Tips for Reading Scholarly Journal Articles in Psychology
- Sections of Empirical Articles in Psychology
- Types of Articles and Papers in the Field of Psychology
- Formatting Papers in APA Style
- Finding Psychological Research
- Reading a Journal Article Exercise
Types of Articles
Authors report original research in which the observed outcomes and data that are gathered are numerically represented. The results are analyzed using statistical methods that rely on numerical properties. | |
Authors report original research in which the data and observed outcomes are communicated using natural language. One common type of qualitative research is the case study, in which researchers report on observations made while working closely with an individual, group, community, or other type of organization. | |
These types of articles combine both qualitative or quantitative methodologies. | |
Authors reproduce a study using the same methodology as a previous researcher. This is often done to confirm the results and conclusions made by prior researchers. This type of work is becoming more common, and the proliferation of replication studies highlight the importance of carefully describing how data are gathered and analyzed in the Method section of a study. | |
These articles can be either quantitative or qualitative. Meta-analysis refers to an article in which the author synthesizes findings from a group of related studies to draw a general conclusion. | |
Nearly all scholarly articles in the field of psychology include a literature review in the Introduction section, however, some articles are stand alone literature reviews. These articles are often written by experts in their area of research, and often the authors are invited by journal editors to write these articles, specifically because they are well known in their field. These articles are extremely useful when you are starting to research a concept. They will summarize research in a given area of interest, and they will identify short-comings, contradictions, gaps, and inconsistencies. These articles can be very helpful for identifying additional research for your own literature review and for finding new, original ways to investigate a concept. | |
These articles draw from existing research to advance a theory. Authors will often trace the development of a theory in order to expand or refine it. These articles do not follow the typical format of other scholarly articles in the field of psychology. | |
These articles focus on examining and refining methodologies that have been used to study phenomena. Authors do not typically collect original data for these articles, but will use existing data to illustrate methodological approaches to research. | |
There are a number of other types of psychology articles that don't fit into one of the categories above. They can include book reviews, brief reports, comments on previously published research, obituaries, letters to the editor, etc. These articles do not follow the typical format found with empirical research. |
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Academic and Writing Resources
- Writing Research Papers
Writing Research Papers
Information and resources.
One of the most important skills that you can learn in this department is how to write a research paper. For many of you, this will be in fulfillment of the Psychology B.S. Degree Research Paper requirement and/or the Psychology Honors Program Thesis requirement. You may also be writing an American Psychological Association (APA) formatted research paper for a Psychology course (such as a term paper or a summary of an empirical research paper). In some cases, such as for certain job, graduate school, and fellowship applications, you may be asked to provide a writing sample; a well-written research paper can be ideal for that purpose. The ability to write research papers is crucial for those who wish to pursue graduate school and research careers. To assist with these potential goals, we’ve gathered important information and helpful tips for you.
Should I Use a Specific Format and Style?
In the psychological sciences, it is common for research papers to adhere to the guidelines of the Publication Manual of the American Psychological Association (papers in other fields often use APA format as well). APA guidelines not only specify the types of sections that a research paper should have, but also the order of those sections, the manner in which scholarly sources should be cited in the text and in a separate references section, appropriate methods of reporting experimental and statistical results, the proper use of language, and other details. A well-written psychology research paper typically follows those guidelines .
How to Write a Successful Research Paper in APA Style
For more information on writing research papers in APA style, please checking out the following pages. Here you’ll find details on multiple aspects of the research paper writing process, ranging from how the paper should be structured to how to write more effectively.
- Structure and Format – the critical components of each section of an APA-formatted research paper (Introduction, Methods, and on), as well as how those sections should be formatted according to APA guidelines.
► Structure of Research Papers in APA Style
► Formatting Research Papers in APA Style
- Finding, Evaluating, and Citing References – how to search databases, how to obtain references, how to take notes when reading references, what types of references to use, how to include in-text citations, and how to create an APA-formatted reference list.
► Using Databases and Finding References
► What Types of References Are Appropriate for Research Papers?
► Evaluating References and Taking Notes
► Citing References in APA Style
- Writing a Literature Review, the Writing Process, and Improving Writing – how to write a literature review (an overview or summary of prior research, which is a common technique of introducing a research topic in the early sections of a paper), as well as recommendations for the writing process, improving clarity and conciseness, examples of adequate and better paragraphs, and links to resources on improving writing.
► Writing Literature Reviews
► Writing Process and Revising
► Improving Scientific Writing
- Avoiding Plagiarism – how to make sure that your research paper represents your writing and ideas and does not erroneously or unethically appropriate the works of others.
► Academic Integrity and Avoiding Plagiarism
- How-To Videos – for video guides to the different major sections of research papers, plus literature reviews and references, please see the following:
► Writing Research Papers Videos
In addition, you may be interested in downloading “ How to Write a Research Paper in APA Style ”, a comprehensive guide developed by Prof. Emma Geller, “ Tips for Writing APA Style Research Papers ” (a short summary of multiple aspects of the paper-writing process), and an Example B.S. Degree Research Paper written in APA Style .
Workshops and Downloadable Resources
- For in-person discussion of the process of writing research papers, please consider attending this department’s “Writing Research Papers” workshop (for dates and times, please check the undergraduate workshops calendar).
- How to Write APA Style Research Papers (a comprehensive guide) [ PDF ]
- Tips for Writing APA Style Research Papers (a brief summary) [ PDF ]
- Example APA Style Research Paper (for B.S. Degree – empirical research) [ PDF ]
- Example APA Style Research Paper (for B.S. Degree – literature review) [ PDF ]
Further Resources
- OASIS Language and Writing Program
- UCSD Writing Programs and Resources
- UCSD Muir College Writing Hub
- UCSD Writing Hub
External Resources
- APA Style Guide from the Purdue University Online Writing Lab (OWL)
- APA Tutorial on the Basics of APA Style
- EasyBib Guide to Writing and Citing in APA Format
- Formatting APA Style Papers in Microsoft Word
- How to Write an APA Style Research Paper from Hamilton University
- Online Learning: Plagiarism and Paraphrasing
- Sample APA Formatted Paper with Comments
- Sample APA Formatted Paper
- Tips for Writing a Paper in APA Style
- WikiHow Guide to Writing APA Research Papers
Back to top
- Research Paper Structure
- Formatting Research Papers
- Using Databases and Finding References
- What Types of References Are Appropriate?
- Evaluating References and Taking Notes
- Citing References
- Writing a Literature Review
- Writing Process and Revising
- Improving Scientific Writing
- Academic Integrity and Avoiding Plagiarism
- Writing Research Papers Videos
- Effective Studying
Psychology Guide for the Major
- Psychology Where to Start
- Research Worksheet
- Psychology Publications
- The Research Cycle
- Systematic Review This link opens in a new window
- Guide to the UMD Libraries This link opens in a new window
- Finding Books This link opens in a new window
- Finding Articles
- Advanced Searching Options and Tips
- Evaluating What You Find
- APA Citations, Writing, and Organization
- Reproducibility Crisis and Open Data
- Research Methods Resources
- Statistics & Analysis Resources
- Tests, Measures, and Assessments
- Analysis Software
- Diagnosis Tools and Reference
- Philosophy and Psychology
- Professional Associations
- Additional Resources & Assoc. Subjects
Click on each tab in the box below for more information about the most common types of Psychology and Behavioral Science publications, including some hallmark traits and benefits of each format. Please contact me, [email protected] , if you have any additional questions or would like some help finding useful material.
Most Common Types of Psychology and Behavioral Science Publications
- Scholarly Books vs. Popular Nonfiction
- Original Research Articles
- Meta Analysis, Literature Review, & Secondary Analysis
- Systematic Review
- Society Communications
- Conference Proceedings
- Chapters in Scholarly Books
- Book Reviews
- Popular Psychology Articles
- Clinical Case Studies
- Field Studies
- Mathematical Model
Like an original research article, a scholarly book is characterized by its academic content and its authoritative author (usually a professor or academic researcher. A scholarly book typically - but not universally - represents a study or a line of work that investigates a hypothesis and illustrates the conclusions and results. This can be a theoretical idea, a proposal, an experiment, and other such academic activities.
This scholarly material sits in contrast to a work of popular science or psychology, often simplified as pop-psyc and can be easily found in book shops and airports.
Importantly, however, one shouldn't get the idea that popular science is a bad thing. Popular science writing is an important public good and when done well can help enlighten society with important scholarly ideas in a more digestible form. The clarity of the writing and the nature of the work should often be praised and not sneered at. For a research paper, however, these sources are typically inappropriate due to their lack of rigor and, importance, the lack of peer-review .
Scholarly Science Books | Popular Science Books | |
Purpose | ||
Cited Sources | ||
Author's Authority | ||
Language | ||
Publisher |
An original experiment conducted and reported by the principal researchers. Typically published in a scientific journal such as Evolutionary Psychology or The Journal of Experimental Psychology .
An example of this would be:
Dr. Jane Smith and Dr. Vicoria Wong conducted a double-blind study in which an experimental drug therapy was tested with the aim of having a significant reduction in the frequency and severity of their focus group's number of acute anxiety episodes. This study was published in the Journal of Social & Clinical Psychology in 2014 and outlined their review of of previous related literature (literature review), their materials and methods, a presentation of their results, a discussion of heir findings, a summary conclusion, a list of their references, and an appendix with a representation of their data.
Associated terms:
- Experimental Replication:
- Follow-up Study:
- Longitudinal Study:
- Prospective Study:
- Retrospective Study:
The main difference between a literature review and an original research article is that a literature review is surveying the existing literature of a topic and exploring the existing theories, hypotheses, studies, trials, etc. and trying to make clear the conversation that is told through the research community. A literature review can and will also be a component of an empirical study, but in this example, the review will be acutely focused on the topic that is being studied and will not, generally, be a holistic review of the larger issues and confounding elements.
- An original research article (empirical study) recounts the methods and results of new research, typically an experiment conducted and reported.
- A literature review is a survey of multiple studies and other writings centered around a field of study. This can illustrate the conversation and the debate within a field and it's status quo .
- A Meta-Analysis is a very important component of scientific, and especially health science literature. A meta-analysis looks to collate and analyze a body of statistical information in order to find the truth despite individual studies and the discrepancies between them. A meta-analysis will investigate particular measures and determine a statistical truth and a story that may remain hidden or confused if not determined correctly.
For more information on developing a systematic review, please see our detailed page outlining the processes and to learn more about our services around systematic review, http://lib.guides.umd.edu/SR
Society publications are one of the most misleading and confusing types of publications for those unfamiliar with the varied forms of scholarly publications. This confusion is made worse by the fact that many databases will include society publications in its list of journal articles with little or no comment to help distinguish between the two.
A society publication is essentially a trade magazine that is commissioned and distributed by a particular professional association (ex. APA), company, sector (ex. psychopharmacological), lobby group, interest group, and more. These are interesting places to learn about the field, but they are rarely peer reviewed and are not typically the place researchers will formally share their work. These publications are often written by journalists and will likely cover recent advancement and studies, but will not be the deep and authoritative source for this information. Because they cover the topic, however, they may be a good place to start if you're investigating a new study or line of research. These publications will also be an interesting window into the discipline you're thinking of entering.
Conference proceedings are sometime difficult to distinguish from other forms of scholarly publications. This is especially true in their electronic form as individual papers, presentations, and meetings are often culled from their context and presented as a stand-alone item in the same way that journal articles are typically presented though the databases as individual items distinct from their journal context. Proceedings are importnat, however, because a lot of the work towards new directions in research and debates among scholars can tell you a lot about both individual scholars (on whose work you may be relying in other contexts) and about the field at large. In other words, this can tell you where the ideas you're researching fall into the general academic discussion and the reception of individual notions from researchers. Like with journals, conferences are often were the heavy lifting in a discipline takes place.
Essays are a little tricky to determine if you are not well versed in the literature. In fact, essays tend to share many of the characteristics of peer reviewed articles, but do not typically reflect the reporting of a direct experiment or new research. Essays as they are defined are the presentation of an argument and therefore tend towards the obviously persuasive. In other words, the author is using known works and research to highlight a particular point and is focused on the established and embellishment of ideas relevant in their field. In Psychology, essays are important as they tend to provide insight into an author's perspective and theoretical grounding. Additionally, essays are a space where new theories are developed and argued. Early insights in Psychology from the likes of Freud, Jung, etc. were a mixture of essay and case study with rather blurred lines. Freud, for example, wrote extended essays that contained elements from his clinical work such as Moses and Monotheism or Totem and Taboo. This distinction can be difficult for students new to the disciplines as often these essays are published along-side studies in journals. Essays can also be found in professional magazines, newsletters, and high-credentialed popular sources such as the New York Review of Books and the Times Literary Supplement (among others).
Chapters in a scholarly book range from the formal presentation of an experiment, theory and discussion, field study, scholarly essays, and more. Scholarly books often stem from conferences when organizers feel new work has been brought to the fore and deserves a wider audience. Typically the chapters represent formal studies arranged around a central theme and is arranged by how the authors fit within this area of study. These books are often exciting as they tend to represent a new direction in a field and often allow authors to experiment with new theories and methods along with colleagues working on similar projects.
Scholars often communicate (in text form) through citations and reviews. Reviews are therefore great for two purposes directly 1) getting a concise summary of a book usually including an analysis of the central thesis and presentation of data and 2) a sense of where both the author being reviewed sits within the field as well as the reviewers' approach to theoretical models and analysis. The latter is especially important if you are trying to understand how a particular researcher or clinician views their field and the approach to practice.
Popular articles are typically found in general interest magazines like Popular Science, Psychology Today, etc. and reflect two things most readily: 1) the public interest in the topic and 2) a plain-English explanation of the content and research. This can be particularly helpful when first first getting into a research area.
