research approaches in thesis

Writing the Research Methodology Section of Your Thesis

This article explains the meaning of research methodology and the purpose and importance of writing a research methodology section or chapter for your thesis paper. It discusses what to include and not include in a research methodology section, the different approaches to research methodology that can be used, and the steps involved in writing a robust research methodology section.

What is a thesis research methodology?

A thesis research methodology explains the type of research performed, justifies the methods that you chose   by linking back to the literature review , and describes the data collection and analysis procedures. It is included in your thesis after the Introduction section . Most importantly, this is the section where the readers of your study evaluate its validity and reliability.

What should the research methodology section in your thesis include?

• The aim of your thesis
• An outline of the research methods chosen (qualitative, quantitative, or mixed methods)
• Background and rationale for the methods chosen, explaining why one method was chosen over another
• Methods used for data collection and data analysis
• Materials and equipment used—keep this brief
• Difficulties encountered during data collection and analysis. It is expected that problems will occur during your research process. Use this as an opportunity to demonstrate your problem-solving abilities by explaining how you overcame all obstacles. This builds your readers’ confidence in your study findings.
• A brief evaluation of your research explaining whether your results were conclusive and whether your choice of methodology was effective in practice

What should not be included in the research methodology section of your thesis?

• Irrelevant details, for example, an extensive review of methodologies (this belongs in the literature review section) or information that does not contribute to the readers’ understanding of your chosen methods
• A description of basic procedures
• Excessive details about materials and equipment used. If an extremely long and detailed list is necessary, add it as an appendix

Types of methodological approaches

The choice of which methodological approach to use depends on your field of research and your thesis question. Your methodology should establish a clear relationship with your thesis question and must also be supported by your  literature review . Types of methodological approaches include quantitative, qualitative, or mixed methods. 

Quantitative studies generate data in the form of numbers   to count, classify, measure, or identify relationships or patterns. Information may be collected by performing experiments and tests, conducting surveys, or using existing data. The data are analyzed using  statistical tests and presented as charts or graphs. Quantitative data are typically used in the Sciences domain.

For example, analyzing the effect of a change, such as alterations in electricity consumption by municipalities after installing LED streetlights.

The raw data will need to be prepared for statistical analysis by identifying variables and checking for missing data and outliers. Details of the statistical software program used (name of the package, version number, and supplier name and location) must also be mentioned.

Qualitative studies gather non-numerical data using, for example, observations, focus groups, and in-depth interviews.   Open-ended questions are often posed. This yields rich, detailed, and descriptive results. Qualitative studies are usually   subjective and are helpful for investigating social and cultural phenomena, which are difficult to quantify. Qualitative studies are typically used in the Humanities and Social Sciences (HSS) domain.

For example, determining customer perceptions on the extension of a range of baking utensils to include silicone muffin trays.

The raw data will need to be prepared for analysis by coding and categorizing ideas and themes to interpret the meaning behind the responses given.

Mixed methods use a combination of quantitative and qualitative approaches to present multiple findings about a single phenomenon. T his enables triangulation: verification of the data from two or more sources.

Data collection

Explain the rationale behind the sampling procedure you have chosen. This could involve probability sampling (a random sample from the study population) or non-probability sampling (does not use a random sample).

For quantitative studies, describe the sampling procedure and whether statistical tests were used to determine the  sample size .

Following our example of analyzing the changes in electricity consumption by municipalities after installing LED streetlights, you will need to determine which municipal areas will be sampled and how the information will be gathered (e.g., a physical survey of the streetlights or reviewing purchase orders).

For qualitative research, describe how the participants were chosen and how the data is going to be collected.

Following our example about determining customer perceptions on the extension of a range of baking utensils to include silicone muffin trays, you will need to decide the criteria for inclusion as a study participant (e.g., women aged 20–70 years, bakeries, and bakery supply shops) and how the information will be collected (e.g., interviews, focus groups, online or in-person questionnaires, or video recordings) .

Data analysis

For quantitative research, describe what tests you plan to perform and why you have chosen them. Popular data analysis methods in quantitative research include:

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

For qualitative research, describe how the data is going to be analyzed and justify your choice. Popular data analysis methods in qualitative research include:

• Qualitative content analysis
• Thematic analysis
• Discourse analysis
• Narrative analysis
• Grounded theory
• Interpretative phenomenological analysis (IPA)

Evaluate and justify your methodological choices

You need to convince the reader that you have made the correct methodological choices. Once again, this ties back to your thesis question and  literature review . Write using a persuasive tone, and use  rhetoric to convince the reader of the quality, reliability, and validity of your research.

Ethical considerations

• The young researcher should maintain objectivity at all times
• All participants have the right to privacy and anonymity
• Research participation must be voluntary
• All subjects have the right to withdraw from the research at any time
• Consent must be obtained from all participants before starting the research
• Confidentiality of data provided by individuals must be maintained
• Consider how the interpretation and reporting of the data will affect the participants

Tips for writing a robust thesis research methodology

• Determine what kind of knowledge you are trying to uncover. For example, subjective or objective, experimental or interpretive.
• A thorough literature review is the best starting point for choosing your methods.
• Ensure that there is continuity throughout the research process. The authenticity of your research depends upon the validity of the research data, the reliability of your data measurements, and the time taken to conduct the analysis.
• Choose a research method that is achievable. Consider the time and funds available, feasibility, ethics, and access and availability of equipment to measure the phenomenon or answer your thesis question correctly.
• If you are struggling with a concept, ask for help from your supervisor, academic staff members, or fellow students.

A thesis methodology justifies why you have chosen a specific approach to address your thesis question. It explains how you will collect the data and analyze it. Above all, it allows the readers of your study to evaluate its validity and reliability.

A thesis is the most crucial document that you will write during your academic studies. For professional thesis editing and thesis proofreading services, visit  Enago Thesis Editing for more information.

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Introduce your methodological approach , for example, quantitative, qualitative, or mixed methods.

Explain why your chosen approach is relevant to the overall research design and how it links with your  thesis question.

Justify your chosen method and why it is more appropriate than others.

Provide background information on methods that may be unfamiliar to readers of your thesis.

Introduce the tools that you will use for data collection , and explain how you plan to use them (e.g., surveys, interviews, experiments, or existing data).

Explain how you will analyze your results. The type of analysis used depends on the methods you chose. For example, exploring theoretical perspectives to support your explanation of observed behaviors in a qualitative study or using statistical analyses in a quantitative study.

Mention any research limitations. All studies are expected to have limitations, such as the sample size, data collection method, or equipment. Discussing the limitations justifies your choice of methodology despite the risks. It also explains under which conditions the results should be interpreted and shows that you have taken a holistic approach to your study.

What is the difference between methodology and methods? +

Methodology  refers to the overall rationale and strategy of your thesis project. It involves studying the theories or principles behind the methods used in your field so that you can explain why you chose a particular method for your research approach.  Methods , on the other hand, refer to how the data were collected and analyzed (e.g., experiments, surveys, observations, interviews, and statistical tests).

What is the difference between reliability and validity? +

Reliability refers to whether a measurement is consistent (i.e., the results can be reproduced under the same conditions).  Validity refers to whether a measurement is accurate (i.e., the results represent what was supposed to be measured). For example, when investigating linguistic and cultural guidelines for administration of the Preschool Language Scales, Fifth Edition (PLS5) in Arab-American preschool children, the normative sample curves should show the same distribution as a monolingual population, which would indicate that the test is valid. The test would be considered reliable if the results obtained were consistent across different sampling sites.

What tense is used to write the methods section? +

The methods section is written in the past tense because it describes what was done.

What software programs are recommended for statistical analysis? +

Recommended programs include Statistical Analysis Software (SAS) ,  Statistical Package for the Social Sciences (SPSS) ,  JMP ,  R software,  MATLAB , Microsoft Excel,  GraphPad Prism , and  Minitab .

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Guide for Thesis Research

• Introduction to the Thesis Process
• Project Planning
• Literature Review
• Theoretical Frameworks
• Research Methodology
• GC Honors Program Theses
• Thesis Submission Instructions This link opens in a new window
• Accessing Guilford Theses from 1898 to 2020 This link opens in a new window

Basics of Methodology

Research is a process of inquiry that is carried out in a pondered, organized, and strategic manner. In order to obtain high quality results, it is important to understand methodology.

Research methodology refers to how your project will be designed, what you will observe or measure, and how you will collect and analyze data. The methods you choose must be appropriate for your field and for the specific research questions you are setting out to answer.

A strong understanding of methodology will help you:

• apply appropriate research techniques
• design effective data collection instruments
• analyze and interpret your data
• develop well-founded conclusions

Below, you will find resources that mostly cover general aspects of research methodology. In the left column, you will find resources that specifically cover qualitative, quantitative, and mixed methods research.

