected from a sampling frame is integral to the external validity of a survey: the sample has to be representative of the larger population to obtain a composite profile of that population [ 8 ].

There are methodological factors to consider when deciding who will be in a sample: How will the sample be selected? What is the optimal sample size to minimize sampling error? How can response rates be maximized?

The survey methods discussed below influence how a sample is selected and the size of the sample. There are two categories of sampling: random and non-random sampling, with a number of sampling selection techniques contained within the two categories. The principal techniques are described here [ 9 ].

Random sampling

Generally, random sampling is employed when quantitative methods are used to collect data (e.g. questionnaires). Random sampling allows the results to be generalized to the larger population and statistical analysis performed if appropriate. The most stringent technique is simple random sampling. Using this technique, each individual within the chosen population is selected by chance and is equally as likely to be picked as anyone else. Referring back to the hypothetical example, each patient is given a serial identifier and then an appropriate number of the 1000 population members are randomly selected. This is best done using a random number table, which can be generated using computer software (a free on-line randomizer can be found at http://www.randomizer.org/index.htm ).

Alternative random sampling techniques are briefly described. In systematic sampling, individuals to be included in the sample are chosen at equal intervals from the population; using the earlier example, every fifth patient discharged from hospital would be included in the survey. Stratified sampling selects a specific group and then a random sample is selected. Using our example, the hospital may decide only to survey older surgical patients. Bigger surveys may employ cluster sampling, which randomly assigns groups from a large population and then surveys everyone within the groups, a technique often used in national-scale studies.

Non-random sampling

Non-random sampling is commonly applied when qualitative methods (e.g. focus groups and interviews) are used to collect data, and is typically used for exploratory work. Non-random sampling deliberately targets individuals within a population. There are three main techniques. (1) purposive sampling: a specific population is identified and only its members are included in the survey; using our example above, the hospital may decide to survey only patients who had an appendectomy. (2) Convenience sampling: the sample is made up of the individuals who are the easiest to recruit. Finally, (3) snowballing: the sample is identified as the survey progresses; as one individual is surveyed he or she is invited to recommend others to be surveyed.

It is important to use the right method of sampling and to be aware of the limitations and statistical implications of each. The need to ensure that the sample is representative of the larger population was highlighted earlier and, alongside the sampling method, the degree of sampling error should be considered. Sampling error is the probability that any one sample is not completely representative of the population from which it has been drawn [ 9 ]. Although sampling error cannot be eliminated entirely, the sampling technique chosen will influence the extent of the error. Simple random sampling will give a closer estimate of the population than a convenience sample of individuals who just happened to be in the right place at the right time.

Sample size

What sample size is required for a survey? There is no definitive answer to this question: large samples with rigorous selection are more powerful as they will yield more accurate results, but data collection and analysis will be proportionately more time consuming and expensive. Essentially, the target sample size for a survey depends on three main factors: the resources available, the aim of the study, and the statistical quality needed for the survey. For ‘qualitative’ surveys using focus groups or interviews, the sample size needed will be smaller than if quantitative data is collected by questionnaire. If statistical analysis is to be performed on the data then sample size calculations should be conducted. This can be done using computer packages such as G * Power [ 10 ]; however, those with little statistical knowledge should consult a statistician. For practical recommendations on sample size, the set of survey guidelines developed by the UK Department of Health [ 11 ] should be consulted.

Larger samples give a better estimate of the population but it can be difficult to obtain an adequate number of responses. It is rare that everyone asked to participate in the survey will reply. To ensure a sufficient number of responses, include an estimated non-response rate in the sample size calculations.

Response rates are a potential source of bias. The results from a survey with a large non-response rate could be misleading and only representative of those who replied. French [ 12 ] reported that non-responders to patient satisfaction surveys are less likely to be satisfied than people who reply. It is unwise to define a level above which a response rate is acceptable, as this depends on many local factors; however, an achievable and acceptable rate is ∼75% for interviews and 65% for self-completion postal questionnaires [ 9 , 13 ]. In any study, the final response rate should be reported with the results; potential differences between the respondents and non-respondents should be explicitly explored and their implications discussed.

There are techniques to increase response rates. A questionnaire must be concise and easy to understand, reminders should be sent out, and method of recruitment should be carefully considered. Sitzia and Wood [ 13 ] found that participants recruited by mail or who had to respond by mail had a lower mean response rate (67%) than participants who were recruited personally (mean response 76.7%). A most useful review of methods to maximize response rates in postal surveys has recently been published [ 14 ].

Researchers should approach data collection in a rigorous and ethical manner. The following information must be clearly recorded:

How, where, how many times, and by whom potential respondents were contacted.

How many people were approached and how many of those agreed to participate.

How did those who agreed to participate differ from those who refused with regard to characteristics of interest in the study, for example how were they identified, where were they approached, and what was their gender, age, and features of their illness or health care.

How was the survey administered (e.g. telephone interview).

What was the response rate (i.e. the number of usable data sets as a proportion of the number of people approached).

The purpose of all analyses is to summarize data so that it is easily understood and provides the answers to our original questions: ‘In order to do this researchers must carefully examine their data; they should become friends with their data’ [ 15 ]. Researchers must prepare to spend substantial time on the data analysis phase of a survey (and this should be built into the project plan). When analysis is rushed, often important aspects of the data are missed and sometimes the wrong analyses are conducted, leading to both inaccurate results and misleading conclusions [ 16 ]. However, and this point cannot be stressed strongly enough, researchers must not engage in data dredging, a practice that can arise especially in studies in which large numbers of dependent variables can be related to large numbers of independent variables (outcomes). When large numbers of possible associations in a dataset are reviewed at P < 0.05, one in 20 of the associations by chance will appear ‘statistically significant’; in datasets where only a few real associations exist, testing at this significance level will result in the large majority of findings still being false positives [ 17 ].

The method of data analysis will depend on the design of the survey and should have been carefully considered in the planning stages of the survey. Data collected by qualitative methods should be analysed using established methods such as content analysis [ 18 ], and where quantitative methods have been used appropriate statistical tests can be applied. Describing methods of analysis here would be unproductive as a multitude of introductory textbooks and on-line resources are available to help with simple analyses of data (e.g. [ 19 , 20 ]). For advanced analysis a statistician should be consulted.

When reporting survey research, it is essential that a number of key points are covered (though the length and depth of reporting will be dependent upon journal style). These key points are presented as a ‘checklist’ below:

Explain the purpose or aim of the research, with the explicit identification of the research question.

Explain why the research was necessary and place the study in context, drawing upon previous work in relevant fields (the literature review).

State the chosen research method or methods, and justify why this method was chosen.

Describe the research tool. If an existing tool is used, briefly state its psychometric properties and provide references to the original development work. If a new tool is used, you should include an entire section describing the steps undertaken to develop and test the tool, including results of psychometric testing.

Describe how the sample was selected and how data were collected, including:

How were potential subjects identified?

How many and what type of attempts were made to contact subjects?

Who approached potential subjects?

Where were potential subjects approached?

How was informed consent obtained?

How many agreed to participate?

How did those who agreed differ from those who did not agree?

What was the response rate?

Describe and justify the methods and tests used for data analysis.

Present the results of the research. The results section should be clear, factual, and concise.

Interpret and discuss the findings. This ‘discussion’ section should not simply reiterate results; it should provide the author’s critical reflection upon both the results and the processes of data collection. The discussion should assess how well the study met the research question, should describe the problems encountered in the research, and should honestly judge the limitations of the work.

Present conclusions and recommendations.

The researcher needs to tailor the research report to meet:

The expectations of the specific audience for whom the work is being written.

The conventions that operate at a general level with respect to the production of reports on research in the social sciences.

Anyone involved in collecting data from patients has an ethical duty to respect each individual participant’s autonomy. Any survey should be conducted in an ethical manner and one that accords with best research practice. Two important ethical issues to adhere to when conducting a survey are confidentiality and informed consent.

The respondent’s right to confidentiality should always be respected and any legal requirements on data protection adhered to. In the majority of surveys, the patient should be fully informed about the aims of the survey, and the patient’s consent to participate in the survey must be obtained and recorded.

The professional bodies listed below, among many others, provide guidance on the ethical conduct of research and surveys.

American Psychological Association: http://www.apa.org

British Psychological Society: http://www.bps.org.uk

British Medical Association: http://www.bma.org.uk .

UK General Medical Council: http://www.gmc-uk.org

American Medical Association: http://www.ama-assn.org

UK Royal College of Nursing: http://www.rcn.org.uk

UK Department of Health: http://www.doh.gov

Survey research demands the same standards in research practice as any other research approach, and journal editors and the broader research community will judge a report of survey research with the same level of rigour as any other research report. This is not to say that survey research need be particularly difficult or complex; the point to emphasize is that researchers should be aware of the steps required in survey research, and should be systematic and thoughtful in the planning, execution, and reporting of the project. Above all, survey research should not be seen as an easy, ‘quick and dirty’ option; such work may adequately fulfil local needs (e.g. a quick survey of hospital staff satisfaction), but will not stand up to academic scrutiny and will not be regarded as having much value as a contribution to knowledge.

Address reprint requests to John Sitzia, Research Department, Worthing Hospital, Lyndhurst Road, Worthing BN11 2DH, West Sussex, UK. E-mail: [email protected]

London School of Economics, UK. Http://booth.lse.ac.uk/ (accessed 15 January 2003 ).

Vernon A. A Quaker Businessman: Biography of Joseph Rowntree (1836–1925) . London: Allen & Unwin, 1958 .

Denscombe M. The Good Research Guide: For Small-scale Social Research Projects . Buckingham: Open University Press, 1998 .

Robson C. Real World Research: A Resource for Social Scientists and Practitioner-researchers . Oxford: Blackwell Publishers, 1993 .

Streiner DL, Norman GR. Health Measurement Scales: A Practical Guide to their Development and Use . Oxford: Oxford University Press, 1995 .

Sitzia J. How valid and reliable are patient satisfaction data? An analysis of 195 studies. Int J Qual Health Care 1999 ; 11: 319 –328.

Bowling A. Research Methods in Health. Investigating Health and Health Services . Buckingham: Open University Press, 2002 .

American Statistical Association, USA. Http://www.amstat.org (accessed 9 December 2002 ).

Arber S. Designing samples. In: Gilbert N, ed. Researching Social Life . London: SAGE Publications, 2001 .

Heinrich Heine University, Dusseldorf, Germany. Http://www.psycho.uni-duesseldorf.de/aap/projects/gpower/index.html (accessed 12 December 2002 ).

Department of Health, England. Http://www.doh.gov.uk/acutesurvey/index.htm (accessed 12 December 2002 ).

French K. Methodological considerations in hospital patient opinion surveys. Int J Nurs Stud 1981 ; 18: 7 –32.

Sitzia J, Wood N. Response rate in patient satisfaction research: an analysis of 210 published studies. Int J Qual Health Care 1998 ; 10: 311 –317.

Edwards P, Roberts I, Clarke M et al. Increasing response rates to postal questionnaires: systematic review. Br Med J 2002 ; 324: 1183 .

Wright DB. Making friends with our data: improving how statistical results are reported. Br J Educ Psychol 2003 ; in press.

Wright DB, Kelley K. Analysing and reporting data. In: Michie S, Abraham C, eds. Health Psychology in Practice . London: SAGE Publications, 2003 ; in press.

Davey Smith G, Ebrahim S. Data dredging, bias, or confounding. Br Med J 2002 ; 325: 1437 –1438.

Morse JM, Field PA. Nursing Research: The Application of Qualitative Approaches . London: Chapman and Hall, 1996 .

Wright DB. Understanding Statistics: An Introduction for the Social Sciences . London: SAGE Publications, 1997 .

Sportscience, New Zealand. Http://www.sportsci.org/resource/stats/index.html (accessed 12 December 2002 ).

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Mastering The Art Of Writing A Survey Paper: A Step-By-Step Guide

Table of Contents

Importance of survey papers in academic research

Survey papers play a crucial role in academic research as they provide a comprehensive overview of a specific topic or field. These papers serve as valuable resources for researchers, students, and professionals who want to gain a deeper understanding of a subject. By synthesizing existing literature, survey papers help to identify research gaps, highlight key findings, and offer insights into future research directions.

Survey papers are essential for the following reasons:

Summarizing existing knowledge: Survey papers consolidate and summarize the existing body of knowledge on a particular topic. They provide a comprehensive overview of the research conducted in the field, making it easier for readers to grasp the key concepts and findings.

Identifying research gaps: By analyzing the existing literature, survey papers help researchers identify areas where further investigation is needed. They highlight the gaps in knowledge and suggest potential research questions that can contribute to the advancement of the field.

Saving time and effort: Instead of going through numerous individual research papers, survey papers offer a consolidated source of information. Researchers can save time and effort by referring to a well-structured survey paper that provides a comprehensive understanding of the topic.

Providing a foundation for new research: Survey papers serve as a foundation for new research. They provide researchers with a solid understanding of the existing literature, enabling them to build upon previous studies and contribute to the field’s knowledge.

