what is a non research article

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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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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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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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Evaluating Resources: Research Articles

Research articles.

A research article is a journal article in which the authors report on the research they did. Research articles are always primary sources. Whether or not a research article is peer reviewed depends on the journal that publishes it.

Published research articles follow a predictable pattern and will contain most, if not all, of the sections listed below. However, the names for these sections may vary.

• Title & Author(s)
• Introduction
• Methodology

To learn about the different parts of a research article, please view this tutorial:

Short video: How to Read Scholarly Articles

Learn some tips on how to efficiently read scholarly articles.

Video: How to Read a Scholarly Article

(4 min 16 sec) Recorded August 2019 Transcript 

More information

The Academic Skills Center and the Writing Center both have helpful resources on critical and academic reading that can further help you understand and evaluate research articles.

• Academic Skills Center Guide: Developing Your Reading Skills
• Academic Skills Center Webinar Archive: Savvy Strategies for Academic Reading
• Writing Center Podcast: WriteCast Episode 5: Five Strategies for Critical Reading

If you'd like to learn how to find research articles in the Library, you can view this Quick Answer.

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Chapter 7: Nonexperimental Research

Overview of Nonexperimental Research

Learning Objectives

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

What Is Nonexperimental Research?

Nonexperimental research  is research that lacks the manipulation of an independent variable, random assignment of participants to conditions or orders of conditions, or both.

In a sense, it is unfair to define this large and diverse set of approaches collectively by what they are  not . But doing so reflects the fact that most researchers in psychology consider the distinction between experimental and nonexperimental research to be an extremely important one. This distinction is because although experimental research can provide strong evidence that changes in an independent variable cause differences in a dependent variable, nonexperimental research generally cannot. As we will see, however, this inability does not mean that nonexperimental research is less important than experimental research or inferior to it in any general sense.

When to Use Nonexperimental Research

As we saw in  Chapter 6 , 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 and randomly assign participants to conditions or to orders of conditions. It stands to reason, therefore, that nonexperimental research is appropriate—even necessary—when these conditions are not met. There are many ways in which preferring nonexperimental research can be the case.

• The research question or hypothesis can be about a single variable rather than a statistical relationship between two variables (e.g., How accurate are people’s first impressions?).
• The research question can be about a noncausal statistical relationship between variables (e.g., Is there a correlation between verbal intelligence and mathematical intelligence?).
• The research question can be about a causal relationship, but the independent variable cannot be manipulated or participants cannot be randomly assigned to conditions or orders of conditions (e.g., Does damage to a person’s hippocampus impair the formation of long-term memory traces?).
• The research question can be broad and exploratory, or it can be 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 nonexperimental approaches is generally dictated by the nature of the research question. If it is about a causal relationship and involves an independent variable that can be manipulated, the experimental approach is typically preferred. Otherwise, the nonexperimental approach is preferred. But the two approaches can also be used to address the same research question in complementary ways. For example, nonexperimental studies establishing that there is a relationship between watching violent television and aggressive behaviour have been complemented by experimental studies confirming that the relationship is a causal one (Bushman & Huesmann, 2001) [1] . 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) [2] .

Types of Nonexperimental Research

Nonexperimental research falls into three broad categories: single-variable research, correlational and quasi-experimental research, and qualitative research. First, research can be nonexperimental because it focuses on a single variable rather than a statistical relationship between two variables. Although there is no widely shared term for this kind of research, we will call it  single-variable research . Milgram’s original obedience study was nonexperimental in this way. 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. The study by Loftus and Pickrell described at the beginning of this chapter is also a good example of single-variable 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 research 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.)

As these examples make clear, single-variable research can answer interesting and important questions. What it cannot do, however, is answer questions about statistical relationships between variables. This detail is a point that beginning researchers sometimes miss. Imagine, for example, a group of research methods students interested in the relationship between children’s being the victim of bullying and the children’s self-esteem. The first thing that is likely to occur to these researchers is to obtain a sample of middle-school students who have been bullied and then to measure their self-esteem. But this design would be a single-variable study with self-esteem as the only variable. Although it would tell the researchers something about the self-esteem of children who have been bullied, it would not tell them what they really want to know, which is how the self-esteem of children who have been bullied  compares  with the self-esteem of children who have not. Is it lower? Is it the same? Could it even be higher? To answer this question, their sample would also have to include middle-school students who have not been bullied thereby introducing another variable.

Research can also be nonexperimental because it focuses on a statistical relationship between two variables but does not include the manipulation of an independent variable, random assignment of participants to conditions or orders of conditions, or both. This kind of research takes two basic forms: correlational research and quasi-experimental research. In correlational research , the researcher measures the two variables of interest with little or no attempt to control extraneous variables and then assesses the relationship between them. A research methods student who finds out whether each of several middle-school students has been bullied and then measures each student’s self-esteem is conducting correlational research. In  quasi-experimental research , the researcher manipulates an independent variable but does not randomly assign participants to conditions or orders of conditions. For example, a researcher might start an antibullying program (a kind of treatment) at one school and compare the incidence of bullying at that school with the incidence at a similar school that has no antibullying program.