General Works on Methodology

Qualitative Research

Quantitative Research

Mixed Methods Research

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A Practical Guide to Writing Quantitative and Qualitative Research Questions and Hypotheses in Scholarly Articles

Edward barroga.

1 Department of General Education, Graduate School of Nursing Science, St. Luke’s International University, Tokyo, Japan.

Glafera Janet Matanguihan

2 Department of Biological Sciences, Messiah University, Mechanicsburg, PA, USA.

The development of research questions and the subsequent hypotheses are prerequisites to defining the main research purpose and specific objectives of a study. Consequently, these objectives determine the study design and research outcome. The development of research questions is a process based on knowledge of current trends, cutting-edge studies, and technological advances in the research field. Excellent research questions are focused and require a comprehensive literature search and in-depth understanding of the problem being investigated. Initially, research questions may be written as descriptive questions which could be developed into inferential questions. These questions must be specific and concise to provide a clear foundation for developing hypotheses. Hypotheses are more formal predictions about the research outcomes. These specify the possible results that may or may not be expected regarding the relationship between groups. Thus, research questions and hypotheses clarify the main purpose and specific objectives of the study, which in turn dictate the design of the study, its direction, and outcome. Studies developed from good research questions and hypotheses will have trustworthy outcomes with wide-ranging social and health implications.

INTRODUCTION

Scientific research is usually initiated by posing evidenced-based research questions which are then explicitly restated as hypotheses. 1 , 2 The hypotheses provide directions to guide the study, solutions, explanations, and expected results. 3 , 4 Both research questions and hypotheses are essentially formulated based on conventional theories and real-world processes, which allow the inception of novel studies and the ethical testing of ideas. 5 , 6

It is crucial to have knowledge of both quantitative and qualitative research 2 as both types of research involve writing research questions and hypotheses. 7 However, these crucial elements of research are sometimes overlooked; if not overlooked, then framed without the forethought and meticulous attention it needs. Planning and careful consideration are needed when developing quantitative or qualitative research, particularly when conceptualizing research questions and hypotheses. 4

There is a continuing need to support researchers in the creation of innovative research questions and hypotheses, as well as for journal articles that carefully review these elements. 1 When research questions and hypotheses are not carefully thought of, unethical studies and poor outcomes usually ensue. Carefully formulated research questions and hypotheses define well-founded objectives, which in turn determine the appropriate design, course, and outcome of the study. This article then aims to discuss in detail the various aspects of crafting research questions and hypotheses, with the goal of guiding researchers as they develop their own. Examples from the authors and peer-reviewed scientific articles in the healthcare field are provided to illustrate key points.

DEFINITIONS AND RELATIONSHIP OF RESEARCH QUESTIONS AND HYPOTHESES

A research question is what a study aims to answer after data analysis and interpretation. The answer is written in length in the discussion section of the paper. Thus, the research question gives a preview of the different parts and variables of the study meant to address the problem posed in the research question. 1 An excellent research question clarifies the research writing while facilitating understanding of the research topic, objective, scope, and limitations of the study. 5

On the other hand, a research hypothesis is an educated statement of an expected outcome. This statement is based on background research and current knowledge. 8 , 9 The research hypothesis makes a specific prediction about a new phenomenon 10 or a formal statement on the expected relationship between an independent variable and a dependent variable. 3 , 11 It provides a tentative answer to the research question to be tested or explored. 4

Hypotheses employ reasoning to predict a theory-based outcome. 10 These can also be developed from theories by focusing on components of theories that have not yet been observed. 10 The validity of hypotheses is often based on the testability of the prediction made in a reproducible experiment. 8

Conversely, hypotheses can also be rephrased as research questions. Several hypotheses based on existing theories and knowledge may be needed to answer a research question. Developing ethical research questions and hypotheses creates a research design that has logical relationships among variables. These relationships serve as a solid foundation for the conduct of the study. 4 , 11 Haphazardly constructed research questions can result in poorly formulated hypotheses and improper study designs, leading to unreliable results. Thus, the formulations of relevant research questions and verifiable hypotheses are crucial when beginning research. 12

CHARACTERISTICS OF GOOD RESEARCH QUESTIONS AND HYPOTHESES

Excellent research questions are specific and focused. These integrate collective data and observations to confirm or refute the subsequent hypotheses. Well-constructed hypotheses are based on previous reports and verify the research context. These are realistic, in-depth, sufficiently complex, and reproducible. More importantly, these hypotheses can be addressed and tested. 13

There are several characteristics of well-developed hypotheses. Good hypotheses are 1) empirically testable 7 , 10 , 11 , 13 ; 2) backed by preliminary evidence 9 ; 3) testable by ethical research 7 , 9 ; 4) based on original ideas 9 ; 5) have evidenced-based logical reasoning 10 ; and 6) can be predicted. 11 Good hypotheses can infer ethical and positive implications, indicating the presence of a relationship or effect relevant to the research theme. 7 , 11 These are initially developed from a general theory and branch into specific hypotheses by deductive reasoning. In the absence of a theory to base the hypotheses, inductive reasoning based on specific observations or findings form more general hypotheses. 10

TYPES OF RESEARCH QUESTIONS AND HYPOTHESES

Research questions and hypotheses are developed according to the type of research, which can be broadly classified into quantitative and qualitative research. We provide a summary of the types of research questions and hypotheses under quantitative and qualitative research categories in Table 1 .

Research questions in quantitative research

In quantitative research, research questions inquire about the relationships among variables being investigated and are usually framed at the start of the study. These are precise and typically linked to the subject population, dependent and independent variables, and research design. 1 Research questions may also attempt to describe the behavior of a population in relation to one or more variables, or describe the characteristics of variables to be measured ( descriptive research questions ). 1 , 5 , 14 These questions may also aim to discover differences between groups within the context of an outcome variable ( comparative research questions ), 1 , 5 , 14 or elucidate trends and interactions among variables ( relationship research questions ). 1 , 5 We provide examples of descriptive, comparative, and relationship research questions in quantitative research in Table 2 .

Hypotheses in quantitative research

In quantitative research, hypotheses predict the expected relationships among variables. 15 Relationships among variables that can be predicted include 1) between a single dependent variable and a single independent variable ( simple hypothesis ) or 2) between two or more independent and dependent variables ( complex hypothesis ). 4 , 11 Hypotheses may also specify the expected direction to be followed and imply an intellectual commitment to a particular outcome ( directional hypothesis ) 4 . On the other hand, hypotheses may not predict the exact direction and are used in the absence of a theory, or when findings contradict previous studies ( non-directional hypothesis ). 4 In addition, hypotheses can 1) define interdependency between variables ( associative hypothesis ), 4 2) propose an effect on the dependent variable from manipulation of the independent variable ( causal hypothesis ), 4 3) state a negative relationship between two variables ( null hypothesis ), 4 , 11 , 15 4) replace the working hypothesis if rejected ( alternative hypothesis ), 15 explain the relationship of phenomena to possibly generate a theory ( working hypothesis ), 11 5) involve quantifiable variables that can be tested statistically ( statistical hypothesis ), 11 6) or express a relationship whose interlinks can be verified logically ( logical hypothesis ). 11 We provide examples of simple, complex, directional, non-directional, associative, causal, null, alternative, working, statistical, and logical hypotheses in quantitative research, as well as the definition of quantitative hypothesis-testing research in Table 3 .

Research questions in qualitative research

Unlike research questions in quantitative research, research questions in qualitative research are usually continuously reviewed and reformulated. The central question and associated subquestions are stated more than the hypotheses. 15 The central question broadly explores a complex set of factors surrounding the central phenomenon, aiming to present the varied perspectives of participants. 15

There are varied goals for which qualitative research questions are developed. These questions can function in several ways, such as to 1) identify and describe existing conditions ( contextual research question s); 2) describe a phenomenon ( descriptive research questions ); 3) assess the effectiveness of existing methods, protocols, theories, or procedures ( evaluation research questions ); 4) examine a phenomenon or analyze the reasons or relationships between subjects or phenomena ( explanatory research questions ); or 5) focus on unknown aspects of a particular topic ( exploratory research questions ). 5 In addition, some qualitative research questions provide new ideas for the development of theories and actions ( generative research questions ) or advance specific ideologies of a position ( ideological research questions ). 1 Other qualitative research questions may build on a body of existing literature and become working guidelines ( ethnographic research questions ). Research questions may also be broadly stated without specific reference to the existing literature or a typology of questions ( phenomenological research questions ), may be directed towards generating a theory of some process ( grounded theory questions ), or may address a description of the case and the emerging themes ( qualitative case study questions ). 15 We provide examples of contextual, descriptive, evaluation, explanatory, exploratory, generative, ideological, ethnographic, phenomenological, grounded theory, and qualitative case study research questions in qualitative research in Table 4 , and the definition of qualitative hypothesis-generating research in Table 5 .