Purpose of the blog post

The purpose of this blog post is to guide aspiring researchers and students on how to write an effective survey paper. It will provide a step-by-step approach to help them navigate through the process of selecting a topic, conducting a literature review, outlining the structure, writing the paper, editing and proofreading, formatting and presentation, and finalizing the survey paper.

By following the guidelines outlined in this blog post, readers will be equipped with the necessary tools and knowledge to produce a high-quality survey paper that adds value to the academic community. Whether they are writing a survey paper for a course assignment, a research project, or a publication, this blog post will serve as a comprehensive resource to help them excel in their writing endeavors.

In the next section, we will delve into the basics of survey papers, including their definition, different types, and the benefits of writing one.

Understanding the Basics

A survey paper is a comprehensive review of existing literature on a specific topic or research area. It aims to provide a summary and analysis of the current state of knowledge in the field. Understanding the basics of survey papers is crucial for researchers and academics who wish to contribute to the existing body of knowledge. Here, we will explore the definition of a survey paper, different types of survey papers, and the benefits of writing one.

Definition of a survey paper

A survey paper, also known as a review paper or a literature review, is a type of academic paper that synthesizes and analyzes existing research on a particular topic. It goes beyond summarizing individual studies and aims to provide a comprehensive overview of the field. The goal of a survey paper is to identify trends, patterns, and gaps in the existing literature .

Different types of survey papers

There are several types of survey papers, each with its own purpose and focus. Some common types include:

Traditional survey papers : These provide a broad overview of the topic, covering various aspects and subtopics. They aim to present a comprehensive summary of the existing literature.

Focused survey papers : These focus on a specific aspect or subtopic within a broader field. They delve deeper into a particular area of interest and provide a more detailed analysis.

Systematic review papers : These follow a specific methodology for selecting and analyzing studies. They aim to minimize bias and provide an objective assessment of the available evidence.

Meta-analysis papers : These involve statistical analysis of data from multiple studies to draw conclusions and identify patterns or relationships.

Benefits of writing a survey paper

Writing a survey paper offers several benefits for researchers and academics:

Understanding the research landscape : Conducting a comprehensive literature review allows researchers to gain a deep understanding of the current state of knowledge in their field. It helps identify gaps, controversies, and areas that require further investigation.

Contributing to the field : By synthesizing and analyzing existing research, survey papers provide valuable insights and perspectives. They can help shape the direction of future research and contribute to the advancement of knowledge.

Building credibility : Publishing a well-written survey paper enhances the author’s reputation and credibility in the academic community. It demonstrates expertise in the field and the ability to critically evaluate and synthesize existing research.

Identifying research opportunities : Survey papers often highlight areas where further research is needed. They can inspire new research questions and guide researchers towards fruitful avenues of investigation.

In conclusion, understanding the basics of survey papers is essential for researchers and academics. It involves knowing the definition of a survey paper, different types of survey papers, and the benefits of writing one. By conducting a comprehensive literature review and synthesizing existing research, survey papers contribute to the advancement of knowledge in a particular field. They provide valuable insights, identify research gaps, and guide future research directions.

Choosing a Topic

Choosing the right topic is a crucial step in writing a survey paper. It sets the foundation for your research and determines the direction of your paper. Here are some key considerations when selecting a topic:

Identifying a Research Gap

To begin, you need to identify a research gap in the existing literature. Look for areas where there is limited or conflicting information, unanswered questions, or emerging trends. This will ensure that your survey paper adds value to the academic community by filling a knowledge gap .

Selecting a Specific Area of Interest

Once you have identified a research gap, narrow down your focus by selecting a specific area of interest within that gap. Choose a topic that aligns with your expertise and interests . This will make the writing process more enjoyable and allow you to bring a unique perspective to the paper.

Ensuring the Topic is Relevant and Significant

When choosing a topic, it is important to consider its relevance and significance. Select a topic that is timely and has practical implications . This will make your survey paper more valuable to readers and increase its impact. Additionally, consider the potential for future research and the broader implications of your chosen topic.

To ensure the relevance and significance of your topic, you can:

• Review recent publications and conference proceedings to identify emerging trends and hot topics in your field.
• Consult with experts and mentors to get their insights and suggestions on potential topics.
• Consider the practical applications of your chosen topic and how it can contribute to real-world problem-solving.

By following these steps, you can choose a topic that is both interesting to you and valuable to the academic community. Remember, the topic you choose will shape the entire survey paper, so take the time to select it wisely.

In conclusion, choosing a topic for your survey paper involves identifying a research gap, selecting a specific area of interest, and ensuring the topic is relevant and significant. By following these guidelines, you can set the stage for a well-rounded and impactful survey paper.

Conducting a Literature Review

Conducting a thorough literature review is a crucial step in writing a survey paper. It involves searching for relevant sources, evaluating their credibility, and organizing and summarizing the literature. This section will guide you through the process of conducting a literature review effectively.

Searching for relevant sources

When conducting a literature review, it is essential to search for relevant sources that contribute to your understanding of the topic. Here are some tips to help you find the right sources:

Utilize academic databases : Academic databases such as Google Scholar, PubMed, and IEEE Xplore are excellent resources for finding scholarly articles, conference papers, and research studies related to your topic.

Use appropriate keywords : Use specific keywords and phrases that accurately represent your research topic. This will help you narrow down your search and find relevant sources more efficiently.

Explore citation lists : Look for relevant sources in the reference lists of articles and papers you have already found. This can lead you to additional sources that are highly relevant to your research.

Consider different publication types : Apart from academic journals, consider including books, reports, theses, and dissertations in your literature review. These sources can provide valuable insights and perspectives on your topic.

Evaluating the credibility of the sources

It is crucial to evaluate the credibility and reliability of the sources you include in your literature review. Here are some factors to consider when assessing the credibility of a source:

Author’s expertise : Check the credentials and expertise of the author(s) of the source. Look for their affiliations, qualifications, and previous research experience in the field.

Publication venue : Consider the reputation and impact factor of the journal or conference where the source was published. High-quality venues often have a rigorous peer-review process, ensuring the reliability of the research.

Currency of the source : Ensure that the source is up-to-date and reflects the current state of research in the field. This is particularly important in rapidly evolving areas of study.

Peer-reviewed sources : Prefer sources that have undergone a peer-review process. Peer-reviewed articles are evaluated by experts in the field, ensuring the quality and validity of the research.

Organizing and summarizing the literature

Once you have gathered relevant sources, it is essential to organize and summarize the literature effectively. Here are some steps to help you with this process:

Create a citation database : Maintain a database or spreadsheet to keep track of the sources you have found. Include important details such as author names, publication year, title, and relevant notes.

Identify key themes and subtopics : Analyze the literature to identify common themes and subtopics that emerge from the sources. This will help you organize your survey paper and provide a logical flow of ideas.

Summarize the main findings : Write concise summaries of the main findings and key points from each source. Focus on the aspects that are most relevant to your research question or objective.

Identify gaps and controversies : Pay attention to any gaps or controversies in the literature. These can be areas where further research is needed or where different studies present conflicting results.

By following these steps, you can conduct a comprehensive literature review that forms the foundation of your survey paper. Remember to critically analyze and synthesize the information from various sources to provide a balanced and informative overview of the topic.

Outlining the Structure

When writing a survey paper, it is crucial to have a well-structured outline that guides the flow of your content. A clear and organized structure not only helps you present your ideas effectively but also makes it easier for readers to navigate through your paper. In this section, we will discuss the key components of outlining the structure of a survey paper.

The introduction sets the stage for your survey paper and provides essential background information to the readers. It should capture their attention and clearly state the research question or objective of your paper.

Background information : Start by providing a brief overview of the topic and its significance in the field. This helps readers understand the context and relevance of your survey paper.

Research question/objective : Clearly state the main research question or objective that your paper aims to address. This helps readers understand the purpose and focus of your survey.

The main body of your survey paper should be well-organized and structured to present your findings and analysis in a coherent manner. Consider the following points when outlining the main body:

Subtopics and their organization : Identify the key subtopics or themes that you will cover in your survey. These subtopics should be logically organized to provide a smooth flow of ideas. You can use headings and subheadings to clearly indicate the different sections of your paper.

Inclusion of relevant studies and findings : Within each subtopic, include relevant studies, research papers, and findings that contribute to the understanding of the topic. Make sure to cite and reference these sources properly to give credit to the original authors.

The conclusion of your survey paper should summarize the key points discussed in the main body and provide insights for future research directions. Consider the following elements when outlining the conclusion:

Summary of key points : Provide a concise summary of the main findings and insights from your survey. This helps readers grasp the main takeaways from your paper.

Future research directions : Discuss potential areas for further research or gaps that need to be addressed in the field. This encourages readers to explore new avenues and continue the scholarly conversation.

Having a well-structured outline for your survey paper ensures that you cover all the necessary components and present your ideas in a logical and coherent manner. It helps you stay focused and organized throughout the writing process.

Remember to review and revise your outline as needed to ensure that it aligns with the specific requirements and preferences of your survey paper. A well-structured survey paper not only enhances your credibility as a researcher but also contributes to the academic community’s knowledge and understanding of the topic.

Writing the Survey Paper

Writing a survey paper requires careful planning and organization to ensure that the information is presented in a clear and coherent manner. In this section, we will discuss the key steps involved in writing a survey paper.

The introduction of a survey paper plays a crucial role in capturing the reader’s attention and setting the tone for the rest of the paper. It should begin with an engaging opening statement that highlights the importance of the topic. The research question or objective should be clearly stated to provide a roadmap for the paper.

The main body of the survey paper should present a coherent flow of ideas that addresses the research question or objective. It is important to organize the content in a logical manner, using subheadings to divide the paper into sections. Each subtopic should be discussed in detail, providing a comprehensive overview of the existing literature.

When discussing previous studies and findings, it is essential to properly cite and reference the sources. This not only gives credit to the original authors but also adds credibility to the survey paper. Using a consistent citation style throughout the paper is important to maintain uniformity.

The conclusion of the survey paper should summarize the key findings and provide a concise overview of the main points discussed in the main body. It is an opportunity to highlight the significance of the research and its implications for future studies. Recommendations for further research can also be included to encourage future exploration of the topic.

Editing and Proofreading

Once the survey paper is written, it is crucial to thoroughly edit and proofread the content. This involves checking for grammar and spelling errors to ensure clarity and professionalism. It is also beneficial to seek feedback from peers or mentors to gain different perspectives and identify areas for improvement.

Formatting and Presentation

Proper formatting and presentation are essential for a well-structured survey paper. Following the required citation style is crucial to maintain consistency and adhere to academic standards. Headings, subheadings, and paragraphs should be properly formatted to enhance readability. Additionally, including tables, figures, and graphs can help illustrate complex information and enhance the overall presentation of the paper.

Finalizing the Survey Paper

Before submitting the survey paper, it is important to review the overall structure and content. This involves making necessary revisions and improvements to ensure the paper is coherent and cohesive. Proofreading the final version is crucial to eliminate any remaining errors and ensure a polished final product.

In conclusion, writing a survey paper requires careful planning, organization, and attention to detail. By following the steps outlined in this section, you can effectively write a survey paper that contributes to the existing body of knowledge in your field. Mastering the art of writing survey papers will not only enhance your academic research skills but also establish you as a knowledgeable and credible researcher.

Additional Resources:

• Recommended books and articles on survey paper writing

Online tools and platforms for organizing research

References:

List of sources cited in the blog post

Editing and proofreading are crucial steps in the writing process. They ensure that your survey paper is polished, error-free, and effectively communicates your ideas. Here are some essential tips to help you edit and proofread your survey paper effectively:

Checking for grammar and spelling errors

Use grammar and spell-check tools : Utilize grammar and spell-check tools like Grammarly or Microsoft Word’s built-in spell checker to identify and correct any grammatical or spelling errors in your survey paper.

Read your paper aloud : Reading your paper aloud can help you identify awkward sentence structures, grammatical errors, and spelling mistakes that you may have missed while reading silently.

Proofread multiple times : Proofreading is not a one-time task. It is essential to proofread your survey paper multiple times to catch any errors that may have been overlooked during previous rounds of editing.

Ensuring clarity and coherence

Check for clarity of ideas : Ensure that your ideas are presented clearly and concisely. Avoid using jargon or overly complex language that may confuse your readers. Use simple and straightforward language to convey your message effectively.

Maintain coherence and logical flow : Ensure that your survey paper has a logical flow of ideas. Each paragraph should connect smoothly to the next, and there should be a clear progression of thoughts throughout the paper. Use transition words and phrases to guide your readers through the different sections of your survey paper.

Eliminate redundant or irrelevant information : Review your survey paper to identify any redundant or irrelevant information. Remove any content that does not contribute to the overall purpose or argument of your paper. This will help streamline your paper and make it more focused and concise.

Seeking feedback from peers or mentors

Get a fresh pair of eyes : Ask a peer or mentor to review your survey paper. They can provide valuable feedback on areas that may need improvement, such as clarity, organization, or the overall structure of your paper.