The final way in which research can be nonexperimental is that it can be qualitative. 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. In  qualitative research , the data are usually nonnumerical and therefore cannot be analyzed using statistical techniques. Rosenhan’s 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 semipublic room, where staff members went about their own business as if we were not there” (Rosenhan, 1973, p. 256). [3] 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 7.1  shows how experimental, quasi-experimental, and correlational research vary in terms of internal validity. Experimental research tends to be highest because it addresses the directionality and third-variable problems through manipulation and the control of extraneous variables through random assignment. 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. Correlational research is lowest because it fails to address either problem. If the average score on the dependent variable differs across levels of the independent variable, it  could  be that the independent variable is responsible, but there are other interpretations. In some situations, the direction of causality could be reversed. In others, there could be a third variable that is causing differences in both the independent and dependent variables. Quasi-experimental research is in the middle because the manipulation of the independent variable addresses some problems, but the lack of random assignment and experimental control fails to address others. Imagine, for example, that a researcher finds two similar schools, starts an antibullying program in one, and then finds fewer bullying incidents in that “treatment school” than in the “control school.” There is no directionality problem because clearly the number of bullying incidents did not determine which school got the program. However, 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.

Notice also in  Figure 7.1  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

• Nonexperimental research is research that lacks the manipulation of an independent variable, control of extraneous variables through random assignment, or both.
• There are three broad types of nonexperimental research. Single-variable research focuses on a single variable rather than a relationship between variables. Correlational and quasi-experimental research focus on a statistical relationship but lack manipulation or random assignment. Qualitative research focuses on broader research questions, typically involves collecting large amounts of data from a small number of participants, and analyses the data nonstatistically.
• In general, experimental research is high in internal validity, correlational research is low in internal validity, and quasi-experimental research is in between.

Discussion: For each of the following studies, decide which type of research design it is and explain why.

• 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.
• Bushman, B. J., & Huesmann, L. R. (2001). Effects of televised violence on aggression. In D. Singer & J. Singer (Eds.), Handbook of children and the media (pp. 223–254). Thousand Oaks, CA: Sage. ↵
• 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. ↵

Research that lacks the manipulation of an independent variable, random assignment of participants to conditions or orders of conditions, or both.

Research that focuses on a single variable rather than a statistical relationship between two variables.

The researcher measures the two variables of interest with little or no attempt to control extraneous variables and then assesses the relationship between them.

The researcher manipulates an independent variable but does not randomly assign participants to conditions or orders of conditions.

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

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Q. What's the difference between a research article (or research study) and a review article?

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Answered By: Priscilla Coulter Last Updated: Jul 29, 2022     Views: 231494

A research paper is a primary source ...that is, it reports the methods and results of an original study performed by the authors . The kind of study may vary (it could have been an experiment, survey, interview, etc.), but in all cases, raw data have been collected and analyzed by the authors , and conclusions drawn from the results of that analysis.

Research papers follow a particular format.  Look for:

• A brief introduction will often include a review of the existing literature on the topic studied, and explain the rationale of the author's study.  This is important because it demonstrates that the authors are aware of existing studies, and are planning to contribute to this existing body of research in a meaningful way (that is, they're not just doing what others have already done).
• A methods section, where authors describe how they collected and analyzed data.  Statistical analyses are included.  This section is quite detailed, as it's important that other researchers be able to verify and/or replicate these methods.
• A results section describes the outcomes of the data analysis.  Charts and graphs illustrating the results are typically included.
• In the discussion , authors will explain their interpretation of their results and theorize on their importance to existing and future research.
• References or works cited are always included.  These are the articles and books that the authors drew upon to plan their study and to support their discussion.

You can use the library's article databases to search for research articles:

• A research article will nearly always be published in a peer-reviewed journal; click here for instructions on limiting your searches to peer-reviewed articles.  
• If you have a particular type of study in mind, you can include keywords to describe it in your search .  For instance, if you would like to see studies that used surveys to collect data, you can add "survey" to your topic in the database's search box. See this example search in our EBSCO databases: " bullying and survey ".   
• Several of our databases have special limiting options that allow you to select specific methodologies.  See, for instance, the " Methodology " box in ProQuest's PsycARTICLES Advanced Search (scroll down a bit to see it).  It includes options like "Empirical Study" and "Qualitative Study", among many others.  

A review article is a secondary source ...it is written about other articles, and does not report original research of its own.  Review articles are very important, as they draw upon the articles that they review to suggest new research directions, to strengthen support for existing theories and/or identify patterns among exising research studies.  For student researchers, review articles provide a great overview of the existing literature on a topic.    If you find a literature review that fits your topic, take a look at its references/works cited list for leads on other relevant articles and books!

You can use the library's article databases to find literature reviews as well!  Click here for tips.

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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.

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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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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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James E. Walker Library

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

• Topic Exploration
• Finding Peer Reviewed Articles
• Finding Non Peer Reviewed Sources
• Finding an Article from a Citation
• Finding Books
• APA Citation Style
• Credibility & Bias
• Types of Articles & Journals
• Library Seminars

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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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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• Fewer than 1% of workers are estimated to be senior executives under the final rule.
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ORIGINAL RESEARCH article

Degradation of chlorophyllic organic matter within the deep estuary of the st. lawrence river as an indicator of remineralization in the water column provisionally accepted.

