research methodology report example

15 Research Methodology Examples

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Research methodologies can roughly be categorized into three group: quantitative, qualitative, and mixed-methods.

• Qualitative Research : This methodology is based on obtaining deep, contextualized, non-numerical data. It can occur, for example, through open-ended questioning of research particiapnts in order to understand human behavior. It’s all about describing and analyzing subjective phenomena such as emotions or experiences.
• Quantitative Research: This methodology is rationally-based and relies heavily on numerical analysis of empirical data . With quantitative research, you aim for objectivity by creating hypotheses and testing them through experiments or surveys, which allow for statistical analyses.
• Mixed-Methods Research: Mixed-methods research combines both previous types into one project. We have more flexibility when designing our research study with mixed methods since we can use multiple approaches depending on our needs at each time. Using mixed methods can help us validate our results and offer greater predictability than just either type of methodology alone could provide.

Below are research methodologies that fit into each category.

Qualitative Research Methodologies

1. case study.

Conducts an in-depth examination of a specific case, individual, or event to understand a phenomenon.

Instead of examining a whole population for numerical trend data, case study researchers seek in-depth explanations of one event.

The benefit of case study research is its ability to elucidate overlooked details of interesting cases of a phenomenon (Busetto, Wick & Gumbinger, 2020). It offers deep insights for empathetic, reflective, and thoughtful understandings of that phenomenon.

However, case study findings aren’t transferrable to new contexts or for population-wide predictions. Instead, they inform practitioner understandings for nuanced, deep approaches to future instances (Liamputtong, 2020).

2. Grounded Theory

Grounded theory involves generating hypotheses and theories through the collection and interpretation of data (Faggiolani, n.d.). Its distinguishing features is that it doesn’t test a hypothesis generated prior to analysis, but rather generates a hypothesis or ‘theory’ that emerges from the data.

It also involves the application of inductive reasoning and is often contrasted with the hypothetico-deductive model of scientific research. This research methodology was developed by Barney Glaser and Anselm Strauss in the 1960s (Glaser & Strauss, 2009). 

The basic difference between traditional scientific approaches to research and grounded theory is that the latter begins with a question, then collects data, and the theoretical framework is said to emerge later from this data.

By contrast, scientists usually begin with an existing theoretical framework , develop hypotheses, and only then start collecting data to verify or falsify the hypotheses.

3. Ethnography

In ethnographic research , the researcher immerses themselves within the group they are studying, often for long periods of time.

This type of research aims to understand the shared beliefs, practices, and values of a particular community by immersing the researcher within the cultural group.

Although ethnographic research cannot predict or identify trends in an entire population, it can create detailed explanations of cultural practices and comparisons between social and cultural groups.

When a person conducts an ethnographic study of themselves or their own culture, it can be considered autoethnography .

Its strength lies in producing comprehensive accounts of groups of people and their interactions.

Common methods researchers use during an ethnographic study include participant observation , thick description, unstructured interviews, and field notes vignettes. These methods can provide detailed and contextualized descriptions of their subjects.

Example Study

Liquidated: An Ethnography of Wall Street by Karen Ho involves an anthropologist who embeds herself with Wall Street firms to study the culture of Wall Street bankers and how this culture affects the broader economy and world.

4. Phenomenology

Phenomenology to understand and describe individuals’ lived experiences concerning a specific phenomenon.

As a research methodology typically used in the social sciences , phenomenology involves the study of social reality as a product of intersubjectivity (the intersection of people’s cognitive perspectives) (Zahavi & Overgaard, n.d.).

This philosophical approach was first developed by Edmund Husserl.

5. Narrative Research

Narrative research explores personal stories and experiences to understand their meanings and interpretations.

It is also known as narrative inquiry and narrative analysis(Riessman, 1993).

This approach to research uses qualitative material like journals, field notes, letters, interviews, texts, photos, etc., as its data.

It is aimed at understanding the way people create meaning through narratives (Clandinin & Connelly, 2004).

6. Discourse Analysis

A discourse analysis examines the structure, patterns, and functions of language in context to understand how the text produces social constructs.

This methodology is common in critical theory , poststructuralism , and postmodernism. Its aim is to understand how language constructs discourses (roughly interpreted as “ways of thinking and constructing knowledge”).

As a qualitative methodology , its focus is on developing themes through close textual analysis rather than using numerical methods. Common methods for extracting data include semiotics and linguistic analysis.

7. Action Research

Action research involves researchers working collaboratively with stakeholders to address problems, develop interventions, and evaluate effectiveness.

Action research is a methodology and philosophy of research that is common in the social sciences.

The term was first coined in 1944 by Kurt Lewin, a German-American psychologist who also introduced applied research and group communication (Altrichter & Gstettner, 1993).

Lewin originally defined action research as involving two primary processes: taking action and doing research (Lewin, 1946).

Action research involves planning, action, and information-seeking about the result of the action.

Since Lewin’s original formulation, many different theoretical approaches to action research have been developed. These include action science, participatory action research, cooperative inquiry, and living educational theory among others.

Using Digital Sandbox Gaming to Improve Creativity Within Boys’ Writing (Ellison & Drew, 2019) is a study conducted by a school teacher who used video games to help teach his students English. It involved action research, where he interviewed his students to see if the use of games as stimuli for storytelling helped draw them into the learning experience, and iterated on his teaching style based on their feedback (disclaimer: I am the second author of this study).

See More: Examples of Qualitative Research

Quantitative Research Methodologies

8. experimental design.

As the name suggests, this type of research is based on testing hypotheses in experimental settings by manipulating variables and observing their effects on other variables.

The main benefit lies in its ability to manipulate specific variables to determine their effect on outcomes which is a great method for those looking for causational links in their research.

This is common, for example, in high-school science labs, where students are asked to introduce a variable into a setting in order to examine its effect.

9. Non-Experimental Design

Non-experimental design observes and measures associations between variables without manipulating them.

It can take, for example, the form of a ‘fly on the wall’ observation of a phenomenon, allowing researchers to examine authentic settings and changes that occur naturally in the environment.

10. Cross-Sectional Design

Cross-sectional design involves analyzing variables pertaining to a specific time period and at that exact moment.

This approach allows for an extensive examination and comparison of distinct and independent subjects, thereby offering advantages over qualitative methodologies such as case studies or surveys.

While cross-sectional design can be extremely useful in taking a ‘snapshot in time’, as a standalone method, it is not useful for examining changes in subjects after an intervention. The next methodology addresses this issue.

The prime example of this type of study is a census. A population census is mailed out to every house in the country, and each household must complete the census on the same evening. This allows the government to gather a snapshot of the nation’s demographics, beliefs, religion, and so on.

11. Longitudinal Design

Longitudinal research gathers data from the same subjects over an extended period to analyze changes and development.

In contrast to cross-sectional tactics, longitudinal designs examine variables more than once, over a pre-determined time span, allowing for multiple data points to be taken at different times.

A cross-sectional design is also useful for examining cohort effects , by comparing differences or changes in multiple different generations’ beliefs over time.

With multiple data points collected over extended periods ,it’s possible to examine continuous changes within things like population dynamics or consumer behavior. This makes detailed analysis of change possible.

12. Quasi-Experimental Design

Quasi-experimental design involves manipulating variables for analysis, but uses pre-existing groups of subjects rather than random groups.

Because the groups of research participants already exist, they cannot be randomly assigned to a cohort as with a true experimental design study. This makes inferring a causal relationship more difficult, but is nonetheless often more feasible in real-life settings.

Quasi-experimental designs are generally considered inferior to true experimental designs.

13. Correlational Research

Correlational research examines the relationships between two or more variables, determining the strength and direction of their association.

Similar to quasi-experimental methods, this type of research focuses on relationship differences between variables.

This approach provides a fast and easy way to make initial hypotheses based on either positive or negative correlation trends that can be observed within dataset.

Methods used for data analysis may include statistic correlations such as Pearson’s or Spearman’s.

Mixed-Methods Research Methodologies

14. sequential explanatory design (quan→qual).

This methodology involves conducting quantitative analysis first, then supplementing it with a qualitative study.

It begins by collecting quantitative data that is then analyzed to determine any significant patterns or trends.

Secondly, qualitative methods are employed. Their intent is to help interpret and expand the quantitative results.

This offers greater depth into understanding both large and smaller aspects of research questions being addressed.

The rationale behind this approach is to ensure that your data collection generates richer context for gaining insight into the particular issue across different levels, integrating in one study, qualitative exploration as well as statistical procedures.

15. Sequential Exploratory Design (QUAL→QUAN)

This methodology goes in the other direction, starting with qualitative analysis and ending with quantitative analysis.

It starts with qualitative research that delves deeps into complex areas and gathers rich information through interviewing or observing participants.

After this stage of exploration comes to an end, quantitative techniques are used to analyze the collected data through inferential statistics.

The idea is that a qualitative study can arm the researchers with a strong hypothesis testing framework, which they can then apply to a larger sample size using qualitative methods.

When I first took research classes, I had a lot of trouble distinguishing between methodologies and methods.

The key is to remember that the methodology sets the direction, while the methods are the specific tools to be used. A good analogy is transport: first you need to choose a mode (public transport, private transport, motorized transit, non-motorized transit), then you can choose a tool (bus, car, bike, on foot).

While research methodologies can be split into three types, each type has many different nuanced methodologies that can be chosen, before you then choose the methods – or tools – to use in the study. Each has its own strengths and weaknesses, so choose wisely!

Altrichter, H., & Gstettner, P. (1993). Action Research: A closed chapter in the history of German social science? Educational Action Research , 1 (3), 329–360. https://doi.org/10.1080/0965079930010302

Audi, R. (1999). The Cambridge dictionary of philosophy . Cambridge ; New York : Cambridge University Press. http://archive.org/details/cambridgediction00audi

Clandinin, D. J., & Connelly, F. M. (2004). Narrative Inquiry: Experience and Story in Qualitative Research . John Wiley & Sons.

Creswell, J. W. (2008). Educational Research: Planning, Conducting, and Evaluating Quantitative and Qualitative Research . Pearson/Merrill Prentice Hall.

Faggiolani, C. (n.d.). Perceived Identity: Applying Grounded Theory in Libraries . https://doi.org/10.4403/jlis.it-4592

Gauch, H. G. (2002). Scientific Method in Practice . Cambridge University Press.

Glaser, B. G., & Strauss, A. L. (2009). The Discovery of Grounded Theory: Strategies for Qualitative Research . Transaction Publishers.

Kothari, C. R. (2004). Research Methodology: Methods and Techniques . New Age International.

Kuada, J. (2012). Research Methodology: A Project Guide for University Students . Samfundslitteratur.

Lewin, K. (1946). Action research and minority problems. Journal of Social Issues , 2,  4 , 34–46. https://doi.org/10.1111/j.1540-4560.1946.tb02295.x

Mills, J., Bonner, A., & Francis, K. (2006). The Development of Constructivist Grounded Theory. International Journal of Qualitative Methods , 5 (1), 25–35. https://doi.org/10.1177/160940690600500103

Mingers, J., & Willcocks, L. (2017). An integrative semiotic methodology for IS research. Information and Organization , 27 (1), 17–36. https://doi.org/10.1016/j.infoandorg.2016.12.001

OECD. (2015). Frascati Manual 2015: Guidelines for Collecting and Reporting Data on Research and Experimental Development . Organisation for Economic Co-operation and Development. https://www.oecd-ilibrary.org/science-and-technology/frascati-manual-2015_9789264239012-en

Peirce, C. S. (1992). The Essential Peirce, Volume 1: Selected Philosophical Writings (1867–1893) . Indiana University Press.

Reese, W. L. (1980). Dictionary of Philosophy and Religion: Eastern and Western Thought . Humanities Press.

Riessman, C. K. (1993). Narrative analysis . Sage Publications, Inc.

Saussure, F. de, & Riedlinger, A. (1959). Course in General Linguistics . Philosophical Library.

Thomas, C. G. (2021). Research Methodology and Scientific Writing . Springer Nature.

Zahavi, D., & Overgaard, S. (n.d.). Phenomenological Sociology—The Subjectivity of Everyday Life .

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Home » Research Report – Example, Writing Guide and Types

Research Report – Example, Writing Guide and Types

Table of Contents

Research Report

Definition:

Research Report is a written document that presents the results of a research project or study, including the research question, methodology, results, and conclusions, in a clear and objective manner.

The purpose of a research report is to communicate the findings of the research to the intended audience, which could be other researchers, stakeholders, or the general public.

Components of Research Report

Components of Research Report are as follows:

Introduction

The introduction sets the stage for the research report and provides a brief overview of the research question or problem being investigated. It should include a clear statement of the purpose of the study and its significance or relevance to the field of research. It may also provide background information or a literature review to help contextualize the research.

Literature Review

The literature review provides a critical analysis and synthesis of the existing research and scholarship relevant to the research question or problem. It should identify the gaps, inconsistencies, and contradictions in the literature and show how the current study addresses these issues. The literature review also establishes the theoretical framework or conceptual model that guides the research.

Methodology

The methodology section describes the research design, methods, and procedures used to collect and analyze data. It should include information on the sample or participants, data collection instruments, data collection procedures, and data analysis techniques. The methodology should be clear and detailed enough to allow other researchers to replicate the study.

The results section presents the findings of the study in a clear and objective manner. It should provide a detailed description of the data and statistics used to answer the research question or test the hypothesis. Tables, graphs, and figures may be included to help visualize the data and illustrate the key findings.

The discussion section interprets the results of the study and explains their significance or relevance to the research question or problem. It should also compare the current findings with those of previous studies and identify the implications for future research or practice. The discussion should be based on the results presented in the previous section and should avoid speculation or unfounded conclusions.

The conclusion summarizes the key findings of the study and restates the main argument or thesis presented in the introduction. It should also provide a brief overview of the contributions of the study to the field of research and the implications for practice or policy.

The references section lists all the sources cited in the research report, following a specific citation style, such as APA or MLA.

The appendices section includes any additional material, such as data tables, figures, or instruments used in the study, that could not be included in the main text due to space limitations.

Types of Research Report

Types of Research Report are as follows:

Thesis is a type of research report. A thesis is a long-form research document that presents the findings and conclusions of an original research study conducted by a student as part of a graduate or postgraduate program. It is typically written by a student pursuing a higher degree, such as a Master’s or Doctoral degree, although it can also be written by researchers or scholars in other fields.

Research Paper

Research paper is a type of research report. A research paper is a document that presents the results of a research study or investigation. Research papers can be written in a variety of fields, including science, social science, humanities, and business. They typically follow a standard format that includes an introduction, literature review, methodology, results, discussion, and conclusion sections.

Technical Report

A technical report is a detailed report that provides information about a specific technical or scientific problem or project. Technical reports are often used in engineering, science, and other technical fields to document research and development work.

Progress Report

A progress report provides an update on the progress of a research project or program over a specific period of time. Progress reports are typically used to communicate the status of a project to stakeholders, funders, or project managers.

Feasibility Report

A feasibility report assesses the feasibility of a proposed project or plan, providing an analysis of the potential risks, benefits, and costs associated with the project. Feasibility reports are often used in business, engineering, and other fields to determine the viability of a project before it is undertaken.

Field Report

A field report documents observations and findings from fieldwork, which is research conducted in the natural environment or setting. Field reports are often used in anthropology, ecology, and other social and natural sciences.

Experimental Report

An experimental report documents the results of a scientific experiment, including the hypothesis, methods, results, and conclusions. Experimental reports are often used in biology, chemistry, and other sciences to communicate the results of laboratory experiments.

Case Study Report

A case study report provides an in-depth analysis of a specific case or situation, often used in psychology, social work, and other fields to document and understand complex cases or phenomena.

Literature Review Report

A literature review report synthesizes and summarizes existing research on a specific topic, providing an overview of the current state of knowledge on the subject. Literature review reports are often used in social sciences, education, and other fields to identify gaps in the literature and guide future research.

Research Report Example

Following is a Research Report Example sample for Students:

Title: The Impact of Social Media on Academic Performance among High School Students

This study aims to investigate the relationship between social media use and academic performance among high school students. The study utilized a quantitative research design, which involved a survey questionnaire administered to a sample of 200 high school students. The findings indicate that there is a negative correlation between social media use and academic performance, suggesting that excessive social media use can lead to poor academic performance among high school students. The results of this study have important implications for educators, parents, and policymakers, as they highlight the need for strategies that can help students balance their social media use and academic responsibilities.

Introduction:

Social media has become an integral part of the lives of high school students. With the widespread use of social media platforms such as Facebook, Twitter, Instagram, and Snapchat, students can connect with friends, share photos and videos, and engage in discussions on a range of topics. While social media offers many benefits, concerns have been raised about its impact on academic performance. Many studies have found a negative correlation between social media use and academic performance among high school students (Kirschner & Karpinski, 2010; Paul, Baker, & Cochran, 2012).

Given the growing importance of social media in the lives of high school students, it is important to investigate its impact on academic performance. This study aims to address this gap by examining the relationship between social media use and academic performance among high school students.

Methodology:

The study utilized a quantitative research design, which involved a survey questionnaire administered to a sample of 200 high school students. The questionnaire was developed based on previous studies and was designed to measure the frequency and duration of social media use, as well as academic performance.

The participants were selected using a convenience sampling technique, and the survey questionnaire was distributed in the classroom during regular school hours. The data collected were analyzed using descriptive statistics and correlation analysis.

The findings indicate that the majority of high school students use social media platforms on a daily basis, with Facebook being the most popular platform. The results also show a negative correlation between social media use and academic performance, suggesting that excessive social media use can lead to poor academic performance among high school students.

Discussion:

The results of this study have important implications for educators, parents, and policymakers. The negative correlation between social media use and academic performance suggests that strategies should be put in place to help students balance their social media use and academic responsibilities. For example, educators could incorporate social media into their teaching strategies to engage students and enhance learning. Parents could limit their children’s social media use and encourage them to prioritize their academic responsibilities. Policymakers could develop guidelines and policies to regulate social media use among high school students.

Conclusion:

In conclusion, this study provides evidence of the negative impact of social media on academic performance among high school students. The findings highlight the need for strategies that can help students balance their social media use and academic responsibilities. Further research is needed to explore the specific mechanisms by which social media use affects academic performance and to develop effective strategies for addressing this issue.

Limitations:

One limitation of this study is the use of convenience sampling, which limits the generalizability of the findings to other populations. Future studies should use random sampling techniques to increase the representativeness of the sample. Another limitation is the use of self-reported measures, which may be subject to social desirability bias. Future studies could use objective measures of social media use and academic performance, such as tracking software and school records.

Implications:

The findings of this study have important implications for educators, parents, and policymakers. Educators could incorporate social media into their teaching strategies to engage students and enhance learning. For example, teachers could use social media platforms to share relevant educational resources and facilitate online discussions. Parents could limit their children’s social media use and encourage them to prioritize their academic responsibilities. They could also engage in open communication with their children to understand their social media use and its impact on their academic performance. Policymakers could develop guidelines and policies to regulate social media use among high school students. For example, schools could implement social media policies that restrict access during class time and encourage responsible use.

References:

• Kirschner, P. A., & Karpinski, A. C. (2010). Facebook® and academic performance. Computers in Human Behavior, 26(6), 1237-1245.
• Paul, J. A., Baker, H. M., & Cochran, J. D. (2012). Effect of online social networking on student academic performance. Journal of the Research Center for Educational Technology, 8(1), 1-19.
• Pantic, I. (2014). Online social networking and mental health. Cyberpsychology, Behavior, and Social Networking, 17(10), 652-657.
• Rosen, L. D., Carrier, L. M., & Cheever, N. A. (2013). Facebook and texting made me do it: Media-induced task-switching while studying. Computers in Human Behavior, 29(3), 948-958.

Note*: Above mention, Example is just a sample for the students’ guide. Do not directly copy and paste as your College or University assignment. Kindly do some research and Write your own.

Applications of Research Report

Research reports have many applications, including:

• Communicating research findings: The primary application of a research report is to communicate the results of a study to other researchers, stakeholders, or the general public. The report serves as a way to share new knowledge, insights, and discoveries with others in the field.
• Informing policy and practice : Research reports can inform policy and practice by providing evidence-based recommendations for decision-makers. For example, a research report on the effectiveness of a new drug could inform regulatory agencies in their decision-making process.
• Supporting further research: Research reports can provide a foundation for further research in a particular area. Other researchers may use the findings and methodology of a report to develop new research questions or to build on existing research.
• Evaluating programs and interventions : Research reports can be used to evaluate the effectiveness of programs and interventions in achieving their intended outcomes. For example, a research report on a new educational program could provide evidence of its impact on student performance.
• Demonstrating impact : Research reports can be used to demonstrate the impact of research funding or to evaluate the success of research projects. By presenting the findings and outcomes of a study, research reports can show the value of research to funders and stakeholders.
• Enhancing professional development : Research reports can be used to enhance professional development by providing a source of information and learning for researchers and practitioners in a particular field. For example, a research report on a new teaching methodology could provide insights and ideas for educators to incorporate into their own practice.

How to write Research Report

Here are some steps you can follow to write a research report:

• Identify the research question: The first step in writing a research report is to identify your research question. This will help you focus your research and organize your findings.
• Conduct research : Once you have identified your research question, you will need to conduct research to gather relevant data and information. This can involve conducting experiments, reviewing literature, or analyzing data.
• Organize your findings: Once you have gathered all of your data, you will need to organize your findings in a way that is clear and understandable. This can involve creating tables, graphs, or charts to illustrate your results.
• Write the report: Once you have organized your findings, you can begin writing the report. Start with an introduction that provides background information and explains the purpose of your research. Next, provide a detailed description of your research methods and findings. Finally, summarize your results and draw conclusions based on your findings.
• Proofread and edit: After you have written your report, be sure to proofread and edit it carefully. Check for grammar and spelling errors, and make sure that your report is well-organized and easy to read.
• Include a reference list: Be sure to include a list of references that you used in your research. This will give credit to your sources and allow readers to further explore the topic if they choose.
• Format your report: Finally, format your report according to the guidelines provided by your instructor or organization. This may include formatting requirements for headings, margins, fonts, and spacing.

Purpose of Research Report

The purpose of a research report is to communicate the results of a research study to a specific audience, such as peers in the same field, stakeholders, or the general public. The report provides a detailed description of the research methods, findings, and conclusions.

Some common purposes of a research report include:

• Sharing knowledge: A research report allows researchers to share their findings and knowledge with others in their field. This helps to advance the field and improve the understanding of a particular topic.
• Identifying trends: A research report can identify trends and patterns in data, which can help guide future research and inform decision-making.
• Addressing problems: A research report can provide insights into problems or issues and suggest solutions or recommendations for addressing them.
• Evaluating programs or interventions : A research report can evaluate the effectiveness of programs or interventions, which can inform decision-making about whether to continue, modify, or discontinue them.
• Meeting regulatory requirements: In some fields, research reports are required to meet regulatory requirements, such as in the case of drug trials or environmental impact studies.

When to Write Research Report

A research report should be written after completing the research study. This includes collecting data, analyzing the results, and drawing conclusions based on the findings. Once the research is complete, the report should be written in a timely manner while the information is still fresh in the researcher’s mind.

In academic settings, research reports are often required as part of coursework or as part of a thesis or dissertation. In this case, the report should be written according to the guidelines provided by the instructor or institution.

In other settings, such as in industry or government, research reports may be required to inform decision-making or to comply with regulatory requirements. In these cases, the report should be written as soon as possible after the research is completed in order to inform decision-making in a timely manner.

Overall, the timing of when to write a research report depends on the purpose of the research, the expectations of the audience, and any regulatory requirements that need to be met. However, it is important to complete the report in a timely manner while the information is still fresh in the researcher’s mind.

Characteristics of Research Report

There are several characteristics of a research report that distinguish it from other types of writing. These characteristics include:

• Objective: A research report should be written in an objective and unbiased manner. It should present the facts and findings of the research study without any personal opinions or biases.
• Systematic: A research report should be written in a systematic manner. It should follow a clear and logical structure, and the information should be presented in a way that is easy to understand and follow.
• Detailed: A research report should be detailed and comprehensive. It should provide a thorough description of the research methods, results, and conclusions.
• Accurate : A research report should be accurate and based on sound research methods. The findings and conclusions should be supported by data and evidence.
• Organized: A research report should be well-organized. It should include headings and subheadings to help the reader navigate the report and understand the main points.
• Clear and concise: A research report should be written in clear and concise language. The information should be presented in a way that is easy to understand, and unnecessary jargon should be avoided.
• Citations and references: A research report should include citations and references to support the findings and conclusions. This helps to give credit to other researchers and to provide readers with the opportunity to further explore the topic.

Advantages of Research Report

Research reports have several advantages, including:

• Communicating research findings: Research reports allow researchers to communicate their findings to a wider audience, including other researchers, stakeholders, and the general public. This helps to disseminate knowledge and advance the understanding of a particular topic.
• Providing evidence for decision-making : Research reports can provide evidence to inform decision-making, such as in the case of policy-making, program planning, or product development. The findings and conclusions can help guide decisions and improve outcomes.
• Supporting further research: Research reports can provide a foundation for further research on a particular topic. Other researchers can build on the findings and conclusions of the report, which can lead to further discoveries and advancements in the field.
• Demonstrating expertise: Research reports can demonstrate the expertise of the researchers and their ability to conduct rigorous and high-quality research. This can be important for securing funding, promotions, and other professional opportunities.
• Meeting regulatory requirements: In some fields, research reports are required to meet regulatory requirements, such as in the case of drug trials or environmental impact studies. Producing a high-quality research report can help ensure compliance with these requirements.

Limitations of Research Report

Despite their advantages, research reports also have some limitations, including:

• Time-consuming: Conducting research and writing a report can be a time-consuming process, particularly for large-scale studies. This can limit the frequency and speed of producing research reports.
• Expensive: Conducting research and producing a report can be expensive, particularly for studies that require specialized equipment, personnel, or data. This can limit the scope and feasibility of some research studies.
• Limited generalizability: Research studies often focus on a specific population or context, which can limit the generalizability of the findings to other populations or contexts.
• Potential bias : Researchers may have biases or conflicts of interest that can influence the findings and conclusions of the research study. Additionally, participants may also have biases or may not be representative of the larger population, which can limit the validity and reliability of the findings.
• Accessibility: Research reports may be written in technical or academic language, which can limit their accessibility to a wider audience. Additionally, some research may be behind paywalls or require specialized access, which can limit the ability of others to read and use the findings.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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• Tags: Academic Research , Research

No dissertation or research paper is complete without the research methodology section. Since this is the chapter where you explain how you carried out your research, this is where all the meat is! Here’s where you clearly lay out the steps you have taken to test your hypothesis or research problem.

Through this blog, we’ll unravel the complexities and meaning of research methodology in academic writing , from its fundamental principles and ethics to the diverse types of research methodology in use today. Alongside offering research methodology examples, we aim to guide you on how to write research methodology, ensuring your research endeavors are both impactful and impeccably grounded!

