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What's the Difference Between a Scholarly and Non-Scholarly Article or Resource?

In academic research it is important to distinguish between scholarly (academic or expert) and non-scholarly (or popular) sources. While both types of sources are valuable in research, most academic work will favor scholarly sources over non-scholarly ones. Below you'll find a brief comparison of the two, and when to use each in your research.

Scholarly (Academic) Sources A scholarly publication is one in which the content is written by experts in a particular field of study - generally for the purpose of sharing original research or analyzing others' findings. Scholarly work will thoroughly cite all source materials used and is usually subject to "peer review" prior to publication. This means that independent experts in the field review, or "referee" the publication to check the accuracy and validity of its claims. The primary audience for this sort of work is fellow experts and students studying the field. As a result the content is typically much more accurate and advanced than articles found in general magazines, or professional/trade journals.

In brief, scholarly work is:

• written by experts for experts
• based on original research or intellectual inquiry
• provides citations for all sources used
• is usually peer reviewed prior to publication

A good example of the typical components of a scholarly journal article can be found in the Anatomy of a Scholarly Article from North Carolina State University Libraries.

Non-Scholarly (Popular) sources While many of your research projects will require you to read articles published in scholarly journals, books, or other peer reviewed sources of information, there is also a wealth of information to be found in more popular publications. These aim to inform a wide array of readers about issues of public interest and are more informal in tone and scope. Examples include general news, business, and entertainment publications such as Time Magazine , Business Weekly , and  Vanity Fair . This can also include .edu and .gov sources you've found on the Internet, that have not been verified as a scholarly source.

Note * Special interest publications which are not specifically written for an academic audience are also considered "popular" i.e., National Geographic , Scientific American , and  Psychology Today .

I've found a journal I like, but how do I know if it's scholarly or not?

One reference source that can help you make the distinction between scholarly and non-scholarly sources is: Ulrich's International Periodical Directory . Ulrich's can help you determine credibility of periodical sources as well as provide basic factual and qualitative information about many periodicals; it also indicates whether a journal is peer reviewed or not. They refer to it as being refereed . You can find which journals have been peer-reviewed by typing in the name of the journal you're searching for, and then from the search results there will be a little black heart-shaped icon nex to the title if it has been refereed. (See screen shot below)

Another way to find articles that are scholarly is to check the Peer Reviewed option box that appears in many of our databases. This way, when you search, it will only pull up journals and articles that have been peer reviewed. Below is an image of where this box is within our  EBSCO databases, but it also appears in many others, such as Academic OneFile,  all the  Gale databases, and all the ProQuest  databases.

If you are not finding your source on Ulrich's , and it doesn't meet the requirements for scholarly sources listed above, then err on the side of caution and assume it is not scholarly. Most sources, if they are from our databases, will say what journal they're from and whether or not they have been peer reviewed. 

As always, if you need help at any point finding good peer reviewed sources, please don't hesitate to Ask Us !

Scholarly or Non-Scholarly Sources Quick Guide

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Basic Research Strategies for the Social Sciences: Scholarly vs. Non-scholarly Articles

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Anatomy of a Scholarly Article

• Anatomy of a scholarly article Presented by NC State University Libraries, this interactive display shows the parts of a research article. Mouse over and click on the different parts to reveal information about each section.

Elements of a Scholarly Article

Source: University of Albany, University Libraries – Common Elements of a Scholarly Article

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Organizing Research for Arts and Humanities Papers and Theses

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What is a Scholarly Source

Both scholarly and non-scholarly materials have a place in arts and humanities research. Their use, and even their definition, depends on the context of the research project.

Books, conference publications, and academic journal articles, regardless of whether they are print-based or electronic, are common types of scholarly materials, which share the following characteristics:

• The authors are scholars or researchers with known affiliations and educational/research credentials
• The authors cite other sources, be they primary or secondary. Many scholarly publications include citations to other sources and bibliographies
• The language used is either academic or complex, and may include disciplinary or theoretical lingo
• The publisher is a scholarly press that practices editorial review to ensure that content and context adhere to the expected research parameters
• The intended audience is composed of researchers, scholars, academics, and other informed or specialized readership.

Scholarly and academic journals, which are periodic publications that contain articles, have additional characteristics, such as:

• An editorial process that is peer reviewed or refereed
• They publish long articles (essays that are ordinarily at least 10 pages), which may also inlcude an abstract. Scholarly journals often publish essay-length scholarly book reviews, which include citations to other sources
• Scholarly journals are published relatively infrequently, usually quarterly (once every 3 months), semi-annually (twice a year), or annually (once a year).

Use the points above to evaluate the scholarly nature of internet sites. It helps if the site's URL ends in .edu.

So far, so good.

But things are not always clear cut, and here are some complexities to keep in mind:

• Scholarly materials in art, architecture, theater, cinema, and related fields often include images
• Images may constitute a large portion of such publications, with text used to illustrate, contextualize, critique, or explicate the visual component
• There may be fewer citations to other sources, and the bibliographies may be shorter
• The author may be a creative practitioner, such as, for example, an architect or a playwright
• The author may be a multi-disciplinary intellectual of a transnational stature, who does not rely on the commonly acceptable scholarly apparatus. For example, works by Roland Barthes, which lack footnotes or bibliographies, are considered scholarly. An essay by Jean Baudrillard about Disneyworld, which appeared in the French daily newspaper Liberation , may also be considered scholarly, given the stature of the author and his importance in the development of a particular theoretical analysis of popular culture.

What is a Non-Scholarly Source

Non-scholarly materials usually consiste of, but are not limited to:

• News sources, newspapers, and materials that are time-based and get updated frequently
• Sources that are primarily journalistic
• Sources written for a broad readership
• Sources that are advocacy or opinion-based. Keep in mind that opinion-based articles, scholarly news, and letters to the editor get published in scholarly journals alongside scholarly articles.
• Sources that lack references to other sources
• Data and statistical publications and compilations
• Primary sources
• Trade and professional sources
• Reviews of books, movies, plays, or gallery and art shows, that are not essay-length and that do not inlcude a bibliographic context

Non-scholarly materials are legitimate sources for research in the arts and humanities, and should be used in context, just as scholarly sources must be used in context. For example, if you are researching something that happened very recently, you will have to, by necessity, use non-scholarly sources. It takes time for scholarship to be written, reviewed by peers, and published. In addition, there is no guarantee that your particular topic is of interest to other scholars. In such cases, look for scholarly materials in related areas that can provide a critical framework for you to use in analyzing your topic.

Remember to keep track of your sources, regardless of the stage of your research. The USC Libraries have an excellent guide to  citation styles  and to  citation management software . 

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Prst 3995: interdisciplinary research and project solving: finding non peer reviewed sources.

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Non Peer Reviewed Sources

Broadly speaking, a non peer reviewed source is anything that is NOT a peer reviewed journal article. A government publication, book or book chapter, a newspaper or magazine article, a website or blog post, a documentary film, or a document published by a government agency are all examples of non-peer reviewed sources. When submitting assignments, be sure to consult your course materials and professor for specific guidelines  about acceptable source types.

One other non-peer reviewed source is an article from a trade journal . Trade journals, also called trade publications, trade magazines or professional magazines, are magazines or newspapers whose target audience is people who work in a particular profession or industry. Articles in these publications are often short and the publications may contain advertisements. Examples of trade publications include Chronicle of Higher Education , Education Week , Ad Week , etc. JEWL Search and some other databases offer a source type limit for trade publications.

The descriptions and suggestions on this page are not prescribed rules--you should always evaluate an information source for relevance, authority and appropriateness for your situation. 

The databases and other resources below include non-peer reviewed sources, as does JEWL Search . You may also wish to search the internet for freely-available non peer reviewed sources. 

Internet Search

One strategy for locating non-peer reviewed sources is to search the internet. Government sponsored publications or research publications from advocacy organizations can be good source. You can limit results in a Google search to a specific domain such as .org or .gov. Here's the format for that search:

search term(s) site:. gov  OR search terms(s) site: .org

See these search results for an example of this technique.

Magazine and Trade Publication Articles

These interdisciplinary databases provide access to articles from general and professional magazines, scholarly journals and some newspapers.

• Academic Search Ultimate This link opens in a new window Fulltext multidisciplinary database of academic journals, magazines, periodicals and other reports, 19th century to present. more... less... Academic Search Ultimate is an excellent source of scholarly journals in all academic disciplines. More than 13,600 journals are indexed and full text is provided for more than 9,000. Searchable cited references are provided for selected titles

• General OneFile (Gale) This link opens in a new window Source for news and periodical articles on most topics with millions of articles in full-text.

Scholarly vs. Popular Periodicals

Scholarly Articles:  Written by and for an expert audience. Also frequently called "peer-reviewed" publications. 

Popular Articles : Written by journalists for a general readership.

Both can be valuable, depending on your need.

More information about scholarly and popular sources

Current News Databases (Fulltext)

• InfoTrac Newsstand (Now News from Gale OneFile) This link opens in a new window Full text articles from national, international, state and local newspapers, 1980 to present. Funded by Tennessee Electronic Library.
• US Newsstream Southeast This link opens in a new window Recent regional news content, as well as archives back to the 1980s, with news sources from Washington DC, Florida, Georgia, Maryland, North Carolina, South Carolina, Tennessee, Virginia, and West Virginia.
• Wall Street Journal Online 1/8/10 - Present
• The New York Times 1/1/1985 - Present

• Tennessean, The (Nashville) (1812-5 days ago) This link opens in a new window Digitized cover to cover contents of The Tennessean (Nashville) newspaper, 1812 to present (with 5 day embargo). Every page is full-text searchable. more... less... Includes full-page and article level PDFs for 1812-1922 and full-page images and PDFs for 1923-present (with 5 day embargo).
• Daily News Journal (Murfreesboro) This link opens in a new window Full text articles February 12, 1999 to present. more... less... DNJ web site is http://www.dnj.com/
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Types of journal articles

It is helpful to familiarise yourself with the different types of articles published by journals. Although it may appear there are a large number of types of articles published due to the wide variety of names they are published under, most articles published are one of the following types; Original Research, Review Articles, Short reports or Letters, Case Studies, Methodologies.

Original Research:

This is the most common type of journal manuscript used to publish full reports of data from research. It may be called an  Original Article, Research Article, Research, or just  Article, depending on the journal. The Original Research format is suitable for many different fields and different types of studies. It includes full Introduction, Methods, Results, and Discussion sections.

Short reports or Letters:

These papers communicate brief reports of data from original research that editors believe will be interesting to many researchers, and that will likely stimulate further research in the field. As they are relatively short the format is useful for scientists with results that are time sensitive (for example, those in highly competitive or quickly-changing disciplines). This format often has strict length limits, so some experimental details may not be published until the authors write a full Original Research manuscript. These papers are also sometimes called Brief communications .

Review Articles:

Review Articles provide a comprehensive summary of research on a certain topic, and a perspective on the state of the field and where it is heading. They are often written by leaders in a particular discipline after invitation from the editors of a journal. Reviews are often widely read (for example, by researchers looking for a full introduction to a field) and highly cited. Reviews commonly cite approximately 100 primary research articles.

TIP: If you would like to write a Review but have not been invited by a journal, be sure to check the journal website as some journals to not consider unsolicited Reviews. If the website does not mention whether Reviews are commissioned it is wise to send a pre-submission enquiry letter to the journal editor to propose your Review manuscript before you spend time writing it.  

Case Studies:

These articles report specific instances of interesting phenomena. A goal of Case Studies is to make other researchers aware of the possibility that a specific phenomenon might occur. This type of study is often used in medicine to report the occurrence of previously unknown or emerging pathologies.

Methodologies or Methods

These articles present a new experimental method, test or procedure. The method described may either be completely new, or may offer a better version of an existing method. The article should describe a demonstrable advance on what is currently available.

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The Importance of Non-research Articles in Scientific Publications of Health

Nowadays scientific publications online through electronic journals are becoming increasingly widespread. Many recent findings have been published through this system so that they can be deployed quickly, so that they can be used immediately by those who need them. Most of the articles that have been published in the form of research articles. This type of article is a summary of research reports conducted by researchers with the intention of getting spread widely so that it can be a reference for other researchers in their research activities, or applicable directly to those who need it. On the other hand, there are also types of non-research articles that are not less useful value such as opinion articles and correspondence. The opinion articles contain opinions about certain phenomena that can lead to ideas for further study, whereas correspondence articles contain responses to published articles. Keywords: Health, Non-research article, Correspondence, Opinion

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Non-Empirical Research

Non-Empirical Research articles focus more on theories, methods and their implications for education research. Non-Empirical Research can include comprehensive reviews and articles that focus on methodology. It should rely on empirical research literature as well but does not need to be essentially data-driven.