Clinical trials and other interventions can include pharmacological (drugs), neurological and physiological measures, and much more. It is crucial to note with trials both the investigators and the funding agencies responsible for the studies as sometimes trials are influenced by stakeholders seeking particular results as opposed to a commitment to pure science. This is not typical, but examples can be found and it is something to be aware of. Additionally, as with other empirical studies, investigate the methods and the literature for reproducibility (see the tab on the "reproducibility crisis" and open data in the left-hand menu).
Field studies owe more to the fields of sociology, public health, and anthropology, but are crucial measurements for understanding societal trends and anomalous occurrences in a given population. For example, a field study looking at the rates of depression amongst American Indians may not seek a treatment, but looks to investigate the phenomenon from both a qualitative and qualitative perspective by gathering human data through interviews, and similar techniques.
Psychology is an increasingly quantitative field of research and researchers are defining new ways of gathering and analysis data. As such, researchers build, modify, and upend statistical models for analysis and create the foundations for new work. These models are often published and useable in programs such as R or SPSS (more in the statistics and the Analysis software tabs).
Anatomy of a Research Article
(click on the image for an interactive view)
(Courtesy of NCSU Libraries under the Creative Commons License )
- Anatomy of a Research Paper This resource (courtesy of Tulane University Libraries) gives a terrific explanation and illustration of all the critical parts of a research article. Longer format than the graphical explanation above, but gives a terrific model of what to look for and how to model your own work.
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The Use of Research Methods in Psychological Research: A Systematised Review
Salomé elizabeth scholtz.
1 Community Psychosocial Research (COMPRES), School of Psychosocial Health, North-West University, Potchefstroom, South Africa
Werner de Klerk
Leon t. de beer.
2 WorkWell Research Institute, North-West University, Potchefstroom, South Africa
Research methods play an imperative role in research quality as well as educating young researchers, however, the application thereof is unclear which can be detrimental to the field of psychology. Therefore, this systematised review aimed to determine what research methods are being used, how these methods are being used and for what topics in the field. Our review of 999 articles from five journals over a period of 5 years indicated that psychology research is conducted in 10 topics via predominantly quantitative research methods. Of these 10 topics, social psychology was the most popular. The remainder of the conducted methodology is described. It was also found that articles lacked rigour and transparency in the used methodology which has implications for replicability. In conclusion this article, provides an overview of all reported methodologies used in a sample of psychology journals. It highlights the popularity and application of methods and designs throughout the article sample as well as an unexpected lack of rigour with regard to most aspects of methodology. Possible sample bias should be considered when interpreting the results of this study. It is recommended that future research should utilise the results of this study to determine the possible impact on the field of psychology as a science and to further investigation into the use of research methods. Results should prompt the following future research into: a lack or rigour and its implication on replication, the use of certain methods above others, publication bias and choice of sampling method.
Introduction
Psychology is an ever-growing and popular field (Gough and Lyons, 2016 ; Clay, 2017 ). Due to this growth and the need for science-based research to base health decisions on (Perestelo-Pérez, 2013 ), the use of research methods in the broad field of psychology is an essential point of investigation (Stangor, 2011 ; Aanstoos, 2014 ). Research methods are therefore viewed as important tools used by researchers to collect data (Nieuwenhuis, 2016 ) and include the following: quantitative, qualitative, mixed method and multi method (Maree, 2016 ). Additionally, researchers also employ various types of literature reviews to address research questions (Grant and Booth, 2009 ). According to literature, what research method is used and why a certain research method is used is complex as it depends on various factors that may include paradigm (O'Neil and Koekemoer, 2016 ), research question (Grix, 2002 ), or the skill and exposure of the researcher (Nind et al., 2015 ). How these research methods are employed is also difficult to discern as research methods are often depicted as having fixed boundaries that are continuously crossed in research (Johnson et al., 2001 ; Sandelowski, 2011 ). Examples of this crossing include adding quantitative aspects to qualitative studies (Sandelowski et al., 2009 ), or stating that a study used a mixed-method design without the study having any characteristics of this design (Truscott et al., 2010 ).
The inappropriate use of research methods affects how students and researchers improve and utilise their research skills (Scott Jones and Goldring, 2015 ), how theories are developed (Ngulube, 2013 ), and the credibility of research results (Levitt et al., 2017 ). This, in turn, can be detrimental to the field (Nind et al., 2015 ), journal publication (Ketchen et al., 2008 ; Ezeh et al., 2010 ), and attempts to address public social issues through psychological research (Dweck, 2017 ). This is especially important given the now well-known replication crisis the field is facing (Earp and Trafimow, 2015 ; Hengartner, 2018 ).
Due to this lack of clarity on method use and the potential impact of inept use of research methods, the aim of this study was to explore the use of research methods in the field of psychology through a review of journal publications. Chaichanasakul et al. ( 2011 ) identify reviewing articles as the opportunity to examine the development, growth and progress of a research area and overall quality of a journal. Studies such as Lee et al. ( 1999 ) as well as Bluhm et al. ( 2011 ) review of qualitative methods has attempted to synthesis the use of research methods and indicated the growth of qualitative research in American and European journals. Research has also focused on the use of research methods in specific sub-disciplines of psychology, for example, in the field of Industrial and Organisational psychology Coetzee and Van Zyl ( 2014 ) found that South African publications tend to consist of cross-sectional quantitative research methods with underrepresented longitudinal studies. Qualitative studies were found to make up 21% of the articles published from 1995 to 2015 in a similar study by O'Neil and Koekemoer ( 2016 ). Other methods in health psychology, such as Mixed methods research have also been reportedly growing in popularity (O'Cathain, 2009 ).
A broad overview of the use of research methods in the field of psychology as a whole is however, not available in the literature. Therefore, our research focused on answering what research methods are being used, how these methods are being used and for what topics in practice (i.e., journal publications) in order to provide a general perspective of method used in psychology publication. We synthesised the collected data into the following format: research topic [areas of scientific discourse in a field or the current needs of a population (Bittermann and Fischer, 2018 )], method [data-gathering tools (Nieuwenhuis, 2016 )], sampling [elements chosen from a population to partake in research (Ritchie et al., 2009 )], data collection [techniques and research strategy (Maree, 2016 )], and data analysis [discovering information by examining bodies of data (Ktepi, 2016 )]. A systematised review of recent articles (2013 to 2017) collected from five different journals in the field of psychological research was conducted.
Grant and Booth ( 2009 ) describe systematised reviews as the review of choice for post-graduate studies, which is employed using some elements of a systematic review and seldom more than one or two databases to catalogue studies after a comprehensive literature search. The aspects used in this systematised review that are similar to that of a systematic review were a full search within the chosen database and data produced in tabular form (Grant and Booth, 2009 ).
Sample sizes and timelines vary in systematised reviews (see Lowe and Moore, 2014 ; Pericall and Taylor, 2014 ; Barr-Walker, 2017 ). With no clear parameters identified in the literature (see Grant and Booth, 2009 ), the sample size of this study was determined by the purpose of the sample (Strydom, 2011 ), and time and cost constraints (Maree and Pietersen, 2016 ). Thus, a non-probability purposive sample (Ritchie et al., 2009 ) of the top five psychology journals from 2013 to 2017 was included in this research study. Per Lee ( 2015 ) American Psychological Association (APA) recommends the use of the most up-to-date sources for data collection with consideration of the context of the research study. As this research study focused on the most recent trends in research methods used in the broad field of psychology, the identified time frame was deemed appropriate.
Psychology journals were only included if they formed part of the top five English journals in the miscellaneous psychology domain of the Scimago Journal and Country Rank (Scimago Journal & Country Rank, 2017 ). The Scimago Journal and Country Rank provides a yearly updated list of publicly accessible journal and country-specific indicators derived from the Scopus® database (Scopus, 2017b ) by means of the Scimago Journal Rank (SJR) indicator developed by Scimago from the algorithm Google PageRank™ (Scimago Journal & Country Rank, 2017 ). Scopus is the largest global database of abstracts and citations from peer-reviewed journals (Scopus, 2017a ). Reasons for the development of the Scimago Journal and Country Rank list was to allow researchers to assess scientific domains, compare country rankings, and compare and analyse journals (Scimago Journal & Country Rank, 2017 ), which supported the aim of this research study. Additionally, the goals of the journals had to focus on topics in psychology in general with no preference to specific research methods and have full-text access to articles.
The following list of top five journals in 2018 fell within the abovementioned inclusion criteria (1) Australian Journal of Psychology, (2) British Journal of Psychology, (3) Europe's Journal of Psychology, (4) International Journal of Psychology and lastly the (5) Journal of Psychology Applied and Interdisciplinary.
Journals were excluded from this systematised review if no full-text versions of their articles were available, if journals explicitly stated a publication preference for certain research methods, or if the journal only published articles in a specific discipline of psychological research (for example, industrial psychology, clinical psychology etc.).
The researchers followed a procedure (see Figure 1 ) adapted from that of Ferreira et al. ( 2016 ) for systematised reviews. Data collection and categorisation commenced on 4 December 2017 and continued until 30 June 2019. All the data was systematically collected and coded manually (Grant and Booth, 2009 ) with an independent person acting as co-coder. Codes of interest included the research topic, method used, the design used, sampling method, and methodology (the method used for data collection and data analysis). These codes were derived from the wording in each article. Themes were created based on the derived codes and checked by the co-coder. Lastly, these themes were catalogued into a table as per the systematised review design.
Systematised review procedure.
According to Johnston et al. ( 2019 ), “literature screening, selection, and data extraction/analyses” (p. 7) are specifically tailored to the aim of a review. Therefore, the steps followed in a systematic review must be reported in a comprehensive and transparent manner. The chosen systematised design adhered to the rigour expected from systematic reviews with regard to full search and data produced in tabular form (Grant and Booth, 2009 ). The rigorous application of the systematic review is, therefore discussed in relation to these two elements.
Firstly, to ensure a comprehensive search, this research study promoted review transparency by following a clear protocol outlined according to each review stage before collecting data (Johnston et al., 2019 ). This protocol was similar to that of Ferreira et al. ( 2016 ) and approved by three research committees/stakeholders and the researchers (Johnston et al., 2019 ). The eligibility criteria for article inclusion was based on the research question and clearly stated, and the process of inclusion was recorded on an electronic spreadsheet to create an evidence trail (Bandara et al., 2015 ; Johnston et al., 2019 ). Microsoft Excel spreadsheets are a popular tool for review studies and can increase the rigour of the review process (Bandara et al., 2015 ). Screening for appropriate articles for inclusion forms an integral part of a systematic review process (Johnston et al., 2019 ). This step was applied to two aspects of this research study: the choice of eligible journals and articles to be included. Suitable journals were selected by the first author and reviewed by the second and third authors. Initially, all articles from the chosen journals were included. Then, by process of elimination, those irrelevant to the research aim, i.e., interview articles or discussions etc., were excluded.
To ensure rigourous data extraction, data was first extracted by one reviewer, and an independent person verified the results for completeness and accuracy (Johnston et al., 2019 ). The research question served as a guide for efficient, organised data extraction (Johnston et al., 2019 ). Data was categorised according to the codes of interest, along with article identifiers for audit trails such as authors, title and aims of articles. The categorised data was based on the aim of the review (Johnston et al., 2019 ) and synthesised in tabular form under methods used, how these methods were used, and for what topics in the field of psychology.
The initial search produced a total of 1,145 articles from the 5 journals identified. Inclusion and exclusion criteria resulted in a final sample of 999 articles ( Figure 2 ). Articles were co-coded into 84 codes, from which 10 themes were derived ( Table 1 ).
Journal article frequency.
Codes used to form themes (research topics).
Social Psychology | 31 | Aggression SP, Attitude SP, Belief SP, Child abuse SP, Conflict SP, Culture SP, Discrimination SP, Economic, Family illness, Family, Group, Help, Immigration, Intergeneration, Judgement, Law, Leadership, Marriage SP, Media, Optimism, Organisational and Social justice, Parenting SP, Politics, Prejudice, Relationships, Religion, Romantic Relationships SP, Sex and attraction, Stereotype, Violence, Work |
Experimental Psychology | 17 | Anxiety, stress and PTSD, Coping, Depression, Emotion, Empathy, Facial research, Fear and threat, Happiness, Humor, Mindfulness, Mortality, Motivation and Achievement, Perception, Rumination, Self, Self-efficacy |
Cognitive Psychology | 12 | Attention, Cognition, Decision making, Impulse, Intelligence, Language, Math, Memory, Mental, Number, Problem solving, Reading |
Health Psychology | 7 | Addiction, Body, Burnout, Health, Illness (Health Psychology), Sleep (Health Psychology), Suicide and Self-harm |
Physiological Psychology | 6 | Gender, Health (Physiological psychology), Illness (Physiological psychology), Mood disorders, Sleep (Physiological psychology), Visual research |
Developmental Psychology | 3 | Attachment, Development, Old age |
Personality | 3 | Machiavellian, Narcissism, Personality |
Psychological Psychology | 3 | Programme, Psychology practice, Theory |
Education and Learning | 1 | Education and Learning |
Psychometrics | 1 | Measure |
Code Total | 84 |
These 10 themes represent the topic section of our research question ( Figure 3 ). All these topics except, for the final one, psychological practice , were found to concur with the research areas in psychology as identified by Weiten ( 2010 ). These research areas were chosen to represent the derived codes as they provided broad definitions that allowed for clear, concise categorisation of the vast amount of data. Article codes were categorised under particular themes/topics if they adhered to the research area definitions created by Weiten ( 2010 ). It is important to note that these areas of research do not refer to specific disciplines in psychology, such as industrial psychology; but to broader fields that may encompass sub-interests of these disciplines.