Qualitative studies usually pose at least one central research question and several subquestions starting with How or What . These research questions use exploratory verbs such as explore or describe . These also focus on one central phenomenon of interest, and may mention the participants and research site. 15

Hypotheses in qualitative research

Hypotheses in qualitative research are stated in the form of a clear statement concerning the problem to be investigated. Unlike in quantitative research where hypotheses are usually developed to be tested, qualitative research can lead to both hypothesis-testing and hypothesis-generating outcomes. 2 When studies require both quantitative and qualitative research questions, this suggests an integrative process between both research methods wherein a single mixed-methods research question can be developed. 1

FRAMEWORKS FOR DEVELOPING RESEARCH QUESTIONS AND HYPOTHESES

Research questions followed by hypotheses should be developed before the start of the study. 1 , 12 , 14 It is crucial to develop feasible research questions on a topic that is interesting to both the researcher and the scientific community. This can be achieved by a meticulous review of previous and current studies to establish a novel topic. Specific areas are subsequently focused on to generate ethical research questions. The relevance of the research questions is evaluated in terms of clarity of the resulting data, specificity of the methodology, objectivity of the outcome, depth of the research, and impact of the study. 1 , 5 These aspects constitute the FINER criteria (i.e., Feasible, Interesting, Novel, Ethical, and Relevant). 1 Clarity and effectiveness are achieved if research questions meet the FINER criteria. In addition to the FINER criteria, Ratan et al. described focus, complexity, novelty, feasibility, and measurability for evaluating the effectiveness of research questions. 14

The PICOT and PEO frameworks are also used when developing research questions. 1 The following elements are addressed in these frameworks, PICOT: P-population/patients/problem, I-intervention or indicator being studied, C-comparison group, O-outcome of interest, and T-timeframe of the study; PEO: P-population being studied, E-exposure to preexisting conditions, and O-outcome of interest. 1 Research questions are also considered good if these meet the “FINERMAPS” framework: Feasible, Interesting, Novel, Ethical, Relevant, Manageable, Appropriate, Potential value/publishable, and Systematic. 14

As we indicated earlier, research questions and hypotheses that are not carefully formulated result in unethical studies or poor outcomes. To illustrate this, we provide some examples of ambiguous research question and hypotheses that result in unclear and weak research objectives in quantitative research ( Table 6 ) 16 and qualitative research ( Table 7 ) 17 , and how to transform these ambiguous research question(s) and hypothesis(es) into clear and good statements.

a These statements were composed for comparison and illustrative purposes only.

b These statements are direct quotes from Higashihara and Horiuchi. 16

a This statement is a direct quote from Shimoda et al. 17

The other statements were composed for comparison and illustrative purposes only.

CONSTRUCTING RESEARCH QUESTIONS AND HYPOTHESES

To construct effective research questions and hypotheses, it is very important to 1) clarify the background and 2) identify the research problem at the outset of the research, within a specific timeframe. 9 Then, 3) review or conduct preliminary research to collect all available knowledge about the possible research questions by studying theories and previous studies. 18 Afterwards, 4) construct research questions to investigate the research problem. Identify variables to be accessed from the research questions 4 and make operational definitions of constructs from the research problem and questions. Thereafter, 5) construct specific deductive or inductive predictions in the form of hypotheses. 4 Finally, 6) state the study aims . This general flow for constructing effective research questions and hypotheses prior to conducting research is shown in Fig. 1 .

Research questions are used more frequently in qualitative research than objectives or hypotheses. 3 These questions seek to discover, understand, explore or describe experiences by asking “What” or “How.” The questions are open-ended to elicit a description rather than to relate variables or compare groups. The questions are continually reviewed, reformulated, and changed during the qualitative study. 3 Research questions are also used more frequently in survey projects than hypotheses in experiments in quantitative research to compare variables and their relationships.

Hypotheses are constructed based on the variables identified and as an if-then statement, following the template, ‘If a specific action is taken, then a certain outcome is expected.’ At this stage, some ideas regarding expectations from the research to be conducted must be drawn. 18 Then, the variables to be manipulated (independent) and influenced (dependent) are defined. 4 Thereafter, the hypothesis is stated and refined, and reproducible data tailored to the hypothesis are identified, collected, and analyzed. 4 The hypotheses must be testable and specific, 18 and should describe the variables and their relationships, the specific group being studied, and the predicted research outcome. 18 Hypotheses construction involves a testable proposition to be deduced from theory, and independent and dependent variables to be separated and measured separately. 3 Therefore, good hypotheses must be based on good research questions constructed at the start of a study or trial. 12

In summary, research questions are constructed after establishing the background of the study. Hypotheses are then developed based on the research questions. Thus, it is crucial to have excellent research questions to generate superior hypotheses. In turn, these would determine the research objectives and the design of the study, and ultimately, the outcome of the research. 12 Algorithms for building research questions and hypotheses are shown in Fig. 2 for quantitative research and in Fig. 3 for qualitative research.

EXAMPLES OF RESEARCH QUESTIONS FROM PUBLISHED ARTICLES

• EXAMPLE 1. Descriptive research question (quantitative research)
• - Presents research variables to be assessed (distinct phenotypes and subphenotypes)
• “BACKGROUND: Since COVID-19 was identified, its clinical and biological heterogeneity has been recognized. Identifying COVID-19 phenotypes might help guide basic, clinical, and translational research efforts.
• RESEARCH QUESTION: Does the clinical spectrum of patients with COVID-19 contain distinct phenotypes and subphenotypes? ” 19
• EXAMPLE 2. Relationship research question (quantitative research)
• - Shows interactions between dependent variable (static postural control) and independent variable (peripheral visual field loss)
• “Background: Integration of visual, vestibular, and proprioceptive sensations contributes to postural control. People with peripheral visual field loss have serious postural instability. However, the directional specificity of postural stability and sensory reweighting caused by gradual peripheral visual field loss remain unclear.
• Research question: What are the effects of peripheral visual field loss on static postural control ?” 20
• EXAMPLE 3. Comparative research question (quantitative research)
• - Clarifies the difference among groups with an outcome variable (patients enrolled in COMPERA with moderate PH or severe PH in COPD) and another group without the outcome variable (patients with idiopathic pulmonary arterial hypertension (IPAH))
• “BACKGROUND: Pulmonary hypertension (PH) in COPD is a poorly investigated clinical condition.
• RESEARCH QUESTION: Which factors determine the outcome of PH in COPD?
• STUDY DESIGN AND METHODS: We analyzed the characteristics and outcome of patients enrolled in the Comparative, Prospective Registry of Newly Initiated Therapies for Pulmonary Hypertension (COMPERA) with moderate or severe PH in COPD as defined during the 6th PH World Symposium who received medical therapy for PH and compared them with patients with idiopathic pulmonary arterial hypertension (IPAH) .” 21
• EXAMPLE 4. Exploratory research question (qualitative research)
• - Explores areas that have not been fully investigated (perspectives of families and children who receive care in clinic-based child obesity treatment) to have a deeper understanding of the research problem
• “Problem: Interventions for children with obesity lead to only modest improvements in BMI and long-term outcomes, and data are limited on the perspectives of families of children with obesity in clinic-based treatment. This scoping review seeks to answer the question: What is known about the perspectives of families and children who receive care in clinic-based child obesity treatment? This review aims to explore the scope of perspectives reported by families of children with obesity who have received individualized outpatient clinic-based obesity treatment.” 22
• EXAMPLE 5. Relationship research question (quantitative research)
• - Defines interactions between dependent variable (use of ankle strategies) and independent variable (changes in muscle tone)
• “Background: To maintain an upright standing posture against external disturbances, the human body mainly employs two types of postural control strategies: “ankle strategy” and “hip strategy.” While it has been reported that the magnitude of the disturbance alters the use of postural control strategies, it has not been elucidated how the level of muscle tone, one of the crucial parameters of bodily function, determines the use of each strategy. We have previously confirmed using forward dynamics simulations of human musculoskeletal models that an increased muscle tone promotes the use of ankle strategies. The objective of the present study was to experimentally evaluate a hypothesis: an increased muscle tone promotes the use of ankle strategies. Research question: Do changes in the muscle tone affect the use of ankle strategies ?” 23