The title page should:

• present a title that includes, if appropriate, the research design
• if a collaboration group should be listed as an author, please list the Group name as an author and include the names of the individual members of the Group in the “Acknowledgements” section in accordance with the instructions below
• indicate the corresponding author
• Declarations: all manuscripts must contain the following sections under the heading 'Declarations': 1. Availability of data and material 2.Competing interests 3. Funding 4. Authors' contributions 5. Acknowledgements 6. Authors' information (optional) Please see below for details on the information to be included in these sections. If any of the sections are not relevant to your manuscript, please include the heading and write 'Not applicable' for that section. 1. Availability of data and materials All manuscripts must include an ‘Availability of data and materials’ statement. Data availability statements should include information on where data supporting the results reported in the article can be found including, where applicable, hyperlinks to publicly archived datasets analysed or generated during the study. By data we mean the minimal dataset that would be necessary to interpret, replicate and build upon the findings reported in the article. We recognise it is not always possible to share research data publicly, for instance when individual privacy could be compromised, and in such instances data availability should still be stated in the manuscript along with any conditions for access. Data availability statements can take one of the following forms (or a combination of more than one if required for multiple datasets):
• The datasets generated and/or analysed during the current study are available in the [NAME] repository, [PERSISTENT WEB LINK TO DATASETS]
• The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.
• All data generated or analysed during this study are included in this published article [and its supplementary information files].
• The datasets generated and/or analysed during the current study are not publicly available due [REASON WHY DATA ARE NOT PUBLIC] but are available from the corresponding author on reasonable request.
• Data sharing is not applicable to this article as no datasets were generated or analysed during the current study.
• The data that support the findings of this study are available from [third party name] but restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly available. Data are however available from the authors upon reasonable request and with permission of [third party name].
• Not applicable. If your manuscript does not contain any data, please state 'Not applicable' in this section.

More examples of template data availability statements, which include examples of openly available and restricted access datasets, are available  here .

SpringerOpen  also requires that authors cite any publicly available data on which the conclusions of the paper rely in the manuscript. Data citations should include a persistent identifier (such as a DOI) and should ideally be included in the reference list. Citations of datasets, when they appear in the reference list, should include the minimum information recommended by DataCite and follow journal style. Dataset identifiers including DOIs should be expressed as full URLs. For example:

Hao Z, AghaKouchak A, Nakhjiri N, Farahmand A. Global integrated drought monitoring and prediction system (GIDMaPS) data sets. figshare. 2014.  http://dx.doi.org/10.6084/m9.figshare.853801

With the corresponding text in the Availability of data and materials statement:

The datasets generated during and/or analysed during the current study are available in the [NAME] repository, [PERSISTENT WEB LINK TO DATASETS]. [Reference number]

2. Competing interests

All financial and non-financial competing interests must be declared in this section.

See our  editorial policies  for a full explanation of competing interests. If you are unsure whether you or any of your co-authors have a competing interest please contact the editorial office.

Please use the authors’ initials to refer to each authors' competing interests in this section.

If you do not have any competing interests, please state "The authors declare that they have no competing interests" in this section.

All sources of funding for the research reported should be declared. The role of the funding body in the design of the study and collection, analysis, and interpretation of data and in writing the manuscript should be declared.

4. Authors' contributions

The individual contributions of authors to the manuscript should be specified in this section. Guidance and criteria for authorship can be found in our  editorial policies .

Please use initials to refer to each author's contribution in this section, for example: "FC analyzed and interpreted the patient data regarding the hematological disease and the transplant. RH performed the histological examination of the kidney, and was a major contributor in writing the manuscript. All authors read and approved the final manuscript."

5. Acknowledgements

Please acknowledge anyone who contributed towards the article who does not meet the criteria for authorship including anyone who provided professional writing services or materials.

Authors should obtain permission to acknowledge from all those mentioned in the Acknowledgements section.

See our  editorial policies  for a full explanation of acknowledgements and authorship criteria.

If you do not have anyone to acknowledge, please write "Not applicable" in this section.

Group authorship (for manuscripts involving a collaboration group): if you would like the names of the individual members of a collaboration Group to be searchable through their individual PubMed records, please ensure that the title of the collaboration Group is included on the title page and in the submission system and also include collaborating author names as the last paragraph of the “Acknowledgements” section. Please add authors in the format First Name, Middle initial(s) (optional), Last Name. You can add institution or country information for each author if you wish, but this should be consistent across all authors.

6. Authors' information : This section is optional.

You may choose to use this section to include any relevant information about the author(s) that may aid the reader's interpretation of the article, and understand the standpoint of the author(s). This may include details about the authors' qualifications, current positions they hold at institutions or societies, or any other relevant background information. Please refer to authors using their initials. Note this section should not be used to describe any competing interests

Blinded Manuscript

Abstract The abstract should briefly summarize the aim, findings or purpose of the article. Please minimize the use of abbreviations and do not cite references in the abstract.

See the criteria section for this article type (located at the top of this page) for information on article word limits.

Three to ten keywords representing the main content of the article.

Introduction

The Introduction section should explain the background to the article, its aims, a summary of a search of the existing literature and the issue under discussion.

This should contain the body of the article, and may also be broken into subsections with short, informative headings.

Conclusions

This should state clearly the main conclusions and include an explanation of their relevance or importance to the field.

List of abbreviations

If abbreviations are used in the text they should be defined in the text at first use, and a list of abbreviations should be provided.

Examples of the American Psychological Association (APA) reference style are shown below. For further guidance, see the Publication Manual of the American Psychological Association and the respective web site of the Association ( http://www.apastyle.org/ ).

See our editorial policies for author guidance on good citation practice.

Web links and URLs: All web links and URLs, including links to the authors' own websites, should be given a reference number and included in the reference list rather than within the text of the manuscript. They should be provided in full, including both the title of the site and the URL, as well as the date the site was accessed, in the following format: The Mouse Tumor Biology Database. http://tumor.informatics.jax.org/mtbwi/index.do . Accessed 20 May 2013. If an author or group of authors can clearly be associated with a web link, such as for weblogs, then they should be included in the reference.

Example reference style:

Article within a journal

Harris, M., Karper, E., Stacks, G., Hoffman, D., DeNiro, & R., Cruz, P. (2001). Writing labs and the Hollywood connection. Journal of Film Writing , 44 (3), 213-245.

Article by DOI (with page numbers)

Slifka, M.K., & Whitton, J.L. (2000). Clinical implications of dysregulated cytokine production. Journal of Molecular Medicine , 78 (2), 74-80. doi:10.1007/s001090000086.

Article by DOI (before issue publication and without page numbers)

Kreger, M., Brindis, C.D., Manuel, D.M., & Sassoubre, L. (2007). Lessons learned in systems change initiatives: benchmarks and indicators. American Journal of Community Psychology . doi: 10.1007/s10464-007-9108-14.

Article in electronic journal by DOI (no paginated version)

Kruger, M., Brandis, C.D., Mandel, D.M., & Sassoure, J. (2007). Lessons to be learned in systems change initiatives: benchmarks and indicators. American Journal of Digital Psychology . doi: 10.1007/s10469-007-5108-14.

Complete book

Calfee, R.C., & Valencia, R.R. (1991). APA guide to preparing manuscripts for journal publication. Washington, DC: American Psychological Association.

Book chapter, or an article within a book

O'Neil, J.M., & Egan, J. (1992). Men's and women's gender role journeys: Metaphor for healing, transition, and transformation. In B.R. Wainrib (Ed.), Gender issues across the life cycle (pp. 107-123). New York: Springer .

Online First chapter in a series (without a volume designation but with a DOI)

Saito, Y., & Hyuga, H. (2007). Rate equation approaches to amplification of enantiomeric excess and chiral symmetry breaking. Topics in Current Chemistry . doi:10.1007/128_2006_108.

Complete book, also showing a translated edition [Either edition may be listed first.]

Adorno, T.W. (1966). Negative Dialektik . Frankfurt: Suhrkamp. English edition: Adorno, TW (1973). Negative Dialectics (trans: Ashton, E.B.). London: Routledge.

Online document

Abou-Allaban, Y., Dell, M.L., Greenberg, W., Lomax, J., Peteet, J., Torres, M., & Cowell, V. (2006). Religious/spiritual commitments and psychiatric practice. Resource document. American Psychiatric Association. http://www.psych.org/edu/other_res/lib_archives/archives/200604.pdf. Accessed 25 June 2007.

Online database

German emigrants database (1998). Historisches Museum Bremerhaven. http://www.deutsche-auswanderer-datenbank.de. Accessed 21 June 2007.

Supplementary material/private homepage

Doe, J. (2006). Title of supplementary material. http://www.privatehomepage.com. Accessed 22 Feb 2007.

Doe, J. (1999). Trivial HTTP, RFC2169. ftp://ftp.isi.edu/in-notes/rfc2169.txt. Accessed 12 Feb 2006.

Organization site

ISSN International Centre (2006). The ISSN register. http://www.issn.org. Accessed 20 Feb 2007.

Figures, tables and additional files

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4 Chapter 4 (Non-academic Sources)

There are some sources that a simple search engine will pull up time and again. Most of these sources are poorly vetted or shallow at best or have an agenda or perpetuate errors at worst. However, instead of summarily dismissing them, it is worth diving into sources that some people might be inclined to lean on at first and then exploring why they are problematic.

The best of the worst, references are works that contain facts and information that one can use to “look up” basic information. Most students in K-12 schools are familiar with using references at least to some degree, and they can feel like a comfortable place to start. However, references are a great example of how a “source” can be useful for general interest inquiries but not all that useful for actual research. References are actually not sources in any pure sense. Britannica and Wikipedia do not actually perform research. Instead, they convey the results of the research that others hand conducted, at best.

This does not mean that references are useless. It means that what references can be used for it limited.  More often than not, references convey information that is compiled and summarized by a non-expert, using more credible sources at their base. In essence, most encyclopedia entries are far closer in quality to college student papers than they are to expert works.

Consider dictionaries, a staple of the K-12 essay. Even dictionaries are wrong, or at least imprecise, based on editorial practices. For example, as of January 2022, the Merriam-Webster dictionary offered the following definition of carnosaur : “any of a group (Carnosauria) of very large theropod dinosaurs (such as a tyrannosaur)”. The problem with this definition is that tyrannosaurs are not carnosaurs, they are coelurosaurs (a related family that is still a different group), and this has been pretty well-established since the 1990s. Does this make a huge difference? It does if the researcher finds information specific to carnosaurs or tyrannosaurs and mistakenly applies it across both groups.

The same dictionary’s definition of autism also encounters some problems: “a variable developmental disorder that appears by age three and is characterized especially by difficulties in forming and maintaining social relationships, by impairment of the ability to communicate verbally or nonverbally, and by repetitive behavior patterns and restricted interests and activities.” Note the language “appears by age three” and consider what that means. ASD is sometimes not diagnosed until adulthood (some 50-year-olds have received such a diagnosis for the first time), and so this definition can be problematic if the person using the definition over-applies it and assumes that the four words in question have medical significance or represent technically sound specificity.

Encyclopedias (online or otherwise) run into the same problems to a lesser degree. By default, when a non-expert tries to condense technical information, that information begins to lose accuracy. This does not mean that researchers should not use references. It means that they should not use references as sources of information, but rather as a means of better understanding information that has been researched.

List-icles and Opinion Pieces

A number of websites (e.g. ProCon.org) offer lists of ideas for why someone might be in favor of a particular proposition or against it. However, not only are these websites often engaging in the fallacy of a false dichotomy, they seldom actually provide evidence for their claims. Instead, they simply list claims made by individuals without providing the underlying evidence or warrants to support those claims. As a result, all they really establish as “sources” is that some people were able to think of the claims as ideas that might be reasons someone might have a belief. They do not, even, establish that anyone believes such things.

One of the most common mistakes made in college writing is when students mistake finding someone who agrees with their opinions with finding evidence. For example, I might find someone who agrees with me that the Loch Ness monster exists, but that does not mean I have any additional evidence of its existence. Instead, “evidence” is present when someone is able to provide both demonstrable facts in support of a claim and is able to articulate the way in which that evidence supports the claim.

For example, the fact that proto-feathers are present on multiple “raptor” dinosaurs and on non-carnivorous dinosaurs is evidence that feather-like structures likely evolved early in the dinosaur family tree (because it is more likely that the same trait developed once and then spread than that the same trait developed multiple times independently in related species). Note that this does not mean I’ve “won,” because convergent evolution is a real phenomenon. It is, however, evidence for my claim. By contrast, having made a friend on Reddit who agrees that raptors look “dumb” with feathers is not evidence.

Likewise, editorial and opinion pieces are frequently carried by newspapers and other organizations. However, that does not mean that they are reliable sources of information. In fact, opinion pieces are so unreliable that courts have actually found that they are not accountable for accurate presentation of facts. In one case, media personality Tucker Carlson’s own lawyers successfully argued in his favor that he could not be held accountable for statements he made because “any reasonable viewer arrives with an appropriate amount of skepticism about the statements he makes” despite the commentary itself being framed with the claim “remember the facts of the story. These are undisputed.”

The lesson for any researcher is clear—be skeptical of almost any supposed source, and do not assume that just because a source claims to be offering facts that it is, in fact, doing so, even if the source shares a platform with news agencies.

Think back to the Toulmin model discussed in an earlier chapter. If the article in question (be it a list, a blog, or an opinion piece) offers data, warrants, and claims then it might be a worthwhile place to start research and get ideas. However, usually each of these pieces is nothing more than another person’s opinion.

News Reports

Of course, the prior section leads to the issue of news reports themselves. There are often suspect—not because they are wrong , but because they have a very different function than presenting information a complete view of an issue. News outlets frequently run into the same problems as references, in that they are staffed not by experts in individual disciplines but rather by individuals who are simply trying to convey information quickly. Likewise, the pressure to offer a story as soon as possible can frequently lead to inaccuracies in the name of expediency.

More importantly than those structural issues, however, is a deeper problem with news outlets. If a paleontologist discovers a new fossil and reports it to the news, the news outlet does not actually perform an examination of the fossil. Instead, it conveys what the paleontologist says about the fossil. If a politician tries to support a new law, the news outlet does not perform a deep analysis of the implications of the law—it quotes what the politician has to say about the law. Sometimes, in the interest of parity, the news outlet will take an additional step to find a paleontologist who disagrees with the first or to find a political opponent who dislikes the law. This might create an illusion of doubt where it does not exist among experts, but it might also force the discussion into binaries when a range of options exist. Note that the word used for news is medium (the plural being media), a word that actually refers to the role that news plays—it’s a bridge between the actual source and the reader. It is only as accurate as the original source, and then only if the bridge itself conveys the information reliably.