Topic frequency (international sample).
In the case of developmental psychology , researchers conduct research into human development from childhood to old age. Social psychology includes research on behaviour governed by social drivers. Researchers in the field of educational psychology study how people learn and the best way to teach them. Health psychology aims to determine the effect of psychological factors on physiological health. Physiological psychology , on the other hand, looks at the influence of physiological aspects on behaviour. Experimental psychology is not the only theme that uses experimental research and focuses on the traditional core topics of psychology (for example, sensation). Cognitive psychology studies the higher mental processes. Psychometrics is concerned with measuring capacity or behaviour. Personality research aims to assess and describe consistency in human behaviour (Weiten, 2010 ). The final theme of psychological practice refers to the experiences, techniques, and interventions employed by practitioners, researchers, and academia in the field of psychology.
Articles under these themes were further subdivided into methodologies: method, sampling, design, data collection, and data analysis. The categorisation was based on information stated in the articles and not inferred by the researchers. Data were compiled into two sets of results presented in this article. The first set addresses the aim of this study from the perspective of the topics identified. The second set of results represents a broad overview of the results from the perspective of the methodology employed. The second set of results are discussed in this article, while the first set is presented in table format. The discussion thus provides a broad overview of methods use in psychology (across all themes), while the table format provides readers with in-depth insight into methods used in the individual themes identified. We believe that presenting the data from both perspectives allow readers a broad understanding of the results. Due a large amount of information that made up our results, we followed Cichocka and Jost ( 2014 ) in simplifying our results. Please note that the numbers indicated in the table in terms of methodology differ from the total number of articles. Some articles employed more than one method/sampling technique/design/data collection method/data analysis in their studies.
What follows is the results for what methods are used, how these methods are used, and which topics in psychology they are applied to . Percentages are reported to the second decimal in order to highlight small differences in the occurrence of methodology.
Firstly, with regard to the research methods used, our results show that researchers are more likely to use quantitative research methods (90.22%) compared to all other research methods. Qualitative research was the second most common research method but only made up about 4.79% of the general method usage. Reviews occurred almost as much as qualitative studies (3.91%), as the third most popular method. Mixed-methods research studies (0.98%) occurred across most themes, whereas multi-method research was indicated in only one study and amounted to 0.10% of the methods identified. The specific use of each method in the topics identified is shown in Table 2 and Figure 4 .
Research methods in psychology.
Quantitative | 401 | 162 | 69 | 60 | 52 | 52 | 48 | 28 | 38 | 13 |
Qualitative | 28 | 4 | 1 | 0 | 5 | 2 | 3 | 5 | 0 | 1 |
Review | 11 | 5 | 2 | 0 | 3 | 4 | 1 | 13 | 0 | 1 |
Mixed Methods | 7 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | 0 | 0 |
Multi-method | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
Total | 447 | 171 | 72 | 60 | 61 | 58 | 53 | 47 | 39 | 15 |
Research method frequency in topics.
Secondly, in the case of how these research methods are employed , our study indicated the following.
Sampling −78.34% of the studies in the collected articles did not specify a sampling method. From the remainder of the studies, 13 types of sampling methods were identified. These sampling methods included broad categorisation of a sample as, for example, a probability or non-probability sample. General samples of convenience were the methods most likely to be applied (10.34%), followed by random sampling (3.51%), snowball sampling (2.73%), and purposive (1.37%) and cluster sampling (1.27%). The remainder of the sampling methods occurred to a more limited extent (0–1.0%). See Table 3 and Figure 5 for sampling methods employed in each topic.
Sampling use in the field of psychology.
Not stated | 331 | 153 | 45 | 57 | 49 | 43 | 43 | 38 | 31 | 14 |
Convenience sampling | 55 | 8 | 10 | 1 | 6 | 8 | 9 | 2 | 6 | 1 |
Random sampling | 15 | 3 | 9 | 1 | 2 | 2 | 0 | 2 | 1 | 1 |
Snowball sampling | 14 | 4 | 4 | 1 | 2 | 0 | 0 | 3 | 0 | 0 |
Purposive sampling | 6 | 0 | 2 | 0 | 0 | 2 | 0 | 3 | 1 | 0 |
Cluster sampling | 8 | 1 | 2 | 0 | 0 | 2 | 0 | 0 | 0 | 0 |
Stratified sampling | 4 | 1 | 2 | 0 | 1 | 1 | 0 | 0 | 0 | 0 |
Non-probability sampling | 4 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
Probability sampling | 3 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Quota sampling | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Criterion sampling | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Self-selection sampling | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Unsystematic sampling | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Total | 443 | 172 | 76 | 60 | 60 | 58 | 52 | 48 | 40 | 16 |
Sampling method frequency in topics.
Designs were categorised based on the articles' statement thereof. Therefore, it is important to note that, in the case of quantitative studies, non-experimental designs (25.55%) were often indicated due to a lack of experiments and any other indication of design, which, according to Laher ( 2016 ), is a reasonable categorisation. Non-experimental designs should thus be compared with experimental designs only in the description of data, as it could include the use of correlational/cross-sectional designs, which were not overtly stated by the authors. For the remainder of the research methods, “not stated” (7.12%) was assigned to articles without design types indicated.
From the 36 identified designs the most popular designs were cross-sectional (23.17%) and experimental (25.64%), which concurred with the high number of quantitative studies. Longitudinal studies (3.80%), the third most popular design, was used in both quantitative and qualitative studies. Qualitative designs consisted of ethnography (0.38%), interpretative phenomenological designs/phenomenology (0.28%), as well as narrative designs (0.28%). Studies that employed the review method were mostly categorised as “not stated,” with the most often stated review designs being systematic reviews (0.57%). The few mixed method studies employed exploratory, explanatory (0.09%), and concurrent designs (0.19%), with some studies referring to separate designs for the qualitative and quantitative methods. The one study that identified itself as a multi-method study used a longitudinal design. Please see how these designs were employed in each specific topic in Table 4 , Figure 6 .
Design use in the field of psychology.
Experimental design | 82 | 82 | 3 | 60 | 10 | 12 | 8 | 6 | 4 | 3 |
Non-experimental design | 115 | 30 | 51 | 0 | 13 | 17 | 13 | 13 | 14 | 3 |
Cross-sectional design | 123 | 31 | 12 | 1 | 19 | 17 | 21 | 5 | 13 | 2 |
Correlational design | 56 | 12 | 3 | 0 | 10 | 2 | 2 | 0 | 4 | 2 |
Not stated | 37 | 7 | 3 | 0 | 4 | 2 | 4 | 14 | 1 | 3 |
Longitudinal design | 21 | 6 | 2 | 1 | 1 | 2 | 2 | 0 | 2 | 3 |
Quasi-experimental design | 4 | 1 | 0 | 0 | 0 | 0 | 2 | 1 | 0 | 0 |
Systematic review | 3 | 0 | 0 | 0 | 1 | 1 | 0 | 1 | 0 | 0 |
Cross-cultural design | 3 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 |
Descriptive design | 2 | 0 | 0 | 0 | 0 | 0 | 3 | 0 | 0 | 0 |
Ethnography | 4 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Literature review | 1 | 1 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 |
Interpretative Phenomenological Analysis (IPA) | 2 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 |
Narrative design | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 |
Case-control research design | 0 | 0 | 0 | 0 | 0 | 2 | 0 | 0 | 0 | 0 |
Concurrent data collection design | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 |
Grounded Theory | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 |
Narrative review | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 |
Auto-ethnography | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Case series evaluation | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 |
Case study | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Comprehensive review | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Descriptive-inferential | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
Explanatory sequential design | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Exploratory mixed-method | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 |
Grounded ethnographic design | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Historical cohort design | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Historical research | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 |
interpretivist approach | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 |
Meta-review | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 |
Prospective design | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Qualitative review | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 |
Qualitative systematic review | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 |
Short-term prospective design | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Total | 461 | 175 | 74 | 63 | 63 | 58 | 56 | 48 | 39 | 16 |
Design frequency in topics.
Data collection and analysis —data collection included 30 methods, with the data collection method most often employed being questionnaires (57.84%). The experimental task (16.56%) was the second most preferred collection method, which included established or unique tasks designed by the researchers. Cognitive ability tests (6.84%) were also regularly used along with various forms of interviewing (7.66%). Table 5 and Figure 7 represent data collection use in the various topics. Data analysis consisted of 3,857 occurrences of data analysis categorised into ±188 various data analysis techniques shown in Table 6 and Figures 1 – 7 . Descriptive statistics were the most commonly used (23.49%) along with correlational analysis (17.19%). When using a qualitative method, researchers generally employed thematic analysis (0.52%) or different forms of analysis that led to coding and the creation of themes. Review studies presented few data analysis methods, with most studies categorising their results. Mixed method and multi-method studies followed the analysis methods identified for the qualitative and quantitative studies included.
Data collection in the field of psychology.
Questionnaire | 364 | 113 | 65 | 42 | 40 | 51 | 39 | 24 | 37 | 11 |
Experimental task | 68 | 66 | 3 | 52 | 9 | 5 | 11 | 5 | 5 | 1 |
Cognitive ability test | 9 | 57 | 1 | 12 | 6 | 1 | 5 | 1 | 1 | 0 |
Physiological measure | 3 | 12 | 1 | 6 | 2 | 5 | 3 | 0 | 1 | 0 |
Interview | 19 | 3 | 0 | 1 | 3 | 0 | 2 | 2 | 0 | 1 |
Online scholarly literature | 10 | 4 | 0 | 0 | 3 | 4 | 0 | 10 | 0 | 0 |
Open-ended questions | 15 | 3 | 0 | 1 | 3 | 1 | 2 | 3 | 0 | 0 |
Semi-structured interviews | 10 | 3 | 0 | 0 | 3 | 2 | 1 | 2 | 0 | 1 |
Observation | 10 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 2 | 0 |
Documents | 5 | 1 | 1 | 0 | 0 | 0 | 0 | 1 | 2 | 0 |
Focus group | 6 | 1 | 2 | 0 | 1 | 0 | 0 | 0 | 0 | 0 |
Not stated | 2 | 1 | 1 | 0 | 0 | 0 | 1 | 4 | 0 | 1 |
Public data | 6 | 1 | 0 | 0 | 0 | 0 | 0 | 2 | 0 | 1 |
Drawing task | 0 | 2 | 0 | 1 | 1 | 1 | 0 | 2 | 0 | 0 |
In-depth interview | 6 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 |
Structured interview | 0 | 2 | 0 | 0 | 1 | 2 | 0 | 0 | 1 | 0 |
Writing task | 1 | 0 | 0 | 0 | 4 | 0 | 0 | 1 | 0 | 0 |
Questionnaire interviews | 1 | 0 | 1 | 0 | 2 | 0 | 1 | 0 | 0 | 0 |
Non-experimental task | 4 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Tests | 2 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Group accounts | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 |
Open-ended prompts | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 |
Field notes | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Open-ended interview | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Qualitative questions | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 |
Social media | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
Assessment procedure | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 |
Closed-ended questions | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 |
Open discussions | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Qualitative descriptions | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Total | 551 | 273 | 75 | 116 | 79 | 73 | 65 | 60 | 50 | 17 |
Data collection frequency in topics.
Data analysis in the field of psychology.