EXAMPLES OF HYPOTHESES IN PUBLISHED ARTICLES

• EXAMPLE 1. Working hypothesis (quantitative research)
• - A hypothesis that is initially accepted for further research to produce a feasible theory
• “As fever may have benefit in shortening the duration of viral illness, it is plausible to hypothesize that the antipyretic efficacy of ibuprofen may be hindering the benefits of a fever response when taken during the early stages of COVID-19 illness .” 24
• “In conclusion, it is plausible to hypothesize that the antipyretic efficacy of ibuprofen may be hindering the benefits of a fever response . The difference in perceived safety of these agents in COVID-19 illness could be related to the more potent efficacy to reduce fever with ibuprofen compared to acetaminophen. Compelling data on the benefit of fever warrant further research and review to determine when to treat or withhold ibuprofen for early stage fever for COVID-19 and other related viral illnesses .” 24
• EXAMPLE 2. Exploratory hypothesis (qualitative research)
• - Explores particular areas deeper to clarify subjective experience and develop a formal hypothesis potentially testable in a future quantitative approach
• “We hypothesized that when thinking about a past experience of help-seeking, a self distancing prompt would cause increased help-seeking intentions and more favorable help-seeking outcome expectations .” 25
• “Conclusion
• Although a priori hypotheses were not supported, further research is warranted as results indicate the potential for using self-distancing approaches to increasing help-seeking among some people with depressive symptomatology.” 25
• EXAMPLE 3. Hypothesis-generating research to establish a framework for hypothesis testing (qualitative research)
• “We hypothesize that compassionate care is beneficial for patients (better outcomes), healthcare systems and payers (lower costs), and healthcare providers (lower burnout). ” 26
• Compassionomics is the branch of knowledge and scientific study of the effects of compassionate healthcare. Our main hypotheses are that compassionate healthcare is beneficial for (1) patients, by improving clinical outcomes, (2) healthcare systems and payers, by supporting financial sustainability, and (3) HCPs, by lowering burnout and promoting resilience and well-being. The purpose of this paper is to establish a scientific framework for testing the hypotheses above . If these hypotheses are confirmed through rigorous research, compassionomics will belong in the science of evidence-based medicine, with major implications for all healthcare domains.” 26
• EXAMPLE 4. Statistical hypothesis (quantitative research)
• - An assumption is made about the relationship among several population characteristics ( gender differences in sociodemographic and clinical characteristics of adults with ADHD ). Validity is tested by statistical experiment or analysis ( chi-square test, Students t-test, and logistic regression analysis)
• “Our research investigated gender differences in sociodemographic and clinical characteristics of adults with ADHD in a Japanese clinical sample. Due to unique Japanese cultural ideals and expectations of women's behavior that are in opposition to ADHD symptoms, we hypothesized that women with ADHD experience more difficulties and present more dysfunctions than men . We tested the following hypotheses: first, women with ADHD have more comorbidities than men with ADHD; second, women with ADHD experience more social hardships than men, such as having less full-time employment and being more likely to be divorced.” 27
• “Statistical Analysis
• ( text omitted ) Between-gender comparisons were made using the chi-squared test for categorical variables and Students t-test for continuous variables…( text omitted ). A logistic regression analysis was performed for employment status, marital status, and comorbidity to evaluate the independent effects of gender on these dependent variables.” 27

EXAMPLES OF HYPOTHESIS AS WRITTEN IN PUBLISHED ARTICLES IN RELATION TO OTHER PARTS

• EXAMPLE 1. Background, hypotheses, and aims are provided
• “Pregnant women need skilled care during pregnancy and childbirth, but that skilled care is often delayed in some countries …( text omitted ). The focused antenatal care (FANC) model of WHO recommends that nurses provide information or counseling to all pregnant women …( text omitted ). Job aids are visual support materials that provide the right kind of information using graphics and words in a simple and yet effective manner. When nurses are not highly trained or have many work details to attend to, these job aids can serve as a content reminder for the nurses and can be used for educating their patients (Jennings, Yebadokpo, Affo, & Agbogbe, 2010) ( text omitted ). Importantly, additional evidence is needed to confirm how job aids can further improve the quality of ANC counseling by health workers in maternal care …( text omitted )” 28
• “ This has led us to hypothesize that the quality of ANC counseling would be better if supported by job aids. Consequently, a better quality of ANC counseling is expected to produce higher levels of awareness concerning the danger signs of pregnancy and a more favorable impression of the caring behavior of nurses .” 28
• “This study aimed to examine the differences in the responses of pregnant women to a job aid-supported intervention during ANC visit in terms of 1) their understanding of the danger signs of pregnancy and 2) their impression of the caring behaviors of nurses to pregnant women in rural Tanzania.” 28
• EXAMPLE 2. Background, hypotheses, and aims are provided
• “We conducted a two-arm randomized controlled trial (RCT) to evaluate and compare changes in salivary cortisol and oxytocin levels of first-time pregnant women between experimental and control groups. The women in the experimental group touched and held an infant for 30 min (experimental intervention protocol), whereas those in the control group watched a DVD movie of an infant (control intervention protocol). The primary outcome was salivary cortisol level and the secondary outcome was salivary oxytocin level.” 29
• “ We hypothesize that at 30 min after touching and holding an infant, the salivary cortisol level will significantly decrease and the salivary oxytocin level will increase in the experimental group compared with the control group .” 29
• EXAMPLE 3. Background, aim, and hypothesis are provided
• “In countries where the maternal mortality ratio remains high, antenatal education to increase Birth Preparedness and Complication Readiness (BPCR) is considered one of the top priorities [1]. BPCR includes birth plans during the antenatal period, such as the birthplace, birth attendant, transportation, health facility for complications, expenses, and birth materials, as well as family coordination to achieve such birth plans. In Tanzania, although increasing, only about half of all pregnant women attend an antenatal clinic more than four times [4]. Moreover, the information provided during antenatal care (ANC) is insufficient. In the resource-poor settings, antenatal group education is a potential approach because of the limited time for individual counseling at antenatal clinics.” 30
• “This study aimed to evaluate an antenatal group education program among pregnant women and their families with respect to birth-preparedness and maternal and infant outcomes in rural villages of Tanzania.” 30
• “ The study hypothesis was if Tanzanian pregnant women and their families received a family-oriented antenatal group education, they would (1) have a higher level of BPCR, (2) attend antenatal clinic four or more times, (3) give birth in a health facility, (4) have less complications of women at birth, and (5) have less complications and deaths of infants than those who did not receive the education .” 30

Research questions and hypotheses are crucial components to any type of research, whether quantitative or qualitative. These questions should be developed at the very beginning of the study. Excellent research questions lead to superior hypotheses, which, like a compass, set the direction of research, and can often determine the successful conduct of the study. Many research studies have floundered because the development of research questions and subsequent hypotheses was not given the thought and meticulous attention needed. The development of research questions and hypotheses is an iterative process based on extensive knowledge of the literature and insightful grasp of the knowledge gap. Focused, concise, and specific research questions provide a strong foundation for constructing hypotheses which serve as formal predictions about the research outcomes. Research questions and hypotheses are crucial elements of research that should not be overlooked. They should be carefully thought of and constructed when planning research. This avoids unethical studies and poor outcomes by defining well-founded objectives that determine the design, course, and outcome of the study.

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

Author Contributions:

• Conceptualization: Barroga E, Matanguihan GJ.
• Methodology: Barroga E, Matanguihan GJ.
• Writing - original draft: Barroga E, Matanguihan GJ.
• Writing - review & editing: Barroga E, Matanguihan GJ.

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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.

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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.

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April 23, 2024

Research in Context: Treating depression

Finding better approaches.

While effective treatments for major depression are available, there is still room for improvement. This special Research in Context feature explores the development of more effective ways to treat depression, including personalized treatment approaches and both old and new drugs.

Everyone has a bad day sometimes. People experience various types of stress in the course of everyday life. These stressors can cause sadness, anxiety, hopelessness, frustration, or guilt. You may not enjoy the activities you usually do. These feelings tend to be only temporary. Once circumstances change, and the source of stress goes away, your mood usually improves. But sometimes, these feelings don’t go away. When these feelings stick around for at least two weeks and interfere with your daily activities, it’s called major depression, or clinical depression.

In 2021, 8.3% of U.S. adults experienced major depression. That’s about 21 million people. Among adolescents, the prevalence was much greater—more than 20%. Major depression can bring decreased energy, difficulty thinking straight, sleep problems, loss of appetite, and even physical pain. People with major depression may become unable to meet their responsibilities at work or home. Depression can also lead people to use alcohol or drugs or engage in high-risk activities. In the most extreme cases, depression can drive people to self-harm or even suicide.

The good news is that effective treatments are available. But current treatments have limitations. That’s why NIH-funded researchers have been working to develop more effective ways to treat depression. These include finding ways to predict whether certain treatments will help a given patient. They're also trying to develop more effective drugs or, in some cases, find new uses for existing drugs.