Frequently, news articles run into the problem that their sources of information are people who are biased on the news being reported. They might learn about a new business venture from a mega corporation from a press release put out by that very same corporation. A mayor might announce a new city-wide project and discuss all the benefits without explaining the drawbacks. In these cases, the news outlet does not always engage in fact-checking. Frequently, it will simply say “so-and-so says the project will bring new jobs,” and then expect the reader to evaluate whether or not the mayor in question was being honest.

An additional complication that comes from news sources is that sometimes they face pressure to provide “fair” reporting of politically charged subjects. Often, this means finding individuals with differing viewpoints and giving both individuals equivalent time or space. People receiving these two seemingly balanced reports might conclude that there are equal chances of each perspective being valid. That is seldom the case. The seeming parity is an artifact of how the subject is presented, not how much evidence there is to support each claim.

Activist Websites and Private Projects

One of the most concerning issues with a web search is how easy it is to confuse quantity with quality, and how easy it is to be led astray. It is very easy to come across private websites promoting individual causes, or else works that exist to further one particular person’s viewpoint. Some of these websites might even look “official” or professionally done. That does not mean that the information on these websites is correct.

Consider the issue of vertebrate evolution and David Peters, a paleo artist with a scientifically trained background. A simple search engine check would show that he seems to have some credentials in the subject of evolution and he has multiple published books. Maybe his work should be fine for “just facts,” especially since his website can be on the first page of sources? No. While Peters updates his webpage actively (helping it move up in search engine algorithms) and while his work in the 1980s, 1990s, and even a little bit afterward tended to represent scientific consensus, at some point he started pushing a number of unsupported claims about animal evolution, and he did so despite the fact that multiple experts offered correction on his mistakes. Most of his claims were unsupported and obviously inaccurate. However, a researcher unaware of this background could be misled.

Note that the same steps that were introduced in previous chapters would be highly useful, here. Is there independent confirmation? No. Transparency? Not really.

On the subject of neurodiversity, the organization Autism Speaks is one of the largest organizations that addresses ASD. However, the organization has frequently been criticized by members of the ASD community, specifically for furthering negative portrayals of neurodiversity and for excluding voices of the ASD themselves. It has been steadily criticized for privileging the viewpoint of its founders and not taking into consideration the current state of research. Here, the popularity and the high profile of this organization can lead to other problems, because it is relatively easy to find other sources that have gained their information from Autism Speaks . Therefore, tracing each source back to its origin is essential to finding quality research.

Unfortunately, a number of students have learned to trust .org and .gov websites due to overly simplistic one-size-fits-all guidelines from their childhood. However, .orgs are often transparently partisan websites, representing politically motivated organizations that actively seek to spread their own version of information as part of a persuasive effort to convert others to their cause–PETA.org, NRA.org, youthrights.org, and so on. Additionally, .gov websites are by definition overseen by those in political office, at least indirectly, and it’s probably unrealistic to expect whitehouse.gov to offer a nuanced account of the agenda of the chief executive.

Similarly, videos might be persuasive (they engage senses and are accompanied by clear charts or graphics, or else other images). Those videos, however, are often produced with funding or resources of those with an agenda. They are then written and directed by individuals with personal opinions and investment in the subject. They are seldom backed up with clear references or objective analysis. All videos (and many activist documentaries) really represent are editorials turned into video form.

Consider one widely distributed documentary that was aimed at the fast food industry in the 2000s. Supposedly a chronicle of one person’s journey through eating fast food, it left out a number of details: the star and his romantic partner were both Vegans, which likely had an impact on his body’s reaction to the food involved, his psychological responses to the diet, and even his motives for the documentary; he had a prior history of a chronic health condition that was left out of the movie; and he forced himself to eat past the point of being full (which is not how most people eat). When challenged, the documentary maker refused to share his food logs, however, and no one else was able to match his results–either in terms of weight gain or side effects–using the same protocol. The documentary was unquestionably persuasive, but it does not actually provide any actual evidence. Instead, it represents a deliberate attempt to attack an industry. It being a successful attack does not increase the factual validity of its claims.

Research, Evidence, and Written Arguments Copyright © by jsunderb. All Rights Reserved.

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6.1: Overview of Non-Experimental Research

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Learning Objectives

• Define non-experimental research, distinguish it clearly from experimental research, and give several examples.
• Explain when a researcher might choose to conduct non-experimental research as opposed to experimental research.

What Is Non-Experimental Research?

Non-experimental research is research that lacks the manipulation of an independent variable. Rather than manipulating an independent variable, researchers conducting non-experimental research simply measure variables as they naturally occur (in the lab or real world).

Most researchers in psychology consider the distinction between experimental and non-experimental research to be an extremely important one. This is because although experimental research can provide strong evidence that changes in an independent variable cause differences in a dependent variable, non-experimental research generally cannot. As we will see, however, this inability to make causal conclusions does not mean that non-experimental research is less important than experimental research.

When to Use Non-Experimental Research

As we saw in the last chapter , experimental research is appropriate when the researcher has a specific research question or hypothesis about a causal relationship between two variables—and it is possible, feasible, and ethical to manipulate the independent variable. It stands to reason, therefore, that non-experimental research is appropriate—even necessary—when these conditions are not met. There are many times in which non-experimental research is preferred, including when:

• the research question or hypothesis relates to a single variable rather than a statistical relationship between two variables (e.g., How accurate are people’s first impressions?).
• the research question pertains to a non-causal statistical relationship between variables (e.g., is there a correlation between verbal intelligence and mathematical intelligence?).
• the research question is about a causal relationship, but the independent variable cannot be manipulated or participants cannot be randomly assigned to conditions or orders of conditions for practical or ethical reasons (e.g., does damage to a person’s hippocampus impair the formation of long-term memory traces?).
• the research question is broad and exploratory, or is about what it is like to have a particular experience (e.g., what is it like to be a working mother diagnosed with depression?).

Again, the choice between the experimental and non-experimental approaches is generally dictated by the nature of the research question. Recall the three goals of science are to describe, to predict, and to explain. If the goal is to explain and the research question pertains to causal relationships, then the experimental approach is typically preferred. If the goal is to describe or to predict, a non-experimental approach will suffice. But the two approaches can also be used to address the same research question in complementary ways. For example, Similarly, after his original study, Milgram conducted experiments to explore the factors that affect obedience. He manipulated several independent variables, such as the distance between the experimenter and the participant, the participant and the confederate, and the location of the study (Milgram, 1974) [1] .

Types of Non-Experimental Research

Non-experimental research falls into three broad categories: cross-sectional research, correlational research, and observational research.

First, cross-sectional research involves comparing two or more pre-existing groups of people. What makes this approach non-experimental is that there is no manipulation of an independent variable and no random assignment of participants to groups. Imagine, for example, that a researcher administers the Rosenberg Self-Esteem Scale to 50 American college students and 50 Japanese college students. Although this “feels” like a between-subjects experiment, it is a cross-sectional study because the researcher did not manipulate the students’ nationalities. As another example, if we wanted to compare the memory test performance of a group of cannabis users with a group of non-users, this would be considered a cross-sectional study because for ethical and practical reasons we would not be able to randomly assign participants to the cannabis user and non-user groups. Rather we would need to compare these pre-existing groups which could introduce a selection bias (the groups may differ in other ways that affect their responses on the dependent variable). For instance, cannabis users are more likely to use more alcohol and other drugs and these differences may account for differences in the dependent variable across groups, rather than cannabis use per se.

Cross-sectional designs are commonly used by developmental psychologists who study aging and by researchers interested in sex differences. Using this design, developmental psychologists compare groups of people of different ages (e.g., young adults spanning from 18-25 years of age versus older adults spanning 60-75 years of age) on various dependent variables (e.g., memory, depression, life satisfaction). Of course, the primary limitation of using this design to study the effects of aging is that differences between the groups other than age may account for differences in the dependent variable. For instance, differences between the groups may reflect the generation that people come from (a cohort effect) rather than a direct effect of age. For this reason, longitudinal studies in which one group of people is followed as they age offer a superior means of studying the effects of aging. Once again, cross-sectional designs are also commonly used to study sex differences. Since researchers cannot practically or ethically manipulate the sex of their participants they must rely on cross-sectional designs to compare groups of men and women on different outcomes (e.g., verbal ability, substance use, depression). Using these designs researchers have discovered that men are more likely than women to suffer from substance abuse problems while women are more likely than men to suffer from depression. But, using this design it is unclear what is causing these differences. So, using this design it is unclear whether these differences are due to environmental factors like socialization or biological factors like hormones?

When researchers use a participant characteristic to create groups (nationality, cannabis use, age, sex), the independent variable is usually referred to as an experimenter-selected independent variable (as opposed to the experimenter-manipulated independent variables used in experimental research). Figure \(\PageIndex{1}\) shows data from a hypothetical study on the relationship between whether people make a daily list of things to do (a “to-do list”) and stress. Notice that it is unclear whether this is an experiment or a cross-sectional study because it is unclear whether the independent variable was manipulated by the researcher or simply selected by the researcher. If the researcher randomly assigned some participants to make daily to-do lists and others not to, then the independent variable was experimenter-manipulated and it is a true experiment. If the researcher simply asked participants whether they made daily to-do lists or not, then the independent variable it is experimenter-selected and the study is cross-sectional. The distinction is important because if the study was an experiment, then it could be concluded that making the daily to-do lists reduced participants’ stress. But if it was a cross-sectional study, it could only be concluded that these variables are statistically related. Perhaps being stressed has a negative effect on people’s ability to plan ahead. Or perhaps people who are more conscientious are more likely to make to-do lists and less likely to be stressed. The crucial point is that what defines a study as experimental or cross-sectional l is not the variables being studied, nor whether the variables are quantitative or categorical, nor the type of graph or statistics used to analyze the data. It is how the study is conducted.

Second, the most common type of non-experimental research conducted in Psychology is correlational research. Correlational research is considered non-experimental because it focuses on the statistical relationship between two variables but does not include the manipulation of an independent variable. More specifically, in correlational research , the researcher measures two continuous variables with little or no attempt to control extraneous variables and then assesses the relationship between them. As an example, a researcher interested in the relationship between self-esteem and school achievement could collect data on students’ self-esteem and their GPAs to see if the two variables are statistically related. Correlational research is very similar to cross-sectional research, and sometimes these terms are used interchangeably. The distinction that will be made in this book is that, rather than comparing two or more pre-existing groups of people as is done with cross-sectional research, correlational research involves correlating two continuous variables (groups are not formed and compared).

Third, observational research is non-experimental because it focuses on making observations of behavior in a natural or laboratory setting without manipulating anything. Milgram’s original obedience study was non-experimental in this way. He was primarily interested in the extent to which participants obeyed the researcher when he told them to shock the confederate and he observed all participants performing the same task under the same conditions. The study by Loftus and Pickrell described at the beginning of this chapter is also a good example of observational research. The variable was whether participants “remembered” having experienced mildly traumatic childhood events (e.g., getting lost in a shopping mall) that they had not actually experienced but that the researchers asked them about repeatedly. In this particular study, nearly a third of the participants “remembered” at least one event. (As with Milgram’s original study, this study inspired several later experiments on the factors that affect false memories.

The types of research we have discussed so far are all quantitative, referring to the fact that the data consist of numbers that are analyzed using statistical techniques. But as you will learn in this chapter, many observational research studies are more qualitative in nature. In qualitative research , the data are usually nonnumerical and therefore cannot be analyzed using statistical techniques. Rosenhan’s observational study of the experience of people in a psychiatric ward was primarily qualitative. The data were the notes taken by the “pseudopatients”—the people pretending to have heard voices—along with their hospital records. Rosenhan’s analysis consists mainly of a written description of the experiences of the pseudopatients, supported by several concrete examples. To illustrate the hospital staff’s tendency to “depersonalize” their patients, he noted, “Upon being admitted, I and other pseudopatients took the initial physical examinations in a semi-public room, where staff members went about their own business as if we were not there” (Rosenhan, 1973, p. 256) [2] . Qualitative data has a separate set of analysis tools depending on the research question. For example, thematic analysis would focus on themes that emerge in the data or conversation analysis would focus on the way the words were said in an interview or focus group.

Internal Validity Revisited

Recall that internal validity is the extent to which the design of a study supports the conclusion that changes in the independent variable caused any observed differences in the dependent variable. Figure \(\PageIndex{2}\) shows how experimental, quasi-experimental, and non-experimental (correlational) research vary in terms of internal validity. Experimental research tends to be highest in internal validity because the use of manipulation (of the independent variable) and control (of extraneous variables) help to rule out alternative explanations for the observed relationships. If the average score on the dependent variable in an experiment differs across conditions, it is quite likely that the independent variable is responsible for that difference. Non-experimental (correlational) research is lowest in internal validity because these designs fail to use manipulation or control. Quasi-experimental research (which will be described in more detail in a subsequent chapter) is in the middle because it contains some, but not all, of the features of a true experiment. For instance, it may fail to use random assignment to assign participants to groups or fail to use counterbalancing to control for potential order effects. Imagine, for example, that a researcher finds two similar schools, starts an anti-bullying program in one, and then finds fewer bullying incidents in that “treatment school” than in the “control school.” While a comparison is being made with a control condition, the lack of random assignment of children to schools could still mean that students in the treatment school differed from students in the control school in some other way that could explain the difference in bullying (e.g., there may be a selection effect).