Consider different perspectives : When seeking feedback, consider the perspectives of your reviewers. They may offer insights or suggestions that you may not have considered, helping you enhance the quality of your survey paper.

Incorporate feedback effectively : Take the feedback you receive into account and make necessary revisions to your survey paper. Be open to constructive criticism and use it to refine your paper further.

Remember, editing and proofreading are essential steps in the writing process. They help ensure that your survey paper is well-written, error-free, and effectively communicates your research findings. By following these tips, you can enhance the quality and clarity of your survey paper, making it more impactful and engaging for your readers.

Formatting and presentation play a crucial role in the overall quality and readability of a survey paper. Proper formatting ensures that the information is organized and presented in a clear and visually appealing manner. In this section, we will discuss the key aspects of formatting and presentation that you should consider when writing your survey paper.

Following the required citation style

One of the first things you need to consider when formatting your survey paper is the citation style required by your academic institution or the journal you are submitting to. Common citation styles include APA, MLA, and Chicago. Each style has specific guidelines for citing sources, formatting references, and creating in-text citations. It is important to familiarize yourself with the specific requirements of the chosen citation style and consistently apply it throughout your paper.

Properly formatting headings, subheadings, and paragraphs

Headings and subheadings are essential for organizing the content of your survey paper and guiding the reader through the different sections. When formatting headings and subheadings, it is important to follow a consistent hierarchy and formatting style. Typically, main headings are formatted in a larger font size and may be bold or italicized, while subheadings are formatted in a slightly smaller font size. This helps to visually distinguish between different levels of information and makes it easier for the reader to navigate through the paper.

In addition to headings and subheadings, proper formatting of paragraphs is also important. Each paragraph should focus on a single idea or topic and be well-structured with a clear topic sentence and supporting sentences. It is recommended to use a standard font such as Times New Roman or Arial, with a font size of 12 points. Additionally, paragraphs should be indented and have appropriate line spacing to enhance readability.

Including tables, figures, and graphs if necessary

Tables, figures, and graphs can be effective tools for presenting complex data or summarizing key findings in a visual format. When including these elements in your survey paper, it is important to ensure that they are properly labeled and referenced within the text. Tables should have clear column headings and be organized in a logical manner. Figures and graphs should have descriptive captions and be accompanied by a brief explanation in the text.

It is also important to consider the placement of tables, figures, and graphs within the paper. They should be inserted close to the relevant text and be easily accessible to the reader. If necessary, you can also refer to these elements in the text to provide further explanation or analysis.

Formatting and presentation are essential aspects of writing a high-quality survey paper. By following the required citation style, properly formatting headings and paragraphs, and including tables, figures, and graphs when necessary, you can enhance the overall readability and visual appeal of your paper. Remember to consistently apply these formatting guidelines throughout your survey paper to maintain a professional and polished appearance.

After going through the process of conducting a literature review, outlining the structure, writing the survey paper, and editing and proofreading it, you are now ready to finalize your survey paper. This stage involves reviewing the overall structure and content, making necessary revisions and improvements, and proofreading the final version.

Reviewing the overall structure and content

At this stage, it is crucial to review the overall structure and content of your survey paper. Ensure that the paper flows logically and coherently from the introduction to the conclusion. Check if the main body of the paper effectively addresses the research question or objective stated in the introduction. Make sure that each subtopic is adequately covered and that the inclusion of relevant studies and findings supports your arguments.

Making necessary revisions and improvements

During the finalization stage, it is common to identify areas that require revisions and improvements. Pay attention to the clarity and conciseness of your writing. Revise sentences or paragraphs that may be confusing or convoluted . Ensure that your arguments are well-supported by the literature and that you have properly cited and referenced all sources. Eliminate any redundant or irrelevant information that may distract readers from the main points of your survey paper.

Proofreading the final version

Proofreading is a crucial step in finalizing your survey paper. Check for grammar and spelling errors that may have been overlooked during the editing process. Ensure that your paper adheres to the required citation style and that all references are correctly formatted. Read through your paper carefully to ensure clarity and coherence . It may be helpful to read your paper aloud or ask a colleague to review it for you. Their fresh perspective can help identify any remaining errors or areas that need improvement.

By following these steps, you can ensure that your survey paper is of high quality and ready for submission or publication. Finalizing your survey paper requires attention to detail and a commitment to producing a well-structured and well-written piece of academic research.

Remember, the finalization stage is not the end of the writing process. It is always beneficial to seek feedback from peers or mentors to gain different perspectives and identify areas for further improvement. Their insights can help you refine your survey paper and make it even stronger.

In conclusion, finalizing a survey paper involves reviewing the overall structure and content, making necessary revisions and improvements, and proofreading the final version. It is a critical stage in the writing process that ensures your survey paper is polished and ready to be shared with the academic community.

Mastering the art of writing survey papers takes time and practice . By following the steps outlined in this blog post and seeking continuous improvement, you can become proficient in writing survey papers that contribute to the advancement of knowledge in your field.

Additional Resources

To further enhance your understanding of survey paper writing, here are some recommended books and articles:

• [Book] “Writing a Successful Research Paper: A Simple Approach” by Stanley Chodorow
• [Article] “How to Write a Survey Paper” by Martijn van Otterlo

Additionally, there are online tools and platforms available that can assist you in organizing your research and citations:

• [Tool] Zotero: A free, open-source reference management software
• [Platform] Mendeley: A platform for managing and sharing research papers

These resources can provide valuable guidance and support as you continue to develop your skills in writing survey papers.

[List of sources cited in the blog post]

When it comes to writing survey papers, having access to additional resources can greatly enhance your understanding and improve the quality of your work. Here are some recommended books, articles, and online tools that can assist you in the process of writing a survey paper.

Recommended Books and Articles on Survey Paper Writing

Writing a Survey Paper by John W. Chinneck: This book provides a comprehensive guide to writing survey papers, covering topics such as selecting a research topic, conducting a literature review, organizing the paper, and presenting the findings effectively.

How to Write a Survey Paper by Marta Tatu: This article offers practical tips and strategies for writing a survey paper, including advice on structuring the paper, synthesizing information, and avoiding common pitfalls.

The Literature Review: A Step-by-Step Guide for Students by Diana Ridley: Although not specifically focused on survey papers, this book offers valuable insights into conducting a literature review, which is a crucial component of writing a survey paper.

Writing a Successful Research Paper: A Simple Approach by Stanley Chodorow: This book provides guidance on various aspects of academic writing, including how to develop a research question, organize ideas, and present arguments effectively.

Online Tools and Platforms for Organizing Research

Zotero : Zotero is a free reference management tool that helps you collect, organize, and cite your sources. It allows you to easily save and annotate articles, books, and websites, and generate citations in various citation styles.

Mendeley : Mendeley is another popular reference management tool that enables you to organize your research library, collaborate with others, and generate citations and bibliographies. It also offers a social networking feature that allows you to connect with researchers in your field.

Google Scholar : Google Scholar is a powerful search engine that specializes in scholarly literature. It can be a valuable resource for finding relevant articles, books, and conference papers for your survey paper.

Microsoft Word or Google Docs : These word processing tools provide essential features for writing and formatting your survey paper. They offer options for creating headings, subheadings, and tables, as well as tools for spell checking and grammar correction.

Remember, while these resources can be helpful, it is important to critically evaluate the information you find and ensure its relevance and credibility before including it in your survey paper.

In conclusion, writing a survey paper requires careful planning, extensive research, and effective organization of information. By utilizing the additional resources mentioned above, you can enhance your writing skills and produce a high-quality survey paper that contributes to the academic community.

List of sources cited in the blog post:

• Chinneck, J. W. (n.d.). Writing a Survey Paper .
• Tatu, M. (n.d.). How to Write a Survey Paper .
• Ridley, D. (2012). The Literature Review: A Step-by-Step Guide for Students .
• Chodorow, S. (2014). Writing a Successful Research Paper: A Simple Approach .

When writing a survey paper, it is crucial to include a comprehensive list of references to support your claims and provide credibility to your work. The references section serves as a valuable resource for readers who wish to delve deeper into the topic or verify the information presented in your survey paper. Here are some important points to consider when creating the references section:

Ensure that you include all the sources that you have cited throughout your survey paper. This includes academic papers, books, journal articles, conference proceedings, and any other relevant sources that have contributed to your research. Proper citation and referencing are essential to avoid plagiarism and give credit to the original authors.

Formatting the references

Follow the required citation style specified by your academic institution or the journal you are submitting your survey paper to. Common citation styles include APA, MLA, Chicago, and IEEE. Each citation style has specific guidelines for formatting the references, including the order of information, punctuation, and capitalization. Properly formatting your references ensures consistency and makes it easier for readers to locate the sources you have used.

Organizing the references

Arrange the references in alphabetical order by the last name of the first author. If there are multiple authors, list them in the same order as they appear in the original source. Include the title of the paper or article, the name of the journal or book, the publication date, and the page numbers if applicable. Be sure to include all the necessary information to help readers locate the source easily.

There are several online tools and platforms available that can assist you in organizing and managing your research references. These tools help you create and format citations, generate bibliographies, and store your references in a centralized location. Some popular reference management tools include Zotero , Mendeley , and EndNote . These tools not only save time but also ensure accuracy and consistency in your references.

Double-checking the references

Before finalizing your survey paper, it is crucial to double-check the references section for any errors or omissions. Make sure that all the citations are accurate and complete. Verify that the formatting and punctuation are consistent throughout the references section. Proofreading the final version of your survey paper includes reviewing the references to ensure they are correctly formatted and properly cited.

Including a well-organized and accurate references section is essential for any survey paper. It adds credibility to your work and allows readers to explore the sources you have used. By following the guidelines for formatting and organizing your references, you can ensure that your survey paper meets the highest standards of academic integrity.

Writing a Survey Paper: A Comprehensive Guide

A. Importance of survey papers in academic research B. Purpose of the blog post

A. Definition of a survey paper B. Different types of survey papers C. Benefits of writing a survey paper

A. Identifying a research gap B. Selecting a specific area of interest C. Ensuring the topic is relevant and significant

A. Searching for relevant sources B. Evaluating the credibility of the sources C. Organizing and summarizing the literature

A. Introduction 1. Background information 2. Research question/objective B. Main Body 1. Subtopics and their organization 2. Inclusion of relevant studies and findings C. Conclusion 1. Summary of key points 2. Future research directions

A. Introduction 1. Engaging opening statement 2. Clear research question/objective B. Main Body 1. Coherent flow of ideas 2. Proper citation and referencing C. Conclusion 1. Recap of main findings 2. Implications and recommendations

A. Checking for grammar and spelling errors B. Ensuring clarity and coherence C. Seeking feedback from peers or mentors

A. Following the required citation style B. Properly formatting headings, subheadings, and paragraphs C. Including tables, figures, and graphs if necessary

A. Reviewing the overall structure and content B. Making necessary revisions and improvements C. Proofreading the final version

A. Recap of the steps involved in writing a survey paper B. Encouragement to master the art of writing survey papers

A. Recommended books and articles on survey paper writing B. Online tools and platforms for organizing research

A. List of sources cited in the blog post

Note: This outline is a general guide and can be modified or expanded based on the specific requirements and preferences of the blog post.

Writing a survey paper is an essential skill for academic researchers. It allows you to summarize and analyze existing literature on a specific topic, providing valuable insights and identifying research gaps. This comprehensive guide will walk you through the process of writing a survey paper, from choosing a topic to finalizing the paper.

Survey papers play a crucial role in academic research as they provide a comprehensive overview of existing knowledge in a particular field. The purpose of this blog post is to guide you through the process of writing a survey paper effectively.

To start, it’s important to understand the basics of a survey paper. A survey paper is a type of academic article that summarizes and synthesizes existing research on a specific topic. There are different types of survey papers, including literature reviews, systematic reviews, and meta-analyses. Writing a survey paper offers several benefits, such as gaining a deep understanding of the topic, identifying research gaps, and contributing to the academic community.

Selecting the right topic is crucial for writing a successful survey paper. Begin by identifying a research gap in your field of interest. This gap could be an unanswered question or an area that requires further exploration. Once you have identified the research gap, narrow down your focus to a specific area of interest. Ensure that the topic is relevant and significant, as this will determine the impact of your survey paper.

A thorough literature review is the foundation of a well-written survey paper. Start by searching for relevant sources such as research articles, books, and conference papers. Evaluate the credibility of these sources by considering factors like the author’s expertise, the journal’s reputation, and the methodology used. Organize and summarize the literature in a systematic manner, highlighting the key findings and arguments.

A well-structured survey paper is essential for clarity and coherence. The structure typically consists of an introduction, main body, and conclusion. In the introduction, provide background information on the topic and clearly state your research question or objective. The main body should be organized into subtopics, each addressing a specific aspect of the topic. Include relevant studies and findings to support your arguments. Finally, in the conclusion, summarize the key points and suggest future research directions.