Finding the right treatments

The most common treatments for depression include psychotherapy, medications, or a combination. Mild depression may be treated with psychotherapy. Moderate to severe depression often requires the addition of medication.

Several types of psychotherapy have been shown to help relieve depression symptoms. For example, cognitive behavioral therapy helps people to recognize harmful ways of thinking and teaches them how to change these. Some researchers are working to develop new therapies to enhance people’s positive emotions. But good psychotherapy can be hard to access due to the cost, scheduling difficulties, or lack of available providers. The recent growth of telehealth services for mental health has improved access in some cases.

There are many antidepressant drugs on the market. Different drugs will work best on different patients. But it can be challenging to predict which drugs will work for a given patient. And it can take anywhere from 6 to 12 weeks to know whether a drug is working. Finding an effective drug can involve a long period of trial and error, with no guarantee of results.

If depression doesn’t improve with psychotherapy or medications, brain stimulation therapies could be used. Electroconvulsive therapy, or ECT, uses electrodes to send electric current into the brain. A newer technique, transcranial magnetic stimulation (TMS), stimulates the brain using magnetic fields. These treatments must be administered by specially trained health professionals.

“A lot of patients, they kind of muddle along, treatment after treatment, with little idea whether something’s going to work,” says psychiatric researcher Dr. Amit Etkin.

One reason it’s difficult to know which antidepressant medications will work is that there are likely different biological mechanisms that can cause depression. Two people with similar symptoms may both be diagnosed with depression, but the causes of their symptoms could be different. As NIH depression researcher Dr. Carlos Zarate explains, “we believe that there’s not one depression, but hundreds of depressions.”

Depression may be due to many factors. Genetics can put certain people at risk for depression. Stressful situations, physical health conditions, and medications may contribute. And depression can also be part of a more complicated mental disorder, such as bipolar disorder. All of these can affect which treatment would be best to use.

Etkin has been developing methods to distinguish patients with different types of depression based on measurable biological features, or biomarkers. The idea is that different types of patients would respond differently to various treatments. Etkin calls this approach “precision psychiatry.”

One such type of biomarker is electrical activity in the brain. A technique called electroencephalography, or EEG, measures electrical activity using electrodes placed on the scalp. When Etkin was at Stanford University, he led a research team that developed a machine-learning algorithm to predict treatment response based on EEG signals. The team applied the algorithm to data from a clinical trial of the antidepressant sertraline (Zoloft) involving more than 300 people.

EEG data for the participants were collected at the outset. Participants were then randomly assigned to take either sertraline or an inactive placebo for eight weeks. The team found a specific set of signals that predicted the participants’ responses to sertraline. The same neural “signature” also predicted which patients with depression responded to medication in a separate group.

Etkin’s team also examined this neural signature in a set of patients who were treated with TMS and psychotherapy. People who were predicted to respond less to sertraline had a greater response to the TMS/psychotherapy combination.

Etkin continues to develop methods for personalized depression treatment through his company, Alto Neuroscience. He notes that EEG has the advantage of being low-cost and accessible; data can even be collected in a patient’s home. That’s important for being able to get personalized treatments to the large number of people they could help. He’s also working on developing antidepressant drugs targeted to specific EEG profiles. Candidate drugs are in clinical trials now.

“It’s not like a pie-in-the-sky future thing, 20-30 years from now,” Etkin explains. “This is something that could be in people's hands within the next five years.”

New tricks for old drugs

While some researchers focus on matching patients with their optimal treatments, others aim to find treatments that can work for many different patients. It turns out that some drugs we’ve known about for decades might be very effective antidepressants, but we didn’t recognize their antidepressant properties until recently.

One such drug is ketamine. Ketamine has been used as an anesthetic for more than 50 years. Around the turn of this century, researchers started to discover its potential as an antidepressant. Zarate and others have found that, unlike traditional antidepressants that can take weeks to take effect, ketamine can improve depression in as little as one day. And a single dose can have an effect for a week or more. In 2019, the FDA approved a form of ketamine for treating depression that is resistant to other treatments.

But ketamine has drawbacks of its own. It’s a dissociative drug, meaning that it can make people feel disconnected from their body and environment. It also has the potential for addiction and misuse. For these reasons, it’s a controlled substance and can only be administered in a doctor’s office or clinic.

Another class of drugs being studied as possible antidepressants are psychedelics. These include lysergic acid diethylamide (LSD) and psilocybin, the active ingredient in magic mushrooms. These drugs can temporarily alter a person’s mood, thoughts, and perceptions of reality. Some have historically been used for religious rituals, but they are also used recreationally.

In clinical studies, psychedelics are typically administered in combination with psychotherapy. This includes several preparatory sessions with a therapist in the weeks before getting the drug, and several sessions in the weeks following to help people process their experiences. The drugs are administered in a controlled setting.

Dr. Stephen Ross, co-director of the New York University Langone Health Center for Psychedelic Medicine, describes a typical session: “It takes place in a living room-like setting. The person is prepared, and they state their intention. They take the drug, they lie supine, they put on eye shades and preselected music, and two therapists monitor them.” Sessions last for as long as the acute effects of the drug last, which is typically several hours. This is a healthcare-intensive intervention given the time and personnel needed.

In 2016, Ross led a clinical trial examining whether psilocybin-assisted therapy could reduce depression and anxiety in people with cancer. According to Ross, as many as 40% of people with cancer have clinically significant anxiety and depression. The study showed that a single psilocybin session led to substantial reductions in anxiety and depression compared with a placebo. These reductions were evident as soon as one day after psilocybin administration. Six months later, 60-80% of participants still had reduced depression and anxiety.

Psychedelic drugs frequently trigger mystical experiences in the people who take them. “People can feel a sense…that their consciousness is part of a greater consciousness or that all energy is one,” Ross explains. “People can have an experience that for them feels more ‘real’ than regular reality. They can feel transported to a different dimension of reality.”

About three out of four participants in Ross’s study said it was among the most meaningful experiences of their lives. And the degree of mystical experience correlated with the drug’s therapeutic effect. A long-term follow-up study found that the effects of the treatment continued more than four years later.

If these results seem too good to be true, Ross is quick to point out that it was a small study, with only 29 participants, although similar studies from other groups have yielded similar results. Psychedelics haven’t yet been shown to be effective in a large, controlled clinical trial. Ross is now conducting a trial with 200 people to see if the results of his earlier study pan out in this larger group. For now, though, psychedelics remain experimental drugs—approved for testing, but not for routine medical use.

Unlike ketamine, psychedelics aren’t considered addictive. But they, too, carry risks, which certain conditions may increase. Psychedelics can cause cardiovascular complications. They can cause psychosis in people who are predisposed to it. In uncontrolled settings, they have the risk of causing anxiety, confusion, and paranoia—a so-called “bad trip”—that can lead the person taking the drug to harm themself or others. This is why psychedelic-assisted therapy takes place in such tightly controlled settings. That increases the cost and complexity of the therapy, which may prevent many people from having access to it.

Better, safer drugs

Despite the promise of ketamine or psychedelics, their drawbacks have led some researchers to look for drugs that work like them but with fewer side effects.

Depression is thought to be caused by the loss of connections between nerve cells, or neurons, in certain regions of the brain. Ketamine and psychedelics both promote the brain’s ability to repair these connections, a quality called plasticity. If we could understand how these drugs encourage plasticity, we might be able to design drugs that can do so without the side effects.

Dr. David Olson at the University of California, Davis studies how psychedelics work at the cellular and molecular levels. The drugs appear to promote plasticity by binding to a receptor in cells called the 5-hydroxytryptamine 2A receptor (5-HT2AR). But many other compounds also bind 5-HT2AR without promoting plasticity. In a recent NIH-funded study, Olson showed that 5-HT2AR can be found both inside and on the surface of the cell. Only compounds that bound to the receptor inside the cells promoted plasticity. This suggests that a drug has to be able to get into the cell to promote plasticity.

Moreover, not all drugs that bind 5-HT2AR have psychedelic effects. Olson’s team has developed a molecular sensor, called psychLight, that can identify which compounds that bind 5-HT2AR have psychedelic effects. Using psychLight, they identified compounds that are not psychedelic but still have rapid and long-lasting antidepressant effects in animal models. He’s founded a company, Delix Therapeutics, to further develop drugs that promote plasticity.

Meanwhile, Zarate and his colleagues have been investigating a compound related to ketamine called hydroxynorketamine (HNK). Ketamine is converted to HNK in the body, and this process appears to be required for ketamine’s antidepressant effects. Administering HNK directly produced antidepressant-like effects in mice. At the same time, it did not cause the dissociative side effects and addiction caused by ketamine. Zarate’s team has already completed phase I trials of HNK in people showing that it’s safe. Phase II trials to find out whether it’s effective are scheduled to begin soon.  