Notice also in Figure \(\PageIndex{2}\) that there is some overlap in the internal validity of experiments, quasi-experiments, and correlational studies. For example, a poorly designed experiment that includes many confounding variables can be lower in internal validity than a well-designed quasi-experiment with no obvious confounding variables. Internal validity is also only one of several validities that one might consider, as noted in Chapter 5.

Key Takeaways

• Non-experimental research is research that lacks the manipulation of an independent variable.
• There are two broad types of non-experimental research. Correlational research that focuses on statistical relationships between variables that are measured but not manipulated, and observational research in which participants are observed and their behavior is recorded without the researcher interfering or manipulating any variables.
• In general, experimental research is high in internal validity, correlational research is low in internal validity, and quasi-experimental research is in between.
• A researcher conducts detailed interviews with unmarried teenage fathers to learn about how they feel and what they think about their role as fathers and summarizes their feelings in a written narrative.
• A researcher measures the impulsivity of a large sample of drivers and looks at the statistical relationship between this variable and the number of traffic tickets the drivers have received.
• A researcher randomly assigns patients with low back pain either to a treatment involving hypnosis or to a treatment involving exercise. She then measures their level of low back pain after 3 months.
• A college instructor gives weekly quizzes to students in one section of his course but no weekly quizzes to students in another section to see whether this has an effect on their test performance.
• Milgram, S. (1974). Obedience to authority: An experimental view . New York, NY: Harper & Row.
• Rosenhan, D. L. (1973). On being sane in insane places. Science, 179 , 250–258.

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Non-Experimental Research

28 Overview of Non-Experimental Research

Learning objectives.

• Define non-experimental research, distinguish it clearly from experimental research, and give several examples.
• Explain when a researcher might choose to conduct non-experimental research as opposed to experimental research.

What Is Non-Experimental Research?

Non-experimental research  is research that lacks the manipulation of an independent variable. Rather than manipulating an independent variable, researchers conducting non-experimental research simply measure variables as they naturally occur (in the lab or real world).

Most researchers in psychology consider the distinction between experimental and non-experimental research to be an extremely important one. This is because although experimental research can provide strong evidence that changes in an independent variable cause differences in a dependent variable, non-experimental research generally cannot. As we will see, however, this inability to make causal conclusions does not mean that non-experimental research is less important than experimental research. It is simply used in cases where experimental research is not able to be carried out.

When to Use Non-Experimental Research

As we saw in the last chapter , experimental research is appropriate when the researcher has a specific research question or hypothesis about a causal relationship between two variables—and it is possible, feasible, and ethical to manipulate the independent variable. It stands to reason, therefore, that non-experimental research is appropriate—even necessary—when these conditions are not met. There are many times in which non-experimental research is preferred, including when:

• the research question or hypothesis relates to a single variable rather than a statistical relationship between two variables (e.g., how accurate are people’s first impressions?).
• the research question pertains to a non-causal statistical relationship between variables (e.g., is there a correlation between verbal intelligence and mathematical intelligence?).
• the research question is about a causal relationship, but the independent variable cannot be manipulated or participants cannot be randomly assigned to conditions or orders of conditions for practical or ethical reasons (e.g., does damage to a person’s hippocampus impair the formation of long-term memory traces?).
• the research question is broad and exploratory, or is about what it is like to have a particular experience (e.g., what is it like to be a working mother diagnosed with depression?).

Again, the choice between the experimental and non-experimental approaches is generally dictated by the nature of the research question. Recall the three goals of science are to describe, to predict, and to explain. If the goal is to explain and the research question pertains to causal relationships, then the experimental approach is typically preferred. If the goal is to describe or to predict, a non-experimental approach is appropriate. But the two approaches can also be used to address the same research question in complementary ways. For example, in Milgram’s original (non-experimental) obedience study, he was primarily interested in one variable—the extent to which participants obeyed the researcher when he told them to shock the confederate—and he observed all participants performing the same task under the same conditions. However,  Milgram subsequently conducted experiments to explore the factors that affect obedience. He manipulated several independent variables, such as the distance between the experimenter and the participant, the participant and the confederate, and the location of the study (Milgram, 1974) [1] .

Types of Non-Experimental Research

Non-experimental research falls into two broad categories: correlational research and observational research. 

The most common type of non-experimental research conducted in psychology is correlational research. Correlational research is considered non-experimental because it focuses on the statistical relationship between two variables but does not include the manipulation of an independent variable. More specifically, in correlational research , the researcher measures two variables with little or no attempt to control extraneous variables and then assesses the relationship between them. As an example, a researcher interested in the relationship between self-esteem and school achievement could collect data on students’ self-esteem and their GPAs to see if the two variables are statistically related.

Observational research  is non-experimental because it focuses on making observations of behavior in a natural or laboratory setting without manipulating anything. Milgram’s original obedience study was non-experimental in this way. He was primarily interested in the extent to which participants obeyed the researcher when he told them to shock the confederate and he observed all participants performing the same task under the same conditions. The study by Loftus and Pickrell described at the beginning of this chapter is also a good example of observational research. The variable was whether participants “remembered” having experienced mildly traumatic childhood events (e.g., getting lost in a shopping mall) that they had not actually experienced but that the researchers asked them about repeatedly. In this particular study, nearly a third of the participants “remembered” at least one event. (As with Milgram’s original study, this study inspired several later experiments on the factors that affect false memories).

Cross-Sectional, Longitudinal, and Cross-Sequential Studies

When psychologists wish to study change over time (for example, when developmental psychologists wish to study aging) they usually take one of three non-experimental approaches: cross-sectional, longitudinal, or cross-sequential. Cross-sectional studies involve comparing two or more pre-existing groups of people (e.g., children at different stages of development). What makes this approach non-experimental is that there is no manipulation of an independent variable and no random assignment of participants to groups. Using this design, developmental psychologists compare groups of people of different ages (e.g., young adults spanning from 18-25 years of age versus older adults spanning 60-75 years of age) on various dependent variables (e.g., memory, depression, life satisfaction). Of course, the primary limitation of using this design to study the effects of aging is that differences between the groups other than age may account for differences in the dependent variable. For instance, differences between the groups may reflect the generation that people come from (a cohort effect ) rather than a direct effect of age. For this reason, longitudinal studies , in which one group of people is followed over time as they age, offer a superior means of studying the effects of aging. However, longitudinal studies are by definition more time consuming and so require a much greater investment on the part of the researcher and the participants. A third approach, known as cross-sequential studies , combines elements of both cross-sectional and longitudinal studies. Rather than measuring differences between people in different age groups or following the same people over a long period of time, researchers adopting this approach choose a smaller period of time during which they follow people in different age groups. For example, they might measure changes over a ten year period among participants who at the start of the study fall into the following age groups: 20 years old, 30 years old, 40 years old, 50 years old, and 60 years old. This design is advantageous because the researcher reaps the immediate benefits of being able to compare the age groups after the first assessment. Further, by following the different age groups over time they can subsequently determine whether the original differences they found across the age groups are due to true age effects or cohort effects.

The types of research we have discussed so far are all quantitative, referring to the fact that the data consist of numbers that are analyzed using statistical techniques. But as you will learn in this chapter, many observational research studies are more qualitative in nature. In  qualitative research , the data are usually nonnumerical and therefore cannot be analyzed using statistical techniques. Rosenhan’s observational study of the experience of people in psychiatric wards was primarily qualitative. The data were the notes taken by the “pseudopatients”—the people pretending to have heard voices—along with their hospital records. Rosenhan’s analysis consists mainly of a written description of the experiences of the pseudopatients, supported by several concrete examples. To illustrate the hospital staff’s tendency to “depersonalize” their patients, he noted, “Upon being admitted, I and other pseudopatients took the initial physical examinations in a semi-public room, where staff members went about their own business as if we were not there” (Rosenhan, 1973, p. 256) [2] . Qualitative data has a separate set of analysis tools depending on the research question. For example, thematic analysis would focus on themes that emerge in the data or conversation analysis would focus on the way the words were said in an interview or focus group.

Internal Validity Revisited

Recall that internal validity is the extent to which the design of a study supports the conclusion that changes in the independent variable caused any observed differences in the dependent variable.  Figure 6.1 shows how experimental, quasi-experimental, and non-experimental (correlational) research vary in terms of internal validity. Experimental research tends to be highest in internal validity because the use of manipulation (of the independent variable) and control (of extraneous variables) help to rule out alternative explanations for the observed relationships. If the average score on the dependent variable in an experiment differs across conditions, it is quite likely that the independent variable is responsible for that difference. Non-experimental (correlational) research is lowest in internal validity because these designs fail to use manipulation or control. Quasi-experimental research (which will be described in more detail in a subsequent chapter) falls in the middle because it contains some, but not all, of the features of a true experiment. For instance, it may fail to use random assignment to assign participants to groups or fail to use counterbalancing to control for potential order effects. Imagine, for example, that a researcher finds two similar schools, starts an anti-bullying program in one, and then finds fewer bullying incidents in that “treatment school” than in the “control school.” While a comparison is being made with a control condition, the inability to randomly assign children to schools could still mean that students in the treatment school differed from students in the control school in some other way that could explain the difference in bullying (e.g., there may be a selection effect).

Notice also in  Figure 6.1 that there is some overlap in the internal validity of experiments, quasi-experiments, and correlational (non-experimental) studies. For example, a poorly designed experiment that includes many confounding variables can be lower in internal validity than a well-designed quasi-experiment with no obvious confounding variables. Internal validity is also only one of several validities that one might consider, as noted in Chapter 5.

• Milgram, S. (1974). Obedience to authority: An experimental view . New York, NY: Harper & Row. ↵
• Rosenhan, D. L. (1973). On being sane in insane places. Science, 179 , 250–258. ↵

A research that lacks the manipulation of an independent variable.

Research that is non-experimental because it focuses on the statistical relationship between two variables but does not include the manipulation of an independent variable.

Research that is non-experimental because it focuses on recording systemic observations of behavior in a natural or laboratory setting without manipulating anything.

Studies that involve comparing two or more pre-existing groups of people (e.g., children at different stages of development).

Differences between the groups may reflect the generation that people come from rather than a direct effect of age.

Studies in which one group of people are followed over time as they age.

Studies in which researchers follow people in different age groups in a smaller period of time.

Research Methods in Psychology Copyright © 2019 by Rajiv S. Jhangiani, I-Chant A. Chiang, Carrie Cuttler, & Dana C. Leighton is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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1.6 Reading, understanding and writing up non-empirical articles

SOWK 621: DeCarlo

Reading and Outlining a Non-empirical Journal Article

Explanation

For this course you will have to read a lot of academic journal articles.  The goal of this exercise is to build skills on how to extract the information you need from each article you come across as efficiently as possible.  This assignment is designed for you to explore in greater detail aspects of the Human Service field that are interesting to you.  After conducting a literature search using an academic database (Google Scholar, Academic Search Complete, PubMed, PSYCinfo), choose one article that you find interesting and want to read. 

Non-empirical articles do not have a specific structure like empirical articles.  Instead, authors organize their articles by topic and subtopic.  Non-empirical articles include articles about social theory, history, philosophy, and literature reviews. 

Go to the Penn State Fayette Library page and search for a Non-empircal journal article. If you need assistance review the following links

• Find Box and Searching
• Fayette Library Homepage
• University Libraries Homepage, My Account, Ask a Librarian
• Using the Catalog or click on University Libraries which have some helpful tutorials

Please create a Word document and submit the following to D2L.

• Write out the citation to the article in APA format.  (Google Scholar will give you a citation that is correct about 80% of the time, you should double-check it.)
• General Idea:
• Facts from the Literature
• (I usually copy the sentence that the author writes with the internal citation at the end so I remember what the original source is.)
• Example: 73 people per year are killed by wombats (Ambrose, 1992).
• Facts from the author
• Sources of Interest:
• From the references, copy all of the citations for any articles you included in the Facts from Other Sources section or that you might find useful in your paper.
• Why would someone seek out this source?  What questions would they try to answer?
• How does this resource build upon, challenge, or relate to other literature on the topic?
• Why do you think this is a reputable source from a competent and trustworthy author?

NOTE: In the future, I will refer to these notes as a “Raw Outline.” 

Guiding While Instilling Hope Copyright © by Jo Ann Jankoski is licensed under a Creative Commons Attribution 4.0 International License , except where otherwise noted.

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6.1 Overview of Non-Experimental Research

Learning objectives.

• Define non-experimental research, distinguish it clearly from experimental research, and give several examples.
• Explain when a researcher might choose to conduct non-experimental research as opposed to experimental research.

What Is Non-Experimental Research?

Non-experimental research  is research that lacks the manipulation of an independent variable. Rather than manipulating an independent variable, researchers conducting non-experimental research simply measure variables as they naturally occur (in the lab or real world).

Most researchers in psychology consider the distinction between experimental and non-experimental research to be an extremely important one. This is because although experimental research can provide strong evidence that changes in an independent variable cause differences in a dependent variable, non-experimental research generally cannot. As we will see, however, this inability to make causal conclusions does not mean that non-experimental research is less important than experimental research.