Ensure your research methodology is foolproof. Learn more

Let’s first take a closer look at a simple research methodology definition:

Defining what is research methodology

Research methodology is the set of procedures and techniques used to collect, analyze, and interpret data to understand and solve a research problem. Methodology in research not only includes the design and methods but also the basic principles that guide the choice of specific methods.

Grasping the concept of methodology in research is essential for students and scholars, as it demonstrates the thorough and structured method used to explore a hypothesis or research question. Understanding the definition of methodology in research aids in identifying the methods used to collect data. Be it through any type of research method approach, ensuring adherence to the proper research paper format is crucial.

Now let’s explore some research methodology types:

Types of research methodology

1. qualitative research methodology.

Qualitative research methodology is aimed at understanding concepts, thoughts, or experiences. This approach is descriptive and is often utilized to gather in-depth insights into people’s attitudes, behaviors, or cultures. Qualitative research methodology involves methods like interviews, focus groups, and observation. The strength of this methodology lies in its ability to provide contextual richness.

2. Quantitative research methodology

Quantitative research methodology, on the other hand, is focused on quantifying the problem by generating numerical data or data that can be transformed into usable statistics. It uses measurable data to formulate facts and uncover patterns in research. Quantitative research methodology typically involves surveys, experiments, or statistical analysis. This methodology is appreciated for its ability to produce objective results that are generalizable to a larger population.

3. Mixed-Methods research methodology

Mixed-methods research combines both qualitative and quantitative research methodologies to provide a more comprehensive understanding of the research problem. This approach leverages the strengths of both methodologies to provide a deeper insight into the research question of a research paper .

Research methodology vs. research methods

The research methodology or design is the overall strategy and rationale that you used to carry out the research. Whereas, research methods are the specific tools and processes you use to gather and understand the data you need to test your hypothesis.

Research methodology examples and application

To further understand research methodology, let’s explore some examples of research methodology:

a. Qualitative research methodology example: A study exploring the impact of author branding on author popularity might utilize in-depth interviews to gather personal experiences and perspectives.

b. Quantitative research methodology example: A research project investigating the effects of a book promotion technique on book sales could employ a statistical analysis of profit margins and sales before and after the implementation of the method.

c. Mixed-Methods research methodology example: A study examining the relationship between social media use and academic performance might combine both qualitative and quantitative approaches. It could include surveys to quantitatively assess the frequency of social media usage and its correlation with grades, alongside focus groups or interviews to qualitatively explore students’ perceptions and experiences regarding how social media affects their study habits and academic engagement.

These examples highlight the meaning of methodology in research and how it guides the research process, from data collection to analysis, ensuring the study’s objectives are met efficiently.

Importance of methodology in research papers

When it comes to writing your study, the methodology in research papers or a dissertation plays a pivotal role. A well-crafted methodology section of a research paper or thesis not only enhances the credibility of your research but also provides a roadmap for others to replicate or build upon your work.

How to structure the research methods chapter

Wondering how to write the research methodology section? Follow these steps to create a strong methods chapter:

Step 1: Explain your research methodology

At the start of a research paper , you would have provided the background of your research and stated your hypothesis or research problem. In this section, you will elaborate on your research strategy. 

Begin by restating your research question and proceed to explain what type of research you opted for to test it. Depending on your research, here are some questions you can consider: 

a. Did you use qualitative or quantitative data to test the hypothesis? 

b. Did you perform an experiment where you collected data or are you writing a dissertation that is descriptive/theoretical without data collection? 

c. Did you use primary data that you collected or analyze secondary research data or existing data as part of your study? 

These questions will help you establish the rationale for your study on a broader level, which you will follow by elaborating on the specific methods you used to collect and understand your data. 

Step 2: Explain the methods you used to test your hypothesis 

Now that you have told your reader what type of research you’ve undertaken for the dissertation, it’s time to dig into specifics. State what specific methods you used and explain the conditions and variables involved. Explain what the theoretical framework behind the method was, what samples you used for testing it, and what tools and materials you used to collect the data. 

Step 3: Explain how you analyzed the results

Once you have explained the data collection process, explain how you analyzed and studied the data. Here, your focus is simply to explain the methods of analysis rather than the results of the study. 

Here are some questions you can answer at this stage: 

a. What tools or software did you use to analyze your results? 

b. What parameters or variables did you consider while understanding and studying the data you’ve collected? 

c. Was your analysis based on a theoretical framework? 

Your mode of analysis will change depending on whether you used a quantitative or qualitative research methodology in your study. If you’re working within the hard sciences or physical sciences, you are likely to use a quantitative research methodology (relying on numbers and hard data). If you’re doing a qualitative study, in the social sciences or humanities, your analysis may rely on understanding language and socio-political contexts around your topic. This is why it’s important to establish what kind of study you’re undertaking at the onset. 

Step 4: Defend your choice of methodology 

Now that you have gone through your research process in detail, you’ll also have to make a case for it. Justify your choice of methodology and methods, explaining why it is the best choice for your research question. This is especially important if you have chosen an unconventional approach or you’ve simply chosen to study an existing research problem from a different perspective. Compare it with other methodologies, especially ones attempted by previous researchers, and discuss what contributions using your methodology makes.  

Step 5: Discuss the obstacles you encountered and how you overcame them

No matter how thorough a methodology is, it doesn’t come without its hurdles. This is a natural part of scientific research that is important to document so that your peers and future researchers are aware of it. Writing in a research paper about this aspect of your research process also tells your evaluator that you have actively worked to overcome the pitfalls that came your way and you have refined the research process. 

Tips to write an effective methodology chapter

1. Remember who you are writing for. Keeping sight of the reader/evaluator will help you know what to elaborate on and what information they are already likely to have. You’re condensing months’ work of research in just a few pages, so you should omit basic definitions and information about general phenomena people already know.

2. Do not give an overly elaborate explanation of every single condition in your study. 

3. Skip details and findings irrelevant to the results.

4. Cite references that back your claim and choice of methodology. 

5. Consistently emphasize the relationship between your research question and the methodology you adopted to study it. 

To sum it up, what is methodology in research? It’s the blueprint of your research, essential for ensuring that your study is systematic, rigorous, and credible. Whether your focus is on qualitative research methodology, quantitative research methodology, or a combination of both, understanding and clearly defining your methodology is key to the success of your research.

Once you write the research methodology and complete writing the entire research paper, the next step is to edit your paper. As experts in research paper editing and proofreading services , we’d love to help you perfect your paper!

Here are some other articles that you might find useful: 

• Essential Research Tips for Essay Writing
• How to Write a Lab Report: Examples from Academic Editors
• The Essential Types of Editing Every Writer Needs to Know
• Editing and Proofreading Academic Papers: A Short Guide
• The Top 10 Editing and Proofreading Services of 2023

Frequently Asked Questions

What does research methodology mean, what types of research methodologies are there, what is qualitative research methodology, how to determine sample size in research methodology, what is action research methodology.

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What Is Research Methodology?

I f you’re new to formal academic research, it’s quite likely that you’re feeling a little overwhelmed by all the technical lingo that gets thrown around. And who could blame you – “research methodology”, “research methods”, “sampling strategies”… it all seems never-ending!

In this post, we’ll demystify the landscape with plain-language explanations and loads of examples (including easy-to-follow videos), so that you can approach your dissertation, thesis or research project with confidence. Let’s get started.

Research Methodology 101

• What exactly research methodology means
• What qualitative , quantitative and mixed methods are
• What sampling strategy is
• What data collection methods are
• What data analysis methods are
• How to choose your research methodology
• Example of a research methodology

What is research methodology?

Research methodology simply refers to the practical “how” of a research study. More specifically, it’s about how  a researcher  systematically designs a study  to ensure valid and reliable results that address the research aims, objectives and research questions . Specifically, how the researcher went about deciding:

• What type of data to collect (e.g., qualitative or quantitative data )
• Who  to collect it from (i.e., the sampling strategy )
• How to  collect  it (i.e., the data collection method )
• How to  analyse  it (i.e., the data analysis methods )

Within any formal piece of academic research (be it a dissertation, thesis or journal article), you’ll find a research methodology chapter or section which covers the aspects mentioned above. Importantly, a good methodology chapter explains not just   what methodological choices were made, but also explains  why they were made. In other words, the methodology chapter should justify  the design choices, by showing that the chosen methods and techniques are the best fit for the research aims, objectives and research questions. 

So, it’s the same as research design?

Not quite. As we mentioned, research methodology refers to the collection of practical decisions regarding what data you’ll collect, from who, how you’ll collect it and how you’ll analyse it. Research design, on the other hand, is more about the overall strategy you’ll adopt in your study. For example, whether you’ll use an experimental design in which you manipulate one variable while controlling others. You can learn more about research design and the various design types here .

Need a helping hand?

What are qualitative, quantitative and mixed-methods?

Qualitative, quantitative and mixed-methods are different types of methodological approaches, distinguished by their focus on words , numbers or both . This is a bit of an oversimplification, but its a good starting point for understanding.

Let’s take a closer look.

Qualitative research refers to research which focuses on collecting and analysing words (written or spoken) and textual or visual data, whereas quantitative research focuses on measurement and testing using numerical data . Qualitative analysis can also focus on other “softer” data points, such as body language or visual elements.

It’s quite common for a qualitative methodology to be used when the research aims and research questions are exploratory  in nature. For example, a qualitative methodology might be used to understand peoples’ perceptions about an event that took place, or a political candidate running for president. 

Contrasted to this, a quantitative methodology is typically used when the research aims and research questions are confirmatory  in nature. For example, a quantitative methodology might be used to measure the relationship between two variables (e.g. personality type and likelihood to commit a crime) or to test a set of hypotheses .

As you’ve probably guessed, the mixed-method methodology attempts to combine the best of both qualitative and quantitative methodologies to integrate perspectives and create a rich picture. If you’d like to learn more about these three methodological approaches, be sure to watch our explainer video below.

What is sampling strategy?

Simply put, sampling is about deciding who (or where) you’re going to collect your data from . Why does this matter? Well, generally it’s not possible to collect data from every single person in your group of interest (this is called the “population”), so you’ll need to engage a smaller portion of that group that’s accessible and manageable (this is called the “sample”).

How you go about selecting the sample (i.e., your sampling strategy) will have a major impact on your study.  There are many different sampling methods  you can choose from, but the two overarching categories are probability   sampling and  non-probability   sampling .

Probability sampling  involves using a completely random sample from the group of people you’re interested in. This is comparable to throwing the names all potential participants into a hat, shaking it up, and picking out the “winners”. By using a completely random sample, you’ll minimise the risk of selection bias and the results of your study will be more generalisable  to the entire population. 

Non-probability sampling , on the other hand,  doesn’t use a random sample . For example, it might involve using a convenience sample, which means you’d only interview or survey people that you have access to (perhaps your friends, family or work colleagues), rather than a truly random sample. With non-probability sampling, the results are typically not generalisable .

To learn more about sampling methods, be sure to check out the video below.

What are data collection methods?

As the name suggests, data collection methods simply refers to the way in which you go about collecting the data for your study. Some of the most common data collection methods include:

• Interviews (which can be unstructured, semi-structured or structured)
• Focus groups and group interviews
• Surveys (online or physical surveys)
• Observations (watching and recording activities)
• Biophysical measurements (e.g., blood pressure, heart rate, etc.)
• Documents and records (e.g., financial reports, court records, etc.)

The choice of which data collection method to use depends on your overall research aims and research questions , as well as practicalities and resource constraints. For example, if your research is exploratory in nature, qualitative methods such as interviews and focus groups would likely be a good fit. Conversely, if your research aims to measure specific variables or test hypotheses, large-scale surveys that produce large volumes of numerical data would likely be a better fit.

What are data analysis methods?

Data analysis methods refer to the methods and techniques that you’ll use to make sense of your data. These can be grouped according to whether the research is qualitative  (words-based) or quantitative (numbers-based).

Popular data analysis methods in qualitative research include:

• Qualitative content analysis
• Thematic analysis
• Discourse analysis
• Narrative analysis
• Interpretative phenomenological analysis (IPA)
• Visual analysis (of photographs, videos, art, etc.)

Qualitative data analysis all begins with data coding , after which an analysis method is applied. In some cases, more than one analysis method is used, depending on the research aims and research questions . In the video below, we explore some  common qualitative analysis methods, along with practical examples.  

• Descriptive statistics (e.g. means, medians, modes )
• Inferential statistics (e.g. correlation, regression, structural equation modelling)

How do I choose a research methodology?

As you’ve probably picked up by now, your research aims and objectives have a major influence on the research methodology . So, the starting point for developing your research methodology is to take a step back and look at the big picture of your research, before you make methodology decisions. The first question you need to ask yourself is whether your research is exploratory or confirmatory in nature.

If your research aims and objectives are primarily exploratory in nature, your research will likely be qualitative and therefore you might consider qualitative data collection methods (e.g. interviews) and analysis methods (e.g. qualitative content analysis). 

Conversely, if your research aims and objective are looking to measure or test something (i.e. they’re confirmatory), then your research will quite likely be quantitative in nature, and you might consider quantitative data collection methods (e.g. surveys) and analyses (e.g. statistical analysis).

Designing your research and working out your methodology is a large topic, which we cover extensively on the blog . For now, however, the key takeaway is that you should always start with your research aims, objectives and research questions (the golden thread). Every methodological choice you make needs align with those three components. 

Example of a research methodology chapter

In the video below, we provide a detailed walkthrough of a research methodology from an actual dissertation, as well as an overview of our free methodology template .

Learn More About Methodology

Triangulation: The Ultimate Credibility Enhancer

Triangulation is one of the best ways to enhance the credibility of your research. Learn about the different options here.

Research Limitations 101: What You Need To Know

Learn everything you need to know about research limitations (AKA limitations of the study). Includes practical examples from real studies.

In Vivo Coding 101: Full Explainer With Examples

Learn about in vivo coding, a popular qualitative coding technique ideal for studies where the nuances of language are central to the aims.

Process Coding 101: Full Explainer With Examples

Learn about process coding, a popular qualitative coding technique ideal for studies exploring processes, actions and changes over time.

Qualitative Coding 101: Inductive, Deductive & Hybrid Coding

Inductive, Deductive & Abductive Coding Qualitative Coding Approaches Explained...

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Thanks for your comment.

We can’t write your methodology for you. If you’re looking for samples, you should be able to find some sample methodologies on Google. Alternatively, you can download some previous dissertations from a dissertation directory and have a look at the methodology chapters therein.

All the best with your research.

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MLA Jansen, Derek, and Kerryn Warren. “What (Exactly) Is Research Methodology?” Grad Coach, June 2021, gradcoach.com/what-is-research-methodology/.

APA Jansen, D., & Warren, K. (2021, June). What (Exactly) Is Research Methodology? Grad Coach. https://gradcoach.com/what-is-research-methodology/

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• Methodology section in a report

Method/Methodology

The method section of a report details how the research was conducted, the research methods used and the reasons for choosing those methods. It should outline:

• the participants and research methods used, e.g. surveys/questionnaire, interviews
• refer to other relevant studies.

The methodology is a step-by-step explanation of the research process. It should be factual and is mainly written in the past tense.

Sample Methodology

The research used a quantitative methodology based on the approach advocated by Williams (2009). This study was conducted by questionnaire and investigated university teaching staff attitudes to the use of mobile phones in tutorials (see Appendix 1). The questionnaire used Likert scales to assess social attitudes (Jones 2007) to student mobile phone use and provided open-ended responses for additional comments. The survey was voluntary and anonymous. A total of 412 questionnaires were distributed online to randomly selected staff from each of the three colleges within the university. The completed questionnaires were returned by email.

• 'Describe' is short for: describing how the research was done.
• 'Refers' is short for: refers to relevant reading/literature.

[Describe: The research used a quantitative methodology based on the approach advocated by Williams (2009).] [Refer: This study was conducted by questionnaire and investigated university teaching staff attitudes to the use of mobile phones in tutorials (see Appendix 1). The questionnaire used Likert scales to assess social attitudes (Jones 2007) to student mobile phone use and provided open-ended responses for additional comments.] [Describes: The survey was voluntary and anonymous. A total of 412 questionnaires were distributed online to randomly selected staff from each of the three colleges within the university. The completed questionnaires were returned by email.]

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• What Is a Research Methodology? | Steps & Tips

What Is a Research Methodology? | Steps & Tips

Published on 25 February 2019 by Shona McCombes . Revised on 10 October 2022.

Your research methodology discusses and explains the data collection and analysis methods you used in your research. A key part of your thesis, dissertation, or research paper, the methodology chapter explains what you did and how you did it, allowing readers to evaluate the reliability and validity of your research.

It should include:

• The type of research you conducted
• How you collected and analysed your data
• Any tools or materials you used in the research
• Why you chose these methods
• Your methodology section should generally be written in the past tense .
• Academic style guides in your field may provide detailed guidelines on what to include for different types of studies.
• Your citation style might provide guidelines for your methodology section (e.g., an APA Style methods section ).

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Table of contents

How to write a research methodology, why is a methods section important, step 1: explain your methodological approach, step 2: describe your data collection methods, step 3: describe your analysis method, step 4: evaluate and justify the methodological choices you made, tips for writing a strong methodology chapter, frequently asked questions about methodology.

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Your methods section is your opportunity to share how you conducted your research and why you chose the methods you chose. It’s also the place to show that your research was rigorously conducted and can be replicated .

It gives your research legitimacy and situates it within your field, and also gives your readers a place to refer to if they have any questions or critiques in other sections.

You can start by introducing your overall approach to your research. You have two options here.

Option 1: Start with your “what”

What research problem or question did you investigate?

• Aim to describe the characteristics of something?
• Explore an under-researched topic?
• Establish a causal relationship?

And what type of data did you need to achieve this aim?

• Quantitative data , qualitative data , or a mix of both?
• Primary data collected yourself, or secondary data collected by someone else?
• Experimental data gathered by controlling and manipulating variables, or descriptive data gathered via observations?

Option 2: Start with your “why”

Depending on your discipline, you can also start with a discussion of the rationale and assumptions underpinning your methodology. In other words, why did you choose these methods for your study?

• Why is this the best way to answer your research question?
• Is this a standard methodology in your field, or does it require justification?
• Were there any ethical considerations involved in your choices?
• What are the criteria for validity and reliability in this type of research ?

Once you have introduced your reader to your methodological approach, you should share full details about your data collection methods .

Quantitative methods

In order to be considered generalisable, you should describe quantitative research methods in enough detail for another researcher to replicate your study.

Here, explain how you operationalised your concepts and measured your variables. Discuss your sampling method or inclusion/exclusion criteria, as well as any tools, procedures, and materials you used to gather your data.

Surveys Describe where, when, and how the survey was conducted.

• How did you design the questionnaire?
• What form did your questions take (e.g., multiple choice, Likert scale )?
• Were your surveys conducted in-person or virtually?
• What sampling method did you use to select participants?
• What was your sample size and response rate?

Experiments Share full details of the tools, techniques, and procedures you used to conduct your experiment.

• How did you design the experiment ?
• How did you recruit participants?
• How did you manipulate and measure the variables ?
• What tools did you use?

Existing data Explain how you gathered and selected the material (such as datasets or archival data) that you used in your analysis.

• Where did you source the material?
• How was the data originally produced?
• What criteria did you use to select material (e.g., date range)?

The survey consisted of 5 multiple-choice questions and 10 questions measured on a 7-point Likert scale.

The goal was to collect survey responses from 350 customers visiting the fitness apparel company’s brick-and-mortar location in Boston on 4–8 July 2022, between 11:00 and 15:00.

Here, a customer was defined as a person who had purchased a product from the company on the day they took the survey. Participants were given 5 minutes to fill in the survey anonymously. In total, 408 customers responded, but not all surveys were fully completed. Due to this, 371 survey results were included in the analysis.

Qualitative methods

In qualitative research , methods are often more flexible and subjective. For this reason, it’s crucial to robustly explain the methodology choices you made.

Be sure to discuss the criteria you used to select your data, the context in which your research was conducted, and the role you played in collecting your data (e.g., were you an active participant, or a passive observer?)

Interviews or focus groups Describe where, when, and how the interviews were conducted.

• How did you find and select participants?
• How many participants took part?
• What form did the interviews take ( structured , semi-structured , or unstructured )?
• How long were the interviews?
• How were they recorded?

Participant observation Describe where, when, and how you conducted the observation or ethnography .

• What group or community did you observe? How long did you spend there?
• How did you gain access to this group? What role did you play in the community?
• How long did you spend conducting the research? Where was it located?
• How did you record your data (e.g., audiovisual recordings, note-taking)?

Existing data Explain how you selected case study materials for your analysis.

• What type of materials did you analyse?
• How did you select them?

In order to gain better insight into possibilities for future improvement of the fitness shop’s product range, semi-structured interviews were conducted with 8 returning customers.

Here, a returning customer was defined as someone who usually bought products at least twice a week from the store.

Surveys were used to select participants. Interviews were conducted in a small office next to the cash register and lasted approximately 20 minutes each. Answers were recorded by note-taking, and seven interviews were also filmed with consent. One interviewee preferred not to be filmed.

Mixed methods

Mixed methods research combines quantitative and qualitative approaches. If a standalone quantitative or qualitative study is insufficient to answer your research question, mixed methods may be a good fit for you.

Mixed methods are less common than standalone analyses, largely because they require a great deal of effort to pull off successfully. If you choose to pursue mixed methods, it’s especially important to robustly justify your methods here.

Next, you should indicate how you processed and analysed your data. Avoid going into too much detail: you should not start introducing or discussing any of your results at this stage.

In quantitative research , your analysis will be based on numbers. In your methods section, you can include:

• How you prepared the data before analysing it (e.g., checking for missing data , removing outliers , transforming variables)
• Which software you used (e.g., SPSS, Stata or R)
• Which statistical tests you used (e.g., two-tailed t test , simple linear regression )

In qualitative research, your analysis will be based on language, images, and observations (often involving some form of textual analysis ).

Specific methods might include:

• Content analysis : Categorising and discussing the meaning of words, phrases and sentences
• Thematic analysis : Coding and closely examining the data to identify broad themes and patterns
• Discourse analysis : Studying communication and meaning in relation to their social context

Mixed methods combine the above two research methods, integrating both qualitative and quantitative approaches into one coherent analytical process.

Above all, your methodology section should clearly make the case for why you chose the methods you did. This is especially true if you did not take the most standard approach to your topic. In this case, discuss why other methods were not suitable for your objectives, and show how this approach contributes new knowledge or understanding.

In any case, it should be overwhelmingly clear to your reader that you set yourself up for success in terms of your methodology’s design. Show how your methods should lead to results that are valid and reliable, while leaving the analysis of the meaning, importance, and relevance of your results for your discussion section .

• Quantitative: Lab-based experiments cannot always accurately simulate real-life situations and behaviours, but they are effective for testing causal relationships between variables .
• Qualitative: Unstructured interviews usually produce results that cannot be generalised beyond the sample group , but they provide a more in-depth understanding of participants’ perceptions, motivations, and emotions.
• Mixed methods: Despite issues systematically comparing differing types of data, a solely quantitative study would not sufficiently incorporate the lived experience of each participant, while a solely qualitative study would be insufficiently generalisable.

Remember that your aim is not just to describe your methods, but to show how and why you applied them. Again, it’s critical to demonstrate that your research was rigorously conducted and can be replicated.

1. Focus on your objectives and research questions

The methodology section should clearly show why your methods suit your objectives  and convince the reader that you chose the best possible approach to answering your problem statement and research questions .

2. Cite relevant sources

Your methodology can be strengthened by referencing existing research in your field. This can help you to:

• Show that you followed established practice for your type of research
• Discuss how you decided on your approach by evaluating existing research
• Present a novel methodological approach to address a gap in the literature

3. Write for your audience

Consider how much information you need to give, and avoid getting too lengthy. If you are using methods that are standard for your discipline, you probably don’t need to give a lot of background or justification.

Regardless, your methodology should be a clear, well-structured text that makes an argument for your approach, not just a list of technical details and procedures.

Methodology refers to the overarching strategy and rationale of your research. Developing your methodology involves studying the research methods used in your field and the theories or principles that underpin them, in order to choose the approach that best matches your objectives.

Methods are the specific tools and procedures you use to collect and analyse data (e.g. interviews, experiments , surveys , statistical tests ).

In a dissertation or scientific paper, the methodology chapter or methods section comes after the introduction and before the results , discussion and conclusion .

Depending on the length and type of document, you might also include a literature review or theoretical framework before the methodology.

Quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings.

Quantitative methods allow you to test a hypothesis by systematically collecting and analysing data, while qualitative methods allow you to explore ideas and experiences in depth.

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

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

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

Cite this Scribbr article

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McCombes, S. (2022, October 10). What Is a Research Methodology? | Steps & Tips. Scribbr. Retrieved 3 September 2024, from https://www.scribbr.co.uk/thesis-dissertation/methodology/

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What is Research Methodology? Definition, Types, and Examples

Research methodology 1,2 is a structured and scientific approach used to collect, analyze, and interpret quantitative or qualitative data to answer research questions or test hypotheses. A research methodology is like a plan for carrying out research and helps keep researchers on track by limiting the scope of the research. Several aspects must be considered before selecting an appropriate research methodology, such as research limitations and ethical concerns that may affect your research.

The research methodology section in a scientific paper describes the different methodological choices made, such as the data collection and analysis methods, and why these choices were selected. The reasons should explain why the methods chosen are the most appropriate to answer the research question. A good research methodology also helps ensure the reliability and validity of the research findings. There are three types of research methodology—quantitative, qualitative, and mixed-method, which can be chosen based on the research objectives.

What is research methodology ?

A research methodology describes the techniques and procedures used to identify and analyze information regarding a specific research topic. It is a process by which researchers design their study so that they can achieve their objectives using the selected research instruments. It includes all the important aspects of research, including research design, data collection methods, data analysis methods, and the overall framework within which the research is conducted. While these points can help you understand what is research methodology, you also need to know why it is important to pick the right methodology.

Having a good research methodology in place has the following advantages: 3

• Helps other researchers who may want to replicate your research; the explanations will be of benefit to them.
• You can easily answer any questions about your research if they arise at a later stage.
• A research methodology provides a framework and guidelines for researchers to clearly define research questions, hypotheses, and objectives.
• It helps researchers identify the most appropriate research design, sampling technique, and data collection and analysis methods.
• A sound research methodology helps researchers ensure that their findings are valid and reliable and free from biases and errors.
• It also helps ensure that ethical guidelines are followed while conducting research.
• A good research methodology helps researchers in planning their research efficiently, by ensuring optimum usage of their time and resources.

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Types of research methodology.

There are three types of research methodology based on the type of research and the data required. 1

• Quantitative research methodology focuses on measuring and testing numerical data. This approach is good for reaching a large number of people in a short amount of time. This type of research helps in testing the causal relationships between variables, making predictions, and generalizing results to wider populations.
• Qualitative research methodology examines the opinions, behaviors, and experiences of people. It collects and analyzes words and textual data. This research methodology requires fewer participants but is still more time consuming because the time spent per participant is quite large. This method is used in exploratory research where the research problem being investigated is not clearly defined.
• Mixed-method research methodology uses the characteristics of both quantitative and qualitative research methodologies in the same study. This method allows researchers to validate their findings, verify if the results observed using both methods are complementary, and explain any unexpected results obtained from one method by using the other method.