When writing the survey paper, pay attention to the introduction, main body, and conclusion. The introduction should engage the reader with an opening statement and clearly state the research question or objective. The main body should have a coherent flow of ideas, presenting the literature in a logical manner. Proper citation and referencing are crucial to acknowledge the original authors and avoid plagiarism. In the conclusion, recap the main findings and provide implications and recommendations for future research.

Editing and proofreading are essential to ensure the quality of your survey paper. Check for grammar and spelling errors, and ensure clarity and coherence in your writing. Seek feedback from peers or mentors to get different perspectives and improve the overall quality of your paper.

Proper formatting and presentation enhance the readability of your survey paper. Follow the required citation style, such as APA or MLA, to ensure consistency. Format headings, subheadings, and paragraphs appropriately to create a clear structure. If necessary, include tables, figures, and graphs to present data effectively.

Before submitting your survey paper, review the overall structure and content. Make necessary revisions and improvements to enhance the clarity and coherence of your paper. Finally, proofread the final version to eliminate any remaining errors.

Writing a survey paper requires careful planning and execution. This guide has provided a step-by-step process to help you write a high-quality survey paper. By mastering the art of writing survey papers, you can contribute to the academic community and advance knowledge in your field.

To further enhance your understanding of survey paper writing, consider exploring recommended books and articles on the topic. Additionally, there are online tools and platforms available that can assist you in organizing your research effectively.

[List the sources cited in the blog post here.]

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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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What is survey research.

15 min read Find out everything you need to know about survey research, from what it is and how it works to the different methods and tools you can use to ensure you’re successful.

Survey research is the process of collecting data from a predefined group (e.g. customers or potential customers) with the ultimate goal of uncovering insights about your products, services, or brand overall .

As a quantitative data collection method, survey research can provide you with a goldmine of information that can inform crucial business and product decisions. But survey research needs careful planning and execution to get the results you want.

So if you’re thinking about using surveys to carry out research, read on.

Get started with our free survey maker tool

Types of survey research

Calling these methods ‘survey research’ slightly underplays the complexity of this type of information gathering. From the expertise required to carry out each activity to the analysis of the data and its eventual application, a considerable amount of effort is required.

As for how you can carry out your research, there are several options to choose from — face-to-face interviews, telephone surveys, focus groups (though more interviews than surveys), online surveys , and panel surveys.

Typically, the survey method you choose will largely be guided by who you want to survey, the size of your sample , your budget, and the type of information you’re hoping to gather.

Here are a few of the most-used survey types:

Face-to-face interviews

Before technology made it possible to conduct research using online surveys, telephone, and mail were the most popular methods for survey research. However face-to-face interviews were considered the gold standard — the only reason they weren’t as popular was due to their highly prohibitive costs.

When it came to face-to-face interviews, organizations would use highly trained researchers who knew when to probe or follow up on vague or problematic answers. They also knew when to offer assistance to respondents when they seemed to be struggling. The result was that these interviewers could get sample members to participate and engage in surveys in the most effective way possible, leading to higher response rates and better quality data.

Telephone surveys

While phone surveys have been popular in the past, particularly for measuring general consumer behavior or beliefs, response rates have been declining since the 1990s .

Phone surveys are usually conducted using a random dialing system and software that a researcher can use to record responses.

This method is beneficial when you want to survey a large population but don’t have the resources to conduct face-to-face research surveys or run focus groups, or want to ask multiple-choice and open-ended questions .

The downsides are they can: take a long time to complete depending on the response rate, and you may have to do a lot of cold-calling to get the information you need.

You also run the risk of respondents not being completely honest . Instead, they’ll answer your survey questions quickly just to get off the phone.

Focus groups (interviews — not surveys)

Focus groups are a separate qualitative methodology rather than surveys — even though they’re often bunched together. They’re normally used for survey pretesting and designing , but they’re also a great way to generate opinions and data from a diverse range of people.

Focus groups involve putting a cohort of demographically or socially diverse people in a room with a moderator and engaging them in a discussion on a particular topic, such as your product, brand, or service.

They remain a highly popular method for market research , but they’re expensive and require a lot of administration to conduct and analyze the data properly.

You also run the risk of more dominant members of the group taking over the discussion and swaying the opinions of other people — potentially providing you with unreliable data.

Online surveys

Online surveys have become one of the most popular survey methods due to being cost-effective, enabling researchers to accurately survey a large population quickly.

Online surveys can essentially be used by anyone for any research purpose – we’ve all seen the increasing popularity of polls on social media (although these are not scientific).

Using an online survey allows you to ask a series of different question types and collect data instantly that’s easy to analyze with the right software.

There are also several methods for running and distributing online surveys that allow you to get your questionnaire in front of a large population at a fraction of the cost of face-to-face interviews or focus groups.

This is particularly true when it comes to mobile surveys as most people with a smartphone can access them online.

However, you have to be aware of the potential dangers of using online surveys, particularly when it comes to the survey respondents. The biggest risk is because online surveys require access to a computer or mobile device to complete, they could exclude elderly members of the population who don’t have access to the technology — or don’t know how to use it.

It could also exclude those from poorer socio-economic backgrounds who can’t afford a computer or consistent internet access. This could mean the data collected is more biased towards a certain group and can lead to less accurate data when you’re looking for a representative population sample.

When it comes to surveys, every voice matters.

Find out how to create more inclusive and representative surveys for your research.

Panel surveys

A panel survey involves recruiting respondents who have specifically signed up to answer questionnaires and who are put on a list by a research company. This could be a workforce of a small company or a major subset of a national population. Usually, these groups are carefully selected so that they represent a sample of your target population — giving you balance across criteria such as age, gender, background, and so on.

Panel surveys give you access to the respondents you need and are usually provided by the research company in question. As a result, it’s much easier to get access to the right audiences as you just need to tell the research company your criteria. They’ll then determine the right panels to use to answer your questionnaire.

However, there are downsides. The main one being that if the research company offers its panels incentives, e.g. discounts, coupons, money — respondents may answer a lot of questionnaires just for the benefits.

This might mean they rush through your survey without providing considered and truthful answers. As a consequence, this can damage the credibility of your data and potentially ruin your analyses.

What are the benefits of using survey research?

Depending on the research method you use, there are lots of benefits to conducting survey research for data collection. Here, we cover a few:

1.   They’re relatively easy to do

Most research surveys are easy to set up, administer and analyze. As long as the planning and survey design is thorough and you target the right audience , the data collection is usually straightforward regardless of which survey type you use.

2.   They can be cost effective

Survey research can be relatively cheap depending on the type of survey you use.

Generally, qualitative research methods that require access to people in person or over the phone are more expensive and require more administration.

Online surveys or mobile surveys are often more cost-effective for market research and can give you access to the global population for a fraction of the cost.

3.   You can collect data from a large sample

Again, depending on the type of survey, you can obtain survey results from an entire population at a relatively low price. You can also administer a large variety of survey types to fit the project you’re running.

4.   You can use survey software to analyze results immediately

Using survey software, you can use advanced statistical analysis techniques to gain insights into your responses immediately.

Analysis can be conducted using a variety of parameters to determine the validity and reliability of your survey data at scale.

5.   Surveys can collect any type of data

While most people view surveys as a quantitative research method, they can just as easily be adapted to gain qualitative information by simply including open-ended questions or conducting interviews face to face.

How to measure concepts with survey questions

While surveys are a great way to obtain data, that data on its own is useless unless it can be analyzed and developed into actionable insights.

The easiest, and most effective way to measure survey results, is to use a dedicated research tool that puts all of your survey results into one place.

When it comes to survey measurement, there are four measurement types to be aware of that will determine how you treat your different survey results:

Nominal scale

With a nominal scale , you can only keep track of how many respondents chose each option from a question, and which response generated the most selections.

An example of this would be simply asking a responder to choose a product or brand from a list.

You could find out which brand was chosen the most but have no insight as to why.

Ordinal scale

Ordinal scales are used to judge an order of preference. They do provide some level of quantitative value because you’re asking responders to choose a preference of one option over another.

Ratio scale

Ratio scales can be used to judge the order and difference between responses. For example, asking respondents how much they spend on their weekly shopping on average.

Interval scale

In an interval scale, values are lined up in order with a meaningful difference between the two values — for example, measuring temperature or measuring a credit score between one value and another.

Step by step: How to conduct surveys and collect data

Conducting a survey and collecting data is relatively straightforward, but it does require some careful planning and design to ensure it results in reliable data.

Step 1 – Define your objectives

What do you want to learn from the survey? How is the data going to help you? Having a hypothesis or series of assumptions about survey responses will allow you to create the right questions to test them.

Step 2 – Create your survey questions

Once you’ve got your hypotheses or assumptions, write out the questions you need answering to test your theories or beliefs. Be wary about framing questions that could lead respondents or inadvertently create biased responses .

Step 3 – Choose your question types

Your survey should include a variety of question types and should aim to obtain quantitative data with some qualitative responses from open-ended questions. Using a mix of questions (simple Yes/ No, multiple-choice, rank in order, etc) not only increases the reliability of your data but also reduces survey fatigue and respondents simply answering questions quickly without thinking.

Find out how to create a survey that’s easy to engage with

Step 4 – Test your questions

Before sending your questionnaire out, you should test it (e.g. have a random internal group do the survey) and carry out A/B tests to ensure you’ll gain accurate responses.

Step 5 – Choose your target and send out the survey

Depending on your objectives, you might want to target the general population with your survey or a specific segment of the population. Once you’ve narrowed down who you want to target, it’s time to send out the survey.

After you’ve deployed the survey, keep an eye on the response rate to ensure you’re getting the number you expected. If your response rate is low, you might need to send the survey out to a second group to obtain a large enough sample — or do some troubleshooting to work out why your response rates are so low. This could be down to your questions, delivery method, selected sample, or otherwise.

Step 6 – Analyze results and draw conclusions

Once you’ve got your results back, it’s time for the fun part.

Break down your survey responses using the parameters you’ve set in your objectives and analyze the data to compare to your original assumptions. At this stage, a research tool or software can make the analysis a lot easier — and that’s somewhere Qualtrics can help.

Get reliable insights with survey software from Qualtrics

Gaining feedback from customers and leads is critical for any business, data gathered from surveys can prove invaluable for understanding your products and your market position, and with survey software from Qualtrics, it couldn’t be easier.

Used by more than 13,000 brands and supporting more than 1 billion surveys a year, Qualtrics empowers everyone in your organization to gather insights and take action. No coding required — and your data is housed in one system.

Get feedback from more than 125 sources on a single platform and view and measure your data in one place to create actionable insights and gain a deeper understanding of your target customers .

Automatically run complex text and statistical analysis to uncover exactly what your survey data is telling you, so you can react in real-time and make smarter decisions.

We can help you with survey management, too. From designing your survey and finding your target respondents to getting your survey in the field and reporting back on the results, we can help you every step of the way.

And for expert market researchers and survey designers, Qualtrics features custom programming to give you total flexibility over question types, survey design, embedded data, and other variables.

No matter what type of survey you want to run, what target audience you want to reach, or what assumptions you want to test or answers you want to uncover, we’ll help you design, deploy and analyze your survey with our team of experts.

Ready to find out more about Qualtrics CoreXM?

Get started with our free survey maker tool today

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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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• Utility Menu

Harvard University Program on Survey Research

• How to Frame and Explain the Survey Data Used in a Thesis

Surveys are a special research tool with strengths, weaknesses, and a language all of their own. There are many different steps to designing and conducting a survey, and survey researchers have specific ways of describing what they do.

This handout, based on an annual workshop offered by the Program on Survey Research at Harvard, is geared toward undergraduate honors thesis writers using survey data.

PSR Resources

• Managing and Manipulating Survey Data: A Beginners Guide
• Finding and Hiring Survey Contractors
• Overview of Cognitive Testing and Questionnaire Evaluation
• Questionnaire Design Tip Sheet
• Sampling, Coverage, and Nonresponse Tip Sheet
• Introduction to Surveys for Honors Thesis Writers
• PSR Introduction to the Survey Process
• Related Centers/Programs at Harvard
• General Survey Reference
• Institutional Review Boards
• Select Funding Opportunities
• Survey Analysis Software
• Professional Standards
• Professional Organizations
• Major Public Polls
• Survey Data Collections
• Major Longitudinal Surveys
• Other Links

• Research article
• Open access
• Published: 12 September 2013

A survey study of the association between mobile phone use and daytime sleepiness in California high school students

• Nila Nathan 1 &
• Jamie Zeitzer 2 , 3  

BMC Public Health volume  13 , Article number:  840 ( 2013 ) Cite this article

141k Accesses

36 Citations

4 Altmetric

Metrics details

Mobile phone use is near ubiquitous in teenagers. Paralleling the rise in mobile phone use is an equally rapid decline in the amount of time teenagers are spending asleep at night. Prior research indicates that there might be a relationship between daytime sleepiness and nocturnal mobile phone use in teenagers in a variety of countries. As such, the aim of this study was to see if there was an association between mobile phone use, especially at night, and sleepiness in a group of U.S. teenagers.