When to Use Non-Experimental Research

As we saw in the last chapter , experimental research is appropriate when the researcher has a specific research question or hypothesis about a causal relationship between two variables—and it is possible, feasible, and ethical to manipulate the independent variable. It stands to reason, therefore, that non-experimental research is appropriate—even necessary—when these conditions are not met. There are many times in which non-experimental research is preferred, including when:

• the research question or hypothesis relates to a single variable rather than a statistical relationship between two variables (e.g., How accurate are people’s first impressions?).
• the research question pertains to a non-causal statistical relationship between variables (e.g., is there a correlation between verbal intelligence and mathematical intelligence?).
• the research question is about a causal relationship, but the independent variable cannot be manipulated or participants cannot be randomly assigned to conditions or orders of conditions for practical or ethical reasons (e.g., does damage to a person’s hippocampus impair the formation of long-term memory traces?).
• the research question is broad and exploratory, or is about what it is like to have a particular experience (e.g., what is it like to be a working mother diagnosed with depression?).

Again, the choice between the experimental and non-experimental approaches is generally dictated by the nature of the research question. Recall the three goals of science are to describe, to predict, and to explain. If the goal is to explain and the research question pertains to causal relationships, then the experimental approach is typically preferred. If the goal is to describe or to predict, a non-experimental approach will suffice. But the two approaches can also be used to address the same research question in complementary ways. For example, Similarly, after his original study, Milgram conducted experiments to explore the factors that affect obedience. He manipulated several independent variables, such as the distance between the experimenter and the participant, the participant and the confederate, and the location of the study (Milgram, 1974) [1] .

Types of Non-Experimental Research

Non-experimental research falls into three broad categories: cross-sectional research, correlational research, and observational research. 

First, cross-sectional research  involves comparing two or more pre-existing groups of people. What makes this approach non-experimental is that there is no manipulation of an independent variable and no random assignment of participants to groups. Imagine, for example, that a researcher administers the Rosenberg Self-Esteem Scale to 50 American college students and 50 Japanese college students. Although this “feels” like a between-subjects experiment, it is a cross-sectional study because the researcher did not manipulate the students’ nationalities. As another example, if we wanted to compare the memory test performance of a group of cannabis users with a group of non-users, this would be considered a cross-sectional study because for ethical and practical reasons we would not be able to randomly assign participants to the cannabis user and non-user groups. Rather we would need to compare these pre-existing groups which could introduce a selection bias (the groups may differ in other ways that affect their responses on the dependent variable). For instance, cannabis users are more likely to use more alcohol and other drugs and these differences may account for differences in the dependent variable across groups, rather than cannabis use per se.

Cross-sectional designs are commonly used by developmental psychologists who study aging and by researchers interested in sex differences. Using this design, developmental psychologists compare groups of people of different ages (e.g., young adults spanning from 18-25 years of age versus older adults spanning 60-75 years of age) on various dependent variables (e.g., memory, depression, life satisfaction). Of course, the primary limitation of using this design to study the effects of aging is that differences between the groups other than age may account for differences in the dependent variable. For instance, differences between the groups may reflect the generation that people come from (a cohort effect) rather than a direct effect of age. For this reason, longitudinal studies in which one group of people is followed as they age offer a superior means of studying the effects of aging. Once again, cross-sectional designs are also commonly used to study sex differences. Since researchers cannot practically or ethically manipulate the sex of their participants they must rely on cross-sectional designs to compare groups of men and women on different outcomes (e.g., verbal ability, substance use, depression). Using these designs researchers have discovered that men are more likely than women to suffer from substance abuse problems while women are more likely than men to suffer from depression. But, using this design it is unclear what is causing these differences. So, using this design it is unclear whether these differences are due to environmental factors like socialization or biological factors like hormones?

When researchers use a participant characteristic to create groups (nationality, cannabis use, age, sex), the independent variable is usually referred to as an experimenter-selected independent variable (as opposed to the experimenter-manipulated independent variables used in experimental research). Figure 6.1 shows data from a hypothetical study on the relationship between whether people make a daily list of things to do (a “to-do list”) and stress. Notice that it is unclear whether this is an experiment or a cross-sectional study because it is unclear whether the independent variable was manipulated by the researcher or simply selected by the researcher. If the researcher randomly assigned some participants to make daily to-do lists and others not to, then the independent variable was experimenter-manipulated and it is a true experiment. If the researcher simply asked participants whether they made daily to-do lists or not, then the independent variable it is experimenter-selected and the study is cross-sectional. The distinction is important because if the study was an experiment, then it could be concluded that making the daily to-do lists reduced participants’ stress. But if it was a cross-sectional study, it could only be concluded that these variables are statistically related. Perhaps being stressed has a negative effect on people’s ability to plan ahead. Or perhaps people who are more conscientious are more likely to make to-do lists and less likely to be stressed. The crucial point is that what defines a study as experimental or cross-sectional l is not the variables being studied, nor whether the variables are quantitative or categorical, nor the type of graph or statistics used to analyze the data. It is how the study is conducted.

Figure 6.1  Results of a Hypothetical Study on Whether People Who Make Daily To-Do Lists Experience Less Stress Than People Who Do Not Make Such Lists

Second, the most common type of non-experimental research conducted in Psychology is correlational research. Correlational research is considered non-experimental because it focuses on the statistical relationship between two variables but does not include the manipulation of an independent variable.  More specifically, in correlational research , the researcher measures two continuous variables with little or no attempt to control extraneous variables and then assesses the relationship between them. As an example, a researcher interested in the relationship between self-esteem and school achievement could collect data on students’ self-esteem and their GPAs to see if the two variables are statistically related. Correlational research is very similar to cross-sectional research, and sometimes these terms are used interchangeably. The distinction that will be made in this book is that, rather than comparing two or more pre-existing groups of people as is done with cross-sectional research, correlational research involves correlating two continuous variables (groups are not formed and compared).

Third,   observational research  is non-experimental because it focuses on making observations of behavior in a natural or laboratory setting without manipulating anything. Milgram’s original obedience study was non-experimental in this way. He was primarily interested in the extent to which participants obeyed the researcher when he told them to shock the confederate and he observed all participants performing the same task under the same conditions. The study by Loftus and Pickrell described at the beginning of this chapter is also a good example of observational research. The variable was whether participants “remembered” having experienced mildly traumatic childhood events (e.g., getting lost in a shopping mall) that they had not actually experienced but that the researchers asked them about repeatedly. In this particular study, nearly a third of the participants “remembered” at least one event. (As with Milgram’s original study, this study inspired several later experiments on the factors that affect false memories.

The types of research we have discussed so far are all quantitative, referring to the fact that the data consist of numbers that are analyzed using statistical techniques. But as you will learn in this chapter, many observational research studies are more qualitative in nature. In  qualitative research , the data are usually nonnumerical and therefore cannot be analyzed using statistical techniques. Rosenhan’s observational study of the experience of people in a psychiatric ward was primarily qualitative. The data were the notes taken by the “pseudopatients”—the people pretending to have heard voices—along with their hospital records. Rosenhan’s analysis consists mainly of a written description of the experiences of the pseudopatients, supported by several concrete examples. To illustrate the hospital staff’s tendency to “depersonalize” their patients, he noted, “Upon being admitted, I and other pseudopatients took the initial physical examinations in a semi-public room, where staff members went about their own business as if we were not there” (Rosenhan, 1973, p. 256) [2] . Qualitative data has a separate set of analysis tools depending on the research question. For example, thematic analysis would focus on themes that emerge in the data or conversation analysis would focus on the way the words were said in an interview or focus group.

Internal Validity Revisited

Recall that internal validity is the extent to which the design of a study supports the conclusion that changes in the independent variable caused any observed differences in the dependent variable.  Figure 6.2  shows how experimental, quasi-experimental, and non-experimental (correlational) research vary in terms of internal validity. Experimental research tends to be highest in internal validity because the use of manipulation (of the independent variable) and control (of extraneous variables) help to rule out alternative explanations for the observed relationships. If the average score on the dependent variable in an experiment differs across conditions, it is quite likely that the independent variable is responsible for that difference. Non-experimental (correlational) research is lowest in internal validity because these designs fail to use manipulation or control. Quasi-experimental research (which will be described in more detail in a subsequent chapter) is in the middle because it contains some, but not all, of the features of a true experiment. For instance, it may fail to use random assignment to assign participants to groups or fail to use counterbalancing to control for potential order effects. Imagine, for example, that a researcher finds two similar schools, starts an anti-bullying program in one, and then finds fewer bullying incidents in that “treatment school” than in the “control school.” While a comparison is being made with a control condition, the lack of random assignment of children to schools could still mean that students in the treatment school differed from students in the control school in some other way that could explain the difference in bullying (e.g., there may be a selection effect).

Figure 6.2 Internal Validity of Correlation, Quasi-Experimental, and Experimental Studies. Experiments are generally high in internal validity, quasi-experiments lower, and correlation studies lower still.

Notice also in  Figure 6.2  that there is some overlap in the internal validity of experiments, quasi-experiments, and correlational studies. For example, a poorly designed experiment that includes many confounding variables can be lower in internal validity than a well-designed quasi-experiment with no obvious confounding variables. Internal validity is also only one of several validities that one might consider, as noted in Chapter 5.

Key Takeaways

• Non-experimental research is research that lacks the manipulation of an independent variable.
• There are two broad types of non-experimental research. Correlational research that focuses on statistical relationships between variables that are measured but not manipulated, and observational research in which participants are observed and their behavior is recorded without the researcher interfering or manipulating any variables.
• In general, experimental research is high in internal validity, correlational research is low in internal validity, and quasi-experimental research is in between.
• A researcher conducts detailed interviews with unmarried teenage fathers to learn about how they feel and what they think about their role as fathers and summarizes their feelings in a written narrative.
• A researcher measures the impulsivity of a large sample of drivers and looks at the statistical relationship between this variable and the number of traffic tickets the drivers have received.
• A researcher randomly assigns patients with low back pain either to a treatment involving hypnosis or to a treatment involving exercise. She then measures their level of low back pain after 3 months.
• A college instructor gives weekly quizzes to students in one section of his course but no weekly quizzes to students in another section to see whether this has an effect on their test performance.
• Milgram, S. (1974). Obedience to authority: An experimental view . New York, NY: Harper & Row. ↵
• Rosenhan, D. L. (1973). On being sane in insane places. Science, 179 , 250–258. ↵

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

Edward barroga.

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

Glafera Janet Matanguihan

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

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

INTRODUCTION

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

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

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

DEFINITIONS AND RELATIONSHIP OF RESEARCH QUESTIONS AND HYPOTHESES

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

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

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

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

CHARACTERISTICS OF GOOD RESEARCH QUESTIONS AND HYPOTHESES

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

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

TYPES OF RESEARCH QUESTIONS AND HYPOTHESES

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

Research questions in quantitative research

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

Hypotheses in quantitative research

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

Research questions in qualitative research

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

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

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

Hypotheses in qualitative research

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

FRAMEWORKS FOR DEVELOPING RESEARCH QUESTIONS AND HYPOTHESES

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

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

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

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

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

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

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

CONSTRUCTING RESEARCH QUESTIONS AND HYPOTHESES

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

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

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

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

EXAMPLES OF RESEARCH QUESTIONS FROM PUBLISHED ARTICLES

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

EXAMPLES OF HYPOTHESES IN PUBLISHED ARTICLES

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

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

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

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

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

Author Contributions:

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

Determining the level of evidence: Nonexperimental research designs

Affiliation.

• 1 Amy Glasofer is a nurse scientist at Virtua Center for Learning in Mt. Laurel, N.J., and Ann B. Townsend is an adult NP with The Nurse Practitioner Group, LLC.
• PMID: 33953103
• DOI: 10.1097/01.NURSE.0000731852.39123.e1

To support evidence-based nursing practice, the authors provide guidelines for appraising research based on quality, quantity, and consistency. This article, the second of a three-part series, focuses on nonexperimental research designs.

Copyright © 2021 Wolters Kluwer Health, Inc. All rights reserved.

• Evidence-Based Nursing*
• Guidelines as Topic
• Research Design*

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130 New Prompts for Argumentative Writing

Questions on everything from mental health and sports to video games and dating. Which ones inspire you to take a stand?

By The Learning Network

Note: We have an updated version of this list, with 300 new argumentative writing prompts .

What issues do you care most about? What topics do you find yourself discussing passionately, whether online, at the dinner table, in the classroom or with your friends?

In Unit 5 of our free yearlong writing curriculum and related Student Editorial Contest , we invite students to research and write about the issues that matter to them, whether that’s Shakespeare , health care , standardized testing or being messy .

But with so many possibilities, where does one even begin? Try our student writing prompts.

In 2017, we compiled a list of 401 argumentative writing prompts , all drawn from our daily Student Opinion column . Now, we’re rounding up 130 more we’ve published since then ( available here as a PDF ). Each prompt links to a free Times article as well as additional subquestions that can help you think more deeply about it.

You might use this list to inspire your own writing and to find links to reliable resources about the issues that intrigue you. But even if you’re not participating in our contest, you can use these prompts to practice the kind of low-stakes writing that can help you hone your argumentation skills.

So scroll through the list below with questions on everything from sports and mental health to dating and video games and see which ones inspire you to take a stand.

Please note: Many of these prompts are still open to comment by students 13 and up.

Technology & Social Media

1. Do Memes Make the Internet a Better Place? 2. Does Online Public Shaming Prevent Us From Being Able to Grow and Change? 3. How Young Is Too Young to Use Social Media? 4. Should the Adults in Your Life Be Worried by How Much You Use Your Phone? 5. Is Your Phone Love Hurting Your Relationships? 6. Should Kids Be Social Media Influencers? 7. Does Grammar Still Matter in the Age of Twitter? 8. Should Texting While Driving Be Treated Like Drunken Driving? 9. How Do You Think Technology Affects Dating?