What are the types of sampling designs in research methodology?

Sampling 4 is an important part of a research methodology and involves selecting a representative sample of the population to conduct the study, making statistical inferences about them, and estimating the characteristics of the whole population based on these inferences. There are two types of sampling designs in research methodology—probability and nonprobability.

• Probability sampling

In this type of sampling design, a sample is chosen from a larger population using some form of random selection, that is, every member of the population has an equal chance of being selected. The different types of probability sampling are:

• Systematic —sample members are chosen at regular intervals. It requires selecting a starting point for the sample and sample size determination that can be repeated at regular intervals. This type of sampling method has a predefined range; hence, it is the least time consuming.
• Stratified —researchers divide the population into smaller groups that don’t overlap but represent the entire population. While sampling, these groups can be organized, and then a sample can be drawn from each group separately.
• Cluster —the population is divided into clusters based on demographic parameters like age, sex, location, etc.
• Convenience —selects participants who are most easily accessible to researchers due to geographical proximity, availability at a particular time, etc.
• Purposive —participants are selected at the researcher’s discretion. Researchers consider the purpose of the study and the understanding of the target audience.
• Snowball —already selected participants use their social networks to refer the researcher to other potential participants.
• Quota —while designing the study, the researchers decide how many people with which characteristics to include as participants. The characteristics help in choosing people most likely to provide insights into the subject.

What are data collection methods?

During research, data are collected using various methods depending on the research methodology being followed and the research methods being undertaken. Both qualitative and quantitative research have different data collection methods, as listed below.

Qualitative research 5

• One-on-one interviews: Helps the interviewers understand a respondent’s subjective opinion and experience pertaining to a specific topic or event
• Document study/literature review/record keeping: Researchers’ review of already existing written materials such as archives, annual reports, research articles, guidelines, policy documents, etc.
• Focus groups: Constructive discussions that usually include a small sample of about 6-10 people and a moderator, to understand the participants’ opinion on a given topic.
• Qualitative observation : Researchers collect data using their five senses (sight, smell, touch, taste, and hearing).

Quantitative research 6

• Sampling: The most common type is probability sampling.
• Interviews: Commonly telephonic or done in-person.
• Observations: Structured observations are most commonly used in quantitative research. In this method, researchers make observations about specific behaviors of individuals in a structured setting.
• Document review: Reviewing existing research or documents to collect evidence for supporting the research.
• Surveys and questionnaires. Surveys can be administered both online and offline depending on the requirement and sample size.

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What are data analysis methods.

The data collected using the various methods for qualitative and quantitative research need to be analyzed to generate meaningful conclusions. These data analysis methods 7 also differ between quantitative and qualitative research.

Quantitative research involves a deductive method for data analysis where hypotheses are developed at the beginning of the research and precise measurement is required. The methods include statistical analysis applications to analyze numerical data and are grouped into two categories—descriptive and inferential.

Descriptive analysis is used to describe the basic features of different types of data to present it in a way that ensures the patterns become meaningful. The different types of descriptive analysis methods are:

• Measures of frequency (count, percent, frequency)
• Measures of central tendency (mean, median, mode)
• Measures of dispersion or variation (range, variance, standard deviation)
• Measure of position (percentile ranks, quartile ranks)

Inferential analysis is used to make predictions about a larger population based on the analysis of the data collected from a smaller population. This analysis is used to study the relationships between different variables. Some commonly used inferential data analysis methods are:

• Correlation: To understand the relationship between two or more variables.
• Cross-tabulation: Analyze the relationship between multiple variables.
• Regression analysis: Study the impact of independent variables on the dependent variable.
• Frequency tables: To understand the frequency of data.
• Analysis of variance: To test the degree to which two or more variables differ in an experiment.

Qualitative research involves an inductive method for data analysis where hypotheses are developed after data collection. The methods include:

• Content analysis: For analyzing documented information from text and images by determining the presence of certain words or concepts in texts.
• Narrative analysis: For analyzing content obtained from sources such as interviews, field observations, and surveys. The stories and opinions shared by people are used to answer research questions.
• Discourse analysis: For analyzing interactions with people considering the social context, that is, the lifestyle and environment, under which the interaction occurs.
• Grounded theory: Involves hypothesis creation by data collection and analysis to explain why a phenomenon occurred.
• Thematic analysis: To identify important themes or patterns in data and use these to address an issue.

How to choose a research methodology?

Here are some important factors to consider when choosing a research methodology: 8

• Research objectives, aims, and questions —these would help structure the research design.
• Review existing literature to identify any gaps in knowledge.
• Check the statistical requirements —if data-driven or statistical results are needed then quantitative research is the best. If the research questions can be answered based on people’s opinions and perceptions, then qualitative research is most suitable.
• Sample size —sample size can often determine the feasibility of a research methodology. For a large sample, less effort- and time-intensive methods are appropriate.
• Constraints —constraints of time, geography, and resources can help define the appropriate methodology.

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How to write a research methodology .

A research methodology should include the following components: 3,9

• Research design —should be selected based on the research question and the data required. Common research designs include experimental, quasi-experimental, correlational, descriptive, and exploratory.
• Research method —this can be quantitative, qualitative, or mixed-method.
• Reason for selecting a specific methodology —explain why this methodology is the most suitable to answer your research problem.
• Research instruments —explain the research instruments you plan to use, mainly referring to the data collection methods such as interviews, surveys, etc. Here as well, a reason should be mentioned for selecting the particular instrument.
• Sampling —this involves selecting a representative subset of the population being studied.
• Data collection —involves gathering data using several data collection methods, such as surveys, interviews, etc.
• Data analysis —describe the data analysis methods you will use once you’ve collected the data.
• Research limitations —mention any limitations you foresee while conducting your research.
• Validity and reliability —validity helps identify the accuracy and truthfulness of the findings; reliability refers to the consistency and stability of the results over time and across different conditions.
• Ethical considerations —research should be conducted ethically. The considerations include obtaining consent from participants, maintaining confidentiality, and addressing conflicts of interest.

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Frequently Asked Questions

Q1. What are the key components of research methodology?

A1. A good research methodology has the following key components:

• Research design
• Data collection procedures
• Data analysis methods
• Ethical considerations

Q2. Why is ethical consideration important in research methodology?

A2. Ethical consideration is important in research methodology to ensure the readers of the reliability and validity of the study. Researchers must clearly mention the ethical norms and standards followed during the conduct of the research and also mention if the research has been cleared by any institutional board. The following 10 points are the important principles related to ethical considerations: 10

• Participants should not be subjected to harm.
• Respect for the dignity of participants should be prioritized.
• Full consent should be obtained from participants before the study.
• Participants’ privacy should be ensured.
• Confidentiality of the research data should be ensured.
• Anonymity of individuals and organizations participating in the research should be maintained.
• The aims and objectives of the research should not be exaggerated.
• Affiliations, sources of funding, and any possible conflicts of interest should be declared.
• Communication in relation to the research should be honest and transparent.
• Misleading information and biased representation of primary data findings should be avoided.

Q3. What is the difference between methodology and method?

A3. Research methodology is different from a research method, although both terms are often confused. Research methods are the tools used to gather data, while the research methodology provides a framework for how research is planned, conducted, and analyzed. The latter guides researchers in making decisions about the most appropriate methods for their research. Research methods refer to the specific techniques, procedures, and tools used by researchers to collect, analyze, and interpret data, for instance surveys, questionnaires, interviews, etc.

Research methodology is, thus, an integral part of a research study. It helps ensure that you stay on track to meet your research objectives and answer your research questions using the most appropriate data collection and analysis tools based on your research design.

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• Data analysis in research: Types & methods. QuestionPro website. Accessed August 16, 2023. https://www.questionpro.com/blog/data-analysis-in-research/#Data_analysis_in_qualitative_research
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• What is research methodology? Research and writing guides. Accessed August 14, 2023. https://paperpile.com/g/what-is-research-methodology/
• Ethical considerations. Business research methodology website. Accessed August 17, 2023. https://research-methodology.net/research-methodology/ethical-considerations/

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Chapter 11: Presenting Your Research

Writing a Research Report in American Psychological Association (APA) Style

Learning Objectives

• Identify the major sections of an APA-style research report and the basic contents of each section.
• Plan and write an effective APA-style research report.

In this section, we look at how to write an APA-style empirical research report , an article that presents the results of one or more new studies. Recall that the standard sections of an empirical research report provide a kind of outline. Here we consider each of these sections in detail, including what information it contains, how that information is formatted and organized, and tips for writing each section. At the end of this section is a sample APA-style research report that illustrates many of these principles.

Sections of a Research Report

Title page and abstract.

An APA-style research report begins with a  title page . The title is centred in the upper half of the page, with each important word capitalized. The title should clearly and concisely (in about 12 words or fewer) communicate the primary variables and research questions. This sometimes requires a main title followed by a subtitle that elaborates on the main title, in which case the main title and subtitle are separated by a colon. Here are some titles from recent issues of professional journals published by the American Psychological Association.

• Sex Differences in Coping Styles and Implications for Depressed Mood
• Effects of Aging and Divided Attention on Memory for Items and Their Contexts
• Computer-Assisted Cognitive Behavioural Therapy for Child Anxiety: Results of a Randomized Clinical Trial
• Virtual Driving and Risk Taking: Do Racing Games Increase Risk-Taking Cognitions, Affect, and Behaviour?

Below the title are the authors’ names and, on the next line, their institutional affiliation—the university or other institution where the authors worked when they conducted the research. As we have already seen, the authors are listed in an order that reflects their contribution to the research. When multiple authors have made equal contributions to the research, they often list their names alphabetically or in a randomly determined order.

In some areas of psychology, the titles of many empirical research reports are informal in a way that is perhaps best described as “cute.” They usually take the form of a play on words or a well-known expression that relates to the topic under study. Here are some examples from recent issues of the Journal Psychological Science .

• “Smells Like Clean Spirit: Nonconscious Effects of Scent on Cognition and Behavior”
• “Time Crawls: The Temporal Resolution of Infants’ Visual Attention”
• “Scent of a Woman: Men’s Testosterone Responses to Olfactory Ovulation Cues”
• “Apocalypse Soon?: Dire Messages Reduce Belief in Global Warming by Contradicting Just-World Beliefs”
• “Serial vs. Parallel Processing: Sometimes They Look Like Tweedledum and Tweedledee but They Can (and Should) Be Distinguished”
• “How Do I Love Thee? Let Me Count the Words: The Social Effects of Expressive Writing”

Individual researchers differ quite a bit in their preference for such titles. Some use them regularly, while others never use them. What might be some of the pros and cons of using cute article titles?

For articles that are being submitted for publication, the title page also includes an author note that lists the authors’ full institutional affiliations, any acknowledgments the authors wish to make to agencies that funded the research or to colleagues who commented on it, and contact information for the authors. For student papers that are not being submitted for publication—including theses—author notes are generally not necessary.

The  abstract  is a summary of the study. It is the second page of the manuscript and is headed with the word  Abstract . The first line is not indented. The abstract presents the research question, a summary of the method, the basic results, and the most important conclusions. Because the abstract is usually limited to about 200 words, it can be a challenge to write a good one.

Introduction

The  introduction  begins on the third page of the manuscript. The heading at the top of this page is the full title of the manuscript, with each important word capitalized as on the title page. The introduction includes three distinct subsections, although these are typically not identified by separate headings. The opening introduces the research question and explains why it is interesting, the literature review discusses relevant previous research, and the closing restates the research question and comments on the method used to answer it.

The Opening

The  opening , which is usually a paragraph or two in length, introduces the research question and explains why it is interesting. To capture the reader’s attention, researcher Daryl Bem recommends starting with general observations about the topic under study, expressed in ordinary language (not technical jargon)—observations that are about people and their behaviour (not about researchers or their research; Bem, 2003 [1] ). Concrete examples are often very useful here. According to Bem, this would be a poor way to begin a research report:

Festinger’s theory of cognitive dissonance received a great deal of attention during the latter part of the 20th century (p. 191)

The following would be much better:

The individual who holds two beliefs that are inconsistent with one another may feel uncomfortable. For example, the person who knows that he or she enjoys smoking but believes it to be unhealthy may experience discomfort arising from the inconsistency or disharmony between these two thoughts or cognitions. This feeling of discomfort was called cognitive dissonance by social psychologist Leon Festinger (1957), who suggested that individuals will be motivated to remove this dissonance in whatever way they can (p. 191).

After capturing the reader’s attention, the opening should go on to introduce the research question and explain why it is interesting. Will the answer fill a gap in the literature? Will it provide a test of an important theory? Does it have practical implications? Giving readers a clear sense of what the research is about and why they should care about it will motivate them to continue reading the literature review—and will help them make sense of it.

Breaking the Rules

Researcher Larry Jacoby reported several studies showing that a word that people see or hear repeatedly can seem more familiar even when they do not recall the repetitions—and that this tendency is especially pronounced among older adults. He opened his article with the following humourous anecdote:

A friend whose mother is suffering symptoms of Alzheimer’s disease (AD) tells the story of taking her mother to visit a nursing home, preliminary to her mother’s moving there. During an orientation meeting at the nursing home, the rules and regulations were explained, one of which regarded the dining room. The dining room was described as similar to a fine restaurant except that tipping was not required. The absence of tipping was a central theme in the orientation lecture, mentioned frequently to emphasize the quality of care along with the advantages of having paid in advance. At the end of the meeting, the friend’s mother was asked whether she had any questions. She replied that she only had one question: “Should I tip?” (Jacoby, 1999, p. 3)

Although both humour and personal anecdotes are generally discouraged in APA-style writing, this example is a highly effective way to start because it both engages the reader and provides an excellent real-world example of the topic under study.

The Literature Review

Immediately after the opening comes the  literature review , which describes relevant previous research on the topic and can be anywhere from several paragraphs to several pages in length. However, the literature review is not simply a list of past studies. Instead, it constitutes a kind of argument for why the research question is worth addressing. By the end of the literature review, readers should be convinced that the research question makes sense and that the present study is a logical next step in the ongoing research process.

Like any effective argument, the literature review must have some kind of structure. For example, it might begin by describing a phenomenon in a general way along with several studies that demonstrate it, then describing two or more competing theories of the phenomenon, and finally presenting a hypothesis to test one or more of the theories. Or it might describe one phenomenon, then describe another phenomenon that seems inconsistent with the first one, then propose a theory that resolves the inconsistency, and finally present a hypothesis to test that theory. In applied research, it might describe a phenomenon or theory, then describe how that phenomenon or theory applies to some important real-world situation, and finally suggest a way to test whether it does, in fact, apply to that situation.

Looking at the literature review in this way emphasizes a few things. First, it is extremely important to start with an outline of the main points that you want to make, organized in the order that you want to make them. The basic structure of your argument, then, should be apparent from the outline itself. Second, it is important to emphasize the structure of your argument in your writing. One way to do this is to begin the literature review by summarizing your argument even before you begin to make it. “In this article, I will describe two apparently contradictory phenomena, present a new theory that has the potential to resolve the apparent contradiction, and finally present a novel hypothesis to test the theory.” Another way is to open each paragraph with a sentence that summarizes the main point of the paragraph and links it to the preceding points. These opening sentences provide the “transitions” that many beginning researchers have difficulty with. Instead of beginning a paragraph by launching into a description of a previous study, such as “Williams (2004) found that…,” it is better to start by indicating something about why you are describing this particular study. Here are some simple examples:

Another example of this phenomenon comes from the work of Williams (2004).

Williams (2004) offers one explanation of this phenomenon.

An alternative perspective has been provided by Williams (2004).

We used a method based on the one used by Williams (2004).

Finally, remember that your goal is to construct an argument for why your research question is interesting and worth addressing—not necessarily why your favourite answer to it is correct. In other words, your literature review must be balanced. If you want to emphasize the generality of a phenomenon, then of course you should discuss various studies that have demonstrated it. However, if there are other studies that have failed to demonstrate it, you should discuss them too. Or if you are proposing a new theory, then of course you should discuss findings that are consistent with that theory. However, if there are other findings that are inconsistent with it, again, you should discuss them too. It is acceptable to argue that the  balance  of the research supports the existence of a phenomenon or is consistent with a theory (and that is usually the best that researchers in psychology can hope for), but it is not acceptable to  ignore contradictory evidence. Besides, a large part of what makes a research question interesting is uncertainty about its answer.

The Closing

The  closing  of the introduction—typically the final paragraph or two—usually includes two important elements. The first is a clear statement of the main research question or hypothesis. This statement tends to be more formal and precise than in the opening and is often expressed in terms of operational definitions of the key variables. The second is a brief overview of the method and some comment on its appropriateness. Here, for example, is how Darley and Latané (1968) [2] concluded the introduction to their classic article on the bystander effect:

These considerations lead to the hypothesis that the more bystanders to an emergency, the less likely, or the more slowly, any one bystander will intervene to provide aid. To test this proposition it would be necessary to create a situation in which a realistic “emergency” could plausibly occur. Each subject should also be blocked from communicating with others to prevent his getting information about their behaviour during the emergency. Finally, the experimental situation should allow for the assessment of the speed and frequency of the subjects’ reaction to the emergency. The experiment reported below attempted to fulfill these conditions. (p. 378)

Thus the introduction leads smoothly into the next major section of the article—the method section.

The  method section  is where you describe how you conducted your study. An important principle for writing a method section is that it should be clear and detailed enough that other researchers could replicate the study by following your “recipe.” This means that it must describe all the important elements of the study—basic demographic characteristics of the participants, how they were recruited, whether they were randomly assigned, how the variables were manipulated or measured, how counterbalancing was accomplished, and so on. At the same time, it should avoid irrelevant details such as the fact that the study was conducted in Classroom 37B of the Industrial Technology Building or that the questionnaire was double-sided and completed using pencils.

The method section begins immediately after the introduction ends with the heading “Method” (not “Methods”) centred on the page. Immediately after this is the subheading “Participants,” left justified and in italics. The participants subsection indicates how many participants there were, the number of women and men, some indication of their age, other demographics that may be relevant to the study, and how they were recruited, including any incentives given for participation.

After the participants section, the structure can vary a bit. Figure 11.1 shows three common approaches. In the first, the participants section is followed by a design and procedure subsection, which describes the rest of the method. This works well for methods that are relatively simple and can be described adequately in a few paragraphs. In the second approach, the participants section is followed by separate design and procedure subsections. This works well when both the design and the procedure are relatively complicated and each requires multiple paragraphs.

What is the difference between design and procedure? The design of a study is its overall structure. What were the independent and dependent variables? Was the independent variable manipulated, and if so, was it manipulated between or within subjects? How were the variables operationally defined? The procedure is how the study was carried out. It often works well to describe the procedure in terms of what the participants did rather than what the researchers did. For example, the participants gave their informed consent, read a set of instructions, completed a block of four practice trials, completed a block of 20 test trials, completed two questionnaires, and were debriefed and excused.

In the third basic way to organize a method section, the participants subsection is followed by a materials subsection before the design and procedure subsections. This works well when there are complicated materials to describe. This might mean multiple questionnaires, written vignettes that participants read and respond to, perceptual stimuli, and so on. The heading of this subsection can be modified to reflect its content. Instead of “Materials,” it can be “Questionnaires,” “Stimuli,” and so on.

The  results section  is where you present the main results of the study, including the results of the statistical analyses. Although it does not include the raw data—individual participants’ responses or scores—researchers should save their raw data and make them available to other researchers who request them. Several journals now encourage the open sharing of raw data online.

Although there are no standard subsections, it is still important for the results section to be logically organized. Typically it begins with certain preliminary issues. One is whether any participants or responses were excluded from the analyses and why. The rationale for excluding data should be described clearly so that other researchers can decide whether it is appropriate. A second preliminary issue is how multiple responses were combined to produce the primary variables in the analyses. For example, if participants rated the attractiveness of 20 stimulus people, you might have to explain that you began by computing the mean attractiveness rating for each participant. Or if they recalled as many items as they could from study list of 20 words, did you count the number correctly recalled, compute the percentage correctly recalled, or perhaps compute the number correct minus the number incorrect? A third preliminary issue is the reliability of the measures. This is where you would present test-retest correlations, Cronbach’s α, or other statistics to show that the measures are consistent across time and across items. A final preliminary issue is whether the manipulation was successful. This is where you would report the results of any manipulation checks.

The results section should then tackle the primary research questions, one at a time. Again, there should be a clear organization. One approach would be to answer the most general questions and then proceed to answer more specific ones. Another would be to answer the main question first and then to answer secondary ones. Regardless, Bem (2003) [3] suggests the following basic structure for discussing each new result:

• Remind the reader of the research question.
• Give the answer to the research question in words.
• Present the relevant statistics.
• Qualify the answer if necessary.
• Summarize the result.

Notice that only Step 3 necessarily involves numbers. The rest of the steps involve presenting the research question and the answer to it in words. In fact, the basic results should be clear even to a reader who skips over the numbers.

The  discussion  is the last major section of the research report. Discussions usually consist of some combination of the following elements:

• Summary of the research
• Theoretical implications
• Practical implications
• Limitations
• Suggestions for future research

The discussion typically begins with a summary of the study that provides a clear answer to the research question. In a short report with a single study, this might require no more than a sentence. In a longer report with multiple studies, it might require a paragraph or even two. The summary is often followed by a discussion of the theoretical implications of the research. Do the results provide support for any existing theories? If not, how  can  they be explained? Although you do not have to provide a definitive explanation or detailed theory for your results, you at least need to outline one or more possible explanations. In applied research—and often in basic research—there is also some discussion of the practical implications of the research. How can the results be used, and by whom, to accomplish some real-world goal?

The theoretical and practical implications are often followed by a discussion of the study’s limitations. Perhaps there are problems with its internal or external validity. Perhaps the manipulation was not very effective or the measures not very reliable. Perhaps there is some evidence that participants did not fully understand their task or that they were suspicious of the intent of the researchers. Now is the time to discuss these issues and how they might have affected the results. But do not overdo it. All studies have limitations, and most readers will understand that a different sample or different measures might have produced different results. Unless there is good reason to think they  would have, however, there is no reason to mention these routine issues. Instead, pick two or three limitations that seem like they could have influenced the results, explain how they could have influenced the results, and suggest ways to deal with them.

Most discussions end with some suggestions for future research. If the study did not satisfactorily answer the original research question, what will it take to do so? What  new  research questions has the study raised? This part of the discussion, however, is not just a list of new questions. It is a discussion of two or three of the most important unresolved issues. This means identifying and clarifying each question, suggesting some alternative answers, and even suggesting ways they could be studied.

Finally, some researchers are quite good at ending their articles with a sweeping or thought-provoking conclusion. Darley and Latané (1968) [4] , for example, ended their article on the bystander effect by discussing the idea that whether people help others may depend more on the situation than on their personalities. Their final sentence is, “If people understand the situational forces that can make them hesitate to intervene, they may better overcome them” (p. 383). However, this kind of ending can be difficult to pull off. It can sound overreaching or just banal and end up detracting from the overall impact of the article. It is often better simply to end when you have made your final point (although you should avoid ending on a limitation).

The references section begins on a new page with the heading “References” centred at the top of the page. All references cited in the text are then listed in the format presented earlier. They are listed alphabetically by the last name of the first author. If two sources have the same first author, they are listed alphabetically by the last name of the second author. If all the authors are the same, then they are listed chronologically by the year of publication. Everything in the reference list is double-spaced both within and between references.

Appendices, Tables, and Figures

Appendices, tables, and figures come after the references. An  appendix  is appropriate for supplemental material that would interrupt the flow of the research report if it were presented within any of the major sections. An appendix could be used to present lists of stimulus words, questionnaire items, detailed descriptions of special equipment or unusual statistical analyses, or references to the studies that are included in a meta-analysis. Each appendix begins on a new page. If there is only one, the heading is “Appendix,” centred at the top of the page. If there is more than one, the headings are “Appendix A,” “Appendix B,” and so on, and they appear in the order they were first mentioned in the text of the report.

After any appendices come tables and then figures. Tables and figures are both used to present results. Figures can also be used to illustrate theories (e.g., in the form of a flowchart), display stimuli, outline procedures, and present many other kinds of information. Each table and figure appears on its own page. Tables are numbered in the order that they are first mentioned in the text (“Table 1,” “Table 2,” and so on). Figures are numbered the same way (“Figure 1,” “Figure 2,” and so on). A brief explanatory title, with the important words capitalized, appears above each table. Each figure is given a brief explanatory caption, where (aside from proper nouns or names) only the first word of each sentence is capitalized. More details on preparing APA-style tables and figures are presented later in the book.

Sample APA-Style Research Report

Figures 11.2, 11.3, 11.4, and 11.5 show some sample pages from an APA-style empirical research report originally written by undergraduate student Tomoe Suyama at California State University, Fresno. The main purpose of these figures is to illustrate the basic organization and formatting of an APA-style empirical research report, although many high-level and low-level style conventions can be seen here too.

Key Takeaways

• An APA-style empirical research report consists of several standard sections. The main ones are the abstract, introduction, method, results, discussion, and references.
• The introduction consists of an opening that presents the research question, a literature review that describes previous research on the topic, and a closing that restates the research question and comments on the method. The literature review constitutes an argument for why the current study is worth doing.
• The method section describes the method in enough detail that another researcher could replicate the study. At a minimum, it consists of a participants subsection and a design and procedure subsection.
• The results section describes the results in an organized fashion. Each primary result is presented in terms of statistical results but also explained in words.
• The discussion typically summarizes the study, discusses theoretical and practical implications and limitations of the study, and offers suggestions for further research.
• Practice: Look through an issue of a general interest professional journal (e.g.,  Psychological Science ). Read the opening of the first five articles and rate the effectiveness of each one from 1 ( very ineffective ) to 5 ( very effective ). Write a sentence or two explaining each rating.
• Practice: Find a recent article in a professional journal and identify where the opening, literature review, and closing of the introduction begin and end.
• Practice: Find a recent article in a professional journal and highlight in a different colour each of the following elements in the discussion: summary, theoretical implications, practical implications, limitations, and suggestions for future research.

Long Descriptions

Figure 11.1 long description: Table showing three ways of organizing an APA-style method section.

In the simple method, there are two subheadings: “Participants” (which might begin “The participants were…”) and “Design and procedure” (which might begin “There were three conditions…”).

In the typical method, there are three subheadings: “Participants” (“The participants were…”), “Design” (“There were three conditions…”), and “Procedure” (“Participants viewed each stimulus on the computer screen…”).