Not stated | 5 | 1 | 2 | 0 | 0 | 1 | 1 | 5 | 0 | 1 |
Actor-Partner Interdependence Model (APIM) | 4 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Analysis of Covariance (ANCOVA) | 17 | 8 | 1 | 3 | 4 | 2 | 1 | 0 | 0 | 1 |
Analysis of Variance (ANOVA) | 112 | 60 | 16 | 29 | 15 | 17 | 15 | 6 | 5 | 3 |
Auto-regressive path coefficients | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Average variance extracted (AVE) | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 |
Bartholomew's classification system | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Bayesian analysis | 3 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 |
Bibliometric analysis | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 |
Binary logistic regression | 1 | 1 | 0 | 0 | 1 | 4 | 1 | 0 | 0 | 0 |
Binary multilevel regression | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 |
Binomial and Bernoulli regression models | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Binomial mixed effects model | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Bivariate Correlations | 32 | 10 | 3 | 0 | 4 | 3 | 5 | 1 | 1 | 1 |
Bivariate logistic correlations | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 |
Bootstrapping | 39 | 16 | 2 | 3 | 5 | 1 | 6 | 1 | 2 | 1 |
Canonical correlations | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 | 0 |
Cartesian diagram | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Case-wise diagnostics | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 |
Casual network analysis | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 |
Categorisation | 5 | 2 | 0 | 0 | 1 | 1 | 0 | 4 | 0 | 0 |
Categorisation of responses | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Category codes | 3 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 |
Cattell's scree-test | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Chi-square tests | 52 | 20 | 17 | 5 | 6 | 11 | 8 | 7 | 4 | 3 |
Classic Parallel Analysis (PA) | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 1 | 0 |
Cluster analysis | 7 | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 0 | 1 |
Coded | 15 | 3 | 1 | 2 | 1 | 1 | 1 | 2 | 1 | 0 |
Cohen d effect size | 14 | 5 | 2 | 1 | 3 | 2 | 3 | 1 | 0 | 1 |
Common method variance (CMV) | 5 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Comprehensive Meta-Analysis (CMA) | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
Confidence Interval (CI) | 2 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 |
Confirmatory Factor Analysis (CFA) | 57 | 13 | 40 | 0 | 2 | 4 | 7 | 1 | 3 | 1 |
Content analysis | 9 | 1 | 0 | 0 | 2 | 1 | 0 | 1 | 0 | 0 |
Convergent validity | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Cook's distance | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 |
Correlated-trait-correlated-method minus one model | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Correlational analysis | 259 | 85 | 44 | 18 | 27 | 31 | 34 | 8 | 33 | 8 |
Covariance matrix | 3 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Covariance modelling | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Covariance structure analyses | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Cronbach's alpha | 61 | 14 | 18 | 6 | 5 | 10 | 8 | 3 | 7 | 5 |
Cross-validation | 0 | 0 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 1 |
Cross-lagged analyses | 1 | 2 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 |
Dependent t-test | 1 | 2 | 0 | 0 | 1 | 1 | 0 | 1 | 0 | 0 |
Descriptive statistics | 324 | 132 | 43 | 49 | 41 | 43 | 36 | 28 | 29 | 10 |
Differentiated analysis | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 |
Discriminate analysis | 1 | 0 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 1 |
Discursive psychology | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Dominance analysis | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Expectation maximisation | 2 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 |
Exploratory data Analysis | 1 | 1 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 |
Exploratory Factor Analysis (EFA) | 14 | 5 | 24 | 0 | 1 | 1 | 4 | 0 | 4 | 0 |
Exploratory structural equation modelling (ESEM) | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
Factor analysis | 12 | 4 | 16 | 0 | 2 | 1 | 5 | 0 | 2 | 0 |
Measurement invariance testing | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Four-way mixed ANOVA | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 |
Frequency rate | 20 | 1 | 4 | 2 | 1 | 2 | 2 | 2 | 0 | 0 |
Friedman test | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Games-Howell | 2 | 2 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 |
General linear model analysis | 1 | 2 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 |
Greenhouse-Geisser correction | 2 | 5 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 1 |
Grounded theory method | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 |
Grounded theory methodology using open and axial coding | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Guttman split-half | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Harman's one-factor test | 13 | 2 | 0 | 0 | 0 | 1 | 2 | 0 | 0 | 0 |
Herman's criteria of experience categorisation | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 |
Hierarchical CFA (HCFA) | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Hierarchical cluster analysis | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Hierarchical Linear Modelling (HLM) | 76 | 22 | 2 | 3 | 7 | 6 | 7 | 4 | 4 | 1 |
Huynh-Felt correction | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Identified themes | 3 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 |
Independent samples t-test | 38 | 9 | 4 | 4 | 4 | 8 | 3 | 3 | 1 | 1 |
Inductive open coding | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Inferential statistics | 2 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 |
Interclass correlation | 3 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Internal consistency | 3 | 1 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Interpreted and defined | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 |
Interpretive Phenomenological Analysis (IPA) | 2 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 |
Item fit analysis | 1 | 0 | 5 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
K-means clustering | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 |
Kaiser-meyer-Olkin measure of sampling adequacy | 2 | 0 | 8 | 0 | 0 | 0 | 2 | 0 | 2 | 0 |
Kendall's coefficients | 3 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Kolmogorov-Smirnov test | 1 | 2 | 1 | 1 | 2 | 2 | 0 | 0 | 1 | 0 |
Lagged-effects multilevel modelling | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Latent class differentiation (LCD) | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Latent cluster analysis | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 |
Latent growth curve modelling (LGCM) | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 |
Latent means | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Latent Profile Analysis (LPA) | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Linear regressions | 69 | 19 | 4 | 10 | 3 | 12 | 5 | 3 | 13 | 0 |
Linguistic Inquiry and Word Count | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 |
Listwise deletion method | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 |
Log-likelihood ratios | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 |
Logistic mixed-effects model | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Logistic regression analyses | 17 | 0 | 1 | 0 | 4 | 2 | 1 | 0 | 0 | 1 |
Loglinear Model | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Mahalanobis distances | 0 | 2 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 |
Mann-Whitney U tests | 6 | 4 | 2 | 1 | 2 | 0 | 2 | 4 | 0 | 0 |
Mauchly's test | 0 | 1 | 0 | 2 | 0 | 0 | 0 | 1 | 0 | 1 |
Maximum likelihood method | 11 | 3 | 9 | 0 | 1 | 3 | 2 | 3 | 1 | 0 |
Maximum-likelihood factor analysis with promax rotation | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Measurement invariance testing | 4 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 |
Mediation analysis | 29 | 7 | 1 | 2 | 4 | 3 | 5 | 0 | 3 | 0 |
Meta-analysis | 3 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 |
Microanalysis | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Minimum significant difference (MSD) comparison | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Mixed ANOVAs | 19 | 6 | 0 | 10 | 1 | 2 | 1 | 4 | 1 | 0 |
Mixed linear model | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 0 |
Mixed-design ANCOVA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Mixed-effects multiple regression models | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Moderated hierarchical regression model | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Moderated regression analysis | 8 | 4 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 |
Monte Carlo Markov Chains | 2 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Multi-group analysis | 3 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Multidimensional Random Coefficient Multinomial Logit (MRCML) | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Multidimensional Scaling | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Multiple-Group Confirmatory Factor Analysis (MGCFA) | 3 | 0 | 0 | 0 | 0 | 2 | 0 | 0 | 0 | 0 |
Multilevel latent class analysis | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 |
Multilevel modelling | 7 | 2 | 1 | 1 | 1 | 0 | 0 | 1 | 1 | 0 |
Multilevel Structural Equation Modelling (MSEM) | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Multinominal logistic regression (MLR) | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Multinominal regression analysis | 1 | 0 | 0 | 0 | 0 | 2 | 0 | 0 | 0 | 0 |
Multiple Indicators Multiple Causes (MIMIC) | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 |
Multiple mediation analysis | 2 | 6 | 0 | 0 | 2 | 2 | 1 | 0 | 0 | 0 |
Multiple regression | 34 | 15 | 3 | 0 | 3 | 4 | 5 | 0 | 7 | 2 |
Multivariate analysis of co-variance (MANCOVA) | 12 | 2 | 1 | 1 | 0 | 1 | 1 | 0 | 1 | 0 |
Multivariate Analysis of Variance (MANOVA) | 38 | 8 | 4 | 5 | 5 | 6 | 9 | 1 | 1 | 2 |
Multivariate hierarchical linear regression | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Multivariate linear regression | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 |
Multivariate logistic regression analyses | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Multivariate regressions | 2 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 |
Nagelkerke's R square | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 |
Narrative analysis | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 |
Negative binominal regression with log link | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 |
Newman-Keuls | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 |
Nomological Validity Analysis | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
One sample t-test | 8 | 10 | 1 | 7 | 4 | 6 | 4 | 0 | 1 | 0 |
Ordinary Least-Square regression (OLS) | 2 | 2 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 |
Pairwise deletion method | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 |
Pairwise parameter comparison | 4 | 0 | 0 | 0 | 0 | 0 | 2 | 0 | 0 | 0 |
Parametric Analysis | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 |
Partial Least Squares regression method (PLS) | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Path analysis | 21 | 9 | 0 | 1 | 2 | 4 | 5 | 1 | 2 | 0 |
Path-analytic model test | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Phenomenological analysis | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 |
Polynomial regression analyses | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Fisher LSD | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Principal axis factoring | 2 | 1 | 4 | 0 | 0 | 0 | 1 | 0 | 0 | 0 |
Principal component analysis (PCA) | 8 | 1 | 12 | 1 | 1 | 0 | 3 | 2 | 5 | 1 |
Pseudo-panel regression | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Quantitative content analysis | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 |
Receiver operating characteristic (ROC) curve analysis | 2 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 |
Relative weight analysis | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Repeated measures analyses of variances (rANOVA) | 18 | 22 | 1 | 7 | 5 | 2 | 1 | 1 | 1 | 1 |
Ryan-Einot-Gabriel-Welsch multiple F test | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Satorra-Bentler scaled chi-square statistic | 0 | 0 | 3 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Scheffe's test | 3 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 |
Sequential multiple mediation analysis | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Shapiro-Wilk test | 2 | 3 | 0 | 2 | 1 | 0 | 0 | 0 | 0 | 0 |
Sobel Test | 13 | 5 | 0 | 1 | 0 | 2 | 4 | 0 | 0 | 0 |
Squared multiple correlations | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Squared semi-partial correlations (sr2) | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Stepwise regression analysis | 3 | 2 | 0 | 0 | 1 | 0 | 0 | 0 | 2 | 0 |
Structural Equation Modelling (SEM) | 56 | 22 | 3 | 3 | 3 | 5 | 5 | 0 | 5 | 3 |
Structure analysis | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 |
Subsequent t-test | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 |
Systematic coding- Gemeinschaft-oriented | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 |
Task analysis | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Thematic analysis | 11 | 2 | 0 | 0 | 3 | 0 | 2 | 2 | 0 | 0 |
Three (condition)-way ANOVA | 0 | 4 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 |
Three-way hierarchical loglinear analysis | 0 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Tukey-Kramer corrections | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 |
Two-paired sample t-test | 7 | 6 | 1 | 1 | 0 | 3 | 1 | 1 | 0 | 1 |
Two-tailed related t-test | 0 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 |
Unadjusted Logistic regression analysis | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Univariate generalized linear models (GLM) | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Variance inflation factor (VIF) | 3 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
Variance-covariance matrix | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 |
Wald test | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Ward's hierarchical cluster method | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 |
Weighted least squares with corrections to means and variances (WLSMV) | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Welch and Brown-Forsythe F-ratios | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 |
Wilcoxon signed-rank test | 3 | 3 | 0 | 2 | 0 | 0 | 0 | 2 | 0 | 1 |
Wilks' Lamba | 6 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 |
Word analysis | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 |
Word Association Analysis | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
scores | 5 | 6 | 1 | 0 | 1 | 1 | 0 | 1 | 0 | 0 |
Total | 1738 | 635 | 329 | 192 | 198 | 237 | 225 | 117 | 152 | 55 |
Results of the topics researched in psychology can be seen in the tables, as previously stated in this article. It is noteworthy that, of the 10 topics, social psychology accounted for 43.54% of the studies, with cognitive psychology the second most popular research topic at 16.92%. The remainder of the topics only occurred in 4.0–7.0% of the articles considered. A list of the included 999 articles is available under the section “View Articles” on the following website: https://methodgarden.xtrapolate.io/ . This website was created by Scholtz et al. ( 2019 ) to visually present a research framework based on this Article's results.
This systematised review categorised full-length articles from five international journals across the span of 5 years to provide insight into the use of research methods in the field of psychology. Results indicated what methods are used how these methods are being used and for what topics (why) in the included sample of articles. The results should be seen as providing insight into method use and by no means a comprehensive representation of the aforementioned aim due to the limited sample. To our knowledge, this is the first research study to address this topic in this manner. Our discussion attempts to promote a productive way forward in terms of the key results for method use in psychology, especially in the field of academia (Holloway, 2008 ).
With regard to the methods used, our data stayed true to literature, finding only common research methods (Grant and Booth, 2009 ; Maree, 2016 ) that varied in the degree to which they were employed. Quantitative research was found to be the most popular method, as indicated by literature (Breen and Darlaston-Jones, 2010 ; Counsell and Harlow, 2017 ) and previous studies in specific areas of psychology (see Coetzee and Van Zyl, 2014 ). Its long history as the first research method (Leech et al., 2007 ) in the field of psychology as well as researchers' current application of mathematical approaches in their studies (Toomela, 2010 ) might contribute to its popularity today. Whatever the case may be, our results show that, despite the growth in qualitative research (Demuth, 2015 ; Smith and McGannon, 2018 ), quantitative research remains the first choice for article publication in these journals. Despite the included journals indicating openness to articles that apply any research methods. This finding may be due to qualitative research still being seen as a new method (Burman and Whelan, 2011 ) or reviewers' standards being higher for qualitative studies (Bluhm et al., 2011 ). Future research is encouraged into the possible biasness in publication of research methods, additionally further investigation with a different sample into the proclaimed growth of qualitative research may also provide different results.
Review studies were found to surpass that of multi-method and mixed method studies. To this effect Grant and Booth ( 2009 ), state that the increased awareness, journal contribution calls as well as its efficiency in procuring research funds all promote the popularity of reviews. The low frequency of mixed method studies contradicts the view in literature that it's the third most utilised research method (Tashakkori and Teddlie's, 2003 ). Its' low occurrence in this sample could be due to opposing views on mixing methods (Gunasekare, 2015 ) or that authors prefer publishing in mixed method journals, when using this method, or its relative novelty (Ivankova et al., 2016 ). Despite its low occurrence, the application of the mixed methods design in articles was methodologically clear in all cases which were not the case for the remainder of research methods.
Additionally, a substantial number of studies used a combination of methodologies that are not mixed or multi-method studies. Perceived fixed boundaries are according to literature often set aside, as confirmed by this result, in order to investigate the aim of a study, which could create a new and helpful way of understanding the world (Gunasekare, 2015 ). According to Toomela ( 2010 ), this is not unheard of and could be considered a form of “structural systemic science,” as in the case of qualitative methodology (observation) applied in quantitative studies (experimental design) for example. Based on this result, further research into this phenomenon as well as its implications for research methods such as multi and mixed methods is recommended.
Discerning how these research methods were applied, presented some difficulty. In the case of sampling, most studies—regardless of method—did mention some form of inclusion and exclusion criteria, but no definite sampling method. This result, along with the fact that samples often consisted of students from the researchers' own academic institutions, can contribute to literature and debates among academics (Peterson and Merunka, 2014 ; Laher, 2016 ). Samples of convenience and students as participants especially raise questions about the generalisability and applicability of results (Peterson and Merunka, 2014 ). This is because attention to sampling is important as inappropriate sampling can debilitate the legitimacy of interpretations (Onwuegbuzie and Collins, 2017 ). Future investigation into the possible implications of this reported popular use of convenience samples for the field of psychology as well as the reason for this use could provide interesting insight, and is encouraged by this study.