10. Are Straight A’s Always a Good Thing? 11. Should Schools Teach You How to Be Happy? 12. How Do You Think American Education Could Be Improved? 13. Should Schools Test Their Students for Nicotine and Drug Use? 14. Can Social Media Be a Tool for Learning and Growth in Schools? 15. Should Facial Recognition Technology Be Used in Schools? 16. Should Your School Day Start Later? 17. How Should Senior Year in High School Be Spent? 18. Should Teachers Be Armed With Guns? 19. Is School a Place for Self-Expression? 20. Should Students Be Punished for Not Having Lunch Money? 21. Is Live-Streaming Classrooms a Good Idea? 22. Should Gifted and Talented Education Be Eliminated? 23. What Are the Most Important Things Students Should Learn in School? 24. Should Schools Be Allowed to Censor Student Newspapers? 25. Do You Feel Your School and Teachers Welcome Both Conservative and Liberal Points of View? 26. Should Teachers and Professors Ban Student Use of Laptops in Class? 27. Should Schools Teach About Climate Change? 28. Should All Schools Offer Music Programs? 29. Does Your School Need More Money? 30. Should All Schools Teach Cursive? 31. What Role Should Textbooks Play in Education? 32. Do Kids Need Recess?

College & Career

33. What Is Your Reaction to the College Admissions Cheating Scandal? 34. Is the College Admissions Process Fair? 35. Should Everyone Go to College? 36. Should College Be Free? 37. Are Lavish Amenities on College Campuses Useful or Frivolous? 38. Should ‘Despised Dissenters’ Be Allowed to Speak on College Campuses? 39. How Should the Problem of Sexual Assault on Campuses Be Addressed? 40. Should Fraternities Be Abolished? 41. Is Student Debt Worth It?

Mental & Physical Health

42. Should Students Get Mental Health Days Off From School? 43. Is Struggle Essential to Happiness? 44. Does Every Country Need a ‘Loneliness Minister’? 45. Should Schools Teach Mindfulness? 46. Should All Children Be Vaccinated? 47. What Do You Think About Vegetarianism? 48. Do We Worry Too Much About Germs? 49. What Advice Should Parents and Counselors Give Teenagers About Sexting? 50. Do You Think Porn Influences the Way Teenagers Think About Sex?

Race & Gender

51. How Should Parents Teach Their Children About Race and Racism? 52. Is America ‘Backsliding’ on Race? 53. Should All Americans Receive Anti-Bias Education? 54. Should All Companies Require Anti-Bias Training for Employees? 55. Should Columbus Day Be Replaced With Indigenous Peoples Day? 56. Is Fear of ‘The Other’ Poisoning Public Life? 57. Should the Boy Scouts Be Coed? 58. What Is Hard About Being a Boy?

59. Can You Separate Art From the Artist? 60. Are There Subjects That Should Be Off-Limits to Artists, or to Certain Artists in Particular? 61. Should Art Come With Trigger Warnings? 62. Should Graffiti Be Protected? 63. Is the Digital Era Improving or Ruining the Experience of Art? 64. Are Museums Still Important in the Digital Age? 65. In the Age of Digital Streaming, Are Movie Theaters Still Relevant? 66. Is Hollywood Becoming More Diverse? 67. What Stereotypical Characters Make You Cringe? 68. Do We Need More Female Superheroes? 69. Do Video Games Deserve the Bad Rap They Often Get? 70. Should Musicians Be Allowed to Copy or Borrow From Other Artists? 71. Is Listening to a Book Just as Good as Reading It? 72. Is There Any Benefit to Reading Books You Hate?

73. Should Girls and Boys Sports Teams Compete in the Same League? 74. Should College Athletes Be Paid? 75. Are Youth Sports Too Competitive? 76. Is It Selfish to Pursue Risky Sports Like Extreme Mountain Climbing? 77. How Should We Punish Sports Cheaters? 78. Should Technology in Sports Be Limited? 79. Should Blowouts Be Allowed in Youth Sports? 80. Is It Offensive for Sports Teams and Their Fans to Use Native American Names, Imagery and Gestures?

81. Is It Wrong to Focus on Animal Welfare When Humans Are Suffering? 82. Should Extinct Animals Be Resurrected? If So, Which Ones? 83. Are Emotional-Support Animals a Scam? 84. Is Animal Testing Ever Justified? 85. Should We Be Concerned With Where We Get Our Pets? 86. Is This Exhibit Animal Cruelty or Art?

Parenting & Childhood

87. Who Should Decide Whether a Teenager Can Get a Tattoo or Piercing? 88. Is It Harder to Grow Up in the 21st Century Than It Was in the Past? 89. Should Parents Track Their Teenager’s Location? 90. Is Childhood Today Over-Supervised? 91. How Should Parents Talk to Their Children About Drugs? 92. What Should We Call Your Generation? 93. Do Other People Care Too Much About Your Post-High School Plans? 94. Do Parents Ever Cross a Line by Helping Too Much With Schoolwork? 95. What’s the Best Way to Discipline Children? 96. What Are Your Thoughts on ‘Snowplow Parents’? 97. Should Stay-at-Home Parents Be Paid? 98. When Do You Become an Adult?

Ethics & Morality

99. Why Do Bystanders Sometimes Fail to Help When They See Someone in Danger? 100. Is It Ethical to Create Genetically Edited Humans? 101. Should Reporters Ever Help the People They Are Covering? 102. Is It O.K. to Use Family Connections to Get a Job? 103. Is $1 Billion Too Much Money for Any One Person to Have? 104. Are We Being Bad Citizens If We Don’t Keep Up With the News? 105. Should Prisons Offer Incarcerated People Education Opportunities? 106. Should Law Enforcement Be Able to Use DNA Data From Genealogy Websites for Criminal Investigations? 107. Should We Treat Robots Like People?

Government & Politics

108. Does the United States Owe Reparations to the Descendants of Enslaved People? 109. Do You Think It Is Important for Teenagers to Participate in Political Activism? 110. Should the Voting Age Be Lowered to 16? 111. What Should Lawmakers Do About Guns and Gun Violence? 112. Should Confederate Statues Be Removed or Remain in Place? 113. Does the U.S. Constitution Need an Equal Rights Amendment? 114. Should National Monuments Be Protected by the Government? 115. Should Free Speech Protections Include Self Expression That Discriminates? 116. How Important Is Freedom of the Press? 117. Should Ex-Felons Have the Right to Vote? 118. Should Marijuana Be Legal? 119. Should the United States Abolish Daylight Saving Time? 120. Should We Abolish the Death Penalty? 121. Should the U.S. Ban Military-Style Semiautomatic Weapons? 122. Should the U.S. Get Rid of the Electoral College? 123. What Do You Think of President Trump’s Use of Twitter? 124. Should Celebrities Weigh In on Politics? 125. Why Is It Important for People With Different Political Beliefs to Talk to Each Other?

Other Questions

126. Should the Week Be Four Days Instead of Five? 127. Should Public Transit Be Free? 128. How Important Is Knowing a Foreign Language? 129. Is There a ‘Right Way’ to Be a Tourist? 130. Should Your Significant Other Be Your Best Friend?

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Original research article, associations between monitor-independent movement summary (mims) and fall risk appraisal combining fear of falling and physiological fall risk in community-dwelling older adults.

• 1 Department of Mechanical Engineering, University of Central Florida, Orlando, FL, United States
• 2 Disability, Aging and Technology Cluster, University of Central Florida, Orlando, FL, United States
• 3 College of Medicine, University of Central Florida, Orlando, FL, United States
• 4 School of Kinesiology and Rehabilitation Sciences, College of Health Professions and Sciences, University of Central Florida, Orlando, FL, United States
• 5 Department of Statistics and Data Science, University of Central Florida, Orlando, FL, United States
• 6 College of Nursing, University of Central Florida, Orlando, FL, United States

Introduction: Fall Risk Appraisal (FRA), a process that integrates perceived and objective fall risk measures, serves as a crucial component for understanding the incongruence between fear of falling (FOF) and physiological fall risk in older adults. Despite its importance, scant research has been undertaken to investigate how habitual physical activity (PA) levels, quantified in Monitor-Independent Movement Summary (MIMS), vary across FRA categories. MIMS is a device-independent acceleration summary metric that helps standardize data analysis across studies by accounting for discrepancies in raw data among research-grade and consumer devices.

Objective: This cross-sectional study explores the associations between MIMS (volume and intensity) and FRA in a sample of older adults in the United States.

Methods: We assessed FOF (Short Falls Efficacy Scale-International), physiological fall risk (balance: BTrackS Balance, leg strength: 30-s sit-to-stand test) and 7-day free-living PA (ActiGraph GT9X) in 178 community-dwelling older adults. PA volume was summarized as average daily MIMS (MIMS/day). PA intensity was calculated as peak 30-min MIMS (average of highest 30 non-consecutive MIMS minutes/day), representing a PA index of higher-intensity epochs. FRA categorized participants into following four groups: Rational (low FOF-low physiological fall risk), Irrational (high FOF-low physiological fall risk), Incongruent (low FOF-high physiological fall risk) and Congruent (high FOF-high physiological fall risk).

Results: Compared to rational group, average MIMS/day and peak 30-min MIMS were, respectively, 15.8% ( p = .025) and 14.0% ( p = .004) lower in irrational group, and 16.6% ( p = .013) and 17.5% ( p < .001) lower in congruent group. No significant differences were detected between incongruent and rational groups. Multiple regression analyses showed that, after adjusting for age, gender, and BMI (reference: rational), only irrational FRA was significantly associated with lower PA volume (β = −1,452.8 MIMS/day, p = .034); whereas irrational and congruent FRAs were significantly associated with lower “peak PA intensity” (irrational: β = −5.40 MIMS/day, p = .007; congruent: β = −5.43 MIMS/day, p = .004).

Conclusion: These findings highlight that FOF is a significant barrier for older adults to participate in high-intensity PA, regardless of their balance and strength. Therefore, PA programs for older adults should develop tailored intervention strategies (cognitive reframing, balance and strength exercises, or both) based on an individual’s FOF and physiological fall risk.

Introduction

In the United States (US), over 14 million adults aged 65 years or older fall each year ( Moreland et al., 2020 ; Kakara et al., 2023 ). According to the US Centers for Disease Control and Prevention, about 20% of falls in older adults cause serious injuries, which results in limited functional mobility, loss of independence, reduced quality of life, and premature death ( Ambrose et al., 2013 ). Fear of falling (FOF) has been recognized as an important psychological aspect associated with falls in older adults ( Jansen et al., 2021 ). However, studies report that many older adults might show a discrepancy between their FOF and physiological fall risk, known as maladaptive fall risk appraisal (FRA) ( Thiamwong et al., 2021a ), and such discrepancies can lead to adverse consequences. For example, individuals with low physiological fall risk but high FOF may overestimate their actual fall risk and restrict their daily activities, which can further lead to physical deconditioning and loss of muscle strength ( Deshpande et al., 2008 ). On the contrary, those with high physiological fall risk but low FOF may underestimate their actual fall risk and engage in unnecessary risky behavior beyond their physical capacity, making them even more vulnerable to falling ( Delbaere et al., 2010 ).

Therefore, FRA combining subjective and objective fall risk measures is important for understanding the discrepancy between FOF and physiological fall risk in older adults to inform more targeted interventions for fall prevention ( Thiamwong et al., 2020a ; Thiamwong et al., 2020b ). FRA is a two-dimensional fall risk assessment matrix that classifies older adults into four groups based on their FOF and physiological fall risk status ( Thiamwong, 2020 ). In FRA matrix, as shown in Figure 1 , two groups have their FOF level aligned with their physiological fall risk status, which are denoted as Rational (low FOF-low physiological fall risk) and Congruent (high FOF-high physiological fall risk). The other two groups show a mismatch between their FOF level and physiological fall risk status and are denoted as Incongruent (low FOF-high physiological fall risk) and Irrational (high FOF-low physiological fall risk).

Figure 1 . Fall Risk Appraisal (FRA) based on Fear of Falling (FOF) and physiological fall risk. Maladaptive FRA = mismatch between FOF and physiological fall risk; Adaptive FRA = FOF aligned with physiological fall risk.

Prior research has mostly focused on exploring the independent associations of FOF and objective fall risk measures with physical activity (PA) participation in older adults ( Gregg et al., 2000 ; Chan et al., 2007 ; Zijlstra et al., 2007 ; Heesch et al., 2008 ; Mendes da Costa et al., 2012 ). To date, only a small number of studies have investigated the combined effects of FOF and objective fall risk on PA engagement. For example, one study examined the joint associations of FOF and objective fall risk with everyday walking activities in older adults. This study used a four-group categorization from ( Delbaere et al., 2010 ), and found that the number of steps/day in their study sample was in accordance with objective fall risk rather than FOF ( Jansen et al., 2021 ). Another study examined accelerometry-based PA levels between FRA categories using the intensity cut-point approach and found that participants with high FOF accumulated significantly less time in moderate-to-vigorous PA (MVPA) compared to those with rational FRA, regardless of their balance performance ( Thiamwong et al., 2023 ). However, there exists a lack of evidence on how habitual PA levels, expressed in Monitor-Independent Movement Summary (MIMS) units, differ between FRA categories in older adults.

MIMS is used to summarize the acceleration measurements obtained on the x-, y-, and z-axes of wrist-worn activity monitors. This PA metric was first introduced in 2019 to summarize participant-level PA data for the 2011-2012 and 2013-2014 cycles of the US National Health and Nutrition Examination Survey (NHANES) ( John et al., 2019 ). The major benefit of using MIMS is that it is generated by a nonproprietary device–independent universal algorithm, allowing us to compare the total movement across studies regardless of the heterogeneity introduced by different brands, models and device types (such as consumer vs. research-grade) ( John et al., 2019 ). Similar to other traditional PA metrics such as steps/day or daily activity counts, PA volume can be expressed as daily MIMS (i.e., total MIMS unit accumulated per day) across valid days of assessment, where larger MIMS/day indicates higher daily PA volume ( Wolff-Hughes et al., 2014 ).