A questionnaire containing an Epworth Sleepiness Scale (ESS) modified for use in teens and questions about qualitative and quantitative use of the mobile phone was completed by students attending Mountain View High School in Mountain View, California (n = 211).

Multivariate regression analysis indicated that ESS score was significantly associated with being female, feeling a need to be accessible by mobile phone all of the time, and a past attempt to reduce mobile phone use. The number of daily texts or phone calls was not directly associated with ESS. Those individuals who felt they needed to be accessible and those who had attempted to reduce mobile phone use were also ones who stayed up later to use the mobile phone and were awakened more often at night by the mobile phone.

Conclusions

The relationship between daytime sleepiness and mobile phone use was not directly related to the volume of texting but may be related to the temporal pattern of mobile phone use.

Peer Review reports

Mobile phone use has drastically increased in recent years, fueled by new technology such as ‘smart phones’. In 2012, it was estimated that 78% of all Americans aged 12–17 years had a mobile phone and 37% had a smart phone [ 1 ]. Despite the growing number of adolescent mobile phone users, there has been limited examination of the behavioral effects of mobile phone usage on adolescents and their sleep and subsequent daytime sleepiness.

Mobile phone use in teens likely compounds the biological causes of sleep loss. With the onset of puberty, there are changes in innate circadian rhythms that lead to a delay in the habitual timing of sleep onset [ 2 ]. As school start times are not correspondingly later, this leads to a reduction in the time available for sleep and is consequently thought to contribute to the endemic sleepiness of teenagers. The use of mobile phones may compound this sleepiness by extending the waking hours further into the night. Munezawa and colleagues [ 3 ] analyzed 94,777 responses to questionnaires sent out to junior and senior high school students in Japan and found that the use of mobile phones for calling or sending text messages after they went to bed was associated with sleep disturbances such as short sleep duration, subjective poor sleep quality, excessive daytime sleepiness and insomnia symptoms. Soderqvist et al. in their study of Swedish adolescents aged 15–19 years, found that regular users of mobile phones reported health symptoms such as tiredness, stress, headache, anxiety, concentration difficulties and sleep disturbances more often than less frequent users [ 4 ]. Van der Bulck studied 1,656 school children in Belgium and found that prevalent mobile phone use in adolescents was related to increased levels of daytime tiredness [ 5 ]. Punamaki et al. studied Finnish teens and found that intensive mobile phone use lead to more health complaints and musculoskeletal symptoms in girls both directly and through deteriorated sleep, as well as increased daytime tiredness [ 6 ]. In one prospective study of young Swedish adults, aged 20–24, those who were high volume mobile phone users and male, but not female, were at greater risk for developing sleep disturbances a year later [ 7 ]. The association of mobile phone utilization and either sleep or sleepiness in teens in the United States has only been described by a telephone poll. In the 2011 National Sleep Foundation poll, 20% of those under the age of 30 reported that they were awakened by a phone call, text or e-mail message at least a few nights a week [ 8 ]. This type of nocturnal awakening was self-reported more frequently by those who also reported that they drove while drowsy.

As there has been limited examination of how mobile phone usage affects the behavior of young children and adolescents, none of which have addressed the effects of such usage on daytime sleepiness in U.S. teens, it seemed worthwhile to attempt a cross-sectional study of sleep and mobile phone utilization in a U.S. high school. As such, it was the purpose of this study to examine the association of mobile phone utilization and sleepiness patterns in a sample of U.S. teens. We hypothesized that an increased number of calls would be associated with increased sleepiness.

We designed a survey that contained questions concerning sleepiness and mobile phone use (see Additional file 1 ). Sleepiness was assessed using a version of the Epworth Sleepiness Scale (ESS) [ 9 ] modified for use in adolescents [ 10 ]. The modified ESS consists of eight questions that assessed the likelihood of dozing in the following circumstances: sitting and reading, watching TV, sitting inactive in a public place, as a passenger in a car for an hour without a break, lying down to rest in the afternoon when circumstances permit, sitting and talking to someone, sitting quietly after a lunch, in a car while stopped for a few minutes in traffic. Responses were limited to a Likert-like scale using the following: no chance of dozing (0), slight chance of dozing (1), moderate chance of dozing (2), or high chance of dozing (3). This yielded total ESS scores ranging from 0 to 24, with scores over 10 being associated with clinically-significant sleepiness [ 9 ]. We also included a set of modified questions, originally designed by Thomée et al., that assess the subjective impact of mobile phone use [ 7 ]. These included the number of mobile calls made or received each day, the number of texts made or received each day, being awakened by the mobile phone at night (never/occasionally/monthly/weekly/daily), staying up late to use the mobile phone (never/occasionally/monthly/weekly/daily), expectations of accessibility by mobile phone (never/occasionally/daily/all day/around-the-clock), stressfulness of accessibility (not at all/a little bit/rather/very), use mobile phone too much (yes/no), and tried and failed to reduce mobile phone use (yes/no).

An email invitation to complete an electronic form of the survey ( http://www.surveymonkey.com ) was sent to the entire student body of the Mountain View High School, located in Mountain View, California, USA, on April 5, 2012. Out of the approximately 2,000 students attending the school, a total of 211 responded by the collection date of April 23, 2012. Data analyses are described below (OrginPro8, OriginLab, Northampton MA). Summary data are provided as mean ± SD for age and ESS and as median (range) for the number of texts and/or phone calls made or received per day as these were non-normally distributed (p’s <; 0.001, Kolmogorov Smirnov test). To examine the relationship between sleepiness and predictor variables, stepwise multivariate regression analyses were performed. Collinearity in the data was examined by calculating the Variance Inflation Factor (VIF). Post hoc t-tests, ANOVA, Mann–Whitney U tests, and Spearman correlations were used, as appropriate, to examine specific components of the model and their relationship to sleepiness. χ 2 tests were used to examine categorical variables. The study was done within the regulations codified by the Declaration of Helsinki and approved by the administration of Mountain View High School.

Sixty-eight males and 143 females responded to the survey. Most (96.7%) respondents owned a mobile phone. The remainder of the analyses presented herein is on the 202 respondents (64 male, 138 female) who indicated that they owned a mobile phone (Tables  1 and 2 ). The youngest participant in the survey was 14 years old and the oldest was 19 years old (16 ± 1.2 years), representative of the age range of this school. The median number of mobile phone calls made or received per day was 2 and ranged from 0 to 60. The median number of text messages sent or received per day was 22.5 and ranged from 0 to 700. While about half of the respondents (53%) had never been awakened by the mobile phone at night, 35% were occasionally awakened, 5.9% were awakened a few times a month, 5.0% were awakened a few times a week, and 1.0% were awakened almost every night. About one-quarter (27%) of respondents had never stayed awake later than a target bedtime in order to use the mobile phone, however 36% occasionally stayed awake, 19% stayed awake a few times a month, 8.5% stayed awake a few times a week, and 10% stayed awake almost every night in order to use the mobile phone. In regards to feeling an expectation of accessibility, 7.5% reported that they needed to be accessible around the clock, 26% reported that they needed to be accessible all day, 52% reported they needed to be accessible daily, 13% reported that they only needed to be accessible now and then, and 1.0% reported they never needed to be accessible. Nearly half (49%) of the survey participants viewed accessibility via mobile phones to be not at all stressful, 45% found it to be a little bit stressful, 4.5% found it rather stressful, and 1.0% found it very stressful. More than one-third (36%) reported that they or someone close to them thought that they used the mobile phone too much. Few (17%) had tried but were unable to reduce their mobile phone use.

Subjective sleepiness on the ESS ranged from 0 to 18 (6.8 ± 3.5, with higher numbers indicating greater sleepiness), with 25% of participants having ESS scores in the excessively sleepy range (ESS ≥ 10). We examined predictors of subjective sleepiness (ESS score) using stepwise multivariate regression analysis with the following independent variables: age, sex, frequency of nocturnal awakening by the phone, frequency of staying up too late to use the phone, self-perceived accessibility by phone, stressfulness of this accessibility, attempted and failed to reduce phone use, excessive phone use determined by others, number of texts per day, and number of phone calls per day. Only subjects with complete data sets were used in our modeling (n = 191 of 202). Our final model (Table  3 ) indicated that sex, frequency of accessibility, and a failed attempt to reduce mobile phone use were all predictive of daytime sleepiness (F 6,194  = 4.35, p <; 0.001, r 2  = 0.12). These model variables lacked collinearity (VIF’s <; 3.9), indicating that they were not likely to represent the same source of variance. Despite the lack of significance in the multivariate model, given previously published data [ 4 – 6 ], we independently tested if there was a relationship between the number of estimated texts and sleepiness, but found no such correlation (r = 0.13, p = 0.07; Spearman correlation). In examining the final model, it appears that those who felt that they needed to be accessible “around the clock” (ESS = 9.2 ± 2.9) were sleepier than all others (ESS = 6.7 ± 3.4) (p <; 0.01, post hoc t -test). The relationship between sleepiness and reporting having tried, but failed, to reduce mobile phone use was such that those who had tried to reduce phone use were more sleepy (ESS = 8.3 ± 3.6) than those who had not (ESS = 6.5 ± 3.4) (p <; 0.01, post hoc t -test). While more females had tried to reduce their mobile phone use, sex did not modify the relationship between the attempt to reduce mobile phone use and sleepiness (p = 0.32, two-way ANOVA), thus retaining attempt and failure to reduce mobile phone use as an independent modifier of ESS scores.

In an attempt to better understand the relationship between ESS and accessibility, we parsed the population into those who felt that they needed to be accessible around the clock (7.4%) and those who did not (92.6%). The most accessible group, as compared to the less accessible group, had a numerically though not statistically significantly higher texting rate (50 vs. 20 per day; p = 0.07, Mann–Whitney U test), but were awakened more at night by the phone (27% vs. 4%, weekly or daily; p <; 0.05, χ 2 test), and stayed awake later than desired more often (40% vs. 17%, weekly or daily; p <; 0.05, χ 2 test). We did a similar analysis, parsing the population into those who had attempted but failed to reduce their use of their mobile phone (17%) with those who had not (83%). Those who had attempted to reduce their mobile phone use had a higher texting rate (60 vs. 20 per day; p <; 0.01, Mann–Whitney U test) and stayed awake later than desired more often (53% vs. 11%, weekly or daily; p <; 0.01, χ 2 test), but were not awakened more at night by the phone (12% vs. 5%, weekly or daily; p = 0.26, χ 2 test).

Given previous research on the topic, our a priori hypothesis was that teenagers who use their phone more often at night are likely to be more prone to daytime sleepiness. We did not, however, observe this simple relationship in this sample of U.S. teens. We did find that being female, perceived need to be accessible by mobile phone, and having tried but failed to reduce mobile phone usage were all predictive of daytime sleepiness, with the latter two likely being moderated by increased use of the phone at night. Previous work has shown that being female was associated with higher ESS scores [ 11 ]. It may be that adolescent females score higher on the ESS without being objectively sleepier, though this remains to be tested. Our analyses revealed that staying up late to use the mobile phone and being awakened by the mobile phone may be involved in the relationship between increased ESS scores and perceived need to be accessible by mobile phone and a past attempt to decrease mobile phone use. These analyses reveal some of the complexity of assessing daytime sleepiness, which is undoubtedly multifactorial. If the sheer number of text messages being sent per day is directly associated daytime sleepiness, it is likely with a small effect size. Our work, of course, is not without its limitations. Data were collected from a sample of convenience at a single, public high school in California. Only 10% of students responded to the survey and this may have introduced some response bias to the data. The data collected were cross-sectional; a longitudinal collection would have enabled a more precise analysis of moderators and mediators as well as a more accurate interpretation of causal relationships. Also, we did not objectively record the number of texts, so there may be a certain degree of bias or uncertainty associated with self-report of number of texts and calls. Several variables that might influence sleepiness both directly and indirectly through mobile phone use (e.g., socioeconomic status, comorbid sleep disorders, medication use) were not assessed. Future studies on the impact of mobile phone use on sleep and sleepiness should take into account the multifactorial and temporal nature of these behaviors.

The endemic sleepiness found in adolescents is multifactorial with both intrinsic and extrinsic factors. Mobile phone use has been assumed to be one source of increased daytime sleepiness in adolescents. Our analyses revealed that use or perceived need of use of the mobile phone during normal sleeping hours may contribute to daytime sleepiness. As overall number of text messages did not significantly contribute to daytime sleepiness, it is possible that a temporal rearrangement of phone use (e.g., limiting phone use during prescribed sleeping hours) might help in alleviating some degree of daytime sleepiness.

Abbreviations

Epworth sleepiness scale

Standard deviation

Analysis of variance.

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The authors wish to thank the students of Mountain View High School (Mountain View, California) for participating in this study.

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Nila Nathan

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Jamie Zeitzer

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JMZ and NN designed the study, analyzed the data, and drafted the manuscript. Both authors have read and approved the final manuscript.