In the complex method, there are four subheadings: “Participants” (“The participants were…”), “Materials” (“The stimuli were…”), “Design” (“There were three conditions…”), and “Procedure” (“Participants viewed each stimulus on the computer screen…”). [Return to Figure 11.1]

• Bem, D. J. (2003). Writing the empirical journal article. In J. M. Darley, M. P. Zanna, & H. R. Roediger III (Eds.),  The compleat academic: A practical guide for the beginning social scientist  (2nd ed.). Washington, DC: American Psychological Association. ↵
• Darley, J. M., & Latané, B. (1968). Bystander intervention in emergencies: Diffusion of responsibility.  Journal of Personality and Social Psychology, 4 , 377–383. ↵

A type of research article which describes one or more new empirical studies conducted by the authors.

The page at the beginning of an APA-style research report containing the title of the article, the authors’ names, and their institutional affiliation.

A summary of a research study.

The third page of a manuscript containing the research question, the literature review, and comments about how to answer the research question.

An introduction to the research question and explanation for why this question is interesting.

A description of relevant previous research on the topic being discusses and an argument for why the research is worth addressing.

The end of the introduction, where the research question is reiterated and the method is commented upon.

The section of a research report where the method used to conduct the study is described.

The main results of the study, including the results from statistical analyses, are presented in a research article.

Section of a research report that summarizes the study's results and interprets them by referring back to the study's theoretical background.

Part of a research report which contains supplemental material.

Research Methods in Psychology - 2nd Canadian Edition Copyright © 2015 by Paul C. Price, Rajiv Jhangiani, & I-Chant A. Chiang is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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How To Write A Lab Report | Step-by-Step Guide & Examples

Published on May 20, 2021 by Pritha Bhandari . Revised on July 23, 2023.

A lab report conveys the aim, methods, results, and conclusions of a scientific experiment. The main purpose of a lab report is to demonstrate your understanding of the scientific method by performing and evaluating a hands-on lab experiment. This type of assignment is usually shorter than a research paper .

Lab reports are commonly used in science, technology, engineering, and mathematics (STEM) fields. This article focuses on how to structure and write a lab report.

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Table of contents

Structuring a lab report, introduction, other interesting articles, frequently asked questions about lab reports.

The sections of a lab report can vary between scientific fields and course requirements, but they usually contain the purpose, methods, and findings of a lab experiment .

Each section of a lab report has its own purpose.

• Title: expresses the topic of your study
• Abstract : summarizes your research aims, methods, results, and conclusions
• Introduction: establishes the context needed to understand the topic
• Method: describes the materials and procedures used in the experiment
• Results: reports all descriptive and inferential statistical analyses
• Discussion: interprets and evaluates results and identifies limitations
• Conclusion: sums up the main findings of your experiment
• References: list of all sources cited using a specific style (e.g. APA )
• Appendices : contains lengthy materials, procedures, tables or figures

Although most lab reports contain these sections, some sections can be omitted or combined with others. For example, some lab reports contain a brief section on research aims instead of an introduction, and a separate conclusion is not always required.

If you’re not sure, it’s best to check your lab report requirements with your instructor.

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Your title provides the first impression of your lab report – effective titles communicate the topic and/or the findings of your study in specific terms.

Create a title that directly conveys the main focus or purpose of your study. It doesn’t need to be creative or thought-provoking, but it should be informative.

• The effects of varying nitrogen levels on tomato plant height.
• Testing the universality of the McGurk effect.
• Comparing the viscosity of common liquids found in kitchens.

An abstract condenses a lab report into a brief overview of about 150–300 words. It should provide readers with a compact version of the research aims, the methods and materials used, the main results, and the final conclusion.

Think of it as a way of giving readers a preview of your full lab report. Write the abstract last, in the past tense, after you’ve drafted all the other sections of your report, so you’ll be able to succinctly summarize each section.

To write a lab report abstract, use these guiding questions:

• What is the wider context of your study?
• What research question were you trying to answer?
• How did you perform the experiment?
• What did your results show?
• How did you interpret your results?
• What is the importance of your findings?

Nitrogen is a necessary nutrient for high quality plants. Tomatoes, one of the most consumed fruits worldwide, rely on nitrogen for healthy leaves and stems to grow fruit. This experiment tested whether nitrogen levels affected tomato plant height in a controlled setting. It was expected that higher levels of nitrogen fertilizer would yield taller tomato plants.

Levels of nitrogen fertilizer were varied between three groups of tomato plants. The control group did not receive any nitrogen fertilizer, while one experimental group received low levels of nitrogen fertilizer, and a second experimental group received high levels of nitrogen fertilizer. All plants were grown from seeds, and heights were measured 50 days into the experiment.

The effects of nitrogen levels on plant height were tested between groups using an ANOVA. The plants with the highest level of nitrogen fertilizer were the tallest, while the plants with low levels of nitrogen exceeded the control group plants in height. In line with expectations and previous findings, the effects of nitrogen levels on plant height were statistically significant. This study strengthens the importance of nitrogen for tomato plants.

Your lab report introduction should set the scene for your experiment. One way to write your introduction is with a funnel (an inverted triangle) structure:

• Start with the broad, general research topic
• Narrow your topic down your specific study focus
• End with a clear research question

Begin by providing background information on your research topic and explaining why it’s important in a broad real-world or theoretical context. Describe relevant previous research on your topic and note how your study may confirm it or expand it, or fill a gap in the research field.

This lab experiment builds on previous research from Haque, Paul, and Sarker (2011), who demonstrated that tomato plant yield increased at higher levels of nitrogen. However, the present research focuses on plant height as a growth indicator and uses a lab-controlled setting instead.

Next, go into detail on the theoretical basis for your study and describe any directly relevant laws or equations that you’ll be using. State your main research aims and expectations by outlining your hypotheses .

Based on the importance of nitrogen for tomato plants, the primary hypothesis was that the plants with the high levels of nitrogen would grow the tallest. The secondary hypothesis was that plants with low levels of nitrogen would grow taller than plants with no nitrogen.

Your introduction doesn’t need to be long, but you may need to organize it into a few paragraphs or with subheadings such as “Research Context” or “Research Aims.”

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A lab report Method section details the steps you took to gather and analyze data. Give enough detail so that others can follow or evaluate your procedures. Write this section in the past tense. If you need to include any long lists of procedural steps or materials, place them in the Appendices section but refer to them in the text here.

You should describe your experimental design, your subjects, materials, and specific procedures used for data collection and analysis.

Experimental design

Briefly note whether your experiment is a within-subjects  or between-subjects design, and describe how your sample units were assigned to conditions if relevant.

A between-subjects design with three groups of tomato plants was used. The control group did not receive any nitrogen fertilizer. The first experimental group received a low level of nitrogen fertilizer, while the second experimental group received a high level of nitrogen fertilizer.

Describe human subjects in terms of demographic characteristics, and animal or plant subjects in terms of genetic background. Note the total number of subjects as well as the number of subjects per condition or per group. You should also state how you recruited subjects for your study.

List the equipment or materials you used to gather data and state the model names for any specialized equipment.

List of materials

35 Tomato seeds

15 plant pots (15 cm tall)

Light lamps (50,000 lux)

Nitrogen fertilizer

Measuring tape

Describe your experimental settings and conditions in detail. You can provide labelled diagrams or images of the exact set-up necessary for experimental equipment. State how extraneous variables were controlled through restriction or by fixing them at a certain level (e.g., keeping the lab at room temperature).

Light levels were fixed throughout the experiment, and the plants were exposed to 12 hours of light a day. Temperature was restricted to between 23 and 25℃. The pH and carbon levels of the soil were also held constant throughout the experiment as these variables could influence plant height. The plants were grown in rooms free of insects or other pests, and they were spaced out adequately.

Your experimental procedure should describe the exact steps you took to gather data in chronological order. You’ll need to provide enough information so that someone else can replicate your procedure, but you should also be concise. Place detailed information in the appendices where appropriate.

In a lab experiment, you’ll often closely follow a lab manual to gather data. Some instructors will allow you to simply reference the manual and state whether you changed any steps based on practical considerations. Other instructors may want you to rewrite the lab manual procedures as complete sentences in coherent paragraphs, while noting any changes to the steps that you applied in practice.

If you’re performing extensive data analysis, be sure to state your planned analysis methods as well. This includes the types of tests you’ll perform and any programs or software you’ll use for calculations (if relevant).

First, tomato seeds were sown in wooden flats containing soil about 2 cm below the surface. Each seed was kept 3-5 cm apart. The flats were covered to keep the soil moist until germination. The seedlings were removed and transplanted to pots 8 days later, with a maximum of 2 plants to a pot. Each pot was watered once a day to keep the soil moist.

The nitrogen fertilizer treatment was applied to the plant pots 12 days after transplantation. The control group received no treatment, while the first experimental group received a low concentration, and the second experimental group received a high concentration. There were 5 pots in each group, and each plant pot was labelled to indicate the group the plants belonged to.

50 days after the start of the experiment, plant height was measured for all plants. A measuring tape was used to record the length of the plant from ground level to the top of the tallest leaf.

In your results section, you should report the results of any statistical analysis procedures that you undertook. You should clearly state how the results of statistical tests support or refute your initial hypotheses.

The main results to report include:

• any descriptive statistics
• statistical test results
• the significance of the test results
• estimates of standard error or confidence intervals

The mean heights of the plants in the control group, low nitrogen group, and high nitrogen groups were 20.3, 25.1, and 29.6 cm respectively. A one-way ANOVA was applied to calculate the effect of nitrogen fertilizer level on plant height. The results demonstrated statistically significant ( p = .03) height differences between groups.

Next, post-hoc tests were performed to assess the primary and secondary hypotheses. In support of the primary hypothesis, the high nitrogen group plants were significantly taller than the low nitrogen group and the control group plants. Similarly, the results supported the secondary hypothesis: the low nitrogen plants were taller than the control group plants.

These results can be reported in the text or in tables and figures. Use text for highlighting a few key results, but present large sets of numbers in tables, or show relationships between variables with graphs.

You should also include sample calculations in the Results section for complex experiments. For each sample calculation, provide a brief description of what it does and use clear symbols. Present your raw data in the Appendices section and refer to it to highlight any outliers or trends.

The Discussion section will help demonstrate your understanding of the experimental process and your critical thinking skills.

In this section, you can:

• Interpret your results
• Compare your findings with your expectations
• Identify any sources of experimental error
• Explain any unexpected results
• Suggest possible improvements for further studies

Interpreting your results involves clarifying how your results help you answer your main research question. Report whether your results support your hypotheses.

• Did you measure what you sought out to measure?
• Were your analysis procedures appropriate for this type of data?

Compare your findings with other research and explain any key differences in findings.

• Are your results in line with those from previous studies or your classmates’ results? Why or why not?

An effective Discussion section will also highlight the strengths and limitations of a study.

• Did you have high internal validity or reliability?
• How did you establish these aspects of your study?

When describing limitations, use specific examples. For example, if random error contributed substantially to the measurements in your study, state the particular sources of error (e.g., imprecise apparatus) and explain ways to improve them.

The results support the hypothesis that nitrogen levels affect plant height, with increasing levels producing taller plants. These statistically significant results are taken together with previous research to support the importance of nitrogen as a nutrient for tomato plant growth.

However, unlike previous studies, this study focused on plant height as an indicator of plant growth in the present experiment. Importantly, plant height may not always reflect plant health or fruit yield, so measuring other indicators would have strengthened the study findings.

Another limitation of the study is the plant height measurement technique, as the measuring tape was not suitable for plants with extreme curvature. Future studies may focus on measuring plant height in different ways.

The main strengths of this study were the controls for extraneous variables, such as pH and carbon levels of the soil. All other factors that could affect plant height were tightly controlled to isolate the effects of nitrogen levels, resulting in high internal validity for this study.

Your conclusion should be the final section of your lab report. Here, you’ll summarize the findings of your experiment, with a brief overview of the strengths and limitations, and implications of your study for further research.

Some lab reports may omit a Conclusion section because it overlaps with the Discussion section, but you should check with your instructor before doing so.

If you want to know more about AI for academic writing, AI tools, or fallacies make sure to check out some of our other articles with explanations and examples or go directly to our tools!

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A lab report conveys the aim, methods, results, and conclusions of a scientific experiment . Lab reports are commonly assigned in science, technology, engineering, and mathematics (STEM) fields.

The purpose of a lab report is to demonstrate your understanding of the scientific method with a hands-on lab experiment. Course instructors will often provide you with an experimental design and procedure. Your task is to write up how you actually performed the experiment and evaluate the outcome.

In contrast, a research paper requires you to independently develop an original argument. It involves more in-depth research and interpretation of sources and data.

A lab report is usually shorter than a research paper.

The sections of a lab report can vary between scientific fields and course requirements, but it usually contains the following:

• Abstract: summarizes your research aims, methods, results, and conclusions
• References: list of all sources cited using a specific style (e.g. APA)
• Appendices: contains lengthy materials, procedures, tables or figures

The results chapter or section simply and objectively reports what you found, without speculating on why you found these results. The discussion interprets the meaning of the results, puts them in context, and explains why they matter.

In qualitative research , results and discussion are sometimes combined. But in quantitative research , it’s considered important to separate the objective results from your interpretation of them.

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• GSS Data Explorer

Data Release 3a for the 2022 GSS Cross-section data, featuring a new multi-mode design, are now available . The additional data features new weighting recommendations, expanded household composition in 2022, and the inclusion of an oversample of Black, Hispanic, and Asian respondents in the 2022 single-year datafile. Release 3a additionally corrects issues with FUND and RELITEN.  We encourage users to review the documentation and consider the potential impact of experiments and data collection approaches on survey estimates.

​​​Articles on methodological issues in survey research specifically dealing with the GSS as well as more general problems.

Wells, Brian M.; Christian, Leah; Bautista, Rene; Lafia, Sara; Davern, Michael

Methodological Reports

Multimode data collection methodologies can help address survey challenges such as declining rates of participation, rising costs, and increasing needs for more timely data collection. However, the order of survey modes as part of a data collection protocol can have an impact on how effective a design can be. This brief explores how the sequential ordering of web and face-to-face (FTF) in a nationally representative survey may impact response rates, key trends, and overall costs. In 2022, the General Social Survey (GSS) was fielded as a multimode study where respondents were randomly assigned to one of two data collection sequences in an experimental design. The first sequence used FTF as the primary mode and then invited all nonrespondents to complete the survey on the web (FTF-first). The second sequence started with a push-to-web (PTW) methodology and then invited a subsample of nonrespondents to complete the survey in a FTF interview (Web-first). Our analyses found that both sequences produced comparable results and neither sequence achieved a better response rate. For costs, the Web-first sequencing was more cost effective per completed interview, but the PTW follow-up in the FTF-first sequence increased response rates at a lower cost and did not require subsampling of nonrespondents.

GSS years: 2022

Morgan, Stephen L.

Some longstanding questionnaire items of the GSS have gender-specific wordings, and the attitudes that they are assumed to measure could be elicited with gender-neutral wordings. This report details and evaluates a 2021 and 2022 experiment that introduces gender-neutral wording alternatives, implemented using a random half-sample assignment of two questionnaire forms. The estimated treatment effects are small, both substantively and with respect to their standard errors. The report recommends that the alternative gender-neutral wordings become the standard wordings for their respective items beginning with the 2026 GSS.

GSS years: 2021, 2022

Wells, Brian M.; Sparkman, Rachel

This report details the inclusion of AmeriSpeak® panelists as an oversample population in the 2022 General Social Survey (GSS) and the implications of including Black, Hispanic, and Asian oversample from this sample source. This report provides an overview of the AmeriSpeak sample and its properties relevant for the 2022 GSS. We examine how the AmeriSpeak oversample cases compare to the baseline GSS sample and how they impact estimates at the population and oversampled group levels.

The high-level findings are as follows:

• The AmeriSpeak cases exhibit some demographic differences from their baseline counterparts, but often improve representation, particularly for racial and ethnic subgroups (e.g., South American Hispanic groups, Chinese).

• Given the AmeriSpeak sample only completed the GSS on the web, there are some differences in substantive responses consistent with previous GSS work suggesting sensitivity to mode.

• U.S. population estimates should exhibit minimal differences between the existing 2022 estimates without the AmeriSpeak oversample as with the AmeriSpeak oversample.

• Including the Black and Hispanic oversamples minimally change the overall estimates for their respective subpopulations, but including the Asian oversample does produce large estimate changes for Asian subpopulation given the oversample accounts for a majority of the total Asian sample.

The AmeriSpeak oversample offers increased sample sizes for Black, Hispanic, and Asian respondents in the 2022 GSS Cross-section. In particular, the sample size for Asian respondents more than doubles with the inclusion of the oversample given their low prevalence in the population. While the Asian subpopulation estimates see more movement than their Black and Hispanic counterparts, we see improved representation for Asian subgroups, suggesting a potential improvement in estimation more broadly given the small initial sample size. Researchers are encouraged to conduct their own research to determine additional impacts of including the AmeriSpeak oversample.

Wells, Brian M.; Seeskin, Zachary H.; Ihde, Amy

This report describes a new set of post-stratification weights available for users of the 1972-2018 General Social Survey (GSS) cross-sectional surveys to help improve nonresponse bias adjustment. The weight derivation follows the approach applied to 2021 and 2022 GSS Cross-sections. Use of these weights results in weighted totals that, for each GSS cross-sectional sample, equal marginal control totals from the U.S. Census Bureau estimates for education, sex, marital status, age, region of the country, race, U.S. born status, and Hispanic origin when available. NORC recommends that GSS data users use this new weight for all analyses in the future. These weights also: (a) correct for the form assignment errors reported in GSS Methodological Report 36 for 1978, 1980, 1982, 1983, 1984, and 1985; (b) correct for the ballot-and-form assignment errors reported in GSS Methodological Report 134 for 2002, 2010, 2012, 2016, and 2018; and (c) support person-level analyses of the combined main and Black oversamples for 1982 and 1987. Given the global trend of declining response rates over the past several years, the use of auxiliary data, such as U.S. Census totals for nonresponse adjustment, is important for improving representativeness of estimates with respect to key demographic characteristics. In addition, this report examines the impact of using the poststratification weights across all GSS cross-sections. The majority of estimate differences observed include poststratification variables and their close correlates.

GSS years: 1972-2018

Wells, Brian M.; Davern, Michael; Ihde, Amy; Bautista, Rene

Methodological Reports, NORC Working Paper

The General Social Survey (GSS), a biennial nationally representative survey of the U.S. adult population, has employed subsampling since 2004. Approximately halfway through the field period in years prior to 2020, half of the remaining cases are randomly subsampled for a more focused follow-up, while the other cases are dropped. Subsampling in the GSS has helped to improve response rates and to achieve cost and sample size efficiencies (O’Muircheartaigh and Eckman 2007). This paper explores the extent to which subsampled (or late) respondents vary from non-subsampled (or early) respondents in GSS 2014, 2016, and 2018. We first examine the demographic characteristics of early and late respondents. Second, we explore substantive differences between the two groups on key analytic variables (e.g., attitudes toward premarital sex, abortion, the death penalty, gun regulation, marijuana legalization, national spending priorities). Finally, we examine differences between early and late respondents on key GSS analytic variables controlling for demographic differences using multivariate logistic regression. Our investigations over three years of the GSS suggest that some demographic and

substantive differences between early and late respondents exist, consistent with previous GSS research (Smith 2006). Our results also suggest that most of the differences on key analytic variables do not persist after controlling for demographic characteristics in multivariate logistic regression models. This finding is consistent with past research on interviewer-administered surveys that find that late respondents are not different from early responders on most variables net of demographic characteristics (e.g., Keeter et al. 2006). Differences found between the 2014, 2016, and 2018 analyses emphasize the need for continued research related to subsampling in the GSS.

GSS years: 2014, 2016, 2018

This memo describes a new set of post-stratification weights available for users of the 2000–2018 GSS cross-sectional surveys. The weight derivation follows the approach applied to the previously released 2021 GSS Cross-section, for which post-stratification weights were developed to improve nonresponse bias adjustment, given the impact of the COVID-19 pandemic on survey operations and response rate. Use of these weights results in weighted totals of each GSS cross-sectional sample that equal marginal control totals from the U.S. Census Bureau estimates for education, sex, marital status, age, region of the country, race, Hispanic origin, and U.S. born status. These weights also correct for the ballot and ballot-and-form assignment errors reported in GSS Methodological Report 134 for 2002, 2010, 2012, 2016, and 2018. The use of auxiliary data such as U.S. Census totals for nonresponse adjustment is important for improving representativeness of estimates with respect to key demographic characteristics, given the global trend of declining response rates over the past several years.

GSS years: 2002, 2010, 2012,2016, 2018

Christian, Leah; Davis, Nicholas; Lancaster, Caroline; Paddock, Susan

As previously reported, an unintended overlap between respondent selection and questionnaire assignment procedures in GSS surveys created an association between questionnaire version (ballot and form) and age order in some households in the historical GSS data. This assignment error occurred in data years 2002, 2010, 2012, 2016 and 2018.  This methodological report describes the equivalence testing to compare original and corrected estimates for each category and each variable for all questions in the affected years. The analysis shows that the error differences due to the assignment error are overall relatively small and corrected weights have been provided for data users.

GSS years: 2002, 2010, 2012, 2016, 2018,

Cowan, Sarah K.; Hout, Michael; Perett, Stuart

Long-running surveys need a systematic way to reflect social change and to keep items relevant to respondents, especially when they ask about controversial subjects, or they threaten the items’ validity. We propose a protocol for updating measures that preserves content and construct validity. First, substantive experts articulate the current and anticipated future terms of debate. Then survey experts use this substantive input and their knowledge of existing measures to develop and pilot a large battery of new items. Third, researchers analyze the pilot data to select items for the survey of record. Finally, the items appear on the survey-of-record, available to the whole user community. Surveys-of-record have procedures for changing content that determine if the new items appear just once or become part of the core. We provide the example of developing new abortion attitude measures in the General Social Survey. Current questions ask whether abortion should be legal under varying circumstances. The new abortion items ask about morality, access, state policy, and interpersonal dynamics. They improve content and construct validity and add new insights into Americans’ abortion attitudes.

Morgan, Stephen L.; Lee, Jiwon

In this report, we present strategies for constructing weights to adjust for attrition in the GSS treble panel. We offer Stata code for the construction of the weights that we explain, as well as data files of weights that researchers may wish to adopt for their own use. 

GSS years: 2006, 2008, 2010, 2012, 2014

(no abstract provided)

GSS years: 2012, 2014, 2016, 2018

Smith, Tom W.

Methodological Report, Chicago, NORC , 2019

* Please note this is an updated version of MR009 (1979). The problem of underrepresentation of males on the GSS reflects the nonresponse tendency of males, possibly exacerbated by female interviewers. Surveys using full probability sampling generally have an underrepresentation of males.

Smith, Tom W.; Son, Jaesok

GSS years: 2016

Stephen L. Morgan

For the 2020 GSS, a review of the free expression items  suggested revisions to “a Muslim clergyman who preaches hatred of the United States,” as part of a broader effort by the GSS Board to reassess all GSS items that are gender-specific in some way. Two gender-neutral alternatives were discussed, “an Islamic cleric who preaches hatred of the United States” and “an Islamic religious leader who preaches hatred of the United States.” For the reasons detailed below, it is possible that a switch to “an Islamic cleric who preaches hatred of the United States” could prompt an undesirable discontinuity in response patterns, beyond what could be expected to result from a gender-neutral substitution. If some GSS respondents are more likely to suspect  that the referenced Islamic cleric has a connection to terrorism, the elicited response may be a mixture of opposition to free expression and a perceived fear of physical violence, with more weighting on the latter. In contrast, “an Islamic religious leader who preaches hatred of the United States” may be preferable, if it is the case that GSS respondents are no more likely to infer a threat to their security than is the case for “a Muslim clergyman who preaches hatred of the United States.” In this report, I offer two sets of results to inform decisions about the questionnaire for the 2020 GSS. First, to set the background, I use GSS data from 2008 through 2018 to summarize levels and changes in attitudes toward free expression for all six existing reference individuals. Second, I offer results from a three-armed experiment that compares “Muslim clergyman” to the two alternatives of “Islamic cleric” and “Islamic religious leader.” The experimental data were collected over the web in January and February of 2019 as part of the AmeriSpeak panel.

on the 2016 General Social Survey (GSS), two question-wording experiements were conducted testing variant versions of core GSS items on job satisfaction (SATJOB) and the co-residence of adult children and their parents (AGED). This report details the findings of these experiments.

Smith, Tom W.; Kim, Jibum

Surveys are conducted using many different modes (e.g. face-to-face, mail, telephone, Internet). Because different modes have different error structures, it is very important to understand the advanctages and disadvantages associated with each mode. In recent years there have been major changes in the mdoes typically utilized in surveys. In particular, there have been increases in the use of computers in data collection, self-administration, and mixed-mode designs. The implications of these and future changes are considered. 

This paper documents an update to the Erickson, Goldthorpe & Portocarero social class schema, first proposed in 1987. Due to the backcoding of the 2010 US Census Occupational Classification, it is now possible to treat all GSS cases according to the same occupational codes, which can then be linked to updated EGP codes. Validity is ascertained using the 2012 American Community Survey’s occupational classification. Please note that this methodological report also includes a .do file for adding EGP codes to a STATA GSS datafile, as well as an OCC10 to EGP crosswalk, included below with download links

GSS years: 1972-2016

http://gss.norc.org/Documents/other/occ10-to-egp-class-crosswalk.csv http://gss.norc.org/Documents/other/code-for-egp-crosswalk.do

Hout, Michael Smith, Tom W. Marsden, Peter V.

Methodological Report, Chicago, NORC

The 2012 GSS included a popular prestige rating (Smith and Son 2014). A sample of 1,001 individuals, first interviewed in 2008 and included in the GSS panel, rated 90 occupations each; a rotation of occupations among respondents resulted in ratings for 860 occupational titles, most of which could be assigned to one of the 840 codes in the 2010 Standard Occupational Classification (SOC). This methodological report explains how we collected the ratings and converted them into prestige scores and a socioeconomic index for each of the 539 occupational categories of the Census Bureau's coding scheme now used in the GSS.

GSS years: 2012, 2014

Smith, Tom W. Laken, Faith Son, Jaesok

Methodological Report, Chicago, NORC , 1, 2014

Given the magnitude and seriousness of gun violence, it is important to have accurate and reliable information on the possession and use of firearms in the United States. This report examines one crucial element, the level of and trends in household and personal gun ownership. First, the report considers methodological issues concerning the measurement of gun ownership. Second, it examines trends in gun ownership. Third, it evaluates the nexus of these two factors, the impact of methodological issues on the measurement of trends gun ownership. Finally, it considers what ancillary trend data on crime, hunting, household size, and number of guns available suggest about trends in gun ownership.

GSS years: 1972-2014

Smith, Tom W. Son, Jaesok

GSS years: 2012

Smith, Tom W. Kim, Jibum

GSS years: N/A

Kim, Jibum Son, Jaesok Kwok, Peter K. Kang, Jeong-han Laken, Faith Daquilanea, Jodie Shin, Hee-Choon Smith, Tom W.