Traditionally, quantification of accelerometer-measured PA intensity has been predominantly based on minutes/day (or minutes/week) spent in MVPA, using either manufacturer-specific or device-specific cut points corresponding with ≥3 Metabolic Equivalents of Task (METs) ( Troiano et al., 2008 ). Recently, to establish an intensity-based expression for MIMS units, the concept of peak 30-min MIMS has been introduced ( Zheng et al., 2023 ). It is analogous to the concept of peak 30-min cadence, i.e., the average of 30 highest cadence (steps/minutes) values within a day, representing an individual’s best efforts ( Tudor-Locke et al., 2012 ). Similar to cadence (steps/minutes), MIMS/minutes values were shown to have a strong correlation with higher PA intensity ( John et al., 2019 ). Therefore, peak 30-min MIMS (i.e., the average of the highest 30 non-consecutive MIMS [minutes/day] values within a day) can be used as a measure of higher-intensity epochs across the PA monitoring period ( Zheng et al., 2023 ). Evaluating daily MIMS (volume) and peak 30-min MIMS (intensity) can facilitate a more comprehensive assessment of PA and its relationship with FRA.

Thus, the aim of this study is to investigate the associations between wrist-worn accelerometer-measured PA (expressed as daily MIMS and peak 30-min MIMS) and FRA in a sample of community-dwelling older adults. We are particularly interested in the question: “Which of the maladaptive FRA groups, i.e., Incongruent (low FOF-high physiological fall risk) and Irrational (high FOF-low physiological fall risk), differ more from the Rational (low FOF-low physiological fall risk) group in terms of habitual PA level?.” This will allow us to understand which of the two factors—FOF or physiological fall risk—has a stronger relationship with reduced PA participation among older adults.

Materials and methods

Study design and participants.

In this cross-sectional study, purposive sampling was used to recruit 178 community-dwelling older adults from the region of Central Florida, United States, between February 2021 and March 2023. The inclusion criteria were: i) 60 years of age or older; ii) being able to walk with or without an assistive device (but without the assistance of another person); iii) no marked cognitive impairment [i.e., Memory Impairment Screen score ≥5 ( Buschke et al., 1999 )], iv) fluency in English or Spanish, and v) living in their own homes or apartments. The exclusion criteria were: i) medical conditions that prevent PA engagement (e.g., shortness of breath, tightness in the chest, dizziness, or unusual fatigue at light exertion), ii) unable to stand on the balance plate, iii) currently receiving treatment from a rehabilitation facility, and iv) having medical implants (e.g., pacemakers). This study was approved by the Institutional Review Board at the University of Central Florida (Protocol No: 2189; 10 September 2020). All subjects provided written informed consent to participate. This cross-sectional assessment required one visit to the study site during which participants completed a demographic survey and anthropometric measurements, followed by assessments of FOF and physiological fall risk. At the end of the visit, each participant was fitted with a wrist-worn accelerometer for 7-day PA monitoring in free-living conditions.

Measurements

Fear of falling (fof).

FOF was assessed using the Short Falls Efficacy Scale-International (FES-I) questionnaire ( Yardley et al., 2005 ; Kempen et al., 2008 ). It is a 7-item, self-administered tool that uses a 4-point Likert scale to measure the level of concern about falling while performing seven activities (1 = not at all concerned to 4 = very concerned). The total scores ranged from 7 to 28. Short FES-I scores of 7–10 indicated low FOF, while scores of 11–28 indicated high FOF.

Physiological fall risk

Physiological fall risk was assessed using balance test and lower limb strength assessment. BTrackS Balance System (Balance Tracking Systems, San Diego, CA, United States) was used to measure static balance. This system includes a portable BTrackS Balance Plate and BTrackS Assess Balance Software running on a computer. It has shown high test–retest reliability (intraclass correlation coefficient, ICC = 0.83) and excellent validity (Pearson’s product-moment correlations, r > 0.90) in evaluating static balance ( Levy et al., 2018 ). The test protocol included four trials (each trial taking 20 s) with less than 10 s of inter-trial delays. During the trials, participants were asked to stand still on the BTrackS Balance Plate with their eyes closed, hands on their hips, and feet placed shoulder-width apart. BTrackS balance plate is an FDA-registered, lightweight force plate that measures center of pressure (COP) excursions during the static stance. The first trial was done for familiarization only. Results from the remaining three trials were used to calculate the average COP path length (in cm) across trials. COP path length is considered as a proxy measure for postural sway magnitude; thus, the larger the COP path length, the greater the postural sway is ( Goble et al., 2017 ). COP path length of 0–30  cm was used to indicate normal balance, while ≥31  cm indicated poor balance ( Thiamwong et al., 2021b ).

Lower limb strength was assessed using the 30-s sit-to-stand (STS) test, in accordance with the established protocol ( Yee et al., 2021 ; Choudhury et al., 2023 ). Participants were instructed to keep their arms folded across their chest, rise from a seated position on a chair to a standing posture and return to the sitting position as many times as possible within 30 s. The number of chair stands completed was counted and recorded. If a participant used his/her arms to stand, the test was stopped, and the score was recorded as zero. Age- and gender-specific STS normative scores were used as cut-offs to classify participants into below-average and average STS scores, as shown in Table 1 ( Rikli and Jones, 1999 ). A below-average STS score was indicative of a higher risk of fall. Meeting both normal balance and average STS score criteria was defined as low physiological fall risk, while not meeting either or both criteria was defined as high physiological fall risk.

Table 1 . Age and gender-specific below average scores for 30-s sit-to-stand test.

Fall risk appraisal (FRA) matrix

The FRA matrix was obtained using a combination of FOF and physiological fall risk status. Participants were grouped into the following four categories based on their FOF and physiological fall risk according to existing literature ( Thiamwong et al., 2020a ): i) Rational (low FOF-low physiological fall risk), ii) Irrational (high FOF-low physiological fall risk), iii) Incongruent (low FOF-high physiological fall risk), and iv) Congruent (high FOF-high physiological fall risk).

Physical activity (PA)

PA was assessed using ActiGraph GT9X Link (ActiGraph LLC., Pensacola, FL, United States), which contains a triaxial accelerometer with a dynamic range of ±8 gravitational units (g). The device was initialized to record acceleration data at 30  Hz sampling frequency. Participants wore the ActiGraph on their non-dominant wrists for seven consecutive days in free-living conditions. They were given instructions to wear it during waking hours and remove it only during sleeping, showering, swimming and medical imaging tests. After 7-day of PA monitoring, ActiGraph devices were collected from participants. Participants with ≥4 valid days were included in the analysis, and a day was considered valid if participants wore the device for at least 14 h or more ( Choudhury et al., 2023 ).

Raw acceleration data were downloaded as “.csv” files using ActiLife software v6.13.4 (ActiGraph LLC, Pensacola, FL, United States) and converted into MIMS units using MIMSunit package ( John et al., 2019 ) in R statistical software (R Core Team, Vienna, Austria). The data processing steps included: i) interpolating data to a consistent sampling rate (i.e., 100  Hz ) to account for inter-device variability in sampling rate, ii) extrapolating data to extend maxed-out signals to account for inter-device variability in dynamic range, iii) band-pass filtering to remove artifacts from acceleration signals that do not pertain to voluntary human movement, and iv) aggregation of processed signals from each axis into a sum of MIMS-units that represents the total amount of movement activity [details on MIMS-unit algorithm are published elsewhere ( John et al., 2019 )].

PA volume, denoted by daily MIMS (MIMS/day), was calculated by summing up all triaxial MIMS/minutes accumulated throughout a day and averaged across all valid days. PA intensity, expressed as peak 30-min MIMS, was obtained by (a) first rank ordering a participant’s triaxial MIMS/minutes values within each valid day, (b) calculating the average of the highest 30 MIMS/minutes values within each day, and (c) finally taking the average of the resulting MIMS/minutes values across all valid wear days.

Anthropometric measurements

Height (in cm) was measured using a stadiometer. Body mass (in kilograms) was measured using a digital scale with no shoes. Body mass index (BMI) was calculated as the weight (kg) divided by the square of height (m 2 ).

Statistical analyses

All statistical analyses were performed in R statistical software (version 4.1.2, R Core Team, Vienna, Austria) with statistical significance level set at .05. Descriptive characteristics of participants were summarized as mean (standard deviation, SD) for normally distributed continuous variables, as median (Interquartile Range, IQR) for non-normally distributed continuous variables, and as frequency (percentage) for categorical variables, stratified by FRA categories. The Shapiro-Wilk test was performed to check if a continuous variable followed a normal distribution. Differences across groups were examined using one-way analysis of variance (ANOVA) for normally distributed data and Kruskal–Wallis test for non-normally distributed data, with Bonferroni adjustment for post hoc comparisons.

Multiple linear regression was conducted for each outcome variable (i.e., daily MIMS and peak 30-min MIMS) using the four FRA groups—“Rational,” “Irrational,” “Incongruent” and “Congruent”—as explanatory variables, controlled by age, gender and BMI. A priori sample size calculation for multiple linear regression revealed that the minimum number of samples for 8 explanatory variables at a statistical power level of 0.8, α = 0.05, and a medium effect size (Cohen f 2 = 0.15) would be 108; therefore, our sample size (i.e., N = 178) had sufficient statistical power for multiple regression. The rational group (i.e., low FOF-low physiological fall risk) was selected as the reference group in the regression analysis.

Among 178 participants, 163 samples were included in the analyses, after retaining only those who had at least 4 days of valid PA data and completed both FOF and physiological fall risk assessments. The mean (SD) age of participants was 75.3 (7.1) years, and 73.6% of participants were in 60–79 years of age group ( n = 120) and 26.4% were above 80 years of age ( n = 43). Figure 2 shows the scatterplot of participants’ age (years) and FOF scores, stratified by physiological fall risk status. The proportion of participants with low FOF was 71.7% ( n = 86) in the 60–79 years of age group and 48.8% ( n = 21) in the ≥80 years of age group. The median (IQR) BMI of participants was 26.6 (6.3) kg/m 2 and majority of participants were female (79.1%). The median (IQR) Short FES-I score was 9 (5) and 34.4% of participants had high FOF. The median (IQR) COP path length was 27 (15) cm , and the median (IQR) sit-to-stand score was 13 (6) reps. 38.0% of participants had poor balance, 27.0% had below average lower limb strength, and 48.5% showed both poor balance and below average lower limb strength. Finally, 37.4% of participants were screened as rational ( n = 61), 14.2% were irrational ( n = 23), 28.2% were incongruent ( n = 46) and 20.2% were congruent ( n = 37). Table 2 summarizes the characteristics of study participants according to FRA categories.

Figure 2 . Scatterplot of Age (years) across Fear of Falling scores, stratified by physiological fall risk status. Low physiological fall risk = meeting both normal static balance cut-off and average sit-to-stand score cut-off. High physiological fall risk = not meeting normal static balance cut-off or average sit-to-stand score cut-off or both.

Table 2 . Participant characteristics stratified by Fall Risk Appraisal matrix.

In Figure 3A , the variations in average MIMS (MIMS/hours) over 24-h by FRA categories are shown. The average MIMS across all groups was in general low at night, then substantially increased during morning hours and gradually decreased as the day progressed and evening approached. In Figure 3B , the mean (line) and standard error (shaded area) of MIMS/hours for each FRA group is shown. Overall, rational group showed the highest average MIMS/hours across the day hours, while congruent had the lowest average MIMS/hours. Among maladaptive FRA groups, the peak was higher in incongruent group than their irrational counterparts, which indicates the potential role of FOF in limiting high-intensity PA participation.

Figure 3 . (A) Daily patterns of average MIMS per hour by Fall Risk Appraisal (FRA) groups. (B) Mean (line) and standard error (shaded area) of MIMS per hour for each FRA group.

The mean (SD) age in congruent group was 78.8 (7.6) years, which was higher than both rational (74.3 [5.8] years, p = .005) and incongruent (74.3 [7.0] years, p = .010) groups, as shown in Supplementary Figure S1 . This suggests that prevalence of high FOF, irrespective of balance performance and lower limb strength, may increase with advanced age. Also, the median (IQR) BMI in congruent group (28.9 [5.8]) kg/m 2 ) was higher in comparison to rational (24.9 [6.4] kg/m 2 , p = .001) and incongruent (26.9 [4.7] kg/m 2 , p = .018) groups (shown in Supplementary Figure S2 ), indicating that higher BMI in older adults may result in high FOF. However, no significant group differences were observed between rational and irrational groups in terms of age and BMI.

The mean (SD) daily MIMS in rational group was 10,408 (2,439) MIMS/day, which was 15.8% higher than irrational ( p = .025) and 16.6% higher than congruent ( p = .013) groups, as shown in Figure 4 . Also, the mean (SD) peak 30-min MIMS in rational group was 39.9 (8.3) MIMS/day, which was 14.0% higher than irrational ( p = .004) and 17.5% higher than congruent ( p < .001) groups ( Figure 5 ). Compared to rational group, incongruent participants showed no significant differences in PA volume and intensity, despite having poor balance and below average lower limb strength.

Figure 4 . Average daily MIMS (MIMS/day) across categories of Fall Risk Appraisal combining FOF and physiological fall risk, * p < .05.