Additionally, and this is indicated in Table 6 , articles seldom report the research designs used, which highlights the pressing aspect of the lack of rigour in the included sample. Rigour with regards to the applied empirical method is imperative in promoting psychology as a science (American Psychological Association, 2020 ). Omitting parts of the research process in publication when it could have been used to inform others' research skills should be questioned, and the influence on the process of replicating results should be considered. Publications are often rejected due to a lack of rigour in the applied method and designs (Fonseca, 2013 ; Laher, 2016 ), calling for increased clarity and knowledge of method application. Replication is a critical part of any field of scientific research and requires the “complete articulation” of the study methods used (Drotar, 2010 , p. 804). The lack of thorough description could be explained by the requirements of certain journals to only report on certain aspects of a research process, especially with regard to the applied design (Laher, 20). However, naming aspects such as sampling and designs, is a requirement according to the APA's Journal Article Reporting Standards (JARS-Quant) (Appelbaum et al., 2018 ). With very little information on how a study was conducted, authors lose a valuable opportunity to enhance research validity, enrich the knowledge of others, and contribute to the growth of psychology and methodology as a whole. In the case of this research study, it also restricted our results to only reported samples and designs, which indicated a preference for certain designs, such as cross-sectional designs for quantitative studies.
Data collection and analysis were for the most part clearly stated. A key result was the versatile use of questionnaires. Researchers would apply a questionnaire in various ways, for example in questionnaire interviews, online surveys, and written questionnaires across most research methods. This may highlight a trend for future research.
With regard to the topics these methods were employed for, our research study found a new field named “psychological practice.” This result may show the growing consciousness of researchers as part of the research process (Denzin and Lincoln, 2003 ), psychological practice, and knowledge generation. The most popular of these topics was social psychology, which is generously covered in journals and by learning societies, as testaments of the institutional support and richness social psychology has in the field of psychology (Chryssochoou, 2015 ). The APA's perspective on 2018 trends in psychology also identifies an increased amount of psychology focus on how social determinants are influencing people's health (Deangelis, 2017 ).
This study was not without limitations and the following should be taken into account. Firstly, this study used a sample of five specific journals to address the aim of the research study, despite general journal aims (as stated on journal websites), this inclusion signified a bias towards the research methods published in these specific journals only and limited generalisability. A broader sample of journals over a different period of time, or a single journal over a longer period of time might provide different results. A second limitation is the use of Excel spreadsheets and an electronic system to log articles, which was a manual process and therefore left room for error (Bandara et al., 2015 ). To address this potential issue, co-coding was performed to reduce error. Lastly, this article categorised data based on the information presented in the article sample; there was no interpretation of what methodology could have been applied or whether the methods stated adhered to the criteria for the methods used. Thus, a large number of articles that did not clearly indicate a research method or design could influence the results of this review. However, this in itself was also a noteworthy result. Future research could review research methods of a broader sample of journals with an interpretive review tool that increases rigour. Additionally, the authors also encourage the future use of systematised review designs as a way to promote a concise procedure in applying this design.
Our research study presented the use of research methods for published articles in the field of psychology as well as recommendations for future research based on these results. Insight into the complex questions identified in literature, regarding what methods are used how these methods are being used and for what topics (why) was gained. This sample preferred quantitative methods, used convenience sampling and presented a lack of rigorous accounts for the remaining methodologies. All methodologies that were clearly indicated in the sample were tabulated to allow researchers insight into the general use of methods and not only the most frequently used methods. The lack of rigorous account of research methods in articles was represented in-depth for each step in the research process and can be of vital importance to address the current replication crisis within the field of psychology. Recommendations for future research aimed to motivate research into the practical implications of the results for psychology, for example, publication bias and the use of convenience samples.
Ethics Statement
This study was cleared by the North-West University Health Research Ethics Committee: NWU-00115-17-S1.
Author Contributions
All authors listed have made a substantial, direct and intellectual contribution to the work, and approved it for publication.
Conflict of Interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
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Research Methods In Psychology
Saul McLeod, PhD
Editor-in-Chief for Simply Psychology
BSc (Hons) Psychology, MRes, PhD, University of Manchester
Saul McLeod, PhD., is a qualified psychology teacher with over 18 years of experience in further and higher education. He has been published in peer-reviewed journals, including the Journal of Clinical Psychology.
Learn about our Editorial Process
Olivia Guy-Evans, MSc
Associate Editor for Simply Psychology
BSc (Hons) Psychology, MSc Psychology of Education
Olivia Guy-Evans is a writer and associate editor for Simply Psychology. She has previously worked in healthcare and educational sectors.
Research methods in psychology are systematic procedures used to observe, describe, predict, and explain behavior and mental processes. They include experiments, surveys, case studies, and naturalistic observations, ensuring data collection is objective and reliable to understand and explain psychological phenomena.
Hypotheses are statements about the prediction of the results, that can be verified or disproved by some investigation.
There are four types of hypotheses :
- Null Hypotheses (H0 ) – these predict that no difference will be found in the results between the conditions. Typically these are written ‘There will be no difference…’
- Alternative Hypotheses (Ha or H1) – these predict that there will be a significant difference in the results between the two conditions. This is also known as the experimental hypothesis.
- One-tailed (directional) hypotheses – these state the specific direction the researcher expects the results to move in, e.g. higher, lower, more, less. In a correlation study, the predicted direction of the correlation can be either positive or negative.
- Two-tailed (non-directional) hypotheses – these state that a difference will be found between the conditions of the independent variable but does not state the direction of a difference or relationship. Typically these are always written ‘There will be a difference ….’
All research has an alternative hypothesis (either a one-tailed or two-tailed) and a corresponding null hypothesis.
Once the research is conducted and results are found, psychologists must accept one hypothesis and reject the other.
So, if a difference is found, the Psychologist would accept the alternative hypothesis and reject the null. The opposite applies if no difference is found.
Sampling techniques
Sampling is the process of selecting a representative group from the population under study.
A sample is the participants you select from a target population (the group you are interested in) to make generalizations about.
Representative means the extent to which a sample mirrors a researcher’s target population and reflects its characteristics.
Generalisability means the extent to which their findings can be applied to the larger population of which their sample was a part.
- Volunteer sample : where participants pick themselves through newspaper adverts, noticeboards or online.
- Opportunity sampling : also known as convenience sampling , uses people who are available at the time the study is carried out and willing to take part. It is based on convenience.
- Random sampling : when every person in the target population has an equal chance of being selected. An example of random sampling would be picking names out of a hat.
- Systematic sampling : when a system is used to select participants. Picking every Nth person from all possible participants. N = the number of people in the research population / the number of people needed for the sample.
- Stratified sampling : when you identify the subgroups and select participants in proportion to their occurrences.
- Snowball sampling : when researchers find a few participants, and then ask them to find participants themselves and so on.
- Quota sampling : when researchers will be told to ensure the sample fits certain quotas, for example they might be told to find 90 participants, with 30 of them being unemployed.
Experiments always have an independent and dependent variable .
- The independent variable is the one the experimenter manipulates (the thing that changes between the conditions the participants are placed into). It is assumed to have a direct effect on the dependent variable.
- The dependent variable is the thing being measured, or the results of the experiment.
Operationalization of variables means making them measurable/quantifiable. We must use operationalization to ensure that variables are in a form that can be easily tested.
For instance, we can’t really measure ‘happiness’, but we can measure how many times a person smiles within a two-hour period.
By operationalizing variables, we make it easy for someone else to replicate our research. Remember, this is important because we can check if our findings are reliable.
Extraneous variables are all variables which are not independent variable but could affect the results of the experiment.
It can be a natural characteristic of the participant, such as intelligence levels, gender, or age for example, or it could be a situational feature of the environment such as lighting or noise.
Demand characteristics are a type of extraneous variable that occurs if the participants work out the aims of the research study, they may begin to behave in a certain way.
For example, in Milgram’s research , critics argued that participants worked out that the shocks were not real and they administered them as they thought this was what was required of them.
Extraneous variables must be controlled so that they do not affect (confound) the results.
Randomly allocating participants to their conditions or using a matched pairs experimental design can help to reduce participant variables.
Situational variables are controlled by using standardized procedures, ensuring every participant in a given condition is treated in the same way
Experimental Design
Experimental design refers to how participants are allocated to each condition of the independent variable, such as a control or experimental group.
- Independent design ( between-groups design ): each participant is selected for only one group. With the independent design, the most common way of deciding which participants go into which group is by means of randomization.
- Matched participants design : each participant is selected for only one group, but the participants in the two groups are matched for some relevant factor or factors (e.g. ability; sex; age).
- Repeated measures design ( within groups) : each participant appears in both groups, so that there are exactly the same participants in each group.
- The main problem with the repeated measures design is that there may well be order effects. Their experiences during the experiment may change the participants in various ways.
- They may perform better when they appear in the second group because they have gained useful information about the experiment or about the task. On the other hand, they may perform less well on the second occasion because of tiredness or boredom.
- Counterbalancing is the best way of preventing order effects from disrupting the findings of an experiment, and involves ensuring that each condition is equally likely to be used first and second by the participants.
If we wish to compare two groups with respect to a given independent variable, it is essential to make sure that the two groups do not differ in any other important way.
Experimental Methods
All experimental methods involve an iv (independent variable) and dv (dependent variable)..
The researcher decides where the experiment will take place, at what time, with which participants, in what circumstances, using a standardized procedure.
- Field experiments are conducted in the everyday (natural) environment of the participants. The experimenter still manipulates the IV, but in a real-life setting. It may be possible to control extraneous variables, though such control is more difficult than in a lab experiment.
- Natural experiments are when a naturally occurring IV is investigated that isn’t deliberately manipulated, it exists anyway. Participants are not randomly allocated, and the natural event may only occur rarely.
Case studies are in-depth investigations of a person, group, event, or community. It uses information from a range of sources, such as from the person concerned and also from their family and friends.
Many techniques may be used such as interviews, psychological tests, observations and experiments. Case studies are generally longitudinal: in other words, they follow the individual or group over an extended period of time.
Case studies are widely used in psychology and among the best-known ones carried out were by Sigmund Freud . He conducted very detailed investigations into the private lives of his patients in an attempt to both understand and help them overcome their illnesses.
Case studies provide rich qualitative data and have high levels of ecological validity. However, it is difficult to generalize from individual cases as each one has unique characteristics.
Correlational Studies
Correlation means association; it is a measure of the extent to which two variables are related. One of the variables can be regarded as the predictor variable with the other one as the outcome variable.
Correlational studies typically involve obtaining two different measures from a group of participants, and then assessing the degree of association between the measures.
The predictor variable can be seen as occurring before the outcome variable in some sense. It is called the predictor variable, because it forms the basis for predicting the value of the outcome variable.
Relationships between variables can be displayed on a graph or as a numerical score called a correlation coefficient.
- If an increase in one variable tends to be associated with an increase in the other, then this is known as a positive correlation .
- If an increase in one variable tends to be associated with a decrease in the other, then this is known as a negative correlation .
- A zero correlation occurs when there is no relationship between variables.
After looking at the scattergraph, if we want to be sure that a significant relationship does exist between the two variables, a statistical test of correlation can be conducted, such as Spearman’s rho.
The test will give us a score, called a correlation coefficient . This is a value between 0 and 1, and the closer to 1 the score is, the stronger the relationship between the variables. This value can be both positive e.g. 0.63, or negative -0.63.
A correlation between variables, however, does not automatically mean that the change in one variable is the cause of the change in the values of the other variable. A correlation only shows if there is a relationship between variables.
Correlation does not always prove causation, as a third variable may be involved.
Interview Methods
Interviews are commonly divided into two types: structured and unstructured.
A fixed, predetermined set of questions is put to every participant in the same order and in the same way.
Responses are recorded on a questionnaire, and the researcher presets the order and wording of questions, and sometimes the range of alternative answers.
The interviewer stays within their role and maintains social distance from the interviewee.
There are no set questions, and the participant can raise whatever topics he/she feels are relevant and ask them in their own way. Questions are posed about participants’ answers to the subject
Unstructured interviews are most useful in qualitative research to analyze attitudes and values.
Though they rarely provide a valid basis for generalization, their main advantage is that they enable the researcher to probe social actors’ subjective point of view.
Questionnaire Method
Questionnaires can be thought of as a kind of written interview. They can be carried out face to face, by telephone, or post.
The choice of questions is important because of the need to avoid bias or ambiguity in the questions, ‘leading’ the respondent or causing offense.
- Open questions are designed to encourage a full, meaningful answer using the subject’s own knowledge and feelings. They provide insights into feelings, opinions, and understanding. Example: “How do you feel about that situation?”
- Closed questions can be answered with a simple “yes” or “no” or specific information, limiting the depth of response. They are useful for gathering specific facts or confirming details. Example: “Do you feel anxious in crowds?”
Its other practical advantages are that it is cheaper than face-to-face interviews and can be used to contact many respondents scattered over a wide area relatively quickly.
Observations
There are different types of observation methods :
- Covert observation is where the researcher doesn’t tell the participants they are being observed until after the study is complete. There could be ethical problems or deception and consent with this particular observation method.
- Overt observation is where a researcher tells the participants they are being observed and what they are being observed for.
- Controlled : behavior is observed under controlled laboratory conditions (e.g., Bandura’s Bobo doll study).
- Natural : Here, spontaneous behavior is recorded in a natural setting.
- Participant : Here, the observer has direct contact with the group of people they are observing. The researcher becomes a member of the group they are researching.