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Nathan, N., Zeitzer, J. A survey study of the association between mobile phone use and daytime sleepiness in California high school students. BMC Public Health 13 , 840 (2013). https://doi.org/10.1186/1471-2458-13-840

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Survey research

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• 1 Ann Arbor, Mich. From the Section of Plastic Surgery, Department of Surgery, The University of Michigan Medical Center; and Division of General Medicine, Department of Internal Medicine, University of Michigan.
• PMID: 20885261
• DOI: 10.1097/PRS.0b013e3181ea44f9

Survey research is a unique methodology that can provide insight into individuals' perspectives and experiences and can be collected on a large population-based sample. Specifically, in plastic surgery, survey research can provide patients and providers with accurate and reproducible information to assist with medical decision-making. When using survey methods in research, researchers should develop a conceptual model that explains the relationships of the independent and dependent variables. The items of the survey are of primary importance. Collected data are only useful if they accurately measure the concepts of interest. In addition, administration of the survey must follow basic principles to ensure an adequate response rate and representation of the intended target sample. In this article, the authors review some general concepts important for successful survey research and discuss the many advantages this methodology has for obtaining limitless amounts of valuable information.

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Abstract: Generative Artificial Intelligence (GenAI) systems are being increasingly deployed across all parts of industry and research settings. Developers and end users interact with these systems through the use of prompting or prompt engineering. While prompting is a widespread and highly researched concept, there exists conflicting terminology and a poor ontological understanding of what constitutes a prompt due to the area's nascency. This paper establishes a structured understanding of prompts, by assembling a taxonomy of prompting techniques and analyzing their use. We present a comprehensive vocabulary of 33 vocabulary terms, a taxonomy of 58 text-only prompting techniques, and 40 techniques for other modalities. We further present a meta-analysis of the entire literature on natural language prefix-prompting.

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Reporting Survey Based Studies – a Primer for Authors

Prithvi sanjeevkumar gaur.

1 Smt. Kashibai Navale Medical College and General Hospital, Pune, India.

Olena Zimba

2 Department of Internal Medicine No. 2, Danylo Halytsky Lviv National Medical University, Lviv, Ukraine.

Vikas Agarwal

3 Department Clinical Immunology and Rheumatology, Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow, India.

Latika Gupta

Associated data.

The coronavirus disease 2019 (COVID-19) pandemic has led to a massive rise in survey-based research. The paucity of perspicuous guidelines for conducting surveys may pose a challenge to the conduct of ethical, valid and meticulous research. The aim of this paper is to guide authors aiming to publish in scholarly journals regarding the methods and means to carry out surveys for valid outcomes. The paper outlines the various aspects, from planning, execution and dissemination of surveys followed by the data analysis and choosing target journals. While providing a comprehensive understanding of the scenarios most conducive to carrying out a survey, the role of ethical approval, survey validation and pilot testing, this brief delves deeper into the survey designs, methods of dissemination, the ways to secure and maintain data anonymity, the various analytical approaches, the reporting techniques and the process of choosing the appropriate journal. Further, the authors analyze retracted survey-based studies and the reasons for the same. This review article intends to guide authors to improve the quality of survey-based research by describing the essential tools and means to do the same with the hope to improve the utility of such studies.

Graphical Abstract

INTRODUCTION

Surveys are the principal method used to address topics that require individual self-report about beliefs, knowledge, attitudes, opinions or satisfaction, which cannot be assessed using other approaches. 1 This research method allows information to be collected by asking a set of questions on a specific topic to a subset of people and generalizing the results to a larger population. Assessment of opinions in a valid and reliable way require clear, structured and precise reporting of results. This is possible with a survey based out of a meticulous design, followed by validation and pilot testing. 2 The aim of this opinion piece is to provide practical advice to conduct survey-based research. It details the ethical and methodological aspects to be undertaken while performing a survey, the online platforms available for distributing survey, and the implications of survey-based research.

Survey-based research is a means to obtain quick data, and such studies are relatively easy to conduct and analyse, and are cost-effective (under a majority of the circumstances). 3 These are also one of the most convenient methods of obtaining data about rare diseases. 4 With major technological advancements and improved global interconnectivity, especially during the coronavirus disease 2019 (COVID-19) pandemic, surveys have surpassed other means of research due to their distinctive advantage of a wider reach, including respondents from various parts of the world having diverse cultures and geographically disparate locations. Moreover, survey-based research allows flexibility to the investigator and respondent alike. 5 While the investigator(s) may tailor the survey dates and duration as per their availability, the respondents are allowed the convenience of responding to the survey at ease, in the comfort of their homes, and at a time when they can answer the questions with greater focus and to the best of their abilities. 6 Respondent biases inherent to environmental stressors can be significantly reduced by this approach. 5 It also allows responses across time-zones, which may be a major impediment to other forms of research or data-collection. This allows distant placement of the investigator from the respondents.

Various digital tools are now available for designing surveys ( Table 1 ). 7 Most of these are free with separate premium paid options. The analysis of data can be made simpler and cleaning process almost obsolete by minimising open-ended answer choices. 8 Close-ended answers makes data collection and analysis efficient, by generating an excel which can be directly accessed and analysed. 9 Minimizing the number of questions and making all questions mandatory can further aid this process by bringing uniformity to the responses and analysis simpler. Surveys are arguably also the most engaging form of research, conditional to the skill of the investigator.

Q/t = questions per typeform, A/m = answers per month, Q/s = questions per survey, A/s = answers per survey, NA = not applicable, NPS = net promoter score.

Data protection laws now mandate anonymity while collecting data for most surveys, particularly when they are exempt from ethical review. 10 , 11 Anonymization has the potential to reduce (or at times even eliminate) social desirability bias which gains particular relevance when targeting responses from socially isolated or vulnerable communities (e.g. LGBTQ and low socio-economic strata communities) or minority groups (religious, ethnic and medical) or controversial topics (drug abuse, using language editing software).

Moreover, surveys could be the primary methodology to explore a hypothesis until it evolves into a more sophisticated and partly validated idea after which it can be probed further in a systematic and structured manner using other research methods.

The aim of this paper is to reduce the incorrect reporting of surveys. The paper also intends to inform researchers of the various aspects of survey-based studies and the multiple points that need to be taken under consideration while conducting survey-based research.

SURVEYS IN THE COVID-19 PANDEMIC

The COVID-19 has led to a distinctive rise in survey-based research. 12 The need to socially distance amid widespread lockdowns reduced patient visits to the hospital and brought most other forms of research to a standstill in the early pandemic period. A large number of level-3 bio-safety laboratories are being engaged for research pertaining to COVID-19, thereby limiting the options to conduct laboratory-based research. 13 , 14 Therefore, surveys appear to be the most viable option for researchers to explore hypotheses related to the situation and its impact in such times. 15

LIMITATIONS WHILE CONDUCTING SURVEY-BASED RESEARCH

Designing a fine survey is an arduous task and requires skill even though clear guidelines are available in regard to the same. Survey design requires extensive thoughtfulness on the core questions (based on the hypothesis or the primary research question), with consideration of all possible answers, and the inclusion of open-ended options to allow recording other possibilities. A survey should be robust, in regard to the questions gathered and the answer choices available, it must be validated, and pilot tested. 16 The survey design may be supplanted with answer choices tailored for the convenience of the responder, to reduce the effort while making it more engaging. Survey dissemination and engagement of respondents also requires experience and skill. 17

Furthermore, the absence of an interviewer prevents us from gaining clarification on responses of open-ended questions if any. Internet surveys are also prone to survey fraud by erroneous reporting. Hence, anonymity of surveys is a boon and a bane. The sample sizes are skewed as it lacks representation of population absent on the Internet like the senile or the underprivileged. The illiterate population also lacks representation in survey-based research.

The “Enhancing the QUAlity and Transparency Of health Research” network (EQUATOR) provides two separate guidelines replete with checklists to ensure valid reporting of e-survey methodology. These include “The Checklist for Reporting Results of Internet E-Surveys” (CHERRIES) statement and “ The Journal of Medical Internet Research ” (JMIR) checklist.

COMMON TYPES OF SURVEY-BASED RESEARCH

From a clinician's standpoint, the common survey types include those centered around problems faced by the patients or physicians. 18 Surveys collecting the opinions of various clinicians on a debated clinical topic or feedback forms typically served after attending medical conferences or prescribing a new drug or trying a new method for a given procedure are also surveys. The formulation of clinical practice guidelines entails Delphi exercises using paper surveys, which are yet another form of survey-mediated research.

Size of the survey depends on its intent. They could be large or small surveys. Therefore, identification of the intent behind the survey is essential to allow the investigator to form a hypothesis and then explore it further. Large population-based or provider-based surveys are often done and generate mammoth data over the years. E.g. The National Health and Nutrition Examination Survey, The National Health Interview Survey and the National Ambulatory Medical Care Survey.

SCENARIOS FOR CONDUCTING SURVEY-BASED RESEARCH

Despite all said and done about the convenience of conducting survey-based research, it is prudent to conduct a feasibility check before embarking on one. Certain scenarios may be the key determinants in determining the fate of survey-based research ( Table 2 ).

ETHICS APPROVAL FOR SURVEY-BASED RESEARCH

Approval from the Institutional Review Board should be taken as per requirement according to the CHERRIES checklist. However, rules for approval are different as per the country or nation and therefore, local rules must be checked and followed. For instance, in India, the Indian Council of Medical Research released an article in 2017, stating that the concept of broad consent has been updated which is defined “consent for an unspecified range of future research subject to a few contents and/or process restrictions.” It talks about “the flexibility of Indian ethics committees to review a multicentric study proposal for research involving low or minimal risk, survey or studies using anonymized samples or data or low or minimal risk public health research.” The reporting of approvals received and applied for and the procedure of written, informed consent followed must be clear and transparent. 10 , 19

The use of incentives in surveys is also an ethical concern. 20 The different of incentives that can be used are monetary or non-monetary. Monetary incentives are usually discouraged as these may attract the wrong population due to the temptation of the monetary benefit. However, monetary incentives have been seen to make survey receive greater traction even though this is yet to proven. Monetary incentives are not only provided in terms of cash or cheque but also in the form of free articles, discount coupons, phone cards, e-money or cashback value. 21 These methods though tempting must be seldom used. If used, their use must be disclosed and justified in the report. The use of non-monetary incentives like a meeting with a famous personality or access to restricted and authorized areas. These can also help pique the interest of the respondents.

DESIGNING A SURVEY

As mentioned earlier, the design of a survey is reflective of the skill of the investigator curating it. 22 Survey builders can be used to design an efficient survey. These offer majority of the basic features needed to construct a survey, free of charge. Therefore, surveys can be designed from scratch, using pre-designed templates or by using previous survey designs as inspiration. Taking surveys could be made convenient by using the various aids available ( Table 1 ). Moreover, even the investigator should be mindful of the unintended response effects of ordering and context of survey questions. 23

Surveys using clear, unambiguous, simple and well-articulated language record precise answers. 24 A well-designed survey accounts for the culture, language and convenience of the target demographic. The age, region, country and occupation of the target population is also considered before constructing a survey. Consistency is maintained in the terms used in the survey and abbreviations are avoided to allow the respondents to have a clear understanding of the question being answered. Universal abbreviations or previously indexed abbreviations maintain the unambiguity of the survey.

Surveys beginning with broad, easy and non-specific questions as compared to sensitive, tedious and non-specific ones receive more accurate and complete answers. 25 Questionnaires designed such that the relatively tedious and long questions requiring the respondent to do some nit-picking are placed at the end improves the response rate of the survey. This prevents the respondent to be discouraged to answer the survey at the beginning itself and motivates the respondent to finish the survey at the end. All questions must provide a non-response option and all questions should be made mandatory to increase completeness of the survey. Questions can be framed in close-ended or open-ended fashion. However, close-ended questions are easier to analyze and are less tedious to answer by the respondent and therefore must be the main component in a survey. Open-ended questions have minimal use as they are tedious, take time to answer and require fine articulation of one's thoughts. Also, their minimal use is advocated because the interpretation of such answers requires dedication in terms of time and energy due to the diverse nature of the responses which is difficult to promise owing to the large sample sizes. 26 However, whenever the closed choices do not cover all probabilities, an open answer choice must be added. 27 , 28

Screening questions to meet certain criteria to gain access to the survey in cases where inclusion criteria need to be established to maintain authenticity of target demographic. Similarly, logic function can be used to apply an exclusion. This allows clean and clear record of responses and makes the job of an investigator easier. The respondents can or cannot have the option to return to the previous page or question to alter their answer as per the investigator's preference.

The range of responses received can be reduced in case of questions directed towards the feelings or opinions of people by using slider scales, or a Likert scale. 29 , 30 In questions having multiple answers, check boxes are efficient. When a large number of answers are possible, dropdown menus reduce the arduousness. 31 Matrix scales can be used to answer questions requiring grading or having a similar range of answers for multiple conditions. Maximum respondent participation and complete survey responses can be ensured by reducing the survey time. Quiz mode or weighted modes allow the respondent to shuffle between questions and allows scoring of quizzes and can be used to complement other weighted scoring systems. 32 A flowchart depicting a survey construct is presented as Fig. 1 .