Figure 5 . Peak 30-min MIMS per day across categories of Fall Risk Appraisal combining FOF and physiological fall risk, ** p < .01, *** p < .001.

Table 2 presents the regression models for daily MIMS. In comparison to reference group (i.e., rational), lower PA volume was associated with irrational ( β [SE] = −1,463.2 [687.7] MIMS/day, p = .035) and congruent ( β [SE] = −1,579.5 [582.9] MIMS/day, p = .007) FRAs in Model 1 (unadjusted). In model 2, after adjusting for age, gender and BMI, only irrational FRA was significantly associated with lower PA volume ( β [SE] = −1,476.41 [582.26] MIMS/day, p = .025; regression coefficients of covariates are presented in Supplementary Table S1 ).

Results for regression analysis for peak 30-min MIMS are presented in Table 3 . In model 1 (unadjusted), lower ‘peak PA intensity’ was associated with irrational ( β [SE] = −5.63 [1.99] MIMS/day, p = .005) and congruent FRAs ( β [SE] = −7.06 [1.76] MIMS/day, p < .001) compared to the reference group. In Model 2 ( Table 4 ), after adjusting for age, gender and BMI, both irrational and congruent FRAs were still significantly associated with lower “peak PA intensity”(irrational: β [SE] = −5.40 [1.97] MIMS/day, p = .007; congruent: β [SE] = −5.43 [1.86] MIMS/day, p = .004; regression coefficients of covariates are presented in Supplementary Table S2 ).

Table 3 . Association between Fall Risk Appraisal groups and average daily MIMS (MIMS/day) using linear regression. Model 2 was adjusted for age, gender and BMI.

Table 4 . Association between Fall Risk Appraisal groups and peak 30-min MIMS per day (MIMS/day) using linear regression. Model 2 was adjusted for age, gender and BMI.

This is the first study, to our knowledge, to evaluate the associations of FRA with daily MIMS and peak 30-min MIMS in a sample of community-dwelling US older adults. In general, both the volume and intensity of PA were highest in the rational group and lowest in the congruent group. In maladaptive FRA groups, high FOF (i.e., irrational FRA) was associated with lower PA volume and intensity compared to the reference group (i.e., rational FRA), but no significant differences were observed for high physiological fall risk (i.e., incongruent FRA).

Prior research has shown that FOF is associated with reduced PA levels in community-dwelling older adults using objectively measured PA data ( Jefferis et al., 2014 ; Choudhury et al., 2022 ). Our results broadly agree with it, showing that total daily PA volume was significantly lower in two high FOF groups (i.e., irrational and congruent) than the rational group. This suggests that regardless of balance performance and lower limb strength, low FOF was associated with high PA volume in our study sample. In linear regression analysis, after accounting for age, gender and BMI, reduced daily MIMS was significantly associated with irrational FRA, but not with congruent FRA. It can be attributed to the fact that the average age and BMI of congruent participants were higher than all other groups, and evidence suggests that that increasing older age and higher BMI contribute to lower PA levels in older adults ( Smith et al., 2015 ).

We did not observe any significant difference between two low FOF groups (i.e., rational and incongruent) in terms of daily PA volume. This suggests that, for maladaptive FRA, high physiological fall risk (not high FOF) had a stronger association with reduced daily PA accumulation in our study sample. In contrast to our findings, a recent study found that low physiological fall risk was more strongly associated with increased walking activity (steps/day) than low perceived fall risk in a sample of community-dwelling German older adults ( n = 294) ( Jansen et al., 2021 ). However, it should be noted that Jansen et al. used multiple independent risk factors (i.e., previous falls, balance impairment, gait impairment, and multimedication) to distinguish between high and low physiological fall risk, whereas they used only one tool (Short FES-I) to assess perceived fall risk. Furthermore, participants with low FOF and high physiological fall risk in that German older adult cohort ( Jansen et al., 2021 ) were relatively older than those in our study sample [mean (SD) age: 81.6 (5.5) years vs. 74.3 (7.0) years in our study]. Previous studies indicate that the likelihood of reduced participation in PA gradually increases with advanced age, because of age-related declines in muscle mass, muscle strength, and functional fitness (i.e., the physical capacity to perform activities of daily living independently and without the early onset of fatigue) ( Milanović et al., 2013 ; Westerterp, 2018 ; Suryadinata et al., 2020 ). Therefore, future research should examine how age-related functional declines mediate the relationship between maladaptive FRA and daily PA volume in older adults.

In our study, the peak PA intensity in both high FOF groups (i.e., irrational and congruent) was significantly lower than the rational group. Despite the differences in the PA metrics, this is in general agreement with the previous findings that showed older adults with irrational and congruent FRAs were more likely to spend less time in MVPA ( Thiamwong et al., 2023 ). Interestingly, after adjusting for confounders, the decrease in peak 30-min MIMS for irrational and congruent groups was almost equivalent in our study. This suggests that older adults with high FOF may restrict their participation in high intensity PA, irrespective of their physiological fall risk status. Our findings extend the previously reported association between PA intensity and FOF in older adults ( Sawa et al., 2020 ), highlighting the need to integrate cognitive behavioral therapy to reduce FOF in fall intervention programs.

For peak 30-min MIMS, we did not find any significant difference between two low FOF groups (i.e., rational and incongruent). This suggests that, similar to total PA volume, peak PA intensity was more strongly associated with high FOF (rather than high physiological fall risk) for maladaptive FRA in our sample. Unlike MVPA cut points that exclude PA intensities ≤3 METs or equivalent, peak 30-min MIMS considers acceleration magnitudes ranging from lower to higher peak efforts within a day, enabling comparison over the whole spectrum of PA intensity levels (e.g., light vs. vigorous) ( Zheng et al., 2023 ). Further research should investigate domains of peak PA efforts across different FRA groups, so that informed strategies can be developed to promote high-intensity PA participation according to the perceived and physiological risk of fall.

Based on the findings of our study, it can be conferred that the FRA assessment may be useful in designing customized PA interventions to promote an active lifestyle in older adults. For example, to increase PA participation in older adults with irrational FRA, cognitive behavioral therapy can be integrated into PA programs to improve their self-efficacy and sense of control over falling ( Tennstedt et al., 1998 ). For incongruent FRA, PA recommendations should include exercise regimens specifically designed to reduce physiological fall risk, such as high intensity balance and strength training, in addition to aerobic activities ( Sherrington et al., 2008 ). On the other hand, older adults with congruent FRA may benefit from PA programs that combine both balance and strength exercises, and cognitive behavioral therapy ( Brouwer et al., 2003 ).

A strength of our study is the use of MIMS metric to provide a comprehensive PA assessment (volume and intensity) enabling reliable, cross-study comparisons of our findings with other MIMS-based studies regardless of the device type, model or manufacturer. Furthermore, we used evidence-based cut-off points to determine FOF level (low vs. high FOF), balance status (poor vs. normal balance) and lower limb strength (below average vs. average strength) to categorize participants into FRA groups. However, our study has several limitations. First, to determine physiological fall risk status, we didn’t use the Physiological Profile Assessment ( Delbaere et al., 2010 ) or multiple independent risk factors ( Jansen et al., 2021 ), which might have led to different group formations than those studies. Instead, we used static balance and lower limb strength as physiological fall risk indicators. While balance and strength deficits are important predictors of falls in older adults, they might not account for all aspects of physiological fall risk (such as gait impairment, visual and sensory deficits, use of multi-medications etc.) ( Fabre et al., 2010 ). Second, it is to be noted that the balance performance measure (i.e., static balance) used in this study may not capture the full spectrum of an individual’s balance capabilities. There are different measures of balance performance, including static steady-state balance (i.e., the ability to maintain a steady position while standing or sitting), dynamic steady-state balance (i.e., the ability to maintain a steady position while performing postural transitions and walking), proactive balance (i.e., the ability to anticipate and mitigate a predicted postural disturbance), and reactive balance (i.e., the ability to recover a stable position following an unexpected postural disturbance) ( Shumway-Cook and Woollacott, 2007 ). Therefore, future studies may consider using more comprehensive assessments of balance performance in older adults to define physiological fall risk in FRA. Third, our study only considered FOF as the psychological fall risk measure in FRA and did not investigate other psychological constructs such as falls efficacy or balance confidence ( Moore et al., 2011 ). FOF and falls efficacy are two major fall-related psychological constructs in preventing and managing fall risks in older adults. It is to be noted that, though FOF and falls efficacy are correlated, they represent theoretically distinct concepts ( Hadjistavropoulos et al., 2011 ). FOF is defined as “the lasting concerns about falling that leads to an individual avoiding activities that one remains capable of performing.” Some common instruments for FOF measurement include FES-I, Short FES-I, Iconographical Falls Efficacy Scale (ICON-FES), Geriatric Fear of Falling Measure (GFFM), Survey of Activities and Fear of Falling in the Elderly (SAFE), Fear of Falling Avoidance Behaviour Questionnaire (FFABQ) etc., ( Soh et al., 2021 ). On the other hand, falls efficacy is defined as the perceived confidence in one’s ability to carry out activities of daily living without experiencing a fall ( Moore and Ellis, 2008 ). Existing instruments for measuring falls efficacy include Falls Efficacy Scale (FES), modified FES (MFES), Perceived Ability to Prevent and Manage Fall Risks (PAPMFR), and Perceived Ability to Manage Risk of Falls or Actual Falls (PAMF) ( Soh et al., 2021 ). Prior research has reported that, compared to FOF, falls efficacy shows stronger relationship with measures of basic and instrumental activities of daily living (ADL-IADL), and physical and social functioning ( Tinetti et al., 1994 ). Therefore, future studies should consider exploring the combined effects of falls efficacy and physiological fall risk measures on habitual PA level to determine whether FOF or fall efficacy should be considered as a target for PA interventions in older adults. Fourth, to date, there exists no established cut-offs for the MIMS metric to categorize total PA volume and intensity that correspond to meeting national PA guidelines, and it is still unknown how well MIMS/minute can estimate energy expenditure ( Vilar-Gomez et al., 2023 ). Our study just provided a first step toward the use of a standardized metric to associate PA behavior with FRA in a community-dwelling older adult sample in the US. Future studies should examine such associations in large, nationally representative populations to establish benchmark values for daily MIMS and peak 30-min MIMS in different FRA categories. Fifth, the cross-sectional design of the study didn’t allow us to determine a causal relationship between FRA and PA, so reverse and/or bidirectional causality might still be present. Sixth, although we controlled for age, gender, and BMI in the regression analyses, there remains the possibility of additional residual confounding [such as neuropsychological constructs that have been associated with FOF, which include depression, anxiety, neuroticism, attention, and executive function ( Delbaere et al., 2010 )]. Finally, our sample size was relatively small and 79% of participants were female. The generalizability of our findings might be restricted by the small, female dominant nature of our sample.

In conclusion, compared to rational FRA, the habitual PA level (daily MIMS and peak 30-min MIMS) was lower in both high FOF groups (i.e., irrational and congruent), but not in incongruent group. This suggests that, for maladaptive FRA in our study sample, high perceived fall risk had a stronger association with reduced PA level, rather than high physiological fall risk. When controlled for covariates, decrease in peak PA intensity remained significantly associated with irrational and congruent FRAs, indicating that older adults with high FOF performed PA at lower peak efforts, irrespective of their physiological fall status. Future prospective studies should focus on identifying the optimal habitual PA level (total PA volume and peak PA intensity) in accordance with an older adult’s FOF and physiological fall risk to better inform public health policies for sustainable, effective PA framework.

Data availability statement

The raw data supporting the conclusion of this article will be made available by the authors, without undue reservation.

Ethics statement

The studies involving humans were approved by the Institutional Review Board, University of Central Florida. The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study.

Author contributions

RC: Data curation, Formal Analysis, Investigation, Methodology, Software, Visualization, Writing–original draft. J-HP: Conceptualization, Funding acquisition, Investigation, Methodology, Resources, Supervision, Writing–review and editing. CB: Formal Analysis, Visualization, Writing–review and editing. MC: Data curation, Investigation, Writing–review and editing. DF: Conceptualization, Funding acquisition, Writing–review and editing. RX: Conceptualization, Funding acquisition, Writing–review and editing. JS: Conceptualization, Funding acquisition, Supervision, Writing–review and editing. LT: Conceptualization, Funding acquisition, Project administration, Resources, Supervision, Writing–review and editing.

The author(s) declare that financial support was received for the research, authorship, and/or publication of this article. The research was funded by the National Institute on Aging (R03AG06799) and the National Institute on Minority Health and Health Disparities (R01MD018025) of National Institutes of Health. This research also received financial support from the University of Central Florida CONNECT CENTRAL (Interdisciplinary research seed grant; AWD00001720 and AWD00005378).

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.

The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision.

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Supplementary material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fragi.2024.1284694/full#supplementary-material

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Keywords: falls, physical activity, accelerometry, aging, fear of falling, fall risk, MIMS

Citation: Choudhury R, Park J-H, Banarjee C, Coca MG, Fukuda DH, Xie R, Stout JR and Thiamwong L (2024) Associations between monitor-independent movement summary (MIMS) and fall risk appraisal combining fear of falling and physiological fall risk in community-dwelling older adults. Front. Aging 5:1284694. doi: 10.3389/fragi.2024.1284694

Received: 28 August 2023; Accepted: 20 March 2024; Published: 09 April 2024.

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Copyright © 2024 Choudhury, Park, Banarjee, Coca, Fukuda, Xie, Stout and Thiamwong. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Joon-Hyuk Park, [email protected]

This article is part of the Research Topic

Insights into Falls Efficacy and Fear of Falling