“What [ketamine and psychedelics] are doing for the field is they’re helping us realize that it is possible to move toward a repair model versus a symptom mitigation model,” Olson says. Unlike existing antidepressants, which just relieve the symptoms of depression, these drugs appear to fix the underlying causes. That’s likely why they work faster and produce longer-lasting effects. This research is bringing us closer to having safer antidepressants that only need to be taken once in a while, instead of every day.

—by Brian Doctrow, Ph.D.

Related Links

• How Psychedelic Drugs May Help with Depression
• Biosensor Advances Drug Discovery
• Neural Signature Predicts Antidepressant Response
• How Ketamine Relieves Symptoms of Depression
• Protein Structure Reveals How LSD Affects the Brain
• Predicting The Usefulness of Antidepressants
• Depression Screening and Treatment in Adults
• Serotonin Transporter Structure Revealed
• Placebo Effect in Depression Treatment
• When Sadness Lingers: Understanding and Treating Depression
• Psychedelic and Dissociative Drugs

References:  An electroencephalographic signature predicts antidepressant response in major depression.  Wu W, Zhang Y, Jiang J, Lucas MV, Fonzo GA, Rolle CE, Cooper C, Chin-Fatt C, Krepel N, Cornelssen CA, Wright R, Toll RT, Trivedi HM, Monuszko K, Caudle TL, Sarhadi K, Jha MK, Trombello JM, Deckersbach T, Adams P, McGrath PJ, Weissman MM, Fava M, Pizzagalli DA, Arns M, Trivedi MH, Etkin A.  Nat Biotechnol.  2020 Feb 10. doi: 10.1038/s41587-019-0397-3. Epub 2020 Feb 10. PMID: 32042166. Rapid and sustained symptom reduction following psilocybin treatment for anxiety and depression in patients with life-threatening cancer: a randomized controlled trial. Ross S, Bossis A, Guss J, Agin-Liebes G, Malone T, Cohen B, Mennenga SE, Belser A, Kalliontzi K, Babb J, Su Z, Corby P, Schmidt BL. J Psychopharmacol . 2016 Dec;30(12):1165-1180. doi: 10.1177/0269881116675512. PMID: 27909164. Long-term follow-up of psilocybin-assisted psychotherapy for psychiatric and existential distress in patients with life-threatening cancer. Agin-Liebes GI, Malone T, Yalch MM, Mennenga SE, Ponté KL, Guss J, Bossis AP, Grigsby J, Fischer S, Ross S. J Psychopharmacol . 2020 Feb;34(2):155-166. doi: 10.1177/0269881119897615. Epub 2020 Jan 9. PMID: 31916890. Psychedelics promote neuroplasticity through the activation of intracellular 5-HT2A receptors.  Vargas MV, Dunlap LE, Dong C, Carter SJ, Tombari RJ, Jami SA, Cameron LP, Patel SD, Hennessey JJ, Saeger HN, McCorvy JD, Gray JA, Tian L, Olson DE.  Science . 2023 Feb 17;379(6633):700-706. doi: 10.1126/science.adf0435. Epub 2023 Feb 16. PMID: 36795823. Psychedelic-inspired drug discovery using an engineered biosensor.  Dong C, Ly C, Dunlap LE, Vargas MV, Sun J, Hwang IW, Azinfar A, Oh WC, Wetsel WC, Olson DE, Tian L.  Cell . 2021 Apr 8: S0092-8674(21)00374-3. doi: 10.1016/j.cell.2021.03.043. Epub 2021 Apr 28. PMID: 33915107. NMDAR inhibition-independent antidepressant actions of ketamine metabolites. Zanos P, Moaddel R, Morris PJ, Georgiou P, Fischell J, Elmer GI, Alkondon M, Yuan P, Pribut HJ, Singh NS, Dossou KS, Fang Y, Huang XP, Mayo CL, Wainer IW, Albuquerque EX, Thompson SM, Thomas CJ, Zarate CA Jr, Gould TD. Nature . 2016 May 26;533(7604):481-6. doi: 10.1038/nature17998. Epub 2016 May 4. PMID: 27144355.

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When it comes to sustainability and environmental impact, this Northeastern Ph.D. grad is at the ‘forefront of innovation’

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Looking at doctorate programs, Abhijeet Parvatker found a perfect match in Northeastern and Matthew Eckelman, a professor of civil, environmental and chemical engineering.

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Before arriving at Northeastern University to pursue a doctoral degree, Abhijeet Parvatker worked as a research engineer at one of the world’s largest petrochemicals manufacturers. 

He was a part of a team that measured sustainability of the company’s products, primarily produced from natural gas.

“There is generally a lot of pressure from stakeholders to understand the environmental impacts that the products have,” Parvatker says. 

He used one of the most common methodologies — life-cycle assessment — that evaluates how a product or service impacts the environment over the course of its life cycle, from the moment raw materials are extracted to manufacture the product, to when it is discarded.

Although the life-cycle assessment methodology was standardized, Parvatker says, it was challenging to find the data needed to determine consumed energy, carbon dioxide emissions or toxicity. 

“I soon realized that there are a lot of gaps in this,” he says. “The methods to get to the data are not as evolved, and I wanted to do a Ph.D. with that focus.”

Looking at doctorate programs, Parvatker found Northeastern and Matthew Eckelman , a professor of civil, environmental and chemical engineering, who was doing research in the exact area he was interested in. 

From then on, his life’s work started to take on a larger meaning.

“It was a really good fit for a research project that I had just gotten funded from the National Science Foundation,” Eckelman says. “I felt like he had the experience to carry out this project.”

Parvatker’s research looks at developing new methods and models for generating data for life-cycle assessments and evaluating the sustainability of different chemicals and chemical manufacturing processes.

“There’s something like tens of thousands of chemicals in commerce,” Eckelman says. “We have inventory information on maybe a couple thousands.”  

It was a big and ambitious project, he says, but Parvatker has made a lot of progress. And it’s been extremely useful, Eckelman says, to the global community.

“I am always getting questions about papers that Abhijeet and I wrote together,” Eckelman says. “People wanting to use the data, wanting to adapt the techniques that we use to generate the data.”

Another project Parvatker worked on was analyzing the environmental impact of intravenous anesthetic drugs used by medical institutions.The health care sector makes a considerable contribution to America’s GDP, Eckelman says, which means that to reduce the country’s carbon dioxide output into the atmosphere, health care must become more sustainable. 

However, pharmaceutical companies don’t share much data about the inputs of chemicals they use in a drug, Parvatker says, for proprietary or other reasons.

He used chemical engineering principles, process design and physics and chemistry knowledge about these products to calculate inputs and outputs. He looked at 20 intravenous anesthetic drugs and about 140 different chemicals, building life-cycle inventory data for them.

“It’s still the largest study in the pharmaceutical sector for those chemicals,” he says.

Together, Parvatker and Eckelman wrote some of the first papers about the contribution of the health care industry to national and global emissions.

“These numbers are quoted all the time,” Eckelman says. “And then the National Academy of Medicine opened up this big effort called the Action Collaborative on Decarbonizing the U.S. Health Sector. And now we’re invited to be a part of that because of his work.”

Parvatker earned his undergraduate degree in chemical engineering back home in India and his master’s degree in advanced process integration and design from the University of Manchester before being accepted into Northeastern’s Ph.D. program.

Parvatker says the university takes experiential learning to the next level by encouraging students to apply their research in the real world through programs such as LEADERs .

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Short for Leadership Education Advancing Discovery through Embedded Research, LEADERs is a customized internship program for Northeastern doctoral students and postdoctoral researchers.

Parvatker credits the program — and his internship at Wayfair that resulted from it — for introducing him to the world of sustainability consulting. At Wayfair, he was tasked with creating guidelines for vendors on the use of chemicals based on the U.S. and the EU regulations. He also gained experience in chemical safety and supply chain management.

After completing his doctoral degree program, Parvatker was offered a full-time job at Sphera Solutions, a provider of consulting services, data and software solutions for risk management and monitoring of environmental, social and governance performance. 

He currently manages a team of five sustainability consultants who help companies with large product portfolios address their sustainability challenges, automate calculations and reports on ESG with Sphera’s software. 

“Imagine companies that have tens of thousands and millions of products,” Parvatker says. “With some initial effort of six months to one year, you can scale the life-cycle assessment methodology to the entire product portfolio and calculate all the life-cycle assessment results for tens of thousands of products in hours.”

Parvatker loves working with different companies, different processes and different people.

“In this space of the implementation of this methodology, we are always at the forefront of innovation,” he says.