Methodological Report, Chicago, NORC , 2012

Using the 40 years of the General Social Survey (GSS), we investigate the long-term trend and the correlates of family and personal income nonresponse. Family and personal income nonresponse has increased slightly by about 5 percentage points from 1974 to 2010 (9% to 13% in family income; 7% to 12% in personal income). While family income nonresponse was equivalently attributed to “Don’t Know” and “Refused,” personal income nonresponse was mainly attributed to “Refused.” We found very similar correlates of family and personal income nonresponse, such as being older, female, married, self employed, those not answering the number of earners, uncooperative respondents, people living in the East, and those surveyed in recent periods. In addition, based on the interviewer’s evaluation, uncooperative respondents are less likely to response “Don’t Know” than “Refused” and respondents with poor comprehension are more likely to respond “Don’t Know” than “Refused.” Our findings suggest that we need to distinguish “Refused” from “Don’t Know” if we aim to better understand income nonresponse and to consider paradata to evaluate the cognitive processing of income nonresponse.

GSS years: 1972-2012

Hout, Michael Hastings, Orestes P

Methodological Report, Chicago, NORC , 6, 2012

We assess the reliability and stability of core items in the General Social Survey using Alwin’s (2007) implementation of Heise’s (1969) model. Of 265 core items examined we find mostly positive results. Eighty items (over 30 percent) have reliability coefficients greater than 0.85; another 84 (32 percent) have reliability coefficients between 0.70 and 0.85. Facts are generally more reliable than other items. Stability was slightly higher, overall, in the 2008-2010 period than the 2006-2008 period. The economic recession of 2007-09 and the election of Barack Obama in 2008 altered the social context in ways that may have contributed to instability.

GSS years: 2006, 2008, 2010

Methodological Report, Chicago, NORC , 5, 2011

GSS years: 2006, 2008

Methodological Report, Chicago, NORC , 5, 2010

Methodological Report, Chicago, NORC , 11, 2009

GSS years: 2002, 2004, 2006, 2008

Methodological Report, Chicago, NORC , 2010

GSS years: 2006,2008

Methodological Report, Chicago, NORC, 2009

GSS years: 2008

MR113 2006-2008 General Social Survey Panel Validation

Smith, Tom W. Sokolowski, John

Methodological Report, Chicago, NORC , 2008

GSS years: 2002,2008

Malhotra, Neil Krosnick, Jon A Haertel, Edward

Methodological Report, Chicago, NORC , 8, 2007

Social scientists in many disciplines have used the GSS's ten-item Wordsum vocabulary test to study the causes and consequences of vocabulary knowledge and related constructs. In adding up the number of correct answers to yield a test score, researchers have implicitly assumed that the ten items all reflect a single, underlying construct and that each item deserves equal weight when generating the total score. In this paper, we report evidence suggesting that extracting the unique variance associated with each word and measuring the latent construct only with the variance shared among all indicators strengthens the validity of the index. We also report evidence suggesting that Wordsum could be improved by adding words of moderate difficulty to accompany the existing questions that are either quite easy or quite difficult. Previous studies that used Wordsum should be revisited in light of these findings, because their results might change when a more optimal analytic method is used.

GSS years: 1974-2004

Smith, Tom W. Kim, Seokho

Methodological Report, Chicago, NORC , 4, 2007

The new Baylor Religion Survey (BRS) is an important addition to the available data on religion in contemporary America ('American Piety,' 2006). Few national surveys have included so many valuable questions on the religious background, beliefs, and behaviors of adult Americans. The BRS is a fruitful source for expanding our knowledge about religion and the initial analysis that accompanied the release of the data last Fall has already made a major contribution to the sociology of religion ('American Piety' 2006; 'American Piety 2005,' 2006; Dougherty, Johnson, and Polson, 2006; Dougherty, Johnson, and Polson, 2007; 'Losing My Religion,' 2006).

GSS years: 2006

Methodological Report, Chicago, NORC , 2007

Kim, Jibum Smith, Tom W. Kang, Jeong-han Sokolowski, John

Methodological Report, Chicago, NORC , 2006

GSS years: 1984-2002

GSS years: 1984-2004

Methodological Report, Chicago, NORC , 2005

Several probes were added to the 2004 GSS to see if the declining Protestant population was due to the data being hidden in Christian or Inter/non-denominational categories. Very few cases were found, but the 2006 GSS will attempt to resolve the status of several dozen cases.

GSS years: 1972-2004

The large rise in multiple ethnic mentions was due to the change in mode to CAPI. Although this change was noted, there was no significant change on the distribution of ethnicities.

GSS years: 2002,2004

Switching from a 4-category to 5-category health scale doesn't change explanatory power and would prohibit trends in these categories from being reliably estimated across scales. Changing from 4 to 5 also shifts distribution at the positive end, but not at the negative end.

NHIS, FQES, National Health and Nutrition Examination Survey II

Using CAPI (introduced in 2002) allows researchers to compare HEF variables and reconcile conflicting information while still in the field. Cleaning and consistency checks will be made of HEF variables to obtain more accurate data.

GSS years: 1980-2004

Hout, Michael

Methodological Report, Chicago, NORC , 2004

GSS years: 1972-2002

Kim, Jibum Smith,Tom W. Kim, Seokho Kang, Jeong-han Berktold, Jennifer

GSS years: 2000, 2002

Smith, Tom W. Michael, J. Michael

Methodological Report, Chicago, NORC , 2003

GSS years: 1984, 2000, 2002

GSS years: 2002

GSS years: 1988-2002

GSS years: 1972-2000

Methodological Report, Chicago, NORC , 10, 2001

GSS years: 2001

Marsden, Peter V.

Methodological Report, Chicago, NORC , 6, 2001

Name generators, used measuring egocentric networks in surveys, are complex questions that make substantial demands on respondents and interviewers alike. They are therefore vulnerable to interviewer effects, which arise when interviewers administer questions differently in ways that affect responses-in particular, the number of names elicited. Van Tilburg (1998) found significant interviewer effects on network size in a study of elderly Dutch respondents; that study included an instrument with seven name generators, the complexity of which may have accentuated interviewer effects. This article examines a simpler single-generator elicitation instrument administered in the 1998 General Social Survey (GSS). Interviewer effects on network size as measured by this instrument are smaller than those found by Van Tilburg, but only modestly so. Variations in the network size of respondents within interviewer caseloads (estimated using a single-item "global" measure of network size and an independent sample of respondents) reduce but do not explain interviewer effects on the name generator measure. Interviewer differences remain significant after controls for between-interviewer differences in the sociodemographic composition of respondent pools. Further insight into the sources of interviewer effects may be obtained via monitoring respondent-interviewer interactions for differences in how name generators are administered. 

GSS years: 2000

Methodological Report, Chicago, NORC , 7, 2001

Methodological Report, Chicago, NORC , 1999

GSS years: 1988-1998

Methodological Report, Chicago, NORC , 12, 2002

GSS years: 1998

Methodological Report, Chicago, NORC , 1998

The relationship between educational attainment and age/cohort is curvilinear, and not negative as the historical trend might indicate, for two reasons: the advent of associate degrees and the time required to obtain graduate degrees. Control variables (for age/cohort) straighten out otherwise confounding relationships.

GSS years: 1990, 1991, 1993, 1994, 1996

ANES 1984-1991

Methodological Report, Chicago, NORC , 1997

GSS years: 1994, 1996

Methodological Report, Chicago, NORC , 2, 1997

GSS years: 1996

Smith, Tom W. Shin, Hee-Choon Xiaoxi, Tong

Methodological Report, Chicago, NORC , 2, 1996

There were few sample frame effects associated with NORC's shift from the 1980 to the 1990 Census. Also, design effects based on the 1990 sample frame are of the same nature and magnitude as indicated by previous research.

GSS years: 1993

Methodological Report, Chicago, NORC , 12, 1995

GSS years: 1972-1994

Methodological Report, Chicago, NORC , 6, 1995

This article reviews questions in the GSS asking a respondent's race or ethnicity and proposes several methods in which these measures could be refined.

Methodological Report, Chicago, NORC , 1995

The GSS recently shortened the length of its core and, as a result, the context of many items changed. Few context effects were caused by these shifts.

GSS years: 1994

GSS years: 1972-1993

Methodological Report, Chicago, NORC , 8, 1994

GSS years: 1975-1993

Methodological Report, Chicago, NORC , 3, 1994

Response differences in two GSS and one ISSP spending scale were slight, except for spending on the environment, which showed a context effect. In all, the spending scales are generally answered in a consistent and meaningful manner.

GSS years: 1990

Methodological Report, Chicago, NORC , 1980

The 1980 General Social Survey and the American National Study by SRC are compared to determine house effects. The difference on frequency of don't know categories between the two surveys is the most significant house effect. Also, the difference in time of interview and training of interviewers causes variation in data.

GSS years: 1980

Methodological Report, Chicago, NORC , 1985

Studies of voting behavior and other political matters in the fifties developed a picture of the American electorate that was startlingly at odds with the basic assumption of a rational citizenry as formulated in classic democratic theory. In general, the low or defective levels of conceptualization, information, participation, attitude constraint, and consistency were seen as indicating a very underdeveloped level of political thought and weak or disorganized political attitudes. In particular, inconsistency in attitudes over time was interpreted as indicating an abundance of non-attitudes. In this paper, we will review the literature on non-attitudes. We will examine how the concept of non-attitudes compares with rival explanations of mass belief systems and evaluate the conceptual and evaluate the conceptual and empirical appropriateness of competing formulations. We will then consider the implications of these findings on survey design and analysis in general.

GSS years: 1972, 1973, 1974, 1975, 1976, 1977, 1978

Schaeffer, Nora Cate

Methodological Report, Chicago, NORC , 1982

Variations in the wording of the child qualities items were examined in order to determine the degree of male bias present. This bias is present in both variations but to a lesser degree in the child item than the he item.

Objective measures of ethnicity and nationality may be inaccurate because substantial numbers of people do not know where their ancestors were born, have multiple nationalities, or do not adopt the ethnicity suggested by place of birth. Generally a combination of behavioral, natal, and subjective approaches is most effective, and even a simple subjective measure may be more effective than an objective one.

GSS years: 1972, 1973, 1974, 1975, 1976, 1977, 1978, 1980

Conflicts found in the work supervision and self-employment items stem from: (1) borderline cases which include both elements, (2) answering the question for one's spouse rather than self, and (3) misinterpretation of the supervision question.

Methodological Report, Chicago, NORC , 12, 1993

Response differences in a GSS scale and the ISSP scales result from measurement differences and group descriptors. Differences in questions wording, in particular, concerning descriptors for the government, produced different responses for subjects suggesting that the two labels were connoting different meanings.

GSS years: 1991

Methodological Report, Chicago, NORC , 7, 1993

John Brehm incorrectly weighted the data when comparing the CPS and the GSS. This article shows that the GSS, when properly weighted, is very similar to the CPS in all demographics except for gender (See also Brehm, 324).

GSS years: 1978-1988

CPS 1978, 1980, 1982, 1984, 1986, 1988; NES

Changes in the alignment of categories or the shift in scale can have significant response effects for surveys. The physical layout of surveys can also affect interviewers and hence data quality negatively through confusing skip patterns or the amount of physical space available corresponding to how much open ended detail is recorded.

ISSP 1987; Gallup 1954; Wirthlin; Gordon Black; ORC; Yankelovich and Hart-Tetter 1990; NORC 1954

Methodological Report, Chicago, NORC , 1992

GSS years: 1972-1991

Respondents with non-attitudes and middle-of-the-road attitudes are attracted to the +1 rather than the -1 response category on a ten-point scalometer. Endpoints, especially the negative endpoint, disproportionately attract responses. Changes in the scalometer, such as including 0 as a midpoint and pointing out all ten or eleven response categories, might cause fewer response effects and more accurate ratings.

GSS years: 1974-1991

Gallup 1953-1973

This article compares the differences in the respondents to the 1991 GSS and the 1992 reinterview, and describes three differences. First, respondents to the reinterview were more upscale than the original interviewees. Second, non-response was higher among those who were uncooperative in the first interview. Third, non-response was higher among non-voters.

Nakao, Keiko Treas, Judith

Following Duncan's procedures new socioeconomic indexes are calculated based on the GSS/NORC study of occupational prestige.

GSS years: 1989

Census 1980

This article describes the addition of 93 variables from the HEF for all full-probability surveys from 1975-1992.

Methodological Report, Chicago, NORC , 1991

Ethno-religious composition, political composition, density, and composition of a network by friends or co-members of organizations are measured with relatively high reliability, and some, such as sex composition, remain problematic, even when the number of alters grows quite large. The sensitivity of reliability estimates to differences in instrument design is examined using design variations in the surveys studied.

GSS years: 1985, 1987, 1988

Northern California Community Study 1977-1978

Missing information is a greater problem for income than for any other demographic and non-response has increased over time. However, non-response in the GSS is less than in many other studies

Census 1960, 1970; CPS 1973; Income Survey Development Program 1978; Survey Income and Program Participation 1983; NES 1988; ISSP 1989

Methodological Report, Chicago, NORC , 1990

The authors construct a new prestige scale for the 1980 Census Occupational classification. Using 1989 GSS data, 740 occupations were ranked according to social prestige.

Nakao, Keiko Hodge, Robert W. Treas, Judith

Methodological Report, Chicago, NORC , 10, 1990

Prestige scores for all occupations developed from the national surveys in the 1960's have been widely used by researchers in the social sciences. The change in the 1980 Census classification of occupations necessitates updating the prestige scale accordingly. New scores can be obtained either by reworking the old scores or by collecting new data. In this paper, we argue for the latter choice based on the methodological, substantive, and theoretical considerations. The plan to collect occupational assessments from a nationally representative sample of 1500 Americans in the 1989 NORC General Social Survey will also be outlined.

Methodological Report, Chicago, NORC , 9, 1990

GSS years: 1988, 1989

Methodological Report, Chicago, NORC , 12, 1989

Missing data on father's occupation may have a small impact on intergenerational comparisons with intergenerational associations weaker for missing data. Possible corrections for missing data may include using mother's and spouse's work information.

GSS years: 1972-1988

Methodological Report, Chicago, NORC , 9, 1989

Difficulty in studying order effects stems from the number of potential causal influences, competing explanations, interaction effects with question type, question specificity, question vagueness, question centrality, response type, history, administration, conflicting attitudes, and other effects. Promising solutions include split ballots, think aloud procedures, follow-up questions, probes on other dimensions, and various experimental designs.

GSS years: 1976, 1978, 1980

SRC 1979-80; NORC 1987; Greater Cincinnati Surveys 1983-84; DAS 1971

Though most of the data on sexual behavior and attitudes from the 1988 and 1989 GSS appear valid and reliable, caution still needs to be use when examining the 1988 responses of male homosexuals and the gender gap in reported number of partners. (See also No. 2954??)

GSS years: 1988, 1989, 1990

Ligon, Ethan

Methodological Report, Chicago, NORC , 1989

Two new GSS income measures (REALINC and RINCOME) constructed from current GSS variables for household and respondent income correct for changes in the price level across years.

BLS 1983; CPS 1980

Alwin, Duane F.

Methodological Report, Chicago, NORC , 2, 1989

In this paper I discuss several of the difficulties involved in estimating the reliability of survey measurement. Reliability is defined on the basis of classical true-score theory, as the correlational consistency of multiple measures of the same construct, net of true change. This concept is presented within the framework of a theoretical discussion of the sources of error in survey data and the design requirements for separating response variation into components representing such response consistency and measurement errors. Discussion focuses on the potential sources of random and nonrandom errors, including "invalidity" of measurement, the term frequently used to refer to components of method variance. Problems with the estimation of these components are enumerated and discussed with respect to both cross-sectional and panel designs. Empirical examples are given of the estimation of the quantities of interest, which are the basis of a discussion of the interpretational difficulties encountered in reliability estimation. Data are drawn from the ISR's Quality of Life surveys, the National Election Studies and the NORC's General Social Surveys. The general conclusion is that both crosssectional and panel estimates of measurement reliability are desirable, but for the purposes of isolating the random component of error, panel designs are probably the most advantageous. 

GSS years: 1973, 1974

Alwin, Duane F. Krosnick, Jon A.

GSS years: 1973 -1988

Methodological Report, Chicago, NORC , 12, 1988

Open ended coding errors for occupation are frequent, but fortunately mistakes do not differ from correct coding by much, and thus do not greatly affect analysis. More attention is needed in training coders and devising coding schemes.

GSS years: 1988

Methodological Report, Chicago, NORC , 11, 1988

For the sexual behavior items on the 1988 GSS, there is little evidence of non-response bias and attitudes and behaviors appear somewhat consistent. Though reports of sexless marriages can reasonably be explained, the data on number of partners and male homosexuals is questionable. (See also No. 2953??)

Methodological Report, Chicago, NORC , 9, 1988

By the recoding of various demographics, GSS respondents can be classified according to the government definition of poverty.

Changes in GSS measurement procedures have distorted some trends in variables across time. These effects are identified, and in cases of extreme distortion, corrections are suggested.

Gallup 1976

Methodological Report, Chicago, NORC , 8, 1988

Rasinski, Kenneth A

Methodological Report, Chicago, NORC , 5, 1988

Past attempts at explaining the effect of question wording on responses to survey questions have stressed the ability of question wording to persuade and influence the respondent, resulting in attitude change. This paper promotes an alternative view, which is that even small changes in wording often shift the meaning of the question and thus affect the way the respondent things about the issue. Analyses of question wording experiments on the 1984, 1985, and 1986 General Social Surveys were conducted to examine the effect of wording changes on public support for various types of government spending. Consistent wording effects were found across the three years. An examination of the effects of wording changes and of their interaction with respondent individual differences led to two conclusions: (1) even minor wording changes can alter the meaning of a survey question, and (2), this effect is not limited to individuals with lower levels of education or with less stable attitudes

GSS years: 1984, 1985, 1986

Schuman, Howard Scott, Jacqueline

Methodological Report, Chicago, NORC , 5, 1989

Two split-ballot experiments, one on DK filtering and one on agreeing response set, were included in the GSS in 1974 and replicated in 1982. Response effects occurred in each experiment in 1974 and were generally replicated in 1982, but the effects do not interact with time. 

GSS years: 1972, 1982

Methodological Report, Chicago, NORC , 2, 1988

The GSS's switch from a rotation to a split ballot design offers advantages of maintaining one year intervals for variables, ease in judging rate of change in items, and applying econometric time series analysis and testing for context effects. Disadvantages include more sampling variability, complications in representation of time in analysis, and the possibility of introducing new context effects.

GSS years: 1984

Methodological Report, Chicago, NORC , 8, 1987

GSS years: 1973-1987

Test/retest consistency varies by attributes of the respondent, and this variation is largely a function of reliability differentials between groups.

GSS years: 1972, 1973, 1974, 1978

The Commission's analysis of public opinion is methodologically unsound and therefore substantively suspect.

GSS years: 1972-1986

Gallup 1977, 1985; Yankelovich 1975 1976 1977 1982; Commission on Obscenity and Pornography 1970; Newsweek/Gallup 1985

Duncan, Greg J. Groskind, Fred

Methodological Report, Chicago, NORC , 5, 1987

Low benefit responses to the 1986 Welfare Vignette supplement are probably not due to misunderstanding the questions. It is also a mistake to assume that respondent-designated incomes were intended to be net benefits.

GSS years: 1986

Krosnick, Jon A. Alwin, Duane F.

Methodological Report, Chicago, NORC , 3, 1987

Respondents often choose merely satisfactory answers to survey questions when the cognitive and motivational demands of choosing optimal answers are high. Satisficing is more prevalent among people with less cognitive sophistication, though it is no more prevalent among people for whom the topic of a question is low in salience and/or personal importance.

Methodological Report, Chicago, NORC , 1986

Disinterest, lack of reading ability, difficulty in judgment, and comprehension lead to nonresponse to the welfare vignettes. Bias was small and related to nonresponse associated variables. Respondents also made marking mistakes. Despite these problems, the vignettes worked well with a small amount of error.

Methodological Report, Chicago, NORC , 1987

This paper discusses the use of survey supplements, factors influencing supplement attrition and nonresponse bias, and attrition and nonresponse bias on the 1985 ISSP Supplement. Overall supplement attrition was moderate and not random. Attrition was higher among those who are politically uninterested and less educated, less likely to discuss problems and socialize with others, Northeasterners, isolationists, and dislike foreign countries.

GSS years: 1984, 1985

OCG I & II 1962, 1973; BSA 1983-1985; Opinion and ISV 1976; Civil Liberties Survey 1978; NORC 1964

Burt, Ronald S.

Methodological Report, Chicago, NORC , 6, 1987

GSS years: 1985

Burt, Ronald S. Marsden, Peter V. Rossi, Peter H.

Building on the GSS network items, the authors propose several changes and improvements which could be used to make a standard set of network items for survey research. This set would be efficient, reliable, and valid.

DAS 1966; Northern California Communities Study 1977

Burt, Ronald S. Guilarte, Miguel G.

The idea of structural balance is used to suggest quantitative intervals between relationship strength response categories in the GSS network data. In contrast to an assumption of equal intervals between the categories of relationship strength, the intervals appear quite uneven.

Methodological Report, Chicago, NORC , 6, 1986

The people identified as important discussion partners in the GSS network data were cited in order of strength of relationship with respondent: the first cited person having the strongest relation, the second having the next strongest, and so on. Order effects on closeness and contact frequency are described in the context of network size and relation content.

Smith, Tom W. Peterson, Bruce L.

An unintended overlap between respondent selection and form assignment procedures in GSS surveys from 1978 to 1985 created an association between form and age order in some households. This led to an association between form and various variables linked to age order. A weight was developed to compensate for the assignment bias and achieve random distribution of affected variables across forms.

GSS years: 1973-1985

Overall proxy reports for spouses were as accurate as self-reports, probably because attributes measured (religion education, occupation, etc.) were major, basic demographics. Significantly higher levels of non-response were found for proxy reports, but a level of missing data was nevertheless negligible.

GSS years: 1972-1978, 1980, 1982-1985

Alteration of the GSS content by the addition or deletion of items, by the switching of items from permanent to rotating status, or by switching items from one rotation to another hampers keeping measurement conditions constant and therefore increases the possibility that true change will be confounded with measurement effects.

GSS years: 1972-1985

The term welfare consistently produces more negative evaluations than does the term poor, illustrating the major impact different words can have on response patterns.

SRC 1972, 1974, 1976, 1982; MAP 1968, 1982; Harris 1972 1976; Gallup 1976; Yankelovich

Methodological Report, Chicago, NORC , 1984

This is an argument for obtaining network data in the General Social Survey.

Peterson, Bruce L.

This report on the 1984 GSS experiment comparing the effect of varying the number of response categories, concludes that the inter-item correlations are not appreciably different in the seven-point version of the confidence question than in the traditional three-point item.

The report is a preliminary analysis of eight methodological experiments and adaptations in the 1984 General Social Survey: New Denominational codes; intra-item order effects, child qualities; sex of child, child qualities; spend priorities; confidence variation in response categories; bible fundamentalism, two trends; Images of God, two scales; and order effect of grace.

GSS years: 1972-1984

Gallup; ANES; NORC

Dempsey, Glenn R.

Methodological Report, Chicago, NORC , 9, 1984

The purpose of these two experiments on the 1983 GSS was to determine whether U.S. and European scaling techniques could measure political ideology and social status in the U.S. in similar ways. POLVIEWS tends to have stronger correlations with political and social attitudes than does POLVIEWX (European scale). CLASS, the standard GSS question also correlates higher than the European counterpart RANK.

GSS years: 1972-1982

Methodological Report, Chicago, NORC , 1983

When question order was reversed so that questions on valued qualities of children came before those on abortion, support for abortion decreased. Although a split ballot in 1983 failed to confirm the effect of altered question order, that may be the result of lower overall support of abortion.

GSS years: 1977, 1978, 1980, 1983

Methodological Report, Chicago, NORC , 4, 1983

Ranking and rating techniques for measuring parental socialization values are found to be similar with respect to ordering aggregate preferences. However, ranked measures account for appreciably more variance in the latent variable, self-direction versus conformity.

Durall 1946; Schuman and Presser, 1981

Methodological Report, Chicago, NORC , 10, 1984

GSS years: 1980, 1982

Results from the 1982 GSS experiment show that non-affective dimensions such as importance, information, firmness, and open-ended questions added to issues like support/opposition to the ERA and abortion, and can discriminate the attitude constraint between two related measures.

Methodological Report, Chicago, NORC , 6, 1983

Clustering scale items together increases inter-item correlations, but has no clear impact between the scale and independent variables.

GSS years: 1973, 1974, 1975, 1976, 1977, 1978, 1980, 1982

GSS years: 1972, 1973, 1982

Methodological Report, Chicago, NORC , 7, 1982

Voter turnout and candidate voted for are difficult variables to reliably measure. Voting is consistently over-reported and votes for winners are usually exaggerated.

ANES 1968, 1972, 1976, 1980; CPS 1968 1972, 1976, 1980

Methodological Report, Chicago, NORC , 5, 1982

Order-effects are an ill-known phenomenon in survey research. There are many different types with distinct causes. Conditional order effects in which the variation occurs mostly or completely among those giving a particular response to the antecedent question are examined in depth.

Methodological Report, Chicago, NORC , 1981

Respondents who contradict themselves on abortion items actually disapprove of abortion. The approving response to the general item is best considered an error in grasping the connection between the general and the situational items.

GSS years: 1977, 1978, 1980

Ethnicity is the most difficult of all background variables to measure, as language, religion, race, nationality and culture must be pieced together. About one quarter of Americans are either over- or under-identifiers of their ancestors. The ability of ethnicity to explain attitudes drops with immigrant generation, though it remains significant even after several generations.

SRC 1978; ANES 1978; Census of Canada 1971

In general, item nonresponse is higher for the less educated. The reverse is true however on obscure and fictive questions without filters. With filters, the obscure and fictive questions show no association between item nonresponse and education.

ANES 1956, 1958, 1960, 1980

Various methods of measuring the impact of non-response bias on survey estimates are examined. It is concluded that there is no simple, general, or accurate way of measuring it. Further research is encouraged.

There is an apparent contradiction between the disapproving responses to the general hitting question and the more specific subquestions. This contradiction is due in part to differences in education and achievement.

GSS years: 1973, 1975, 1976, 1978

Methodological Report, Chicago, NORC , 1979

* Please note there is a version updated in 2009 (MR009a). The problem of underrepresentation of males on the GSS reflects the nonresponse tendency of males, possibly exacerbated by female interviewers. Surveys using full probability sampling generally have an underrepresentation of males.

Census 1970, 1972-78; CPS 1975-77; CNS 1973-74; ANES 1972-78

Smith, Tom W. Bruce, C. Stephenson

Methodological Report, Chicago, NORC , 1979.

The authors explain various techniques to determine measurement error in opinion surveys. Focusing on test/retest experiments, they conclude that the problems of distinguishing measurement error from true change are sufficiently fundamental and sufficiently complex that they must be attacked with various techniques.