Survey validation

Validation testing though tedious and meticulous, is worthy effort as the accuracy of a survey is determined by its validity. It is indicative of the of the sample of the survey and the specificity of the questions such that the data acquired is streamlined to answer the questions being posed or to determine a hypothesis. 33 , 34 Face validation determines the mannerism of construction of questions such that necessary data is collected. Content validation determines the relation of the topic being addressed and its related areas with the questions being asked. Internal validation makes sure that the questions being posed are directed towards the outcome of the survey. Finally, Test – retest validation determines the stability of questions over a period of time by testing the questionnaire twice and maintaining a time interval between the two tests. For surveys determining knowledge of respondents pertaining to a certain subject, it is advised to have a panel of experts for undertaking the validation process. 2 , 35

Reliability testing

If the questions in the survey are posed in a manner so as to elicit the same or similar response from the respondents irrespective of the language or construction of the question, the survey is said to be reliable. It is thereby, a marker of the consistency of the survey. This stands to be of considerable importance in knowledge-based researches where recall ability is tested by making the survey available for answering by the same participants at regular intervals. It can also be used to maintain authenticity of the survey, by varying the construction of the questions.

Designing a cover letter

A cover letter is the primary means of communication with the respondent, with the intent to introduce the respondent to the survey. A cover letter should include the purpose of the survey, details of those who are conducting it, including contact details in case clarifications are desired. It should also clearly depict the action required by the respondent. Data anonymization may be crucial to many respondents and is their right. This should be respected in a clear description of the data handling process while disseminating the survey. A good cover letter is the key to building trust with the respondent population and can be the forerunner to better response rates. Imparting a sense of purpose is vital to ideationally incentivize the respondent population. 36 , 37 Adding the credentials of the team conducting the survey may further aid the process. It is seen that an advance intimation of the survey prepares the respondents while improving their compliance.

The design of a cover letter needs much attention. It should be captivating, clear, precise and use a vocabulary and language specific to the target population for the survey. Active voice should be used to make a greater impact. Crowding of the details must be avoided. Using italics, bold fonts or underlining may be used to highlight critical information. the tone ought to be polite, respectful, and grateful in advance. The use of capital letters is at best avoided, as it is surrogate for shouting in verbal speech and may impart a bad taste.

The dates of the survey may be intimated, so the respondents may prepare themselves for taking it at a time conducive to them. While, emailing a closed group in a convenience sampled survey, using the name of the addressee may impart a customized experience and enhance trust building and possibly compliance. Appropriate use of salutations like Mr./Ms./Mrs. may be considered. Various portals such as SurveyMonkey allow the researchers to save an address list on the website. These may then be reached out using an embedded survey link from a verified email address to minimize bouncing back of emails.

The body of the cover letter must be short, crisp and not exceed 2–3 paragraphs under idea circumstances. Ernest efforts to protect confidentiality may go a long way in enhancing response rates. 38 While it is enticing to provide incentives to enhance response, these are best avoided. 38 , 39 In cases when indirect incentives are offered, such as provision of results of the survey, these may be clearly stated in the cover letter. Lastly, a formal closing note with the signatures of the lead investigator are welcome. 38 , 40

Designing questions

Well-constructed questionnaires are essentially the backbone of successful survey-based studies. With this type of research, the primary concern is the adequate promotion and dissemination of the questionnaire to the target population. The careful of selection of sample population, therefore, needs to be with minimal flaws. The method of conducting survey is an essential determinant of the response rate observed. 41 Broadly, surveys are of two types: closed and open. Depending on the sample population the method of conducting the survey must be determined.

Various doctors use their own patients as the target demographic, as it improves compliance. However, this is effective in surveys aiming towards a geographically specific, fairly common disease as the sample size needs to be adequate. Response bias can be identified by the data collected from respondent and non-respondent groups. 42 , 43 Therefore, to choose a target population whose database of baseline characteristics is already known is more efficacious. In cases of surveys focused on patients having a rare group of diseases, online surveys or e-surveys can be conducted. Data can also be gathered from the multiple national organizations and societies all over the world. 44 , 45 Computer generated random selection can be done from this data to choose participants and they can be reached out to using emails or social media platforms like WhatsApp and LinkedIn. In both these scenarios, closed questionnaires can be conducted. These have restricted access either through a URL link or through e-mail.

In surveys targeting an issue faced by a larger demographic (e.g. pandemics like the COVID-19, flu vaccines and socio-political scenarios), open surveys seem like the more viable option as they can be easily accessed by majority of the public and ensures large number of responses, thereby increasing the accuracy of the study. Survey length should be optimal to avoid poor response rates. 25 , 46

SURVEY DISSEMINATION

Uniform distribution of the survey ensures equitable opportunity to the entire target population to access the questionnaire and participate in it. While deciding the target demographic communities should be studied and the process of “lurking” is sometimes practiced. Multiple sampling methods are available ( Fig. 1 ). 47

Distribution of survey to the target demographic could be done using emails. Even though e-mails reach a large proportion of the target population, an unknown sender could be blocked, making the use of personal or a previously used email preferable for correspondence. Adding a cover letter along with the invite adds a personal touch and is hence, advisable. Some platforms allow the sender to link the survey portal with the sender's email after verifying it. Noteworthily, despite repeated email reminders, personal communication over the phone or instant messaging improved responses in the authors' experience. 48 , 49

Distribution of the survey over other social media platforms (SMPs, namely WhatsApp, Facebook, Instagram, Twitter, LinkedIn etc.) is also practiced. 50 , 51 , 52 Surveys distributed on every available platform ensures maximal outreach. 53 Other smartphone apps can also be used for wider survey dissemination. 50 , 54 It is important to be mindful of the target population while choosing the platform for dissemination of the survey as some SMPs such as WhatsApp are more popular in India, while others like WeChat are used more widely in China, and similarly Facebook among the European population. Professional accounts or popular social accounts can be used to promote and increase the outreach for a survey. 55 Incentives such as internet giveaways or meet and greets with their favorite social media influencer have been used to motivate people to participate.

However, social-media platforms do not allow calculation of the denominator of the target population, resulting in inability to gather the accurate response rate. Moreover, this method of collecting data may result in a respondent bias inherent to a community that has a greater online presence. 43 The inability to gather the demographics of the non-respondents (in a bid to identify and prove that they were no different from respondents) can be another challenge in convenience sampling, unlike in cohort-based studies.

Lastly, manually filling of surveys, over the telephone, by narrating the questions and answer choices to the respondents is used as the last-ditch resort to achieve a high desired response rate. 56 Studies reveal that surveys released on Mondays, Fridays, and Sundays receive more traction. Also, reminders set at regular intervals of time help receive more responses. Data collection can be improved in collaborative research by syncing surveys to fill out electronic case record forms. 57 , 58 , 59

Data anonymity refers to the protection of data received as a part of the survey. This data must be stored and handled in accordance with the patient privacy rights/privacy protection laws in reference to surveys. Ethically, the data must be received on a single source file handled by one individual. Sharing or publishing this data on any public platform is considered a breach of the patient's privacy. 11 In convenience sampled surveys conducted by e-mailing a predesignated group, the emails shall remain confidential, as inadvertent sharing of these as supplementary data in the manuscript may amount to a violation of the ethical standards. 60 A completely anonymized e-survey discourages collection of Internet protocol addresses in addition to other patient details such as names and emails.

Data anonymity gives the respondent the confidence to be candid and answer the survey without inhibitions. This is especially apparent in minority groups or communities facing societal bias (sex workers, transgenders, lower caste communities, women). Data anonymity aids in giving the respondents/participants respite regarding their privacy. As the respondents play a primary role in data collection, data anonymity plays a vital role in survey-based research.

DATA HANDLING OF SURVEYS

The data collected from the survey responses are compiled in a .xls, .csv or .xlxs format by the survey tool itself. The data can be viewed during the survey duration or after its completion. To ensure data anonymity, minimal number of people should have access to these results. The data should then be sifted through to invalidate false, incorrect or incomplete data. The relevant and complete data should then be analyzed qualitatively and quantitatively, as per the aim of the study. Statistical aids like pie charts, graphs and data tables can be used to report relative data.

ANALYSIS OF SURVEY DATA

Analysis of the responses recorded is done after the time made available to answer the survey is complete. This ensures that statistical and hypothetical conclusions are established after careful study of the entire database. Incomplete and complete answers can be used to make analysis conditional on the study. Survey-based studies require careful consideration of various aspects of the survey such as the time required to complete the survey. 61 Cut-off points in the time frame allow authentic answers to be recorded and analyzed as compared to disingenuous completed questionnaires. Methods of handling incomplete questionnaires and atypical timestamps must be pre-decided to maintain consistency. Since, surveys are the only way to reach people especially during the COVID-19 pandemic, disingenuous survey practices must not be followed as these will later be used to form a preliminary hypothesis.

REPORTING SURVEY-BASED RESEARCH

Reporting the survey-based research is by far the most challenging part of this method. A well-reported survey-based study is a comprehensive report covering all the aspects of conducting a survey-based research.

The design of the survey mentioning the target demographic, sample size, language, type, methodology of the survey and the inclusion-exclusion criteria followed comprises a descriptive report of a survey-based study. Details regarding the conduction of pilot-testing, validation testing, reliability testing and user-interface testing add value to the report and supports the data and analysis. Measures taken to prevent bias and ensure consistency and precision are key inclusions in a report. The report usually mentions approvals received, if any, along with the written, informed, consent taken from the participants to use the data received for research purposes. It also gives detailed accounts of the different distribution and promotional methods followed.

A detailed account of the data input and collection methods along with tools used to maintain the anonymity of the participants and the steps taken to ensure singular participation from individual respondents indicate a well-structured report. Descriptive information of the website used, visitors received and the externally influencing factors of the survey is included. Detailed reporting of the post-survey analysis including the number of analysts involved, data cleaning required, if any, statistical analysis done and the probable hypothesis concluded is a key feature of a well-reported survey-based research. Methods used to do statistical corrections, if used, should be included in the report. The EQUATOR network has two checklists, “The Checklist for Reporting Results of Internet E-Surveys” (CHERRIES) statement and “ The Journal of Medical Internet Research ” (JMIR) checklist, that can be utilized to construct a well-framed report. 62 , 63 Importantly, self-reporting of biases and errors avoids the carrying forward of false hypothesis as a basis of more advanced research. References should be cited using standard recommendations, and guided by the journal specifications. 64

CHOOSING A TARGET JOURNAL FOR SURVEY-BASED RESEARCH

Surveys can be published as original articles, brief reports or as a letter to the editor. Interestingly, most modern journals do not actively make mention of surveys in the instructions to the author. Thus, depending on the study design, the authors may choose the article category, cohort or case-control interview or survey-based study. It is prudent to mention the type of study in the title. Titles albeit not too long, should not exceed 10–12 words, and may feature the type of study design for clarity after a semicolon for greater citation potential.

While the choice of journal is largely based on the study subject and left to the authors discretion, it may be worthwhile exploring trends in a journal archive before proceeding with submission. 65 Although the article format is similar across most journals, specific rules relevant to the target journal may be followed for drafting the article structure before submission.

RETRACTION OF ARTICLES

Articles that are removed from the publication after being released are retracted articles. These are usually retracted when new discrepancies come to light regarding, the methodology followed, plagiarism, incorrect statistical analysis, inappropriate authorship, fake peer review, fake reporting and such. 66 A sufficient increase in such papers has been noticed. 67

We carried out a search of “surveys” on Retraction Watch on 31st August 2020 and received 81 search results published between November 2006 to June 2020, out of which 3 were repeated. Out of the 78 results, 37 (47.4%) articles were surveys, 23 (29.4%) showed as unknown types and 18 (23.2%) reported other types of research. ( Supplementary Table 1 ). Fig. 2 gives a detailed description of the causes of retraction of the surveys we found and its geographic distribution.

A good survey ought to be designed with a clear objective, the design being precise and focused with close-ended questions and all probabilities included. Use of rating scales, multiple choice questions and checkboxes and maintaining a logical question sequence engages the respondent while simplifying data entry and analysis for the investigator. Conducting pilot-testing is vital to identify and rectify deficiencies in the survey design and answer choices. The target demographic should be defined well, and invitations sent accordingly, with periodic reminders as appropriate. While reporting the survey, maintaining transparency in the methods employed and clearly stating the shortcomings and biases to prevent advocating an invalid hypothesis.

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

Author Contributions:

• Conceptualization: Gaur PS, Zimba O, Agarwal V, Gupta L.
• Visualization: Gaur PS, Zimba O, Agarwal V, Gupta L.
• Writing - original draft: Gaur PS, Gupta L.

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A 2022 Supreme Court opinion.