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APS Editorial Fellows to Help Build a Pipeline of Diverse Editors 

• Advances in Methods and Practices in Psychological Science
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Psychological Science

Editorial Fellows, clockwise from top left: Ivan Carbajal, Leyla Loued-Khenissi, Chelsea Boccagno, Aishwarya Rajesh, Kongmeng Liew, Dieu Truong.

Six psychological scientists representing different cultures and nationalities have been named inaugural APS Editorial Fellows.

APS launched the Fellows program to help scientists develop their skills as editors, with a goal of creating and sustaining a pipeline of diverse and representative journal editors. Two Fellows are assigned to each of three APS journals: Psychological Science ,  Clinical Psychological Science , and  Advances in Methods and Practices in Psychological Science ( AMPPS ) . Each Fellow is paired with an editor mentor at the journal who is available for consultation and discussion regarding any of the editorial tasks for the manuscripts assigned to the Fellow. 

“Our first cohort is up and running, and we received many outstanding applications,” said AMPPS Editor David A. Sbarra. “I believe this reflects a large desire across the field for people to gain a deeper understanding of the editorial process and journal workflows.”

Fellows will complete all the editorial tasks typically required of an Associate Editor, including completing initial evaluations of submitted manuscripts, selecting and inviting reviewers to evaluate the manuscripts, synthesizing reviews, and writing decision letters. They each will receive a stipend for their year-long fellowship.

Meet the first Editorial Fellows. 

Ivan Carbajal   Oregon State University 

Carbajal’s research interests focus on the impact of bilingualism and biculturalism on executive functioning among Latinx individuals. He is focused on developing a range of methodological and culturally sensitive research approaches involving understudied populations. His work has already identified and begun to address critical gaps in research involving bilingual Latinx individuals. Carbajal has served as a reviewer for several journals covering clinical and counseling psychology, teaching and learning, and social issues.

Leyla Loued-Khenissi  Lausanne University Hospital 

Loued-Khenissi is a cognitive neuroscientist focusing on predictive coding models in brain and behavior. Her expertise includes neuroimaging design, computational models, and statistical methods. She has lived in many countries representing a range of cultural practices and national income levels. Her experience living in some of the world’s most economically deprived countries drives her advocacy for inclusive research. Loued-Khenissi has served as a reviewer for journals in neuroscience, biology, and psychology. 

Clinical Psychological Science  

Chelsea Boccagno Harvard T. H. Chan School of Public Health Massachusetts General Hospital

As a first-generation college graduate from the Bronx, New York, Boccagno says she believes intersectional identities are overlooked in clinical science. She says she hopes her diverse research background across different fields (e.g., clinical science, epidemiology, social neuroscience) will help her strengthen her ability to evaluate research, select suitable reviewers, and write decision letters synthesizing unique perspectives. Boccagno uses causal inference methods on observational, ecological momentary assessment, and randomized control trial data sets to identify the most effective treatment strategies for suicide prevention. She also conducts behavioral studies and leverages social media data to examine how sense of self influences the ability to regulate emotions in clinical populations. She has served as an ad-hoc reviewer for several journals. 

Dieu Truong Sam Houston State University 

Truong’s research centers on intellectual and developmental disabilities, particularly autism and attention-deficit/hyperactivity disorder. She studies healthcare disparities in the autism community and how those disparities intersect with identities such as race, ethnicity, gender, and socioeconomic status. An immigrant from Vietnam, Truong’s work also extends to developing and evaluating culturally and linguistically appropriate measures for Southeast Asian families with autistic members. In academic publishing, she has experience in manuscript review and coordination, subscriber relations, and database maintenance.

Advances in Methods and Practices in Psychological Science ( AMPPS )  

Kongmeng Liew   University of Canterbury 

Liew applies computational methods to the study of culture and human psychology and has conducted his research within the Asia-Pacific region. He says he looks forward to bringing more geographic diversity to the AMPPS editorial team. Liew mines social media data, video-game statistics, streaming services, and other data sources and utilizes machine-learning approaches. He uses these methods to understand how and why cultures differ from each other and how mental health is expressed in online environments. Liew has reviewed for psychology and computational journals as well as workshops and conferences. 

Aishwarya Rajesh   Washington University in St. Louis 

Rajesh studies the intersection of stress, mood, and brain injury, with the aim of fostering treatment protocols and intervention models that reduce the risk of clinical psychological disorders. Her research aims to identify individual differences in brain morphology and their association with cognitive abilities and co-occurring biopsychosocial symptoms in traumatic brain injury. As a statistical consultant, Rajesh has mentored students and trainees of various minoritized identities and career stages, which she says has helped her communicate statistical language in approachable and empowering ways. 

Feedback on this article? Email  [email protected]  or login to comment.

APS regularly opens certain online articles for discussion on our website. Effective February 2021, you must be a logged-in APS member to post comments. By posting a comment, you agree to our Community Guidelines and the display of your profile information, including your name and affiliation. Any opinions, findings, conclusions, or recommendations present in article comments are those of the writers and do not necessarily reflect the views of APS or the article’s author. For more information, please see our Community Guidelines .

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APS Fellow Jennifer Richeson Named to White House Science Council

The Yale psychology professor has been appointed to an influential group charged with directly advising the president and the White House on science, technology, and innovation.

AAAS Names 10 Psychological Scientists as 2020 Fellows

Eight APS members and two APS Fellows are elected as 2020 Fellows.

APS Fellow Alison Gopnik Named Guggenheim Fellow

Alison Gopnik, an APS Fellow who is recognized internationally for her study of children’s learning and development, has been selected as a 2020 Guggenheim Fellow.

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Home » Research Methods – Types, Examples and Guide

Research Methods – Types, Examples and Guide

Table of Contents

Research Methods

Definition:

Research Methods refer to the techniques, procedures, and processes used by researchers to collect , analyze, and interpret data in order to answer research questions or test hypotheses. The methods used in research can vary depending on the research questions, the type of data that is being collected, and the research design.

Types of Research Methods

Types of Research Methods are as follows:

Qualitative research Method

Qualitative research methods are used to collect and analyze non-numerical data. This type of research is useful when the objective is to explore the meaning of phenomena, understand the experiences of individuals, or gain insights into complex social processes. Qualitative research methods include interviews, focus groups, ethnography, and content analysis.

Quantitative Research Method

Quantitative research methods are used to collect and analyze numerical data. This type of research is useful when the objective is to test a hypothesis, determine cause-and-effect relationships, and measure the prevalence of certain phenomena. Quantitative research methods include surveys, experiments, and secondary data analysis.

Mixed Method Research

Mixed Method Research refers to the combination of both qualitative and quantitative research methods in a single study. This approach aims to overcome the limitations of each individual method and to provide a more comprehensive understanding of the research topic. This approach allows researchers to gather both quantitative data, which is often used to test hypotheses and make generalizations about a population, and qualitative data, which provides a more in-depth understanding of the experiences and perspectives of individuals.

Key Differences Between Research Methods

The following Table shows the key differences between Quantitative, Qualitative and Mixed Research Methods

Examples of Research Methods

Examples of Research Methods are as follows:

Qualitative Research Example:

A researcher wants to study the experience of cancer patients during their treatment. They conduct in-depth interviews with patients to gather data on their emotional state, coping mechanisms, and support systems.

Quantitative Research Example:

A company wants to determine the effectiveness of a new advertisement campaign. They survey a large group of people, asking them to rate their awareness of the product and their likelihood of purchasing it.

Mixed Research Example:

A university wants to evaluate the effectiveness of a new teaching method in improving student performance. They collect both quantitative data (such as test scores) and qualitative data (such as feedback from students and teachers) to get a complete picture of the impact of the new method.

Applications of Research Methods

Research methods are used in various fields to investigate, analyze, and answer research questions. Here are some examples of how research methods are applied in different fields:

• Psychology : Research methods are widely used in psychology to study human behavior, emotions, and mental processes. For example, researchers may use experiments, surveys, and observational studies to understand how people behave in different situations, how they respond to different stimuli, and how their brains process information.
• Sociology : Sociologists use research methods to study social phenomena, such as social inequality, social change, and social relationships. Researchers may use surveys, interviews, and observational studies to collect data on social attitudes, beliefs, and behaviors.
• Medicine : Research methods are essential in medical research to study diseases, test new treatments, and evaluate their effectiveness. Researchers may use clinical trials, case studies, and laboratory experiments to collect data on the efficacy and safety of different medical treatments.
• Education : Research methods are used in education to understand how students learn, how teachers teach, and how educational policies affect student outcomes. Researchers may use surveys, experiments, and observational studies to collect data on student performance, teacher effectiveness, and educational programs.
• Business : Research methods are used in business to understand consumer behavior, market trends, and business strategies. Researchers may use surveys, focus groups, and observational studies to collect data on consumer preferences, market trends, and industry competition.
• Environmental science : Research methods are used in environmental science to study the natural world and its ecosystems. Researchers may use field studies, laboratory experiments, and observational studies to collect data on environmental factors, such as air and water quality, and the impact of human activities on the environment.
• Political science : Research methods are used in political science to study political systems, institutions, and behavior. Researchers may use surveys, experiments, and observational studies to collect data on political attitudes, voting behavior, and the impact of policies on society.