- Non-participant (aka “fly on the wall): The researcher does not have direct contact with the people being observed. The observation of participants’ behavior is from a distance
Pilot Study
A pilot study is a small scale preliminary study conducted in order to evaluate the feasibility of the key s teps in a future, full-scale project.
A pilot study is an initial run-through of the procedures to be used in an investigation; it involves selecting a few people and trying out the study on them. It is possible to save time, and in some cases, money, by identifying any flaws in the procedures designed by the researcher.
A pilot study can help the researcher spot any ambiguities (i.e. unusual things) or confusion in the information given to participants or problems with the task devised.
Sometimes the task is too hard, and the researcher may get a floor effect, because none of the participants can score at all or can complete the task – all performances are low.
The opposite effect is a ceiling effect, when the task is so easy that all achieve virtually full marks or top performances and are “hitting the ceiling”.
Research Design
In cross-sectional research , a researcher compares multiple segments of the population at the same time
Sometimes, we want to see how people change over time, as in studies of human development and lifespan. Longitudinal research is a research design in which data-gathering is administered repeatedly over an extended period of time.
In cohort studies , the participants must share a common factor or characteristic such as age, demographic, or occupation. A cohort study is a type of longitudinal study in which researchers monitor and observe a chosen population over an extended period.
Triangulation means using more than one research method to improve the study’s validity.
Reliability
Reliability is a measure of consistency, if a particular measurement is repeated and the same result is obtained then it is described as being reliable.
- Test-retest reliability : assessing the same person on two different occasions which shows the extent to which the test produces the same answers.
- Inter-observer reliability : the extent to which there is an agreement between two or more observers.
Meta-Analysis
Meta-analysis is a statistical procedure used to combine and synthesize findings from multiple independent studies to estimate the average effect size for a particular research question.
Meta-analysis goes beyond traditional narrative reviews by using statistical methods to integrate the results of several studies, leading to a more objective appraisal of the evidence.
This is done by looking through various databases, and then decisions are made about what studies are to be included/excluded.
- Strengths : Increases the conclusions’ validity as they’re based on a wider range.
- Weaknesses : Research designs in studies can vary, so they are not truly comparable.
Peer Review
A researcher submits an article to a journal. The choice of the journal may be determined by the journal’s audience or prestige.
The journal selects two or more appropriate experts (psychologists working in a similar field) to peer review the article without payment. The peer reviewers assess: the methods and designs used, originality of the findings, the validity of the original research findings and its content, structure and language.
Feedback from the reviewer determines whether the article is accepted. The article may be: Accepted as it is, accepted with revisions, sent back to the author to revise and re-submit or rejected without the possibility of submission.
The editor makes the final decision whether to accept or reject the research report based on the reviewers comments/ recommendations.
Peer review is important because it prevent faulty data from entering the public domain, it provides a way of checking the validity of findings and the quality of the methodology and is used to assess the research rating of university departments.
Peer reviews may be an ideal, whereas in practice there are lots of problems. For example, it slows publication down and may prevent unusual, new work being published. Some reviewers might use it as an opportunity to prevent competing researchers from publishing work.
Some people doubt whether peer review can really prevent the publication of fraudulent research.
The advent of the internet means that a lot of research and academic comment is being published without official peer reviews than before, though systems are evolving on the internet where everyone really has a chance to offer their opinions and police the quality of research.
Types of Data
- Quantitative data is numerical data e.g. reaction time or number of mistakes. It represents how much or how long, how many there are of something. A tally of behavioral categories and closed questions in a questionnaire collect quantitative data.
- Qualitative data is virtually any type of information that can be observed and recorded that is not numerical in nature and can be in the form of written or verbal communication. Open questions in questionnaires and accounts from observational studies collect qualitative data.
- Primary data is first-hand data collected for the purpose of the investigation.
- Secondary data is information that has been collected by someone other than the person who is conducting the research e.g. taken from journals, books or articles.
Validity means how well a piece of research actually measures what it sets out to, or how well it reflects the reality it claims to represent.
Validity is whether the observed effect is genuine and represents what is actually out there in the world.
- Concurrent validity is the extent to which a psychological measure relates to an existing similar measure and obtains close results. For example, a new intelligence test compared to an established test.
- Face validity : does the test measure what it’s supposed to measure ‘on the face of it’. This is done by ‘eyeballing’ the measuring or by passing it to an expert to check.
- Ecological validit y is the extent to which findings from a research study can be generalized to other settings / real life.
- Temporal validity is the extent to which findings from a research study can be generalized to other historical times.
Features of Science
- Paradigm – A set of shared assumptions and agreed methods within a scientific discipline.
- Paradigm shift – The result of the scientific revolution: a significant change in the dominant unifying theory within a scientific discipline.
- Objectivity – When all sources of personal bias are minimised so not to distort or influence the research process.
- Empirical method – Scientific approaches that are based on the gathering of evidence through direct observation and experience.
- Replicability – The extent to which scientific procedures and findings can be repeated by other researchers.
- Falsifiability – The principle that a theory cannot be considered scientific unless it admits the possibility of being proved untrue.
Statistical Testing
A significant result is one where there is a low probability that chance factors were responsible for any observed difference, correlation, or association in the variables tested.
If our test is significant, we can reject our null hypothesis and accept our alternative hypothesis.
If our test is not significant, we can accept our null hypothesis and reject our alternative hypothesis. A null hypothesis is a statement of no effect.
In Psychology, we use p < 0.05 (as it strikes a balance between making a type I and II error) but p < 0.01 is used in tests that could cause harm like introducing a new drug.
A type I error is when the null hypothesis is rejected when it should have been accepted (happens when a lenient significance level is used, an error of optimism).
A type II error is when the null hypothesis is accepted when it should have been rejected (happens when a stringent significance level is used, an error of pessimism).
Ethical Issues
- Informed consent is when participants are able to make an informed judgment about whether to take part. It causes them to guess the aims of the study and change their behavior.
- To deal with it, we can gain presumptive consent or ask them to formally indicate their agreement to participate but it may invalidate the purpose of the study and it is not guaranteed that the participants would understand.
- Deception should only be used when it is approved by an ethics committee, as it involves deliberately misleading or withholding information. Participants should be fully debriefed after the study but debriefing can’t turn the clock back.
- All participants should be informed at the beginning that they have the right to withdraw if they ever feel distressed or uncomfortable.
- It causes bias as the ones that stayed are obedient and some may not withdraw as they may have been given incentives or feel like they’re spoiling the study. Researchers can offer the right to withdraw data after participation.
- Participants should all have protection from harm . The researcher should avoid risks greater than those experienced in everyday life and they should stop the study if any harm is suspected. However, the harm may not be apparent at the time of the study.
- Confidentiality concerns the communication of personal information. The researchers should not record any names but use numbers or false names though it may not be possible as it is sometimes possible to work out who the researchers were.
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Descriptive Research and Case Studies
Learning objectives.
- Explain the importance and uses of descriptive research, especially case studies, in studying abnormal behavior
Types of Research Methods
There are many research methods available to psychologists in their efforts to understand, describe, and explain behavior and the cognitive and biological processes that underlie it. Some methods rely on observational techniques. Other approaches involve interactions between the researcher and the individuals who are being studied—ranging from a series of simple questions; to extensive, in-depth interviews; to well-controlled experiments.
The three main categories of psychological research are descriptive, correlational, and experimental research. Research studies that do not test specific relationships between variables are called descriptive, or qualitative, studies . These studies are used to describe general or specific behaviors and attributes that are observed and measured. In the early stages of research, it might be difficult to form a hypothesis, especially when there is not any existing literature in the area. In these situations designing an experiment would be premature, as the question of interest is not yet clearly defined as a hypothesis. Often a researcher will begin with a non-experimental approach, such as a descriptive study, to gather more information about the topic before designing an experiment or correlational study to address a specific hypothesis. Descriptive research is distinct from correlational research , in which psychologists formally test whether a relationship exists between two or more variables. Experimental research goes a step further beyond descriptive and correlational research and randomly assigns people to different conditions, using hypothesis testing to make inferences about how these conditions affect behavior. It aims to determine if one variable directly impacts and causes another. Correlational and experimental research both typically use hypothesis testing, whereas descriptive research does not.
Each of these research methods has unique strengths and weaknesses, and each method may only be appropriate for certain types of research questions. For example, studies that rely primarily on observation produce incredible amounts of information, but the ability to apply this information to the larger population is somewhat limited because of small sample sizes. Survey research, on the other hand, allows researchers to easily collect data from relatively large samples. While surveys allow results to be generalized to the larger population more easily, the information that can be collected on any given survey is somewhat limited and subject to problems associated with any type of self-reported data. Some researchers conduct archival research by using existing records. While existing records can be a fairly inexpensive way to collect data that can provide insight into a number of research questions, researchers using this approach have no control on how or what kind of data was collected.
Correlational research can find a relationship between two variables, but the only way a researcher can claim that the relationship between the variables is cause and effect is to perform an experiment. In experimental research, which will be discussed later, there is a tremendous amount of control over variables of interest. While performing an experiment is a powerful approach, experiments are often conducted in very artificial settings, which calls into question the validity of experimental findings with regard to how they would apply in real-world settings. In addition, many of the questions that psychologists would like to answer cannot be pursued through experimental research because of ethical concerns.
The three main types of descriptive studies are case studies, naturalistic observation, and surveys.
Clinical or Case Studies
Psychologists can use a detailed description of one person or a small group based on careful observation. Case studies are intensive studies of individuals and have commonly been seen as a fruitful way to come up with hypotheses and generate theories. Case studies add descriptive richness. Case studies are also useful for formulating concepts, which are an important aspect of theory construction. Through fine-grained knowledge and description, case studies can fully specify the causal mechanisms in a way that may be harder in a large study.
Sigmund Freud developed many theories from case studies (Anna O., Little Hans, Wolf Man, Dora, etc.). F or example, he conducted a case study of a man, nicknamed “Rat Man,” in which he claimed that this patient had been cured by psychoanalysis. T he nickname derives from the fact that among the patient’s many compulsions, he had an obsession with nightmarish fantasies about rats.
Today, more commonly, case studies reflect an up-close, in-depth, and detailed examination of an individual’s course of treatment. Case studies typically include a complete history of the subject’s background and response to treatment. From the particular client’s experience in therapy, the therapist’s goal is to provide information that may help other therapists who treat similar clients.
Case studies are generally a single-case design, but can also be a multiple-case design, where replication instead of sampling is the criterion for inclusion. Like other research methodologies within psychology, the case study must produce valid and reliable results in order to be useful for the development of future research. Distinct advantages and disadvantages are associated with the case study in psychology.
A commonly described limit of case studies is that they do not lend themselves to generalizability . The other issue is that the case study is subject to the bias of the researcher in terms of how the case is written, and that cases are chosen because they are consistent with the researcher’s preconceived notions, resulting in biased research. Another common problem in case study research is that of reconciling conflicting interpretations of the same case history.
Despite these limitations, there are advantages to using case studies. One major advantage of the case study in psychology is the potential for the development of novel hypotheses of the cause of abnormal behavior for later testing. Second, the case study can provide detailed descriptions of specific and rare cases and help us study unusual conditions that occur too infrequently to study with large sample sizes. The major disadvantage is that case studies cannot be used to determine causation, as is the case in experimental research, where the factors or variables hypothesized to play a causal role are manipulated or controlled by the researcher.
Link to Learning: Famous Case Studies
Some well-known case studies that related to abnormal psychology include the following:
- Harlow— Phineas Gage
- Breuer & Freud (1895)— Anna O.
- Cleckley’s case studies: on psychopathy ( The Mask of Sanity ) (1941) and multiple personality disorder ( The Three Faces of Eve ) (1957)
- Freud and Little Hans
- Freud and the Rat Man
- John Money and the John/Joan case
- Genie (feral child)
- Piaget’s studies
- Rosenthal’s book on the murder of Kitty Genovese
- Washoe (sign language)
- Patient H.M.
Naturalistic Observation
If you want to understand how behavior occurs, one of the best ways to gain information is to simply observe the behavior in its natural context. However, people might change their behavior in unexpected ways if they know they are being observed. How do researchers obtain accurate information when people tend to hide their natural behavior? As an example, imagine that your professor asks everyone in your class to raise their hand if they always wash their hands after using the restroom. Chances are that almost everyone in the classroom will raise their hand, but do you think hand washing after every trip to the restroom is really that universal?
This is very similar to the phenomenon mentioned earlier in this module: many individuals do not feel comfortable answering a question honestly. But if we are committed to finding out the facts about handwashing, we have other options available to us.
Suppose we send a researcher to a school playground to observe how aggressive or socially anxious children interact with peers. Will our observer blend into the playground environment by wearing a white lab coat, sitting with a clipboard, and staring at the swings? We want our researcher to be inconspicuous and unobtrusively positioned—perhaps pretending to be a school monitor while secretly recording the relevant information. This type of observational study is called naturalistic observation : observing behavior in its natural setting. To better understand peer exclusion, Suzanne Fanger collaborated with colleagues at the University of Texas to observe the behavior of preschool children on a playground. How did the observers remain inconspicuous over the duration of the study? They equipped a few of the children with wireless microphones (which the children quickly forgot about) and observed while taking notes from a distance. Also, the children in that particular preschool (a “laboratory preschool”) were accustomed to having observers on the playground (Fanger, Frankel, & Hazen, 2012).
It is critical that the observer be as unobtrusive and as inconspicuous as possible: when people know they are being watched, they are less likely to behave naturally. For example, psychologists have spent weeks observing the behavior of homeless people on the streets, in train stations, and bus terminals. They try to ensure that their naturalistic observations are unobtrusive, so as to minimize interference with the behavior they observe. Nevertheless, the presence of the observer may distort the behavior that is observed, and this must be taken into consideration (Figure 1).