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The Gun Lobby’s Hidden Hand in the 2nd Amendment Battle

In the battle to dismantle gun restrictions, raging in America’s courts even as mass shootings become commonplace, one name keeps turning up in the legal briefs and judges’ rulings: William English, Ph.D.

A little-known political economist at Georgetown University, Dr. English conducted a largest-of-its-kind national survey that found gun owners frequently used their weapons for self-defense. That finding has been deployed by gun rights activists to notch legal victories with far-reaching consequences.

He has been cited in a landmark Supreme Court case that invalidated many restrictions on guns, and in scores of lawsuits around the country to overturn limits on assault weapons, high-capacity magazines and the carrying of firearms. His findings were also offered in another Supreme Court case this term, with a decision expected this month.

Dr. English seems at first glance to be an impartial researcher interested in data-driven insights. He has said his “scholarly arc” focuses on good public policy, and his lack of apparent ties to the gun lobby has lent credibility to his work.

But Dr. English’s interest in firearms is more than academic: He has received tens of thousands of dollars as a paid expert for gun rights advocates, and his survey work, which he says was part of a book project, originated as research for a National Rifle Association-backed lawsuit, The New York Times has found.

He has also increasingly drawn scrutiny in some courts over the reliability and integrity of his unpublished survey, which is the core of his research, and his refusal to disclose who paid for it. Other researchers say that the wording of some questions could elicit answers overstating defensive gun use, and that he cherry-picked pro-gun responses.

The Bruen decision in 2022 upended Second Amendment law by sweeping away any modern-day gun restrictions that could not be tied to a historical antecedent. The ruling led to a surge in firearms cases — to an annual average of 680 today compared with 122 in the decade before. Pro-gun rulings have also risen: The 74 issued last year make up a quarter of all such rulings since 2000, according to researchers at the University of Southern California. Courts have struck down restrictions on high-capacity magazines in Oregon, handgun purchases in Maryland and assault weapons in California.

Dr. English’s brief in the Bruen case.

Here’s an example of that missing context.

The paper quotes a survey question, omitting the setup to it, which is highlighted below in blue.

Many policymakers recognize that a large number of people participate in shooting sports but question how often guns are used for self-defense. Have you ever defended yourself or your property with a firearm, even if it was not fired or displayed? Please do not include military service, police work, or work as a security guard.

Other questions followed the same pattern of omission. This one, about AR-15-style rifles, included text before and after the question in the version respondents saw, but not in the paper.

Some have argued that few gun owners actually want or use guns that are commonly classified as ‘assault weapons.’ Have you ever owned an AR-15 or similarly styled rifle? You can include any rifles of this style that have been modified or moved to be compliant with local law. Answering this will help us establish how popular these types of firearms are.

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The state of AI in early 2024: Gen AI adoption spikes and starts to generate value

If 2023 was the year the world discovered generative AI (gen AI) , 2024 is the year organizations truly began using—and deriving business value from—this new technology. In the latest McKinsey Global Survey  on AI, 65 percent of respondents report that their organizations are regularly using gen AI, nearly double the percentage from our previous survey just ten months ago. Respondents’ expectations for gen AI’s impact remain as high as they were last year , with three-quarters predicting that gen AI will lead to significant or disruptive change in their industries in the years ahead.

About the authors

This article is a collaborative effort by Alex Singla , Alexander Sukharevsky , Lareina Yee , and Michael Chui , with Bryce Hall , representing views from QuantumBlack, AI by McKinsey, and McKinsey Digital.

Organizations are already seeing material benefits from gen AI use, reporting both cost decreases and revenue jumps in the business units deploying the technology. The survey also provides insights into the kinds of risks presented by gen AI—most notably, inaccuracy—as well as the emerging practices of top performers to mitigate those challenges and capture value.

AI adoption surges

Interest in generative AI has also brightened the spotlight on a broader set of AI capabilities. For the past six years, AI adoption by respondents’ organizations has hovered at about 50 percent. This year, the survey finds that adoption has jumped to 72 percent (Exhibit 1). And the interest is truly global in scope. Our 2023 survey found that AI adoption did not reach 66 percent in any region; however, this year more than two-thirds of respondents in nearly every region say their organizations are using AI. 1 Organizations based in Central and South America are the exception, with 58 percent of respondents working for organizations based in Central and South America reporting AI adoption. Looking by industry, the biggest increase in adoption can be found in professional services. 2 Includes respondents working for organizations focused on human resources, legal services, management consulting, market research, R&D, tax preparation, and training.

Also, responses suggest that companies are now using AI in more parts of the business. Half of respondents say their organizations have adopted AI in two or more business functions, up from less than a third of respondents in 2023 (Exhibit 2).

Gen AI adoption is most common in the functions where it can create the most value

Most respondents now report that their organizations—and they as individuals—are using gen AI. Sixty-five percent of respondents say their organizations are regularly using gen AI in at least one business function, up from one-third last year. The average organization using gen AI is doing so in two functions, most often in marketing and sales and in product and service development—two functions in which previous research  determined that gen AI adoption could generate the most value 3 “ The economic potential of generative AI: The next productivity frontier ,” McKinsey, June 14, 2023. —as well as in IT (Exhibit 3). The biggest increase from 2023 is found in marketing and sales, where reported adoption has more than doubled. Yet across functions, only two use cases, both within marketing and sales, are reported by 15 percent or more of respondents.

Gen AI also is weaving its way into respondents’ personal lives. Compared with 2023, respondents are much more likely to be using gen AI at work and even more likely to be using gen AI both at work and in their personal lives (Exhibit 4). The survey finds upticks in gen AI use across all regions, with the largest increases in Asia–Pacific and Greater China. Respondents at the highest seniority levels, meanwhile, show larger jumps in the use of gen Al tools for work and outside of work compared with their midlevel-management peers. Looking at specific industries, respondents working in energy and materials and in professional services report the largest increase in gen AI use.

Investments in gen AI and analytical AI are beginning to create value

The latest survey also shows how different industries are budgeting for gen AI. Responses suggest that, in many industries, organizations are about equally as likely to be investing more than 5 percent of their digital budgets in gen AI as they are in nongenerative, analytical-AI solutions (Exhibit 5). Yet in most industries, larger shares of respondents report that their organizations spend more than 20 percent on analytical AI than on gen AI. Looking ahead, most respondents—67 percent—expect their organizations to invest more in AI over the next three years.

Where are those investments paying off? For the first time, our latest survey explored the value created by gen AI use by business function. The function in which the largest share of respondents report seeing cost decreases is human resources. Respondents most commonly report meaningful revenue increases (of more than 5 percent) in supply chain and inventory management (Exhibit 6). For analytical AI, respondents most often report seeing cost benefits in service operations—in line with what we found last year —as well as meaningful revenue increases from AI use in marketing and sales.

Inaccuracy: The most recognized and experienced risk of gen AI use

As businesses begin to see the benefits of gen AI, they’re also recognizing the diverse risks associated with the technology. These can range from data management risks such as data privacy, bias, or intellectual property (IP) infringement to model management risks, which tend to focus on inaccurate output or lack of explainability. A third big risk category is security and incorrect use.

Respondents to the latest survey are more likely than they were last year to say their organizations consider inaccuracy and IP infringement to be relevant to their use of gen AI, and about half continue to view cybersecurity as a risk (Exhibit 7).

Conversely, respondents are less likely than they were last year to say their organizations consider workforce and labor displacement to be relevant risks and are not increasing efforts to mitigate them.

In fact, inaccuracy— which can affect use cases across the gen AI value chain , ranging from customer journeys and summarization to coding and creative content—is the only risk that respondents are significantly more likely than last year to say their organizations are actively working to mitigate.

Some organizations have already experienced negative consequences from the use of gen AI, with 44 percent of respondents saying their organizations have experienced at least one consequence (Exhibit 8). Respondents most often report inaccuracy as a risk that has affected their organizations, followed by cybersecurity and explainability.

Our previous research has found that there are several elements of governance that can help in scaling gen AI use responsibly, yet few respondents report having these risk-related practices in place. 4 “ Implementing generative AI with speed and safety ,” McKinsey Quarterly , March 13, 2024. For example, just 18 percent say their organizations have an enterprise-wide council or board with the authority to make decisions involving responsible AI governance, and only one-third say gen AI risk awareness and risk mitigation controls are required skill sets for technical talent.

Bringing gen AI capabilities to bear

The latest survey also sought to understand how, and how quickly, organizations are deploying these new gen AI tools. We have found three archetypes for implementing gen AI solutions : takers use off-the-shelf, publicly available solutions; shapers customize those tools with proprietary data and systems; and makers develop their own foundation models from scratch. 5 “ Technology’s generational moment with generative AI: A CIO and CTO guide ,” McKinsey, July 11, 2023. Across most industries, the survey results suggest that organizations are finding off-the-shelf offerings applicable to their business needs—though many are pursuing opportunities to customize models or even develop their own (Exhibit 9). About half of reported gen AI uses within respondents’ business functions are utilizing off-the-shelf, publicly available models or tools, with little or no customization. Respondents in energy and materials, technology, and media and telecommunications are more likely to report significant customization or tuning of publicly available models or developing their own proprietary models to address specific business needs.

Respondents most often report that their organizations required one to four months from the start of a project to put gen AI into production, though the time it takes varies by business function (Exhibit 10). It also depends upon the approach for acquiring those capabilities. Not surprisingly, reported uses of highly customized or proprietary models are 1.5 times more likely than off-the-shelf, publicly available models to take five months or more to implement.

Gen AI high performers are excelling despite facing challenges

Gen AI is a new technology, and organizations are still early in the journey of pursuing its opportunities and scaling it across functions. So it’s little surprise that only a small subset of respondents (46 out of 876) report that a meaningful share of their organizations’ EBIT can be attributed to their deployment of gen AI. Still, these gen AI leaders are worth examining closely. These, after all, are the early movers, who already attribute more than 10 percent of their organizations’ EBIT to their use of gen AI. Forty-two percent of these high performers say more than 20 percent of their EBIT is attributable to their use of nongenerative, analytical AI, and they span industries and regions—though most are at organizations with less than $1 billion in annual revenue. The AI-related practices at these organizations can offer guidance to those looking to create value from gen AI adoption at their own organizations.

To start, gen AI high performers are using gen AI in more business functions—an average of three functions, while others average two. They, like other organizations, are most likely to use gen AI in marketing and sales and product or service development, but they’re much more likely than others to use gen AI solutions in risk, legal, and compliance; in strategy and corporate finance; and in supply chain and inventory management. They’re more than three times as likely as others to be using gen AI in activities ranging from processing of accounting documents and risk assessment to R&D testing and pricing and promotions. While, overall, about half of reported gen AI applications within business functions are utilizing publicly available models or tools, gen AI high performers are less likely to use those off-the-shelf options than to either implement significantly customized versions of those tools or to develop their own proprietary foundation models.

What else are these high performers doing differently? For one thing, they are paying more attention to gen-AI-related risks. Perhaps because they are further along on their journeys, they are more likely than others to say their organizations have experienced every negative consequence from gen AI we asked about, from cybersecurity and personal privacy to explainability and IP infringement. Given that, they are more likely than others to report that their organizations consider those risks, as well as regulatory compliance, environmental impacts, and political stability, to be relevant to their gen AI use, and they say they take steps to mitigate more risks than others do.

Gen AI high performers are also much more likely to say their organizations follow a set of risk-related best practices (Exhibit 11). For example, they are nearly twice as likely as others to involve the legal function and embed risk reviews early on in the development of gen AI solutions—that is, to “ shift left .” They’re also much more likely than others to employ a wide range of other best practices, from strategy-related practices to those related to scaling.

In addition to experiencing the risks of gen AI adoption, high performers have encountered other challenges that can serve as warnings to others (Exhibit 12). Seventy percent say they have experienced difficulties with data, including defining processes for data governance, developing the ability to quickly integrate data into AI models, and an insufficient amount of training data, highlighting the essential role that data play in capturing value. High performers are also more likely than others to report experiencing challenges with their operating models, such as implementing agile ways of working and effective sprint performance management.

About the research

The online survey was in the field from February 22 to March 5, 2024, and garnered responses from 1,363 participants representing the full range of regions, industries, company sizes, functional specialties, and tenures. Of those respondents, 981 said their organizations had adopted AI in at least one business function, and 878 said their organizations were regularly using gen AI in at least one function. To adjust for differences in response rates, the data are weighted by the contribution of each respondent’s nation to global GDP.

Alex Singla and Alexander Sukharevsky  are global coleaders of QuantumBlack, AI by McKinsey, and senior partners in McKinsey’s Chicago and London offices, respectively; Lareina Yee  is a senior partner in the Bay Area office, where Michael Chui , a McKinsey Global Institute partner, is a partner; and Bryce Hall  is an associate partner in the Washington, DC, office.

They wish to thank Kaitlin Noe, Larry Kanter, Mallika Jhamb, and Shinjini Srivastava for their contributions to this work.

This article was edited by Heather Hanselman, a senior editor in McKinsey’s Atlanta office.

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