Stephenson, C. Bruce

Methodological Report, Chicago, NORC , 4, 1979.

Probability sampling with quotas (PSQ) overrepresents large households. Both PSQ and full probability sampling (FP) underrepresent people from large households. Also, PSQ underrepresents men who are working full-time. Finally, difficult respondents may be underrepresented more seriously in the PSQ sample. However, FP underrepresents men and urbanites.

GSS years: 1972, 1973, 1974, 1975, 1976

Methodological Report, Chicago, NORC , 3, 1980.

Ethnicity is a difficult attribute to measure. It can be determined for about 78 percent of all non-blacks when measured subjectively and for about 85 percent when determined subjectively and natally. A lack of ethnic affiliation is related to being a member of the old stock, host culture; having low education and social standing; and poor transmission of family information between generations.

GSS years: 1972, 1973, 1974, 1975, 1976, 1977

CPS 1972; SRC 1972, 1974, 1978

Methodological Report, Chicago, NORC , 1978.

This report examines response rates of NORC and SRC and finds that on the GSS the causes of non-response are explicit refusals, unavailable, and a small residual group of sick or otherwise uninterviewable people. The mixture of non-responses appears to differ between the GSS's and SRC's surveys, although total response rates are nearly identical.

SRC 1972-78

Methodological Report, Chicago, NORC , 4, 1984.

Review of the GSS size of place codes resolved suspected sampling frame artifact but uncovered miscoded size of place variables. Fortunately, the magnitude of the misclassifications is minimal.

Both full probability and block-quota sampling techniques overrepresent people from small households. This bias can be eliminated by weighting the number of eligible respondents per household. The distortions caused by this bias fortunately appear to be small.

While house effects are not an insurmountable and pervasive survey problem, they do affect survey response particularly in the area of the don't know response level.

Stouffer 1954; NORC 1960; Gallup 1971-76 (14); Roper 1971, 1973; SRC 1972, 1974-76

Christian, Leah; Paddock, Susan; Blumerman, Lisa; Bautista, Rene; Davern, Michael

Methodological Report, Chicago, NORC , 1981.

Differences in survey procedures, i.e., format, wording placement, and order, artificially increase the variation of responses to questions on institutional confidence. Also, the concept of confidence is somewhat vague and allows for fluctuations that complicate an analysis of opinions on confidence. All in all, much of the inter- and intra-survey changes in trends are true fluctuations.

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Parenting Styles and Youth’s Externalizing and Internalizing Behaviors: Does Self-Control Matter?

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• Published: 06 September 2024

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• Diana Almeida 1 &
• Gilda Santos   ORCID: orcid.org/0000-0002-8699-0126 1 , 2  

The externalizing and internalizing behaviors of children and youth have been the object of extensive criminological research, mainly due to the potentially harmful impact on these individuals' future development and adjustment. The current study aimed to explore the influence of parenting styles on the emergence of children and youth’s externalizing and internalizing behaviors and to understand the influence of self-control in this relationship. Following a quantitative self-report approach and using a sample of 472 Portuguese middle-school children, this study found that the children’s sex, low self-control, and authoritative parenting style significantly predicted externalizing and internalizing behaviors. The data also revealed that children's age and the permissive parenting style significantly predicted externalizing but not internalizing behaviors and that the authoritarian parenting style significantly predicted internalizing behaviors. Low self-control partially mediated the relationship between parenting styles and externalizing and internalizing behaviors in most tested models. Implications for theory and practice are discussed.

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Introduction

Over the last decades, there has been a growing interest in the study of children and youth’s problem behavior, mainly due to its relation to difficulties in later behavioral, emotional, cognitive, and social adjustment (Calkins et al., 2007 ; Campbell et al., 2000 ; Keane & Calkins, 2004 ; Lier et al., 2012 ; Liu et al., 2011 ; Min et al., 2018 ; Rinaldi & Howe, 2012 ; Sommer, 2010 ).

A common approach is the one that classifies children and youth’s problem behaviors into two major categories, namely externalizing and internalizing behaviors (Akhter et al., 2011 ; Alizadeh et al., 2011 ; Rinaldi & Howe, 2012 ), acknowledging that adolescence is one of the most critical developmental periods for the emergence and development of such behaviors (Braza et al., 2015 ; Lorber & Egeland, 2009 ; Risper, 2012 ).

Externalizing behaviors are complex and can cause severe consequences for the child and the community as whole in the immediate or long term (Georgiou & Symeou, 2018 ). Largely, these behaviors involve actions and include disruptive ( e.g., hyperactivity, anger, frustration, attention problems, impulsivity), antisocial, aggressive, and/or delinquent behaviors (Alizadeh et al., 2011 ; Braza et al., 2015 ; Rose et al., 2018 ), being, therefore, characterized by their visibility and exteriority (Georgiou & Symeou, 2018 ; Liu, 2004 ; Rinaldi & Howe, 2012 ; Sommer, 2010 ). In other words, externalizing behaviors constitute an evident type of behavior, based on which the child interacts negatively with the environment that surrounds him and adopts inadequate behaviors, such as defiance, verbal aggression, restlessness (Rinaldi & Howe, 2012 ), destruction of property, among others (Keil & Price, 2006 ).

On the other hand, internalizing behaviors are intrapersonal, that is, turned inside out (Achenbach & Edelbrock, 1978 ) and expressed at the child's psychological and emotional levels. Internalizing behaviors include anxiety ( e.g., worry, fear), distress ( e.g., difficulty being calm), shyness and/or social isolation, withdrawal, depression, and somatization, among others (Alizadeh et al., 2011 ; Braza et al., 2015 ; Georgiou & Symeou, 2018 ; Liu, 2004 ; Rinaldi & Howe, 2012 ). These behavioral problems have a more pronounced and negative impact on the child's psychological functioning than on their exterior environment since, in most situations, the behavior is covert and difficult to detect (Georgiou & Symeou, 2018 ; Rose et al., 2018 ).

When comparing the expression of such behaviors as a function of the child’s sex, previous studies have been consistently demonstrating that girls tend to express more internalizing behaviors, such as anxiety and depression, while boys tend to adopt more externalizing behaviors, such as anger and aggressive behavior (Bongers et al., 2003 ; Campos et al., 2014 ; Chaplin & Aldao, 2013 ; Crijnen et al., 1997 ; Moral et al., 2012).

The importance of studying these behaviors is related to the fact that they are usually associated with several negative outcomes over the life course. For example, previous studies have revealed that externalizing behaviors increase the risk of juvenile delinquency, adult crime, violent and antisocial behaviors, and substance abuse. Also, internalizing behaviors appear to be associated with a greater risk of depression, anxiety, suicide in adolescence and adulthood, and school failure (Farrington, 2003 ; Liu, 2004 ; Lorber & Egeland, 2009 ; Min et al., 2014 ; Moffitt, 1993 ). As such, the importance of understanding the origin of these behaviors (Georgiou & Symeou, 2018 ) and their developmental patterns is acknowledged, reinforcing the need to adopt intervention strategies suitable for preventing those behaviors and their iatrogenic effects (Liu, 2004 ).

Prior research has focused on the influence that individual, familiar, or contextual factors play in the emergence and development of such behaviors (Min et al., 2018 ). Particularly, focusing on the individual and family levels, previous studies have consistently shown that parenting styles and self-control might play a central role in the emergence and development of children and youth’s disruptive behaviors, such as externalizing, internalizing and even delinquent behaviors (Georgiou & Symeou, 2018 ; Farrington, 2003 ; Hoeve et al., 2009 ; Lorber & Egeland, 2009 ; Liu, 2004 ; Min et al., 2014 ; Moffitt, 1993 ; Steinberg et al., 2006 ; Cauffman et al., 2005 ; Moffitt et al,. 2011 ; Pratt & Cullen, 2000 ).

Thus, the current study seeks to explore the influence that permissive, authoritarian, and authoritative parenting styles have on the development of externalizing and internalizing behaviors, as well as to understand the potential indirect effects that self-control can have on this relationship, using a sample of 472 Portuguese middle school children and youth.

Parenting Styles

Parenting is a complex task, particularly when considering the different elements, processes, and dynamics it comprises (Rose et al., 2018 ). Over the years, there has been extensive theoretical and empirical research into the influence of parenting on children’s socialization (Baumrind, 1967 , 1971 , 1978 ), which has commonly followed two distinct theoretical approaches (Darling & Steinberg, 1993 ): either dimensional or typological. The former focuses on the individual dimensions of parenting, i.e., parenting practices ( e.g., affection, monitoring, and parental discipline). The latter labels parents with a particular parenting style according to different dimensions (Baumrind, 1967 ; Pinquart, 2017 ). There are a series of reasons based upon which the typological approach has been considered preferable for a comprehensive understanding of the influence parenting exert on children and youth behavior. First, it provides a holistic, interactive, and dynamic understanding of the processes and environments on which the family context is based (O’Connor, 2002 ). Furthermore, it possesses an " increased ecological validity " (Pereira et al., 2009 , p. 455) to the extent that it can capture the interaction effects of the different dimensions and how they affect and influence each other (Steward & Bond, 2002 ). Finally, this approach captures more comprehensively the multiple aspects underlying a child’s upbringing and, as such, provides a broader understanding of the role that behaviors, interactions, and emotions play in shaping children and youth’s behavior (Hoeve et al., 2011 ).

Baumrind ( 1967 ) proposes a typological approach based on two dimensions: parental control/demand and parental warmth/involvement and responsiveness. The first concerns the “ active role that parents play in promoting respect for rules and social conventions ” (Akhter et al., 2011 , p.24) and is related to high expectations, the definition of behavioral limits, and the application of rules and standards of conduct, including monitoring child’s behavior. The second is focused on responding to the child's needs, being available to talk, and providing a safe environment for learning and integral development. According to Baumrind ( 1967 ), combining the above-mentioned dimensions allows the conception of three distinct parenting styles: authoritative, authoritarian, and permissive (Baumrind, 1967 ).

The authoritative parenting style is rational and issue-oriented and is characterized by a parental attitude particularly oriented toward the child's activities and behaviors. Usually, parents adopting such a style are highly responsive, affectionate, and cognitive, establishing and encouraging flexible networks and communication with their children. Authoritative parents tend to exert firm control and set clear limits and boundaries in the face of disagreements between themselves and their children, motivating obedience but not limiting them incessantly (Baumrind, 1978 ). Empirical evidence has shown that children exposed to this parenting style present lower levels of externalizing and internalizing behaviors (Akhter et al., 2011 ; Alizadeh et al., 2011 ; Pinquart, 2017 ; Rose et al., 2018 ), mainly because these are parents who are warm, providing the child with structured environments, but who are also capable of adapting this environment to the child's needs. This parenting style is perceived as the most suitable for promoting the child’s behavioral and psychological development and adjustment (Rose et al., 2018 ).

On the other hand, authoritarian and permissive parenting styles have been systematically associated with increased rates of externalizing and internalizing behaviors (e.g., Baumrind et al., 2010 ; Pinquart, 2017 ; Rinaldi & Howe, 2012 ). The authoritarian parenting style embodies parental efforts to shape, control, and evaluate the child's conduct according to pre-established behavioral standards. These standards are usually absolute, theologically motivated, and directed by a figure of authority and superiority. This limits the child's individuality since punitive measures and strict rules are used when the child adopts any behavior that goes against what the parents think is the appropriate way to behave. Authoritarian parents do not encourage dialog or the debate of ideas, believing that the child must comply with what the parental figure imposes (Baumrind, 1978 ), thus contributing to the development of children’s negativity and tension in terms of family dynamics and communications, which, in turn, has been associated with children’s lower levels of attachment to their parents and higher rates of disruptive behavior, such as externalizing or internalizing (Amran & Basri, 2020 ).

A permissive parenting style refers to parents who do not set standards, limits, and behavioral expectations for their children despite being warm and affectionate with them. Permissive parents tend to be unable to enforce consistent discipline thus leaving the children free to satisfy their impulses, actions, and desires (Baumrind, 1978 ), which, in turn, has been associated with higher rates of children’s externalizing and internalizing behaviors.

Considering this, it is relatively easy to assume that the relationship between parenting styles and children’s externalizing and internalizing behaviors is robust and well-documented. Furthermore, previous studies have demonstrated that these relationships are sustained regardless of the child sex (Akhter et al., 2011 ; Alizadeh et al., 2011 ; Braza et al., 2015 ; Pinquart, 2017 ; Rinaldi & Howe, 2012 ).

However, less is known about the processes, mechanisms, or variables underlying such a relationship. This reinforced the need to research further the influence that other factors might exert at individual, familial, or contextual levels. In this regard, research has been conducted to understand self-control’s role in this relationship. These studies have revealed that self-control plays an important role in the relationship between parenting styles and children’s externalizing and internalizing behaviors, as it is explored below (Bai et al., 2020 ; Finkenauer et al., 2005 ; Özdemir et al., 2013 ; Pan et al., 2021 ; Tehrani & Yamini, 2020 ; Van Prooijen et al., 2018 ; Zhang & Wang, 2022 ).

Self-Control

Self-control is a widely used and researched construct, and a considerable number of definitions can be found throughout the literature (e.g., Finkenauer et al., 2005 ; Gottfredson & Hirschi, 1990 ; Moffitt et al., 2011 ; Pan et al., 2021 ; Tangney et al., 2004 ). For example, Moffitt et al., ( 2011 , p. 2693) see self-control as an "umbrella construct" encompassing concepts and measures from different areas such as impulsivity, delay of gratification, inattention, conscientiousness, and timeless choice. On the other hand, at the heart of the concept of self-control proposed by Tangney et al. ( 2004 ) is the ability to override or modify internal responses, suspend undesirable tendencies (e.g., impulses), and refrain from acting on them.

The current study follows Gottfredson and Hirschi’s ( 1990 ) conceptualization, according to which self-control constitutes an individual factor that takes the form of “ the tendency to avoid acts whose long-term costs exceed their momentary advantages ” (Hirschi & Gottfredson, 1994 , p. 3). According to the authors, there are six core elements of low self-control: (i) impulsiveness and the inability to delay gratification, i.e., an attitude and behavior focused on the immediate and the present; (ii) lack of persistence or tenacity, which means that individuals with low self-control have a tendency to avoid complex tasks, little enthusiasm for work or persistence to finish a task already started; (iii) participation in risk-seeking activities, i.e., involvement in risky, exciting, and arousing activities; (iv) a low appreciation of intellectual ability, in other words, a person that lacks self-control prefers to engage in physical and risky activities rather than cognitive and mental ones; (v) egocentrism, i.e., being unable to take into account the perspective of others or caring to their needs; and (vi) volatile temperament, which means minimal tolerance for frustration and little ability to respond to conflicts using verbal rather than physical means (Gottfredson & Hirschi, 1990 ).

Previous studies have also explored whether self-control manifests itself differently as a function of sex. In their General Theory of Crime , Gottfredson and Hirschi ( 1990 ) refer that women develop higher levels of self-control, which is corroborated by Duckworth et al. ( 2015 ). Furthermore, previous studies have demonstrated that the influence of low self-control on behavior occurs in the same way, regardless of sex (Botchkovar et al., 2015 ; Ivert et al., 2018 ). However, several other studies showed that the influence of self-control on behavior varies depending on the sex of the individuals (Chui & Chan, 2016 ; De Ridder et al., 2012 ; Flexon et al., 2016 ), reinforcing the need for further research (Pechorro et al., 2021 ).

Empirical evidence has shown a robust association between deviance, crime, and self-control, and criminologists have focused on exploring the factors responsible for the differences in the levels of self-control, particularly those most commonly associated with low self-control (Beaver et al., 2010 ). A fundamental theoretical assumption from the General Theory of Crime (Gottfredson & Hirschi, 1990 ) concerns the fact that it proposes that self-control develops during the first years of a child's life and becomes stable around ten years of age, even though this stability is not absolute, but rather between individuals (Vazsonyi & Jiskrova, 2018 ). In this sense, Gottfredson and Hirschi ( 1990 ) attribute the greatest weight to parenting in developing self-control. Parents are usually responsible for monitoring and supervising their children's behavior, recognizing inappropriate behavior, and punishing it when it occurs, thus instilling the development of self-control. Based on these theoretical premises, several empirical studies have tested this hypothesis and verified that parenting is important in developing children’s self-control ( e.g., Marcone et al., 2020 ; Özdemir et al., 2013 ; Tehrani & Yamini, 2020 ). Overall, these studies highlighted family stability, positive parenting, good parent–child relationships, monitoring, affection, emotional support, consistent discipline, and an authoritative parenting style as the most important aspects of parenting for developing self-control. Particularly, it was found that ineffective parenting practices in which authoritarian and/or permissive parenting styles prevail, combined with poor family stability, negative parenting, and poor relations and interactions between parents and children, are associated with lower levels of self-control in children (Marcone et al., 2020 ; Tehrani & Yamini, 2020 ).

Indirect Effects Between Parenting Styles, Externalizing and Internalizing Behaviors, and Self-Control

Over the years, several studies and theoretical assumptions have highlighted the importance of self-control as a mediator of the relationship between parenting and children’s externalizing, internalizing, antisocial, or even delinquent behaviors. For example, Tehrani and Yamini’s ( 2020 ) meta-analysis explored the relationship between effective parenting practices, low self-control, and antisocial behavior. The results showed that parenting practices indirectly affected antisocial behavior through low self-control and directly affected antisocial behavior regardless of low self-control, thus suggesting the mediation effect of self-control on the relationship between parenting practices and children’s antisocial behavior (Tehrani & Yamini, 2020 ). Van Prooijen et al. ( 2018 ) found no interaction effects between self-control and concerning externalizing and internalizing problems. Nevertheless, it was found that higher levels of children’s self-control, reported by both the mother and the father, were associated with lower levels of externalizing behaviors. In comparison, higher levels of self-control reported by the mother were also associated with fewer internalizing behaviors. Overall, positive parenting practices by both parents were associated with fewer externalizing and internalizing behaviors.

In their study, Özdemir et al. ( 2013 ) explored the direct and indirect relationships between parenting practices, such as closeness, monitoring and affection, low self-control, and aggression. The results revealed that parental measures of closeness and monitoring were significantly and negatively correlated with low self-control and aggressive behavior. In addition, the authors analyzed the role of self-control in this relationship. They concluded that parental measures were directly correlated with aggressive behavior and indirectly through low self-control. Specifically, monitoring by parents had significant direct and indirect effects on aggression through low self-control, suggesting that adolescents whose parents monitored their behaviors were more likely to develop greater self-control, which, in turn, led to the adoption of fewer aggressive behaviors.

Rezaei et al. ( 2019 ) sought to explore the relationship between parenting styles and the capacity for self-control in delinquent adolescents. The results showed that juvenile delinquents with a higher perception of authoritative parenting style and a lower perception of permissive parenting style had higher levels of self-control. Regression analyses show that an increase in the perception of authoritative parenting style and a decrease in the perception of authoritarian parenting style was associated with higher levels of self-control, thus suggesting that parenting styles “ can predict self-control capacity of juvenile delinquents ” (p. 61). Specifically, authoritative parenting creates favorable socialization conditions for developing self-control, while authoritarian parenting reduces juvenile delinquents’ ability to exercise self-control (Rezaei et al., 2019 ).

Similarly, Finkenauer et al. ( 2005 ) showed that both self-control and some parenting features, such as psychological control, poor parental monitoring and supervision, were independently associated with higher rates of emotional problems ( e.g., depression, stress, and low self-esteem) and behavioral problems ( e.g., aggression) in adolescents between 10 and 14 years. Also, low levels of self-control reported by the youth were strongly associated with behavioral and emotional problems, regardless of gender. Additionally, perceiving parents as restrictive and psychologically controlling was associated with higher emotional and behavioral problems. On the other hand, perceived parental receptivity, solidarity, and proper monitoring of adolescents’ activities and whereabouts were associated with youth’s lower emotional and behavioral problems. The results also indicated that the link between parenting and behavioral and emotional problems was partially mediated by self-control.

Recently, using a sample of 611 Chinese adolescents, Zhang and Wang ( 2022 ) examined the mediating role of self-control in the relationship between parenting styles, namely paternal and maternal rejection, affection and overprotection, and externalizing and internalizing behaviors. In addition, they also sought to explore if there were gender differences in the abovementioned relationships. The results showed that parenting variables had different influences on adolescent behavior. Specifically, paternal rejection was positively associated with externalizing behaviors, while maternal rejection was positively correlated with internalizing behaviors. Paternal affection, not maternal affection, was negatively correlated with internalizing behaviors. Maternal overprotection was positively associated with externalizing and internalizing behaviors. Adolescents’ self-control was significantly and negatively correlated with externalizing and internalizing behaviors. Also, adolescents’ self-control significantly mediated the effect of maternal rejection on internalizing behaviors and paternal rejection on externalizing behaviors (Zhang & Wang, 2022 ).

The above-mentioned studies have shown that positive parenting, such as the authoritative parenting style, contributes to lower levels of externalizing and internalizing behaviors through its influence on reducing low self-control. In turn, children exposed to negative parenting, such as authoritarian and permissive parenting styles, have more externalizing and internalizing behaviors due to the influence of these parenting styles on higher levels of low self-control (Liu et al., 2019 ; Pan et al., 2021 ; Tehrani & Yamini, 2020 ; Van Prooijen et al., 2018 ; Zhang & Wang, 2022 ).

Given the empirical evidence described above, it should be noted that externalizing and internalizing behaviors have a central influence on the development of children and youth and that parenting styles and self-control play an important role in developing these behaviors. Despite this, the development of this study is essential since, to the best of our knowledge, no other study has yet explored the relationship between parenting styles and externalizing and internalizing behaviors, neither in the Portuguese context nor with this specific population. In addition, few studies have allowed us to understand the role of self-control in this relationship. Those carried out have shown mixed results, thus reinforcing the need for further research to understand how the parenting styles developed by Baumrind ( 1971 , 1978 ) influence the externalizing and internalizing behaviors of children and youth, as well as the role of self-control in this relationship.

Current Study

Given the theoretical and empirical considerations presented, this exploratory cross-sectional study sought to explore and compare the relative influence of the parenting styles proposed by Baumrind ( 1971 , 1978 ) on the emergence and development of children and youth’s externalizing and internalizing behaviors. Furthermore, it aimed to analyze self-control’s potential mediating role in this relationship. Following this goal and considering the theoretical rationale underlying this subject, the following hypotheses were tested: (i) authoritarian and permissive parenting styles positively influence children and youth’s externalizing and internalizing behaviors; (ii) authoritative parenting style negatively influences children and youth’s externalizing and internalizing behaviors; (iii) as age increases, the levels of externalizing and internalizing behaviors increase; (iv) female children report higher levels of internalizing behaviors while male children report higher levels externalizing behaviors; (v) children and youth’s low self-control is positively associated with externalizing and internalizing behaviors; (vi) children and youth’s low self-control has a mediating effect on the relationship between parenting styles and externalizing and internalizing behaviors, that is, each of the parenting styles influences externalizing and internalizing behaviors, through their influence on increasing and/or decreasing low self-control.

Participants

The study was conducted with a non-clinical convenience sample. The participants ( n  = 472) were children and youth between 12 and 15 years old, attending the 7th ( n  = 161), 8th ( n  = 144), and 9th ( n  = 167) grades of middle school. The sample consisted of 57% males ( n  = 268), with an average age of 13.30 (SD = 0.983).

The data were collected during 2022. The participating schools were selected based on the school years administrated and their availability and willingness to participate in the study. To ensure the school’s participation, the researchers contacted each principal to obtain consent for the research development. From the twelve schools in the district of Porto that were invited to participate in the study, only four agreed to participate (the remaining eight either formally declined to participate or did not provide any kind of response). The schools that agreed to collaborate in the study were then contacted for the joint selection of the specific classes that would be sampled, considering the eligibility criteria defined, namely the participant’s age and grade. Students with special educational needs were not considered eligible for participation in the research. This contact also allowed the outline of the procedures needed to contact the parents/legal guardians to obtain their informed consent and authorization for their children’s participation in the research, considering all participants were under-aged. Furthermore, the consent of the participating children and youth was also requested before the data collection. Finally, it should also be mentioned that before the data collection procedure, the research project was submitted to the Faculty of Law of the University of Porto’s Ethics Committee, which approved the current study’s execution. All participants completed a paper and pencil self-report measure after the researchers explained and provided the necessary study details and instructions on completing the forms.

Parenting styles (permissive, authoritarian, and authoritative) were assessed using the Parental Authority Questionnaire (PAQ; Buri, 1991 , adapted for the Portuguese population by Morgado et al., 2006 ), which is a self-report measure directed at children and youth. This measure comprises 30 items that reflect parents’ educational strategies and perspectives during their children’s childhood and adolescence. Children and youth are asked to express the degree of agreement with each one of the statements presented using a five-point Likert scale, ranging from (1) “totally disagree” to (5) “totally agree.” The items are grouped into three sub-scales of 10, each corresponding to the specific parenting style under study. Each subscale is scored between 10 and 50 points. The subscale with the highest score represents the parenting style predominantly adopted by the parent (Buri, 1991 ; Morgado et al., 2006 ). Concerning reliability, the PAQ consistency analyses conducted in this study revealed an adequate internal consistency (permissive parenting style α  = 0.64; authoritarian parenting style α  = . 82; authoritative parenting style α  = 0.83).

Externalizing and Internalizing Behaviors

Externalizing and internalizing behaviors were measured using the Youth Self Report (YSR/11–18; adapted and validated for the Portuguese population by Fonseca & Monteiro, 1999). Being part of the Achenbach System of Empirically Based Assessment (Achenbach & Rescorla, 2001 ), YSR is a high-quality diagnostic self-report measure for emotional and behavioral problems and social skills of children and adolescents, whose standard classification period is the last six months (Achenbach & Rescorla, 2001 ). The internalizing syndrome scale, which measures emotional problems, comprises three subscales: anxious/depressed, withdrawn/depressed, and somatic complaints. The externalizing syndrome scale assesses behavioral problems and comprises the subscales of rule-breaking behavior and aggressive behavior. For each item presented, respondents are requested to indicate the frequency of each behavior on a scale ranging from (0) “ not true ,” (1) “ somewhat or sometimes true, ” and (2) “ very true or often true ” (Achenbach & Rescorla, 2001 ). In the current study, the YSR showed satisfactory internal consistency indexes, specifically α  = 0.67 for the externalizing and α  = 0.72 for the internalizing syndrome scales.

• Self-control

Self-control was assessed using the Low Self-Control Scale (LSCS) by Grasmick et al. ( 1993 ). The original Grasmick LSCS is an attitudinal and self-report measure comprising 24 items, corresponding to the six dimensions of self-control proposed in Gottfredson and Hirschi’s ( 1990 ) General Theory of Crime , namely impulsivity, preference for simple tasks, risk-seeking, preference for physical activities, being self-centered, and having trouble controlling one’s temper. The children and youth were asked to rate their degree of agreement for each of the items, using a 4-point Likert scale, ranging from (1) “ totally disagree ” to (4) “ totally agree.” The items are aggregated to form a total score; the higher this score, the lower the levels of self-control. In the current study, good levels of internal consistency were found for the total scale ( α  = 0.82).