The greatest benefit of naturalistic observation is the validity, or accuracy, of information collected unobtrusively in a natural setting. Having individuals behave as they normally would in a given situation means that we have a higher degree of ecological validity, or realism, than we might achieve with other research approaches. Therefore, our ability to generalize the findings of the research to real-world situations is enhanced. If done correctly, we need not worry about people modifying their behavior simply because they are being observed. Sometimes, people may assume that reality programs give us a glimpse into authentic human behavior. However, the principle of inconspicuous observation is violated as reality stars are followed by camera crews and are interviewed on camera for personal confessionals. Given that environment, we must doubt how natural and realistic their behaviors are.
The major downside of naturalistic observation is that they are often difficult to set up and control. Although something as simple as observation may seem like it would be a part of all research methods, participant observation is a distinct methodology that involves the researcher embedding themselves into a group in order to study its dynamics. For example, Festinger, Riecken, and Shacter (1956) were very interested in the psychology of a particular cult. However, this cult was very secretive and wouldn’t grant interviews to outside members. So, in order to study these people, Festinger and his colleagues pretended to be cult members, allowing them access to the behavior and psychology of the cult. Despite this example, it should be noted that the people being observed in a participant observation study usually know that the researcher is there to study them. [1]
Another potential problem in observational research is observer bias . Generally, people who act as observers are closely involved in the research project and may unconsciously skew their observations to fit their research goals or expectations. To protect against this type of bias, researchers should have clear criteria established for the types of behaviors recorded and how those behaviors should be classified. In addition, researchers often compare observations of the same event by multiple observers, in order to test inter-rater reliability : a measure of reliability that assesses the consistency of observations by different observers.
Often, psychologists develop surveys as a means of gathering data. Surveys are lists of questions to be answered by research participants, and can be delivered as paper-and-pencil questionnaires, administered electronically, or conducted verbally (Figure 3). Generally, the survey itself can be completed in a short time, and the ease of administering a survey makes it easy to collect data from a large number of people.
Surveys allow researchers to gather data from larger samples than may be afforded by other research methods . A sample is a subset of individuals selected from a population , which is the overall group of individuals that the researchers are interested in. Researchers study the sample and seek to generalize their findings to the population.
There is both strength and weakness in surveys when compared to case studies. By using surveys, we can collect information from a larger sample of people. A larger sample is better able to reflect the actual diversity of the population, thus allowing better generalizability. Therefore, if our sample is sufficiently large and diverse, we can assume that the data we collect from the survey can be generalized to the larger population with more certainty than the information collected through a case study. However, given the greater number of people involved, we are not able to collect the same depth of information on each person that would be collected in a case study.
Another potential weakness of surveys is something we touched on earlier in this module: people do not always give accurate responses. They may lie, misremember, or answer questions in a way that they think makes them look good. For example, people may report drinking less alcohol than is actually the case.
Any number of research questions can be answered through the use of surveys. One real-world example is the research conducted by Jenkins, Ruppel, Kizer, Yehl, and Griffin (2012) about the backlash against the U.S. Arab-American community following the terrorist attacks of September 11, 2001. Jenkins and colleagues wanted to determine to what extent these negative attitudes toward Arab-Americans still existed nearly a decade after the attacks occurred. In one study, 140 research participants filled out a survey with 10 questions, including questions asking directly about the participant’s overt prejudicial attitudes toward people of various ethnicities. The survey also asked indirect questions about how likely the participant would be to interact with a person of a given ethnicity in a variety of settings (such as, “How likely do you think it is that you would introduce yourself to a person of Arab-American descent?”). The results of the research suggested that participants were unwilling to report prejudicial attitudes toward any ethnic group. However, there were significant differences between their pattern of responses to questions about social interaction with Arab-Americans compared to other ethnic groups: they indicated less willingness for social interaction with Arab-Americans compared to the other ethnic groups. This suggested that the participants harbored subtle forms of prejudice against Arab-Americans, despite their assertions that this was not the case (Jenkins et al., 2012).
Think it Over
Research has shown that parental depressive symptoms are linked to a number of negative child outcomes. A classmate of yours is interested in the associations between parental depressive symptoms and actual child behaviors in everyday life [2] because this associations remains largely unknown. After reading this section, what do you think is the best way to better understand such associations? Which method might result in the most valid data?
clinical or case study: observational research study focusing on one or a few people
correlational research: tests whether a relationship exists between two or more variables
descriptive research: research studies that do not test specific relationships between variables; they are used to describe general or specific behaviors and attributes that are observed and measured
experimental research: tests a hypothesis to determine cause-and-effect relationships
generalizability: inferring that the results for a sample apply to the larger population
inter-rater reliability: measure of agreement among observers on how they record and classify a particular event
naturalistic observation: observation of behavior in its natural setting
observer bias: when observations may be skewed to align with observer expectations
population: overall group of individuals that the researchers are interested in
sample: subset of individuals selected from the larger population
survey: list of questions to be answered by research participants—given as paper-and-pencil questionnaires, administered electronically, or conducted verbally—allowing researchers to collect data from a large number of people
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- Slatcher, R. B., & Trentacosta, C. J. (2011). A naturalistic observation study of the links between parental depressive symptoms and preschoolers' behaviors in everyday life. Journal of family psychology : JFP : journal of the Division of Family Psychology of the American Psychological Association (Division 43), 25(3), 444–448. https://doi.org/10.1037/a0023728 ↵
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How to Write an APA Methods Section | With Examples
Published on February 5, 2021 by Pritha Bhandari . Revised on June 22, 2023.
The methods section of an APA style paper is where you report in detail how you performed your study. Research papers in the social and natural sciences often follow APA style. This article focuses on reporting quantitative research methods .
In your APA methods section, you should report enough information to understand and replicate your study, including detailed information on the sample , measures, and procedures used.
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Table of contents
Structuring an apa methods section.
Participants
Example of an APA methods section
Other interesting articles, frequently asked questions about writing an apa methods section.
The main heading of “Methods” should be centered, boldfaced, and capitalized. Subheadings within this section are left-aligned, boldfaced, and in title case. You can also add lower level headings within these subsections, as long as they follow APA heading styles .
To structure your methods section, you can use the subheadings of “Participants,” “Materials,” and “Procedures.” These headings are not mandatory—aim to organize your methods section using subheadings that make sense for your specific study.
Heading | What to include |
---|---|
Participants | |
Materials | |
Procedure |
Note that not all of these topics will necessarily be relevant for your study. For example, if you didn’t need to consider outlier removal or ways of assigning participants to different conditions, you don’t have to report these steps.
The APA also provides specific reporting guidelines for different types of research design. These tell you exactly what you need to report for longitudinal designs , replication studies, experimental designs , and so on. If your study uses a combination design, consult APA guidelines for mixed methods studies.
Detailed descriptions of procedures that don’t fit into your main text can be placed in supplemental materials (for example, the exact instructions and tasks given to participants, the full analytical strategy including software code, or additional figures and tables).
Prevent plagiarism. Run a free check.
Begin the methods section by reporting sample characteristics, sampling procedures, and the sample size.
Participant or subject characteristics
When discussing people who participate in research, descriptive terms like “participants,” “subjects” and “respondents” can be used. For non-human animal research, “subjects” is more appropriate.
Specify all relevant demographic characteristics of your participants. This may include their age, sex, ethnic or racial group, gender identity, education level, and socioeconomic status. Depending on your study topic, other characteristics like educational or immigration status or language preference may also be relevant.
Be sure to report these characteristics as precisely as possible. This helps the reader understand how far your results may be generalized to other people.
The APA guidelines emphasize writing about participants using bias-free language , so it’s necessary to use inclusive and appropriate terms.
Sampling procedures
Outline how the participants were selected and all inclusion and exclusion criteria applied. Appropriately identify the sampling procedure used. For example, you should only label a sample as random if you had access to every member of the relevant population.
Of all the people invited to participate in your study, note the percentage that actually did (if you have this data). Additionally, report whether participants were self-selected, either by themselves or by their institutions (e.g., schools may submit student data for research purposes).
Identify any compensation (e.g., course credits or money) that was provided to participants, and mention any institutional review board approvals and ethical standards followed.
Sample size and power
Detail the sample size (per condition) and statistical power that you hoped to achieve, as well as any analyses you performed to determine these numbers.
It’s important to show that your study had enough statistical power to find effects if there were any to be found.
Additionally, state whether your final sample differed from the intended sample. Your interpretations of the study outcomes should be based only on your final sample rather than your intended sample.
Write up the tools and techniques that you used to measure relevant variables. Be as thorough as possible for a complete picture of your techniques.
Primary and secondary measures
Define the primary and secondary outcome measures that will help you answer your primary and secondary research questions.
Specify all instruments used in gathering these measurements and the construct that they measure. These instruments may include hardware, software, or tests, scales, and inventories.
- To cite hardware, indicate the model number and manufacturer.
- To cite common software (e.g., Qualtrics), state the full name along with the version number or the website URL .
- To cite tests, scales or inventories, reference its manual or the article it was published in. It’s also helpful to state the number of items and provide one or two example items.
Make sure to report the settings of (e.g., screen resolution) any specialized apparatus used.
For each instrument used, report measures of the following:
- Reliability : how consistently the method measures something, in terms of internal consistency or test-retest reliability.
- Validity : how precisely the method measures something, in terms of construct validity or criterion validity .
Giving an example item or two for tests, questionnaires , and interviews is also helpful.
Describe any covariates—these are any additional variables that may explain or predict the outcomes.
Quality of measurements
Review all methods you used to assure the quality of your measurements.
These may include:
- training researchers to collect data reliably,
- using multiple people to assess (e.g., observe or code) the data,
- translation and back-translation of research materials,
- using pilot studies to test your materials on unrelated samples.
For data that’s subjectively coded (for example, classifying open-ended responses), report interrater reliability scores. This tells the reader how similarly each response was rated by multiple raters.
Report all of the procedures applied for administering the study, processing the data, and for planned data analyses.
Data collection methods and research design
Data collection methods refers to the general mode of the instruments: surveys, interviews, observations, focus groups, neuroimaging, cognitive tests, and so on. Summarize exactly how you collected the necessary data.
Describe all procedures you applied in administering surveys, tests, physical recordings, or imaging devices, with enough detail so that someone else can replicate your techniques. If your procedures are very complicated and require long descriptions (e.g., in neuroimaging studies), place these details in supplementary materials.
To report research design, note your overall framework for data collection and analysis. State whether you used an experimental, quasi-experimental, descriptive (observational), correlational, and/or longitudinal design. Also note whether a between-subjects or a within-subjects design was used.
For multi-group studies, report the following design and procedural details as well:
- how participants were assigned to different conditions (e.g., randomization),
- instructions given to the participants in each group,
- interventions for each group,
- the setting and length of each session(s).
Describe whether any masking was used to hide the condition assignment (e.g., placebo or medication condition) from participants or research administrators. Using masking in a multi-group study ensures internal validity by reducing research bias . Explain how this masking was applied and whether its effectiveness was assessed.
Participants were randomly assigned to a control or experimental condition. The survey was administered using Qualtrics (https://www.qualtrics.com). To begin, all participants were given the AAI and a demographics questionnaire to complete, followed by an unrelated filler task. In the control condition , participants completed a short general knowledge test immediately after the filler task. In the experimental condition, participants were asked to visualize themselves taking the test for 3 minutes before they actually did. For more details on the exact instructions and tasks given, see supplementary materials.
Data diagnostics
Outline all steps taken to scrutinize or process the data after collection.
This includes the following:
- Procedures for identifying and removing outliers
- Data transformations to normalize distributions
- Compensation strategies for overcoming missing values
To ensure high validity, you should provide enough detail for your reader to understand how and why you processed or transformed your raw data in these specific ways.
Analytic strategies
The methods section is also where you describe your statistical analysis procedures, but not their outcomes. Their outcomes are reported in the results section.
These procedures should be stated for all primary, secondary, and exploratory hypotheses. While primary and secondary hypotheses are based on a theoretical framework or past studies, exploratory hypotheses are guided by the data you’ve just collected.
This annotated example reports methods for a descriptive correlational survey on the relationship between religiosity and trust in science in the US. Hover over each part for explanation of what is included.
The sample included 879 adults aged between 18 and 28. More than half of the participants were women (56%), and all participants had completed at least 12 years of education. Ethics approval was obtained from the university board before recruitment began. Participants were recruited online through Amazon Mechanical Turk (MTurk; www.mturk.com). We selected for a geographically diverse sample within the Midwest of the US through an initial screening survey. Participants were paid USD $5 upon completion of the study.
A sample size of at least 783 was deemed necessary for detecting a correlation coefficient of ±.1, with a power level of 80% and a significance level of .05, using a sample size calculator (www.sample-size.net/correlation-sample-size/).
The primary outcome measures were the levels of religiosity and trust in science. Religiosity refers to involvement and belief in religious traditions, while trust in science represents confidence in scientists and scientific research outcomes. The secondary outcome measures were gender and parental education levels of participants and whether these characteristics predicted religiosity levels.
Religiosity
Religiosity was measured using the Centrality of Religiosity scale (Huber, 2003). The Likert scale is made up of 15 questions with five subscales of ideology, experience, intellect, public practice, and private practice. An example item is “How often do you experience situations in which you have the feeling that God or something divine intervenes in your life?” Participants were asked to indicate frequency of occurrence by selecting a response ranging from 1 (very often) to 5 (never). The internal consistency of the instrument is .83 (Huber & Huber, 2012).
Trust in Science
Trust in science was assessed using the General Trust in Science index (McCright, Dentzman, Charters & Dietz, 2013). Four Likert scale items were assessed on a scale from 1 (completely distrust) to 5 (completely trust). An example question asks “How much do you distrust or trust scientists to create knowledge that is unbiased and accurate?” Internal consistency was .8.