Purpose of Research Methods

Research methods serve several purposes, including:

• Identify research problems: Research methods are used to identify research problems or questions that need to be addressed through empirical investigation.
• Develop hypotheses: Research methods help researchers develop hypotheses, which are tentative explanations for the observed phenomenon or relationship.
• Collect data: Research methods enable researchers to collect data in a systematic and objective way, which is necessary to test hypotheses and draw meaningful conclusions.
• Analyze data: Research methods provide tools and techniques for analyzing data, such as statistical analysis, content analysis, and discourse analysis.
• Test hypotheses: Research methods allow researchers to test hypotheses by examining the relationships between variables in a systematic and controlled manner.
• Draw conclusions : Research methods facilitate the drawing of conclusions based on empirical evidence and help researchers make generalizations about a population based on their sample data.
• Enhance understanding: Research methods contribute to the development of knowledge and enhance our understanding of various phenomena and relationships, which can inform policy, practice, and theory.

When to Use Research Methods

Research methods are used when you need to gather information or data to answer a question or to gain insights into a particular phenomenon.

Here are some situations when research methods may be appropriate:

• To investigate a problem : Research methods can be used to investigate a problem or a research question in a particular field. This can help in identifying the root cause of the problem and developing solutions.
• To gather data: Research methods can be used to collect data on a particular subject. This can be done through surveys, interviews, observations, experiments, and more.
• To evaluate programs : Research methods can be used to evaluate the effectiveness of a program, intervention, or policy. This can help in determining whether the program is meeting its goals and objectives.
• To explore new areas : Research methods can be used to explore new areas of inquiry or to test new hypotheses. This can help in advancing knowledge in a particular field.
• To make informed decisions : Research methods can be used to gather information and data to support informed decision-making. This can be useful in various fields such as healthcare, business, and education.

Advantages of Research Methods

Research methods provide several advantages, including:

• Objectivity : Research methods enable researchers to gather data in a systematic and objective manner, minimizing personal biases and subjectivity. This leads to more reliable and valid results.
• Replicability : A key advantage of research methods is that they allow for replication of studies by other researchers. This helps to confirm the validity of the findings and ensures that the results are not specific to the particular research team.
• Generalizability : Research methods enable researchers to gather data from a representative sample of the population, allowing for generalizability of the findings to a larger population. This increases the external validity of the research.
• Precision : Research methods enable researchers to gather data using standardized procedures, ensuring that the data is accurate and precise. This allows researchers to make accurate predictions and draw meaningful conclusions.
• Efficiency : Research methods enable researchers to gather data efficiently, saving time and resources. This is especially important when studying large populations or complex phenomena.
• Innovation : Research methods enable researchers to develop new techniques and tools for data collection and analysis, leading to innovation and advancement in the field.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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Most U.S. parents pass along their religion and politics to their children

Which are American parents more likely to pass along to their kids – their religion or their politics?

Turns out, most parents pass along both kinds of affiliation, and they do so at similarly high rates, according to a new analysis of several Pew Research Center surveys.

This analysis examines how much American parents care about passing on their religious and political affiliations to their children and how effective they are at doing so, based on three Pew Research Center surveys conducted between 2015 and 2022.

To see whether parents place more importance on raising their children to carry on their religious beliefs or their political beliefs, we surveyed 3,757 parents with children younger than 18 from Sept. 20-Oct. 2, 2022. Most of the parents who took part are members of the Center’s American Trends Panel (ATP), an online survey panel recruited through national, random sampling of residential addresses. The survey also included an oversample of Black, Hispanic and Asian parents from Ipsos’ KnowledgePanel, another online panel recruited primarily through national, random sampling of residential addresses. Here are the questions used in the 2022 parenting survey , along with responses, and its methodology .

To see whether parents are more successful at passing on their religious affiliation or their U.S. political party identification, we looked at a survey of 1,811 pairs of parents and their teenage children. Each pair consisted of one parent and one teen ages 13 to 17. The survey was designed by Pew Research Center and conducted online from March 29-April 14, 2019, by Ipsos, drawing on households in its KnowledgePanel. Here are the questions used in the 2019 survey of parents and teens , along with responses, and its methodology . 

This may be surprising, considering that parents are more likely to prioritize the transmission of their religious views than their political views. In a fall survey by the Center , 35% of U.S. parents said it was extremely or very important that their kids grow up to share their religious views, while fewer than half as many (16%) said the same about their political views. Notably, parents saw both religious and political transmission as much less important than passing along other values, such as being honest and ethical, hardworking, and ambitious.

Still, people in some religious groups did place a high priority on raising their kids to carry on their faith. For example, 70% of White born-again or evangelical Protestant parents said it was extremely or very important for their children to hold similar religious beliefs, compared with just 8% of religiously unaffiliated parents.

As every parent knows, though, wanting a child to do something is not the same as getting a child to do something. So how successful are American parents, overall, at transmitting their religious and political affiliations to their children?

One way of answering the question is to compare U.S. teenagers and their parents. That’s what we did in a 2019 survey of more than 1,800 teens ages 13 to 17 , each of whom was interviewed along with one parent. In most cases, the parent was a biological mother or father, but sometimes it was an adoptive parent, stepparent, foster parent, grandparent or other guardian.

The survey indicated that the vast majority of parents with teens have passed along their political loyalties. Roughly eight-in-ten parents who were Republican or leaned toward the Republican Party (81%) had teens who also identified as Republicans or leaned that way. And about nine-in-ten parents who were Democratic or leaned Democratic (89%) had teens who described themselves the same way.

The transmission of religion through American families appears to be similarly efficient. In the same 2019 survey, 82% of Protestant parents had teens who also identified as Protestant, 81% of Catholic parents had Catholic teens, and 86% of religiously unaffiliated parents – those who described themselves as atheist, agnostic or nothing in particular – had teens who were also “nones.”

The survey sample was not large enough to estimate transmission rates among parents who belong to non-Christian religious groups, such as Jews and Muslims. But there were enough parents from some Christian subgroups to estimate their “success” at passing on their faith. Among evangelical Protestant parents of all races and ethnicities, for example, 80% had teens who identified as evangelicals, and an additional 7% had teens who identified with other Protestant traditions. Just 12% had teens who were unaffiliated and 1% had teens who were Catholic.

In other words, even though evangelical Protestants place much higher importance on passing their religion to their children than religiously unaffiliated parents do, the two groups are about equally successful at actually doing so, at least through about age 17.

Still, many people switch religious affiliations or leave organized religion entirely between the ages of 18 and 29. So another way to gauge the transmission of religion is to look at how American adults describe the religion of the person or people who raised them, and then compare it with their own religious affiliation today. That’s what we did in another survey in 2015 .

The survey found that most people who were raised in a single religion – either by two parents of the same faith or by a single parent – retained that religion. Roughly eight-in-ten of those raised Protestant (79%) were still Protestant. About six-in-ten of those raised Catholic were still Catholic (62%), and an identical proportion of those raised with no religious affiliation were still unaffiliated (62%).

There was much more flux among the roughly one-in-five U.S. adults (21%) who were raised in interfaith households. Among those raised by two people, one of whom was Protestant and the other unaffiliated, the Protestant identity proved to be “stickier”: 56% identified as Protestant, while 34% were unaffiliated, 3% were Catholic, and 7% belonged to other religions.

Among those raised by two people, one of whom was Catholic and the other unaffiliated, 42% were unaffiliated in adulthood while 32% were Catholic, 20% were Protestant, and 5% identified with other religions. Meanwhile, among those who were brought up by two people, one Protestant and one Catholic, the outcome was close to a toss-up. In adulthood, 38% identified as Protestant, 29% were Catholic, 26% were unaffiliated, and 7% belonged to other religions.

Note: Here are the questions used in the 2019 survey of parents and teens , along with responses, and its methodology . 

• Family & Relationships
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• Religion & Politics
• Religious Identity & Affiliation

Alan Cooperman is director of religion research at Pew Research Center

Few East Asian adults believe women have an obligation to society to have children

Among parents with young adult children, some dads feel less connected to their kids than moms do, how teens and parents approach screen time, most east asian adults say men and women should share financial and caregiving duties, among young adults without children, men are more likely than women to say they want to be parents someday, most popular.

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