Data Analysis

Descriptive statistics and reliability analyses of the scales were used to assess the psychometric features of the sample. Independent samples t -tests and Cohen’s d (effect size measure) were used to explore gender differences. Pearson’s r correlations coefficients were used to analyzed the relationships between the variables under study. Additional data analysis procedures explored the direct and indirect effects of parenting styles, externalizing and internalizing behaviors, and self-control. Multiple linear regression analysis was conducted to identify significant predictors of children and youth’s externalizing and internalizing behaviors. The Ordinary Least Squares method was used to obtain the Beta values ( β ) and the adjusted r 2 . In addition, to assess the quality of the model's fit, the Coefficient of Determination ( R 2 ) and the F -test were calculated to check the overall significance of the regression. In turn, the assumptions of the linear regression were validated using the Durbin-Watson Test for the Independence of Random Terms (ui). Finally, the Variance Inflation Factor (VIF) was used to check for multicollinearity. Values greater than 5 would indicate multicollinearity (Field, 2013 ). In addition, SPSS PROCESS MACRO 4.3 was used to examine the indirect effects between the variables under study (Hayes, 2012 ). Briefly, this tool allows us to (1) estimate the total effect of the Independent Variable (IV) on the Dependent Variable (DV); (2) to understand the effect of the IV on the DV by controlling for the Mediating Variable (MV); and (3) to analyze the indirect effect of the IV on the DV through the MV. In addition, PROCESS also makes it possible to test mediation and moderation models by estimating the coefficients of linear or logistic regressions, regardless of the nature of the variables under analysis, calculating the direct and indirect effects in mediation and moderation models (Hayes, 2012 ).

Sample Descriptive Statistics for Externalizing and Internalizing Behaviors, Parenting Styles and Self-Control, Both for the Total Sample and by Gender

Table 1 presents the descriptive statistics of the main study variables: externalizing and internalizing behaviors, parenting styles and low self-control, for the total sample and for females and males, separately. Girls presented significantly higher mean scores for internalizing behaviors ( M  = 22.64; SD = 11.04) than boys ( M  = 13.26; SD = 8.86). Concerning parenting styles, the results revealed that the authoritative parenting style is the most prevalent in the sample ( M  = 37.39; SD = 6.51). Furthermore, although higher mean levels for all parenting styles were observed for boys, compared with girls, significant differences were only found for the authoritarian parenting style ( p  < 0.00; d  = 0.33). Lastly, regarding self-control, the majority of participants presented moderate to high levels of low self-control ( M  = 55.43; SD = 9.63; Gottfredson & Hirschi, 1990 ). No significant differences were found between boys and girls.

Correlations Between Externalizing Behaviors, Internalizing Behaviors, Parenting Styles and Self-Control

Table 2 reports the Pearson’s correlations between studied variables. The results revealed that externalizing and internalizing behaviors are significantly correlated ( r  = 0.504**), indicating that higher levels of externalizing behaviors are associated with higher levels of internalizing behaviors. Furthermore, authoritarian parenting style is positively correlated with externalizing behaviors ( r  = 0.246**) and internalizing behaviors ( r  = 0.182**), suggesting that the higher the frequency of authoritarian parenting style perceived by the children, the higher the rates of externalizing and internalizing behaviors. In line with this, the authoritative parenting style is negatively correlated with externalizing behaviors ( r  = − 0.410*) and internalizing behaviors ( r  = − 0.379**), demonstrating that the more prevalent this parenting style is, the lower the rates of children and youth’s externalizing and internalizing behaviors. Regarding self-control, it is important to note it is positively associated with externalizing behaviors ( r  = 0.518**) and internalizing behaviors ( r  = 0.241**). Finally, it should also be mentioned that low self-control is positively correlated with permissive ( r  = 0.127**) and authoritarian ( r  = 0.264**) parenting styles, as well as negatively correlated with authoritative parenting style ( r  = − 0.281**), thus suggesting that children exposed to an authoritarian and permissive parenting style have higher levels of low self-control, and that children exposed to an authoritative parenting style have lower levels of low self-control.

Regression Models for Internalizing and Externalizing Behaviors

Table 3 presents the final regression models developed for children and youth’s externalizing and internalizing behaviors. As displayed in the table, the regression model for the externalizing behaviors is significant, explaining around 37% ( p  < 0.001) of the total variance of the dependent variable. The children’s sex ( β  = 0.084; p  = 0.041), age ( β  = 0.093; p  = 0.021), and low self-control ( β  = 0.461; p  < 0.001) significantly predicted externalizing behaviors, suggesting that girls are less likely to adopt externalizing behaviors; that as age increases, so do the levels of externalizing behaviors; and those higher levels of low self-control contribute to explaining higher levels of externalizing behavior. In turn, the permissive ( β  = − 0.097; p  = 0.023) and authoritative parenting styles ( β  = − 0.242; p  < 0.001) significantly integrate the model but in a negative manner, thus suggesting that greater exposure to each one of these parenting styles leads to lower levels of children and youth’s externalizing behaviors.

As for internalizing behaviors, the regression model executed is statistically significant and explains around 35% (p < 0.001) of the total variability of the dependent variable. Considering the predictors introduced in the model, the results revealed that the children’s sex ( β  = 0.438; p  < 0.001), authoritarian parenting style ( β  = 0.130; p  < 0.005), and low self-control ( β  = 0.179; p  < 0.001) integrate the model in a positive and statistically significant way, thus indicating that female children are more likely to present higher levels of internalizing behaviors; that the more the children are exposed to an authoritarian parenting style, the higher the rates of internalizing behaviors; and that, similarly to what was found for externalizing behaviors, higher levels of low self-control predicted more internalizing behaviors. In turn, the authoritative parenting style is the only statistically significant variable ( β  = − 0.266; p  < 0.001), which suggests that the more children are exposed to this parenting style, the lower the levels of internalizing behaviors.

Indirect Effects of Low Self-Control

Mediation models were tested to explore the indirect effects of low self-control in the relationship between parenting styles and externalizing and internalizing behaviors. Three models were generated to analyze the mediation processes associated with predicting externalizing behaviors, as presented in Table  4 .

Figure  1 illustrates the first model that tested the mediating effect of low self-control on the relationship between permissive parenting style and externalizing behaviors. The results show that the independent variable, permissive parenting style, has a positive and statistically significant effect on the mediating variable low self-control (direct effect = 0.215; p  = 0.025) and that the mediating variable has a positive and statistically significant effect on the dependent variable, externalizing behaviors (direct effect = 0.390; p  < 0.000).

Mediation models: permissive, authoritarian and authoritative parenting styles, externalizing behaviors, and low self-control

In turn, the permissive parenting style negatively and significantly predicted externalizing behaviors (direct effect = − 0.218; p  = 0.000). However, as far as indirect effects are concerned, these were tested using bootstrapping procedures, which showed that the standardized effect was 0.047 with a 95% confidence interval ranging from − 0.010 to 0.177, including a value of 0. This indicates that although a permissive parenting style has a negative and significant direct effect on externalizing behaviors, the indirect effect through low self-control is insignificant.

The second model, shown in Fig.  1 , tested the mediating effect of low self-control on the relationship between authoritarian parenting style and externalizing behaviors to analyze whether authoritarian parenting style increases levels of low self-control, and these, in turn, lead to higher rates of externalizing behaviors. As can be seen, the independent variable authoritarian parenting style has a positive and statistically significant effect on the mediating variable low self-control (direct effect = 0.363; p  = 0.000), and the mediating variable also has a positive and significant effect on the dependent variable (direct effect = 0.348; p  = 0.000). As for the independent variable, it has a positive and statistically significant effect on the dependent variable (direct effect = 0.133; p  = 0.004). However, there was a standardized indirect effect of 0.029 with a 95% confidence interval ranging from 0.075 to 0.187, indicating that the indirect effect was statistically significant. This indicates a partial mediation relationship between the variables because, despite the direct and significant effect between the independent and dependent variables, the authoritarian parenting style indirectly influences increasing levels of externalizing behavior through its positive influence on low self-control.

As for model 3, the aim was to understand the mediating effect of low self-control on the relationship between authoritarian parenting style and externalizing behaviors to understand whether authoritarian parenting style reduces low self-control, which in turn leads to a reduction in externalizing behaviors.

As shown in Fig.  1 , the independent variable has a negative and significant effect on the mediating variable (direct effect = − 0.429; p  = 0.000), and the mediating variable has a positive and significant effect on the dependent variable (direct effect = 0.317; p  = 0.000). As for the independent variable, it has a negative and significant effect on the dependent variable (direct effect = − 0.303; p  = 0.000). Despite this, there was a standardized effect of 0.033, with a 95% confidence interval of − 0.206 to − 0.077, which suggests that the indirect effect tested is significant. This indicates a partial mediation relationship between the variables since, despite the significant direct effect between the dependent and independent variables, the authoritarian parenting style reduces externalizing behavior by reducing low self-control.

On the other hand, to analyze the mediation processes underlying the prediction of internalizing behaviors, the three models shown in Table  5 were processed.

The fourth model tested the mediating effect of low self-control on the relationship between the independent variable, permissive parenting style, and the dependent variable, internalizing behaviors. The results shown in Fig.  2 indicate that the independent variable has a positive and significant effect on the mediating variable (direct effect = 0.233; p  = 0.012) and that the mediating variable influences the dependent variable in a positive and statistically significant way (direct effect = 0.325; p  = 0.000). In turn, the independent variable has a negative and significant effect on the dependent variable (direct effect = − 0.248; p  = 0.024). Despite this, there is a standardized indirect effect of 0.040, with a 95% confidence interval of 0.000 to 0.158, which means a partial mediation relationship exists. In other words, despite the significant direct effect recorded between the dependent and independent variables, the permissive parenting style contributes to the increase in levels of internalizing behaviors through its influence on the increase in levels of low self-control.

Mediation models: permissive authoritarian and authoritative parenting styles, internalizing behaviors, and low self-control

The fifth model investigated the mediating effect of low self-control on the relationship between authoritarian parenting style and internalizing behaviors. As can be seen in Fig.  2 , it is possible to understand that the independent variable has a positive and statistically significant effect on the mediating variable (direct effect = 0.368; p  = 0.000) and that the mediating variable has a positive and significant effect on the dependent variable (direct effect = 0.251; p  = 0.000).

The independent variable positively and significantly affects the dependent variable (direct effect = 0.229; p  = 0.007). Finally, as in the previous model, there is a standardized indirect effect of 0.040 for a 95% confidence interval of 0.037 to 0.153). This indicates a partial mediation relationship because, despite the significant direct effect between the dependent and independent variables, the authoritarian parenting style contributes to an increase in internalizing behaviors through its positive influence on low self-control (Fig.  2 ).

The sixth model focused on analyzing the mediating effects of low self-control on the relationship between authoritative parenting style and internalizing behaviors. The results shown in Fig.  2 indicate that authoritarian parenting style has a statistically significant negative effect on the mediating variable (direct effect = − 0.431; p  = 0.000) and that the mediating variable has a positive and significant effect on the dependent variable (right effect = 0.160; p  = 0.007). In turn, the authoritative parenting style has a negative and significant effect on internalizing behaviors (direct effect = − 0.580; p  = 0.000). Finally, there is a standardized indirect effect of 0.031 for a 95% confidence interval of − 0.133 to − 0.012). This suggests that, although the authoritarian parenting style contributes to a decrease in internalizing behaviors, there is a partial mediation relationship in that the authoritarian parenting style affects the decrease of internalizing behaviors by decreasing low self-control.

The main goal of this research was to analyze and compare the relative influence of authoritative, authoritarian, and permissive parenting styles on children and youth’s externalizing and internalizing behaviors and explore the indirect effects of self-control on this relation.

Thus, concerning the first research hypothesis, it was defined that authoritarian and permissive parenting styles positively influence children and youth’s externalizing and internalizing behaviors. As for the authoritarian parenting style, the hypothesis was partially confirmed since this variable is a significant predictor only of internalizing behaviors. Nevertheless, this is a result that finds empirical support in different studies ( e.g., Alizadeh et al., 2011 ; Akhter et al., 2011 ; Braza et al., 2015 ) which have shown cross-sectionally and longitudinally, that children exposed to a parenting style based on levels of authority and behavioral demands, and little freedom of expression, present higher levels of internalizing behaviors (Akhter et al., 2011 ). Thus, the results observed in the current study might be related to the fact that parents who adopt this parenting style do not establish an interactive dialogue with their children and are, in most situations and life contexts, strict, rigid, and inflexible, both in terms of limits and in terms of the behavioral expectations they impose, not responding to their children's emotional and affective needs. As Amran and Basri ( 2020 ) suggest, this type of parenting incites certain negativity in children, leading to higher levels of internalizing behaviors, as demonstrated in this study, because when parents do not respond to their children's needs and emotions, tensions are created in terms of communication and family dynamics. This leads to what Rose et al. ( 2018 , p. 1482) describe as " parenting stress and child-rearing stress.”, leading children to look for opportunities to release their tensions when they enter other socialization contexts, and in many of these situations, internalizing behaviors occur.

On the other hand, the permissive parenting style variable is statistically significant being a statistically significant predictor of externalizing behaviors, suggesting that children's greater exposure to this parenting style leads to lower externalizing behaviors. This was one of the results that did not follow the same direction as previous studies (e.g., Akhter et al., 2011 ; Alizadeh et al., 2011 ; Braza et al., 2015 ), nor the research hypothesis defined for this study. This result might be explained by the fact that this parenting style has fewer direct and immediate consequences on this type of behavior in children during this development period (Rinaldi & Howe, 2012 ). On the other hand, this parenting style was the least reported by the children, so given the low levels of this style in the sample, it is possible to understand why this relationship exists.

As for the second research hypothesis, it was defined that authoritative parenting style negatively influences the externalizing and internalizing behaviors of children and young people. This hypothesis was confirmed since the authoritarian parenting style variable was statistically significant, indicating that children exposed to this style have lower externalizing and internalizing behaviors. These results align with others from previous studies ( e.g., Pinquart, 2017 ; Rinaldi & Howe, 2012 ). As such, the results found in this study might be explained by what Rose et al. ( 2018 ) propose, i.e., authoritative parents are warm from an affective point of view, set clear and structured limits for their children's actions and behaviors, and can adapt them to their needs. This makes children develop greater levels of affection for their parents and feel safe and understood in the relationships they establish with them, leading to lower levels of internalizing and externalizing behaviors. As Baumrind et al. ( 2010 ) argue, childhood is a period of development in which children begin to create their independence and capacity for autonomy, and authoritarian parenting is ideal for providing children with the right support for this development.

The third research hypothesis states that the externalizing and internalizing behaviors increase as age increases. This hypothesis was partially confirmed, considering that the age of the children was a significant predictor only of internalizing behaviors. There have been mixed results in the literature ( e.g., Bishop et al., 2020 ; Bongers et al., 2003 ; Crijnen et al., 1997 ). However, the results obtained in the current study might be explained because the children and youth who took part in the study were starting puberty, a developmental period in which various hormonal, social, and behavioral changes occur, which may make this behavior more likely to occur. This reality was tested in the study by Bishop et al. ( 2020 ), which found that levels of externalizing behaviors increased between the ages of 11 and 15 and decreased when the children were between 16 and 20. In this sense, longitudinal studies are needed to understand better the evolution of these behaviors over different age groups and the individual, community, and social factors that can affect their development.

Furthermore, the fourth research hypothesis states that girls report more internalizing behaviors, and boys are more likely to report more externalizing behaviors. This hypothesis was partially confirmed, as being female significantly predicts both externalizing and internalizing behaviors, which also contradicts the results from previous studies ( e.g., Bongers et al., 2003 ; Campos et al., 2014 ; Chaplin & Aldao, 2013 ; Crijnen et al., 1997 ). Regarding internalizing behaviors, according to Chaplin and Aldao ( 2013 ), this result could be explained by the tendency of girls, especially during adolescence, to be more emotionally expressive. On the other hand, Brown ( 1999 ) states that the expression of externalizing behaviors has become increasingly common among adolescents and is more prevalent in female children, potentially reflecting a change in gender roles in today's society. However, longitudinal research would be necessary to analyze how the expression of these behaviors changes from childhood to adulthood. The result regarding internalizing behaviors aligns with previous studies’ findings ( e.g., Bongers et al., 2003 ; Campos et al., 2014 ; Crijnen et al., 1997 ) and with the hypothesis defined in the study. As shown by Bongers et al. ( 2003 ), the prevalence of internalizing behaviors between boys and girls in childhood does not differ. However, with the onset and entry into adolescence, an increase in internalizing behaviors in girls is common, which can be explained by the fact that girls struggle earlier with physical, hormonal, and behavioral changes that can lead to a greater expression of this type of behavior due to the uncertainty and instability typical of this period of development (Bongers et al., 2003 ).

The fifth research hypothesis tested in the current study which proposes that low self-control in children and youth is positively associated with externalizing and internalizing behaviors, was fully confirmed. Other studies have widely documented the relationship between low self-control and externalizing and internalizing behaviors (e.g., Bai et al., 2020 ; Van Prooijen et al., 2018 ; Zhang & Wang, 2022 ). Thus, children with low self-control are characterized by being more impulsive, egocentric, preferring simple, physical, and risky activities, and having a difficult temperament (Gottfredson & Hirschi, 1990 ). As such, the results of the current study might be understood in light of what Zhang and Wang ( 2022 ) propose since children with low self-control have greater difficulty in redirecting their attention away from impulses, and if this tendency continues, they are more likely to adopt externalizing behaviors. As for internalizing behaviors, the authors highlight the attentional component of self-control, in that children with low self-control have difficulty shifting their attention from negative to positive aspects and may develop more internalizing behaviors (Eisenberg et al., 2001 ). In turn, the fact that low self-control is a stronger predictor of externalizing behavior can be understood from the research carried out by Krueger et al. ( 1996 ). The authors analyzed low self-control as a specific risk factor for externalizing behaviors. Through laboratory tasks, they concluded that children with externalizing behaviors tended to seek immediate gratification more than children with internalizing behaviors.

The last hypothesis states that low self-control in children and youth has a mediating effect on the relationship between parenting styles and externalizing and internalizing behaviors, i.e., each parenting style influences externalizing and internalizing behaviors through its influence on increasing and/or decreasing low self-control. The hypothesis was partially confirmed because low self-control significantly mediated the relationship between parenting styles and externalizing and internalizing behaviors in only five of the six models tested. Thus, each parenting style influences externalizing and internalizing behaviors, and parenting styles also influence low self-control, which influences externalizing and internalizing behaviors.

As for the partial mediation models that were confirmed, the results of the analyses follow the same direction as those found in other empirical research that has analyzed the relationship between several aspects of parenting, self-control, and behavior problems, including externalizing and internalizing behaviors ( e.g., Liu et al., 2019 ; Pan et al., 2021 ; Tehrani & Yamini, 2020 ; Van Prooijen et al., 2018 ; Zhang & Wang, 2022 ). The results of the current study might be explained by the fact that positive parenting, as the authoritative parenting style, contributes to lower levels of externalizing and internalizing behaviors through its influence on reducing low self-control. On the other hand, children exposed to negative parenting, such as authoritarian and permissive parenting styles, show more externalizing and internalizing behaviors due to the influence of these parenting styles on higher levels of low self-control.

In this regard, there is a debate in the scientific literature about whether it is more appropriate to talk about the role of low self-control in terms of total or partial mediation, and there are some gaps in the literature due to the mixed results found. The study by Tehrani and Yamini ( 2020 ) set out to fill this gap based on the idea that low self-control may not be able to "absorb" all the effects of parental practices and styles on externalizing and internalizing behaviors, so in the light of this study, as in the present research, the partial mediation model is the most appropriate to describe the relationship between these dimensions and variables under analysis. Thus, these results, in the light of what Tehrani and Yamini ( 2020 ) explain based on the General Theory of Crime (Gottfredson & Hirschi, 1990 ), allow us to argue that children exposed to ineffective or inadequate parenting styles are not exposed to the necessary parenting and socialization practices that allow them to develop adequate levels of self-control, which in turn explain the emergence of externalizing and internalizing behaviors.

The opposite is also possible, i.e., when parents do not fail to emotionally support the child, monitor their behavior, and exert effective discipline and control. From authoritative parents, children learn, for example, to control their impulses, postpone their immediate gratification, be less egocentric, develop adequate self-control, and, as such, are less likely to adopt externalizing and internalizing behaviors. In short, externalizing and internalizing behaviors could be prevented if parents adopted appropriate socialization and education strategies, such as those typical of an authoritative parenting style (Pan et al., 2021 ; Tehrani & Yamini, 2020 ; Zhang & Wang, 2022 ). Therefore, the results presented reinforce the importance of studying self-control and different parenting styles in the emergence and development of externalizing and internalizing behaviors while explaining the mechanisms by which this influence occurs.

Limitations and Directions for Future Research

Despite the added value of the current study, it is not immune to some limitations. First, this study used a convenience sample of middle-school children from a restricted geographical area, thus impeding the generalization of the results. Future research should consider using a probabilistic sample of children from different geographical areas and cultural backgrounds. In line with this, it would be interesting that future research explores, in greater detail, the specific influence that some cultural features might exert in the explanation of the observed results (e.g., education, values, beliefs). In fact, previous studies have suggested that child-rearing (e.g., parenting styles) might be influenced by cultural values and that its impact on children’s behavior and adjustment might vary, depending on whether the adopted parenting strategies are considered more or less usual and accepted (e.g., Bornstein, 2013 ; Gershoff et al., 2010 ; Tehrani & Yamini, 2020 ).

Also, it would be interesting that future studies explore and analyze the potential maintenance of the results found with samples with low, medium, and high levels of antisocial and delinquent behavior, and not just normative ones, as the one used in the current study, while exploring further the gender differences for the relationships analyzed in the current study (particularly considering the mixed results found in previous studies, as described above; e.g., Braza et al., 2015 ; Chui & Chan, 2016 ; Pechorro et al., 2021 ; Pinquart, 2017 ).

In addition, there might have been a margin of bias in the data due to the self-report nature of the questionnaires. This bias may have occurred due to the children's reduced ability to remember past behaviors and/or events since for externalizing and internalizing behaviors, the children were asked to refer to behaviors adopted over the last six months. On the other hand, one can exclude the possibility of distortions or difficulties in understanding some of the questions, which might have influenced the results observed.

Finally, it is important to note that this was a correlational study, thus limiting the possibility of understanding the bidirectional influences of the variables and dimensions under study. This is important since other authors and previous studies have shown that the influence of parenting styles on externalizing and internalizing behaviors is a relationship that can be bidirectional because children with certain levels of externalizing and internalizing behaviors can trigger the adoption of specific parenting styles in their parents (Pardini et al., 2008 ; Pinquart, 2017 ). Thus, although this study demonstrated that parenting styles have a transversal and important influence in explaining externalizing and internalizing behaviors and the role of low self-control in this relationship, it does not allow us to understand whether externalizing and internalizing behaviors and low self-control explain parenting styles. As such, future studies should, using a multi-informant and multi-method approach, seek to understand the cumulative influences of parenting styles on externalizing and internalizing behaviors over different developmental periods, which is only possible through a longitudinal research design.

Implications

Despite the above-mentioned limitations and its exploratory nature, this study has several strengths and important theoretical and practical implications. First, this study extends previous research into the influence of parenting styles on the externalizing and internalizing behaviors of children and youth while also helping to understand the variables that predict these behaviors. In addition, the mediation analyses contributed to the scarce evidence and mixed results regarding the specific role that low self-control plays in the relationship between parenting styles and externalizing and internalizing behaviors.

Moreover, this study provides critical insights for developing prevention and intervention strategies targeting parents, children, and youth. By emphasizing the importance of specific factors consistently identified as crucial predictors of externalizing and internalizing behaviors, this research informs the design of targeted interventions. Specifically, it enhances our understanding of which parenting styles are most likely to contribute to the emergence, prevention, or reduction of these behaviors (Pinquart, 2017 ). This knowledge is essential for crafting prevention programs and intervention strategies that are not only grounded in theory but also supported by robust empirical evidence (Akhter et al., 2011 ; Hoeve et al., 2009 ; Kawabata et al., 2011 ; Kazdin, 2001 ).

Data Availability

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Almeida, D., Santos, G. Parenting Styles and Youth’s Externalizing and Internalizing Behaviors: Does Self-Control Matter?. Int Criminol (2024). https://doi.org/10.1007/s43576-024-00137-1

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DOI : https://doi.org/10.1007/s43576-024-00137-1

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• Volume 58, Issue 17
• Where is the research on sport-related concussion in Olympic athletes? A descriptive report and assessment of the impact of access to multidisciplinary care on recovery
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• http://orcid.org/0000-0002-3298-5719 Thomas Romeas 1 , 2 , 3 ,
• http://orcid.org/0000-0003-1748-7241 Félix Croteau 3 , 4 , 5 ,
• Suzanne Leclerc 3 , 4
• 1 Sport Sciences , Institut national du sport du Québec , Montreal , Quebec , Canada
• 2 School of Optometry , Université de Montréal , Montreal , Quebec , Canada
• 3 IOC Research Centre for Injury Prevention and Protection of Athlete Health , Réseau Francophone Olympique de la Recherche en Médecine du Sport , Montreal , Quebec , Canada
• 4 Sport Medicine , Institut national du sport du Québec , Montreal , Quebec , Canada
• 5 School of Physical and Occupational Therapy , McGill University , Montreal , Quebec , Canada
• Correspondence to Dr Thomas Romeas; thomas.romeas{at}umontreal.ca

Objectives This cohort study reported descriptive statistics in athletes engaged in Summer and Winter Olympic sports who sustained a sport-related concussion (SRC) and assessed the impact of access to multidisciplinary care and injury modifiers on recovery.

Methods 133 athletes formed two subgroups treated in a Canadian sport institute medical clinic: earlier (≤7 days) and late (≥8 days) access. Descriptive sample characteristics were reported and unrestricted return to sport (RTS) was evaluated based on access groups as well as injury modifiers. Correlations were assessed between time to RTS, history of concussions, the number of specialist consults and initial symptoms.

Results 160 SRC (median age 19.1 years; female=86 (54%); male=74 (46%)) were observed with a median (IQR) RTS duration of 34.0 (21.0–63.0) days. Median days to care access was different in the early (1; n SRC =77) and late (20; n SRC =83) groups, resulting in median (IQR) RTS duration of 26.0 (17.0–38.5) and 45.0 (27.5–84.5) days, respectively (p<0.001). Initial symptoms displayed a meaningful correlation with prognosis in this study (p<0.05), and female athletes (52 days (95% CI 42 to 101)) had longer recovery trajectories than male athletes (39 days (95% CI 31 to 65)) in the late access group (p<0.05).