Potential participants were invited to participate in the survey online using Qualtrics (www.qualtrics.com). The survey consisted of multiple choice questions regarding demographic characteristics, the Centrality of Religiosity scale, an unrelated filler anagram task, and finally the General Trust in Science index. The filler task was included to avoid priming or demand characteristics, and an attention check was embedded within the religiosity scale. For full instructions and details of tasks, see supplementary materials.
For this correlational study , we assessed our primary hypothesis of a relationship between religiosity and trust in science using Pearson moment correlation coefficient. The statistical significance of the correlation coefficient was assessed using a t test. To test our secondary hypothesis of parental education levels and gender as predictors of religiosity, multiple linear regression analysis was used.
If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.
- Normal distribution
- Measures of central tendency
- Chi square tests
- Confidence interval
- Quartiles & Quantiles
Methodology
- Cluster sampling
- Stratified sampling
- Thematic analysis
- Cohort study
- Peer review
- Ethnography
Research bias
- Implicit bias
- Cognitive bias
- Conformity bias
- Hawthorne effect
- Availability heuristic
- Attrition bias
- Social desirability bias
In your APA methods section , you should report detailed information on the participants, materials, and procedures used.
- Describe all relevant participant or subject characteristics, the sampling procedures used and the sample size and power .
- Define all primary and secondary measures and discuss the quality of measurements.
- Specify the data collection methods, the research design and data analysis strategy, including any steps taken to transform the data and statistical analyses.
You should report methods using the past tense , even if you haven’t completed your study at the time of writing. That’s because the methods section is intended to describe completed actions or research.
In a scientific paper, the methodology always comes after the introduction and before the results , discussion and conclusion . The same basic structure also applies to a thesis, dissertation , or research proposal .
Depending on the length and type of document, you might also include a literature review or theoretical framework before the methodology.
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Understanding Methods for Research in Psychology
A Psychology Research Methods Study Guide
Types of Research in Psychology
- Cross-Sectional vs. Longitudinal Research
- Reliability and Validity
Glossary of Terms
Research in psychology focuses on a variety of topics , ranging from the development of infants to the behavior of social groups. Psychologists use the scientific method to investigate questions both systematically and empirically.
Research in psychology is important because it provides us with valuable information that helps to improve human lives. By learning more about the brain, cognition, behavior, and mental health conditions, researchers are able to solve real-world problems that affect our day-to-day lives.
At a Glance
Knowing more about how research in psychology is conducted can give you a better understanding of what those findings might mean to you. Psychology experiments can range from simple to complex, but there are some basic terms and concepts that all psychology students should understand.
Start your studies by learning more about the different types of research, the basics of experimental design, and the relationships between variables.
Research in Psychology: The Basics
The first step in your review should include a basic introduction to psychology research methods . Psychology research can have a variety of goals. What researchers learn can be used to describe, explain, predict, or change human behavior.
Psychologists use the scientific method to conduct studies and research in psychology. The basic process of conducting psychology research involves asking a question, designing a study, collecting data, analyzing results, reaching conclusions, and sharing the findings.
The Scientific Method in Psychology Research
The steps of the scientific method in psychology research are:
- Make an observation
- Ask a research question and make predictions about what you expect to find
- Test your hypothesis and gather data
- Examine the results and form conclusions
- Report your findings
Research in psychology can take several different forms. It can describe a phenomenon, explore the causes of a phenomenon, or look at relationships between one or more variables. Three of the main types of psychological research focus on:
Descriptive Studies
This type of research can tell us more about what is happening in a specific population. It relies on techniques such as observation, surveys, and case studies.
Correlational Studies
Correlational research is frequently used in psychology to look for relationships between variables. While research look at how variables are related, they do not manipulate any of the variables.
While correlational studies can suggest a relationship between two variables, finding a correlation does not prove that one variable causes a change in another. In other words, correlation does not equal causation.
Experimental Research Methods
Experiments are a research method that can look at whether changes in one variable cause changes in another. The simple experiment is one of the most basic methods of determining if there is a cause-and-effect relationship between two variables.
A simple experiment utilizes a control group of participants who receive no treatment and an experimental group of participants who receive the treatment.
Experimenters then compare the results of the two groups to determine if the treatment had an effect.
Cross-Sectional vs. Longitudinal Research in Psychology
Research in psychology can also involve collecting data at a single point in time, or gathering information at several points over a period of time.
Cross-Sectional Research
In a cross-sectional study , researchers collect data from participants at a single point in time. These are descriptive type of research and cannot be used to determine cause and effect because researchers do not manipulate the independent variables.
However, cross-sectional research does allow researchers to look at the characteristics of the population and explore relationships between different variables at a single point in time.
Longitudinal Research
A longitudinal study is a type of research in psychology that involves looking at the same group of participants over a period of time. Researchers start by collecting initial data that serves as a baseline, and then collect follow-up data at certain intervals. These studies can last days, months, or years.
The longest longitudinal study in psychology was started in 1921 and the study is planned to continue until the last participant dies or withdraws. As of 2003, more than 200 of the partipants were still alive.
The Reliability and Validity of Research in Psychology
Reliability and validity are two concepts that are also critical in psychology research. In order to trust the results, we need to know if the findings are consistent (reliability) and that we are actually measuring what we think we are measuring (validity).
Reliability
Reliability is a vital component of a valid psychological test. What is reliability? How do we measure it? Simply put, reliability refers to the consistency of a measure. A test is considered reliable if we get the same result repeatedly.
When determining the merits of a psychological test, validity is one of the most important factors to consider. What exactly is validity? One of the greatest concerns when creating a psychological test is whether or not it actually measures what we think it is measuring.
For example, a test might be designed to measure a stable personality trait but instead measures transitory emotions generated by situational or environmental conditions. A valid test ensures that the results accurately reflect the dimension undergoing assessment.
Review some of the key terms that you should know and understand about psychology research methods. Spend some time studying these terms and definitions before your exam. Some key terms that you should know include:
- Correlation
- Demand characteristic
- Dependent variable
- Hawthorne effect
- Independent variable
- Naturalistic observation
- Placebo effect
- Random assignment
- Replication
- Selective attrition
Erol A. How to conduct scientific research ? Noro Psikiyatr Ars . 2017;54(2):97-98. doi:10.5152/npa.2017.0120102
Aggarwal R, Ranganathan P. Study designs: Part 2 - Descriptive studies . Perspect Clin Res . 2019;10(1):34-36. doi:10.4103/picr.PICR_154_18
Curtis EA, Comiskey C, Dempsey O. Importance and use of correlational research . Nurse Res . 2016;23(6):20-25. doi:10.7748/nr.2016.e1382
Wang X, Cheng Z. Cross-sectional studies: Strengths, weaknesses, and recommendations . Chest . 2020;158(1S):S65-S71. doi:10.1016/j.chest.2020.03.012
Caruana EJ, Roman M, Hernández-Sánchez J, Solli P. Longitudinal studies . J Thorac Dis . 2015;7(11):E537-E540. doi:10.3978/j.issn.2072-1439.2015.10.63
Stanford Magazine. The vexing legacy of Lewis Terman .
By Kendra Cherry, MSEd Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."
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A complete research paper in APA style that is reporting on experimental research will typically contain a Title page, Abstract, Introduction, Methods, Results, Discussion, and References sections. 1 Many will also contain Figures and Tables and some will have an Appendix or Appendices. These sections are detailed as follows (for a more in ...
Research Methods in Psychology AP A Han dbook s in Psychology VOLUME Research Designs: Quantitative, Qualitative, Neuropsychological, and Biological SECOND EDITION Harris Cooper, Editor-in-Chief Marc N. Coutanche, Linda M. McMullen, A. T. Panter, sychological Association. Not for further distribution.
Psychology research can usually be classified as one of three major types. 1. Causal or Experimental Research. When most people think of scientific experimentation, research on cause and effect is most often brought to mind. Experiments on causal relationships investigate the effect of one or more variables on one or more outcome variables.
Common Types of Psychology Papers Research psychologists engage in a variety of kinds of writing, including grant proposals, research applications and renewals, review articles, research articles, and ... This is a research proposal. This type of paper tends to be divided into six parts, indicated by subheadings: • Abstract The abstract is a ...
Authors report original research in which the data and observed outcomes are communicated using natural language. One common type of qualitative research is the case study, in which researchers report on observations made while working closely with an individual, group, community, or other type of organization. Mixed Methods Articles
Component 1: The Title Page. • On the right side of the header, type the first 2-3 words of your full title followed by the page number. This header will appear on every page of you report. • At the top of the page, type flush left the words "Running head:" followed by an abbreviation of your title in all caps.
Here you'll find details on multiple aspects of the research paper writing process, ranging from how the paper should be structured to how to write more effectively. Structure and Format - the critical components of each section of an APA-formatted research paper (Introduction, Methods, and on), as well as how those sections should be ...
good psychology paper. Much of the information that follows is explained in greater detail by Kosslyn and Rosenberg (. 001) and Maher (1978). You are encouraged to read. both sources directly.The first step in learning to write well in field of psychology is to learn to r. ad sources critically. There are at leas.
This guide is intended as a landing page and research platform for diving deeper into the world of mental health research, academic psychology, clinical research, research methods, quantitative and qualitative research methods, and innovative science In this page you will learn about the most common types of publications in Psychology and how to identify and use them
Remember to follow APA format as you write your paper and include in-text citations for any materials you reference. Make sure to cite any information in the body of your paper in your reference section at the end of your document. Writing a psychology research paper can be intimidating at first, but breaking the process into a series of ...
III. Title: Handbook of research methods in psychology. BF76.5.A73 2012 150.72 1 dc23 2011045200 British Library Cataloguing-in-Publication Data A CIP record is available from the British Library. Printed in the United States of America ... Automated Analysis of Essays and Open-Ended Verbal Responses . . . . . . . . .307
Contractions are not allowed in formal writing. Don't use "flowery" or complex words. Never use a thesaurus when writing psychology papers; always use the simpler of two words (e.g., use vs. utilize, help vs. assist), and avoid superlatives (incredible, fantastic, amazing). Don't use unnecessary words.
Hero Images / Getty Images. Writing in psychology is formal, concise, and straightforward. When writing a psychology paper, avoid using metaphors, anecdotes, or narrative. Your paper should be well-cited and the point should be clear. In almost all cases, you will need to structure your paper in a specific way and follow the rules of APA format.
Review and conceptual articles. Articles in this category summarize previously published research or address theoretical or conceptual issues of interest to behavior analysts. Such articles support conclusions of potential theoretical, clinical, or practical importance to behavior analysts and are written in a clear and comprehensible style.
Writing Guide for Psychologists. by. Staff Writers. Updated June 28, 2024. Use this guide to learn about types of writing aspiring psychologists, helpful information about common writing styles, and a number of resources for those looking to learn more. Credit: Integrity Pictures Inc / Royalty-free Collection: The Image Bank / Getty Image.
So, for example, I might propose that the sales of research methods handbooks are caused by (a) the editor's level of compulsiveness, which affects (b) the level of expertise of those chosen to be associate editors. Next, the expertise of the associate editors affects (c) who is chosen to be chapter authors.
Introduction. Psychology is an ever-growing and popular field (Gough and Lyons, 2016; Clay, 2017).Due to this growth and the need for science-based research to base health decisions on (Perestelo-Pérez, 2013), the use of research methods in the broad field of psychology is an essential point of investigation (Stangor, 2011; Aanstoos, 2014).Research methods are therefore viewed as important ...
Olivia Guy-Evans, MSc. Research methods in psychology are systematic procedures used to observe, describe, predict, and explain behavior and mental processes. They include experiments, surveys, case studies, and naturalistic observations, ensuring data collection is objective and reliable to understand and explain psychological phenomena.
To write your methods section in APA format, describe your participants, materials, study design, and procedures. Keep this section succinct, and always write in the past tense. The main heading of this section should be labeled "Method" and it should be centered, bolded, and capitalized. Each subheading within this section should be bolded ...
Surveys. Often, psychologists develop surveys as a means of gathering data. Surveys are lists of questions to be answered by research participants, and can be delivered as paper-and-pencil questionnaires, administered electronically, or conducted verbally (Figure 3). Generally, the survey itself can be completed in a short time, and the ease of administering a survey makes it easy to collect ...
Psychological Methods ® is devoted to the development and dissemination of methods for collecting, analyzing, understanding, and interpreting psychological data. Its purpose is the dissemination of innovations in research design, measurement, methodology, and quantitative and qualitative analysis to the psychological community; its further purpose is to promote effective communication about ...
The main heading of "Methods" should be centered, boldfaced, and capitalized. Subheadings within this section are left-aligned, boldfaced, and in title case. You can also add lower level headings within these subsections, as long as they follow APA heading styles. To structure your methods section, you can use the subheadings of ...
Research in Psychology: The Basics. The first step in your review should include a basic introduction to psychology research methods. Psychology research can have a variety of goals. What researchers learn can be used to describe, explain, predict, or change human behavior. Psychologists use the scientific method to conduct studies and research ...
Social Psychology and Qualitative Research Methods, Austral University of Chile, Valdivia, Chile. Institute of Psychology, Austral University of Chile, Valdivia, Chile ... From a critical social psychology position, the paper will consider the usefulness of these concepts in revealing how the field of spirituality currently seems to be a ...
Recently published articles from subdisciplines of psychology covered by more than 90 APA Journals™ publications. For additional free resources (such as article summaries, podcasts, and more), please visit the Highlights in Psychological Research page. Browse and read free articles from APA Journals across the field of psychology, selected by ...