Conclusions Olympic athletes in this cohort experienced an RTS time frame of about a month, partly due to limited access to multidisciplinary care and resources. Earlier access to care shortened the RTS delay. Greater initial symptoms and female sex in the late access group were meaningful modifiers of a longer RTS.

• Brain Concussion
• Cohort Studies
• Retrospective Studies

Data availability statement

Data are available on reasonable request. Due to the confidential nature of the dataset, it will be shared through a controlled access repository and made available on specific and reasonable requests.

https://doi.org/10.1136/bjsports-2024-108211

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WHAT IS ALREADY KNOWN ON THIS TOPIC

Most data regarding the impact of sport-related concussion (SRC) guidelines on return to sport (RTS) are derived from collegiate or recreational athletes. In these groups, time to RTS has steadily increased in the literature since 2005, coinciding with the evolution of RTS guidelines. However, current evidence suggests that earlier access to care may accelerate recovery and RTS time frames.

WHAT THIS STUDY ADDS

This study reports epidemiological data on the occurrence of SRC in athletes from several Summer and Winter Olympic sports with either early or late access to multidisciplinary care. We found the median time to RTS for Olympic athletes with an SRC was 34.0 days which is longer than that reported in other athletic groups such as professional or collegiate athletes. Time to RTS was reduced by prompt access to multidisciplinary care following SRC, and sex-influenced recovery in the late access group with female athletes having a longer RTS timeline. Greater initial symptoms, but not prior concussion history, were also associated with a longer time to RTS.

HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY

Considerable differences exist in access to care for athletes engaged in Olympic sports, which impact their recovery. In this cohort, several concussions occurred during international competitions where athletes are confronted with poor access to organised healthcare. Pathways for prompt access to multidisciplinary care should be considered by healthcare authorities, especially for athletes who travel internationally and may not have the guidance or financial resources to access recommended care.

Introduction

After two decades of consensus statements, sport-related concussion (SRC) remains a high focus of research, with incidence ranging from 0.1 to 21.5 SRC per 1000 athlete exposures, varying according to age, sex, sport and level of competition. 1 2 Evidence-based guidelines have been proposed by experts to improve its identification and management, such as those from the Concussion in Sport Group. 3 Notably, they recommend specific strategies to improve SRC detection and monitoring such as immediate removal, 4 prompt access to healthcare providers, 5 evidence-based interventions 6 and multidisciplinary team approaches. 7 It is believed that these guidelines contribute to improving the early identification and management of athletes with an SRC, thereby potentially mitigating its long-term consequences.

Nevertheless, evidence regarding the impact of SRC guidelines implementation remains remarkably limited, especially within high-performance sport domains. In fact, most reported SRC data focus on adolescent student-athletes, collegiate and sometimes professional athletes in the USA but often neglect Olympians. 1 2 8–11 Athletes engaged in Olympic sports, often referred to as elite amateurs, are typically classified among the highest performers in elite sport, alongside professional athletes. 12 13 They train year-round and uniquely compete regularly on the international stage in sports that often lack professional leagues and rely on highly variable resources and facilities, mostly dependent on winning medals. 14 Unlike professional athletes, Olympians do not have access to large financial rewards. Although some Olympians work or study in addition to their intensive sports practice, they can devote more time to full-time sports practice compared with collegiate athletes. Competition calendars in Olympians differ from collegiate athletes, with periodic international competitions (eg, World Cups, World Championships) throughout the whole year rather than regular domestic competitions within a shorter season (eg, semester). Olympians outclass most collegiate athletes, and only the best collegiate athletes will have the chance to become Olympians and/or professionals. 12 13 15 In Canada, a primary reason for limited SRC data in Olympic sports is that the Canadian Olympic and Paralympic Sports Institute (COPSI) network only adopted official guidelines in 2018 to standardise care for athletes’ SRC nationwide. 16 17 The second reason could be the absence of a centralised medical structure and surveillance systems, identified as key factors contributing to the under-reporting and underdiagnosis of athletes with an SRC. 18

Among the available evidence on the evolution of SRC management, a 2023 systematic review and meta-analysis in athletic populations including children, adolescents and adults indicated that a full return to sport (RTS) could take up to a month but is estimated to require 19.8 days on average (15.4 days in adults), as opposed to the initial expectation of approximately 10.0 days based on studies published prior to 2005. 19 In comparison, studies focusing strictly on American collegiate athletes report median times to RTS of 16 days. 9 20 21 Notably, a recent study of military cadets reported an even longer return to duty times of 29.4 days on average, attributed to poorer access to care and fewer incentives to return to play compared with elite sports. 22 In addition, several modifiers have also been identified as influencing the time to RTS, such as the history of concussions, type of sport, sex, past medical problems (eg, preinjury modifiers), as well as the initial number of symptoms and their severity (eg, postinjury modifiers). 20 22 The evidence regarding the potential influence of sex on the time to RTS has yielded mixed findings in this area. 23–25 In fact, females are typically under-represented in SRC research, highlighting the need for additional studies that incorporate more balanced sample representation across sexes and control for known sources of bias. 26 Interestingly, a recent Concussion Assessment, Research and Education Consortium study, which included a high representation of concussed female athletes (615 out of 1071 patients), revealed no meaningful differences in RTS between females and males (13.5 and 11.8 days, respectively). 27 Importantly, findings in the sporting population suggested that earlier initiation of clinical care is linked to shorter recovery after concussion. 5 28 However, these factors affecting the time to RTS require a more thorough investigation, especially among athletes engaged in Olympic sports who may or may not have equal access to prompt, high-quality care.

Therefore, the primary objective of this study was to provide descriptive statistics among athletes with SRC engaged in both Summer and Winter Olympic sport programmes over a quadrennial, and to assess the influence of recommended guidelines of the COPSI network and the fifth International Consensus Conference on Concussion in Sport on the duration of RTS performance. 16 17 Building on available evidence, the international schedule constraints, variability in resources 14 and high-performance expectation among this elite population, 22 prolonged durations for RTS, compared with what is typically reported (eg, 16.0 or 15.4 days), were hypothesised in Olympians. 3 19 The secondary objective was to more specifically evaluate the impact of access to multidisciplinary care and injury modifiers on the time to RTS. Based on current evidence, 5 7 29 30 the hypothesis was formulated that athletes with earlier multidisciplinary access would experience a faster RTS. Regarding injury modifiers, it was expected that female and male athletes would show similar time to RTS despite presenting sex-specific characteristics of SRC. 31 The history of concussions, the severity of initial symptoms and the number of specialist consults were expected to be positively correlated to the time to RTS. 20 32

Participants

A total of 133 athletes (F=72; M=61; mean age±SD: 20.7±4.9 years old) who received medical care at the Institut national du sport du Québec, a COPSI training centre set up with a medical clinic, were included in this cohort study with retrospective analysis. They participated in 23 different Summer and Winter Olympic sports which were classified into six categories: team (soccer, water polo), middle distance/power (rowing, swimming), speed/strength (alpine skiing, para alpine skiing, short and long track speed skating), precision/skill-dependent (artistic swimming, diving, equestrian, figure skating, gymnastics, skateboard, synchronised skating, trampoline) and combat/weight-making (boxing, fencing, judo, para judo, karate, para taekwondo, wrestling) sports. 13 This sample consists of two distinct groups: (1) early access group in which athletes had access to a medical integrated support team of multidisciplinary experts within 7 days following their SRC and (2) late access group composed of athletes who had access to a medical integrated support team of multidisciplinary experts eight or more days following their SRC. 5 30 Inclusion criteria for the study were participation in a national or international-level sports programme 13 and having sustained at least one SRC diagnosed by an authorised healthcare practitioner (eg, physician and/or physiotherapist).

Clinical context

The institute clinic provides multidisciplinary services for care of patients with SRC including a broad range of recommended tests for concussion monitoring ( table 1 ). The typical pathway for the athletes consisted of an initial visit to either a sports medicine physician or their team sports therapist. A clinical diagnosis of SRC was then confirmed by a sports medicine physician, and referral for the required multidisciplinary assessments ensued based on the patient’s signs and symptoms. Rehabilitation progression was based on the evaluation of exercise tolerance, 33 priority to return to cognitive tasks and additional targeted support based on clinical findings of a cervical, visual or vestibular nature. 17 The expert team worked in an integrated manner with the athlete and their coaching staff for the rehabilitation phase, including regular round tables and ongoing communication. 34 For some athletes, access to recommended care was fee based, without a priori agreements with a third party payer (eg, National Sports Federation).

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Main evaluations performed to guide the return to sport following sport-related concussion

Data collection

Data were collected at the medical clinic using a standardised injury surveillance form based on International Olympic Committee guidelines. 35 All injury characteristics were extracted from the central injury database between 1 July 2018 and 31 July 2022. This period corresponds to a Winter Olympic sports quadrennial but also covers 3 years for Summer Olympic sports due to the postponing of the Tokyo 2020 Olympic Games. Therefore, the observation period includes a typical volume of competitions across sports and minimises differences in exposure based on major sports competition schedules. The information extracted from the database included: participant ID, sex, date of birth, sport, date of injury, type of injury, date of their visit at the clinic, clearance date of unrestricted RTS (eg, defined as step 6 of the RTS strategy with a return to normal gameplay including competitions), the number and type of specialist consults, mechanism of injury (eg, fall, hit), environment where the injury took place (eg, training, competition), history of concussions, history of modifiers (eg, previous head injury, migraines, learning disability, attention deficit disorder or attention deficit/hyperactivity disorder, depression, anxiety, psychotic disorder), as well as the number of symptoms and the total severity score from the first Sport Concussion Assessment Tool 5 (SCAT5) assessment following SRC. 17

Following a Shapiro-Wilk test, medians, IQR and non-parametric tests were used for the analyses because of the absence of normal distributions for all the variables in the dataset (all p<0.001). The skewness was introduced by the presence of individuals that required lengthy recovery periods. One participant was removed from the analysis because their time to consult with the multidisciplinary team was extremely delayed (>1 year).

Descriptive statistics were used to describe the participant’s demographics, SRC characteristics and risk factors in the total sample. Estimated incidences of SRC were also reported for seven resident sports at the institute for which it was possible to quantify a detailed estimate of training volume based on the annual number of training and competition hours as well as the number of athletes in each sport.

To assess if access to multidisciplinary care modified the time to RTS, we compared time to RTS between early and late access groups using a method based on median differences described elsewhere. 36 Wilcoxon rank sum tests were also performed to make between-group comparisons on single variables of age, time to first consult, the number of specialists consulted and medical visits. Fisher’s exact tests were used to compare count data between groups on variables of sex, history of concussion, time since the previous concussion, presence of injury modifiers, environment and mechanism of injury. Bonferroni corrections were applied for multiple comparisons in case of meaningful differences.

To assess if injury modifiers modified time to RTS in the total sample, we compared time to RTS between sexes, history of concussions, time since previous concussion or other injury modifiers using a method based on median differences described elsewhere. 36 Kaplan-Meier curves were drawn to illustrate time to RTS differences between sexes (origin and start time: date of injury; end time: clearance date of unrestricted RTS). Trajectories were then assessed for statistical differences using Cox proportional hazards model. Wilcoxon rank sum tests were employed for comparing the total number of symptoms and severity scores on the SCAT5. The association of multilevel variables on return to play duration was evaluated in the total sample with Kruskal-Wallis rank tests for environment, mechanism of injury, history of concussions and time since previous concussion. For all subsequent analyses of correlations between SCAT5 results and secondary variables, only data obtained from SCAT5 assessments within the acute phase of injury (≤72 hours) were considered (n=65 SRC episodes in the early access group). 37 Spearman rank correlations were estimated between RTS duration, history of concussions, number of specialist consults and total number of SCAT5 symptoms or total symptom severity. All statistical tests were performed using RStudio (R V.4.1.0, The R Foundation for Statistical Computing). The significance level was set to p<0.05.

Equity, diversity and inclusion statement

The study population is representative of the Canadian athletic population in terms of age, gender, demographics and includes a balanced representation of female and male athletes. The study team consists of investigators from different disciplines and countries, but with a predominantly white composition and under-representation of other ethnic groups. Our study population encompasses data from the Institut national du sport du Québec, covering individuals of all genders, ethnicities and geographical regions across Canada.

Patient and public involvement

The patients or the public were not involved in the design, conduct, reporting or dissemination plans of our research.

Sample characteristics

During the 4-year period covered by this retrospective chart review, a total of 160 SRC episodes were recorded in 132 athletes with a median (IQR) age of 19.1 (17.8–22.2) years old ( table 2 ). 13 female and 10 male athletes had multiple SRC episodes during this time. The sample had a relatively balanced number of females (53.8%) and males (46.2%) with SRC included. 60% of the sample reported a history of concussion, with 35.0% reporting having experienced more than two episodes. However, most of these concussions had occurred more than 1 year before the SRC for which they were being treated. Within this sample, 33.1% of participants reported a history of injury modifiers. Importantly, the median (IQR) time to first clinic consult was 10.0 (1.0–20.0) days and the median (IQR) time to RTS was 34.0 (21.0–63.0) days in this sample ( table 3 ). The majority of SRCs occurred during training (56.3%) rather than competition (33.1%) and were mainly due to a fall (63.7%) or a hit (31.3%). The median (IQR) number of follow-up consultations and specialists consulted after the SRC were, respectively, 9 (5.0–14.3) and 3 (2.0–4.0).

Participants demographics

Sport-related concussion characteristics

Among seven sports of the total sample (n=89 SRC), the estimated incidence of athletes with SRC was highest in short-track speed skating (0.47/1000 hours; 95% CI 0.3 to 0.6), and lower in boxing, trampoline, water polo, judo, artistic swimming, and diving (0.24 (95% CI 0.0 to 0.5), 0.16 (95% CI 0.0 to 0.5), 0.13 (95% CI 0.1 to 0.2), 0.11 (95% CI 0.1 to 0.2), 0.09 (95% CI 0.0 to 0.2) and 0.06 (95% CI 0.0 to 0.1)/1000, respectively ( online supplemental material ). Furthermore, most athletes sustained an SRC in training (66.5%; 95% CI 41.0 to 92.0) rather than competition (26.0%; 95% CI 0.0 to 55.0) except for judo athletes (20.0% (95% CI 4.1 to 62.0) and 80.0% (95% CI 38.0 to 96.0), respectively). Falls were the most common injury mechanism in speed skating, trampoline and judo while hits were the most common injury mechanism in boxing, water polo, artistic swimming and diving.

Supplemental material

Access to care.

The median difference in time to RTS was 19 days (95% CI 9.3 to 28.7; p<0.001) between the early (26 (IQR 17.0–38.5) days) and late (45 (IQR 27.5–84.5) days) access groups ( table 3 ; figure 1 ). Importantly, the distribution of SRC environments was different between both groups (p=0.008). The post hoc analysis demonstrated a meaningful difference in the distribution of SRC in training and competition environments between groups (p=0.029) but not for the other comparisons. There was a meaningful difference between the groups in time to first consult (p<0.001; 95% CI −23.0 to −15.0), but no meaningful differences between groups in median age (p=0.176; 95% CI −0.3 to 1.6), sex distribution (p=0.341; 95% CI 0.7 to 2.8), concussion history (p=0.210), time since last concussion (p=0.866), mechanisms of SRC (p=0.412), the presence of modifiers (p=0.313; 95% CI 0.3 to 1.4) and the number of consulted specialists (p=0.368; 95% CI −5.4 to 1.0) or medical visits (p=0.162; 95% CI −1.0 to 3.0).

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Time to return to sport following sport-related concussion as a function of group’s access to care and sex. Outliers: below=Q1−1.5×IQR; above=Q3+1.5×IQR.

The median difference in time to RTS was 6.5 days (95% CI −19.3 to 5.3; p=0.263; figure 1 ) between female (37.5 (IQR 22.0–65.3) days) and male (31.0 (IQR 20.0–48.0) days) athletes. Survival analyses highlighted an increased hazard of longer recovery trajectory in female compared with male athletes (HR 1.4; 95% CI 1.4 to 0.7; p=0.052; figure 2A ), which was mainly driven by the late (HR 1.8; 95% CI 1.8 to 0.6; p=0.019; figure 2C ) rather than the early (HR 1.1; 95% CI 1.1 to 0.9; p=0.700; figure 2B ) access group. Interestingly, a greater number of female athletes (n=15) required longer than 100 days for RTS as opposed to the male athletes (n=6). There were no meaningful differences between sexes for the total number of symptoms recorded on the SCAT5 (p=0.539; 95% CI −1.0 to 2.0) nor the total symptoms total severity score (p=0.989; 95% CI −5.0 to 5.0).

Time analysis of sex differences in the time to return to sport following sport-related concussion in the (A) total sample, as well as (B) early, and (C) late groups using survival curves with 95% confidence bands and tables of time-specific number of patients at risk (censoring proportion: 0%).

History of modifiers

SRC modifiers are presented in table 2 , and their influence on RTP is shown in table 4 . The median difference in time to RTS was 1.5 days (95% CI −10.6 to 13.6; p=0.807) between athletes with none and one episode of previous concussion, was 3.5 days (95% CI −13.9 to 19.9; p=0.728) between athletes with none and two or more episodes of previous concussion, and was 2 days (95% CI −12.4 to 15.4; p=0.832) between athletes with one and two or more episodes of previous concussion. The history of concussions (none, one, two or more) had no meaningful impact on the time to RTS (p=0.471). The median difference in time to RTS was 4.5 days (95% CI −21.0 to 30.0; p=0.729) between athletes with none and one episode of concussion in the previous year, was 2 days (95% CI −10.0 to 14.0; p=0.744) between athletes with none and one episode of concussion more than 1 year ago, and was 2.5 days (95% CI −27.7 to 22.7; p=0.846) between athletes with an episode of concussion in the previous year and more than 1 year ago. Time since the most recent concussion did not change the time to RTS (p=0.740). The longest time to RTS was observed in the late access group in which athletes had a concussion in the previous year, with a very large spread of durations (65.0 (IQR 33.0–116.5) days). The median difference in time to RTS was 3 days (95% CI −13.1 to 7.1; p=0.561) between athletes with and without other injury modifiers. The history of other injury modifiers had no meaningful influence on the time to RTS (95% CI −6.0 to 11.0; p=0.579).

Preinjury modifiers of time to return to sport following SRC

SCAT5 symptoms and severity scores

Positive associations were observed between the time to RTS and the number of initial symptoms (r=0.3; p=0.010; 95% CI 0.1 to 0.5) or initial severity score (r=0.3; p=0.008; 95% CI 0.1 to 0.5) from the SCAT5. The associations were not meaningful between the number of specialist consultations and the initial number of symptoms (r=−0.1; p=0.633; 95% CI −0.3 to 0.2) or initial severity score (r=−0.1; p=0.432; 95% CI −0.3 to 0.2). Anecdotally, most reported symptoms following SRC were ‘headache’ (86.2%) and ‘pressure in the head’ (80.0%), followed by ‘fatigue’ (72.3%), ‘neck pain’ (70.8%) and ‘not feeling right’ (67.7%; online supplemental material ).

This study is the first to report descriptive data on athletes with SRC collected across several sports during an Olympic quadrennial, including athletes who received the most recent evidence-based care at the time of data collection. Primarily, results indicate that the time to RTS in athletes engaged in Summer and Winter Olympic sports may require a median (IQR) of 34.0 (21.0–63.0) days. Importantly, findings demonstrated that athletes with earlier (≤7 days) access to multidisciplinary concussion care showed faster RTS compared with those with late access. Time to RTS exhibited large variability where sex had a meaningful influence on the recovery pathway in the late access group. Initial symptoms, but not history of concussion, were correlated with prognosis in this sample. The main reported symptoms were consistent with previous studies. 38 39

Time to RTS in Olympic sports

This study provides descriptive data on the impact of SRC monitoring programmes on recovery in elite athletes engaged in Olympic sports. As hypothesised, the median time to RTS found in this study (eg, 34.0 days) was about three times longer than those found in reports from before 2005, and 2 weeks longer than the typical median values (eg, 19.8 days) recently reported in athletic levels including youth (high heterogeneity, I 2 =99.3%). 19 These durations were also twice as long as the median unrestricted time to RTS observed among American collegiate athletes, which averages around 16 days. 9 20 21 However, they were more closely aligned with findings from collegiate athletes with slow recovery (eg, 34.7 days) and evidence from military cadets with poor access where return to duty duration was 29.4 days. 8 22 Several reasons could explain such extended time to RTS, but the most likely seems to be related to the diversity in access among these sports to multidisciplinary services (eg, 10.0 median days (1–20)), well beyond the delays experienced by collegiate athletes, for example (eg, 0.0 median days (0–2)). 40 In the total sample, the delays to first consult with the multidisciplinary clinic were notably mediated by the group with late access, whose athletes had more SRC during international competition. One of the issues for athletes engaged in Olympic sports is that they travel abroad year-round for competitions, in contrast with collegiate athletes who compete domestically. These circumstances likely make access to quality care very variable and make the follow-up of care less centralised. Also, access to resources among these sports is highly variable (eg, medal-dependant), 14 and at the discretion of the sport’s leadership (eg, sport federation), who may decide to prioritise more or fewer resources to concussion management considering the relatively low incidence of this injury. Another explanation for the longer recovery times in these athletes could be the lack of financial incentives to return to play faster, which are less prevalent among Olympic sports compared with professionals. However, the stakes of performance and return to play are still very high among these athletes.

Additionally, it is plausible that studies vary their outcome with shifting operational definitions such as resolution of symptoms, return to activities, graduated return to play or unrestricted RTS. 19 40 It is understood that resolution of symptoms may occur much earlier than return to preinjury performance levels. Finally, an aspect that has been little studied to date is the influence of the sport’s demands on the RTS. For example, acrobatic sports requiring precision/technical skills such as figure skating, trampoline and diving, which involve high visuospatial and vestibular demands, 41 might require more time to recover or elicit symptoms for longer times. Anecdotally, athletes who experienced a long time to RTS (>100 days) were mostly from precision/skill-dependent sports in this sample. The sports demand should be further considered as an injury modifier. More epidemiological reports that consider the latest guidelines are therefore necessary to gain a better understanding of the true time to RTS and impact following SRC in Olympians.

Supporting early multidisciplinary access to care

In this study, athletes who obtained early access to multidisciplinary care after SRC recovered faster than those with late access to multidisciplinary care. This result aligns with findings showing that delayed access to a healthcare practitioner delays recovery, 19 including previous evidence in a sample of patients from a sports medicine clinic (ages 12–22), indicating that the group with a delayed first clinical visit (eg, 8–20 days) was associated with a 5.8 times increased likelihood of a recovery longer than 30 days. 5 Prompt multidisciplinary approach for patients with SRC is suggested to yield greater effectiveness over usual care, 3 6 17 which is currently evaluated under randomised controlled trial. 42 Notably, early physical exercise and prescribed exercise (eg, 48 hours postinjury) are effective in improving recovery compared with strict rest or stretching. 43 44 In fact, preclinical and clinical studies have shown that exercise has the potential to improve neurotransmission, neuroplasticity and cerebral blood flow which supports that the physically trained brain enhanced recovery. 45 46 Prompt access to specialised healthcare professionals can be challenging in some contexts (eg, during international travel), and the cost of accessing medical care privately may prove further prohibitive. This barrier to recovery should be a priority for stakeholders in Olympic sports and given more consideration by health authorities.

Estimated incidences and implications

The estimated incidences of SRC were in the lower range compared with what is reported in other elite sport populations. 1 2 However, the burden of injury remained high for these sports, and the financial resources as well as expertise required to facilitate athletes’ rehabilitation was considerable (median number of consultations: 9.0). Notably, the current standard of public healthcare in Canada does not subsidise the level of support recommended following SRC as first-line care, and the financial subsidisation of this recommended care within each federation is highly dependent on the available funding, varying significantly between sports. 14 Therefore, the ongoing efforts to improve education, prevention and early recognition, modification of rules to make the environments safer and multidisciplinary care access for athletes remain crucial. 7

Strength and limitations

This unique study provides multisport characteristics following the evolution of concussion guidelines in Summer and Winter Olympic sports in North America. Notably, it features a balance between the number of female and male athletes, allowing the analysis of sex differences. 23 26 In a previous review of 171 studies informing consensus statements, samples were mostly composed of more than 80% of male participants, and more than 40% of these studies did not include female participants at all. 26 This study also included multiple non-traditional sports typically not encompassed in SRC research, feature previously identified as a key requirement of future epidemiological research. 47

However, it must be acknowledged that potential confounding factors could influence the results. For example, the number of SRC detected during the study period does not account for potentially unreported concussions. Nevertheless, this figure should be minimal because these athletes are supervised both in training and in competition by medical staff. Next, the sport types were heterogeneous, with inconsistent risk for head impacts or inconsistent sport demand which might have an influence on recovery. Furthermore, the number of participants or sex in each sport was not evenly distributed, with short-track speed skaters representing a large portion of the overall sample (32.5%), for example. Additionally, the number of participants with specific modifiers was too small in the current sample to conclude whether the presence of precise characteristics (eg, history of concussion) impacted the time to RTS. Also, the group with late access was more likely to consist of athletes who sought specialised care for persistent symptoms. These complex cases are often expected to require additional time to recover. 48 Furthermore, athletes in the late group may have sought support outside of the institute medical clinic, without a coordinated multidisciplinary approach. Therefore, the estimation of clinical consultations was tentative for this group and may represent a potential confounding factor in this study.

This is the first study to provide evidence of the prevalence of athletes with SRC and modifiers of recovery in both female and male elite-level athletes across a variety of Summer and Winter Olympic sports. There was a high variability in access to care in this group, and the median (IQR) time to RTS following SRC was 34.0 (21.0–63.0) days. Athletes with earlier access to multidisciplinary care took nearly half the time to RTS compared with those with late access. Sex had a meaningful influence on the recovery pathway in the late access group. Initial symptom number and severity score but not history of concussion were meaningful modifiers of recovery. Injury surveillance programmes targeting national sport organisations should be prioritised to help evaluate the efficacy of recommended injury monitoring programmes and to help athletes engaged in Olympic sports who travel a lot internationally have better access to care. 35 49

Ethics statements

Patient consent for publication.

Not applicable.

Ethics approval

This study involves human participants and was approved by the ethics board of Université de Montréal (certificate #2023-4052). Participants gave informed consent to participate in the study before taking part.

Acknowledgments

The authors would like to thank the members of the concussion interdisciplinary clinic of the Institut national du sport du Québec for collecting the data and for their unconditional support to the athletes.

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Supplementary materials

Supplementary data.

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• Data supplement 1

X @ThomasRomeas

Correction notice This article has been corrected since it published Online First. The ORCID details have been added for Dr Croteau.

Contributors TR, FC and SL were involved in planning, conducting and reporting the work. François Bieuzen and Magdalena Wojtowicz critically reviewed the manuscript. TR is guarantor.

Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

Competing interests None declared.

Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.

Provenance and peer review Not commissioned; externally peer reviewed.

Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.

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