• 1 Maurice Lamontagne Institute, Fisheries and Oceans Canada (DFO), Canada
• 2 Québec Océan, Laval University, Canada

The final, formatted version of the article will be published soon.

Coastal hypoxia, driven by remineralization of chlorophyllic particulate organic matter (POM) in dark environments, poses a threat to deep estuarine and shelf ecosystems. To better understand the fate of POM along a depth gradient, we investigated the degradation of chloropigments, particulate organic carbon (POC), and nitrogen (PON) across the water column in the St. Lawrence Estuary, one of the largest and deepest estuarine system in the world that is facing strong persistent and increasing hypoxia. Our objectives were to establish causal relationships among suspended POM descriptors and assess the potential of a chlorophyll-based degradation index, known as the chlorin index (CI), in evaluating OM degradation within the water column. The CI, ranging from 0.2 for pure chlorophyll to almost 1 for highly degraded pigments, was initially developed for uses in the sediments. Water samples from multiple depths were collected, characterized, and statistically analyzed with a combination of variation partitioning, non-linear regressions and piecewise structural equation modeling (pSEM).We found that the combined influence of chloropigments and depth explained 84.0% of POC and 90.0 % of PON variations; the pure fraction attributed to chloropigments accounted for 73.4% and 75.6% (R 2 adj, both with p < 0.001), respectively. The decline of chloropigments, PON, and POC with increasing depth was reflected by the concomitant increase in CI, whose rate decreases as particles sink resulting in reduced degradation due to less labile organic matter. The pSEM causal model indicated that CI increased with depth and POC concentration, while it decreased in the presence of elevated PON concentrations, known for their high reactivity. The direct effect of depth on CI could be linked to the distinct water column properties influencing particle residence time and thus the degradation potential by biotic and abiotic factors. Finally, CI explained 86% (R 2 ) of the apparent oxygen utilization highlighting the strong connection between POM degradation and hypoxia of deep coastal ecosystems. Our study underscores the utility of the chlorin index as a simple yet robust tool for monitoring OM degradation in the water column, particularly in the St. Lawrence Estuary.

Keywords: organic matter, Chlorophyll, degradation, remineralization, St. Lawrence Estuary, hypoxia, chloropigments, Oxygen

Received: 12 Mar 2024; Accepted: 29 Apr 2024.

Copyright: © 2024 Levesque, Lebeuf and Starr. 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) or licensor 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: Mx. David Levesque, Maurice Lamontagne Institute, Fisheries and Oceans Canada (DFO), Mont‐Joli, Canada

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What the data says about crime in the U.S.

A growing share of Americans say reducing crime should be a top priority for the president and Congress to address this year. Around six-in-ten U.S. adults (58%) hold that view today, up from 47% at the beginning of Joe Biden’s presidency in 2021.

We conducted this analysis to learn more about U.S. crime patterns and how those patterns have changed over time.

The analysis relies on statistics published by the FBI, which we accessed through the Crime Data Explorer , and the Bureau of Justice Statistics (BJS), which we accessed through the  National Crime Victimization Survey data analysis tool .

To measure public attitudes about crime in the U.S., we relied on survey data from Pew Research Center and Gallup.

Additional details about each data source, including survey methodologies, are available by following the links in the text of this analysis.

With the issue likely to come up in this year’s presidential election, here’s what we know about crime in the United States, based on the latest available data from the federal government and other sources.

How much crime is there in the U.S.?

It’s difficult to say for certain. The  two primary sources of government crime statistics  – the Federal Bureau of Investigation (FBI) and the Bureau of Justice Statistics (BJS) – paint an incomplete picture.

The FBI publishes  annual data  on crimes that have been reported to law enforcement, but not crimes that haven’t been reported. Historically, the FBI has also only published statistics about a handful of specific violent and property crimes, but not many other types of crime, such as drug crime. And while the FBI’s data is based on information from thousands of federal, state, county, city and other police departments, not all law enforcement agencies participate every year. In 2022, the most recent full year with available statistics, the FBI received data from 83% of participating agencies .

BJS, for its part, tracks crime by fielding a  large annual survey of Americans ages 12 and older and asking them whether they were the victim of certain types of crime in the past six months. One advantage of this approach is that it captures both reported and unreported crimes. But the BJS survey has limitations of its own. Like the FBI, it focuses mainly on a handful of violent and property crimes. And since the BJS data is based on after-the-fact interviews with crime victims, it cannot provide information about one especially high-profile type of offense: murder.

All those caveats aside, looking at the FBI and BJS statistics side-by-side  does  give researchers a good picture of U.S. violent and property crime rates and how they have changed over time. In addition, the FBI is transitioning to a new data collection system – known as the National Incident-Based Reporting System – that eventually will provide national information on a much larger set of crimes , as well as details such as the time and place they occur and the types of weapons involved, if applicable.

Which kinds of crime are most and least common?

Property crime in the U.S. is much more common than violent crime. In 2022, the FBI reported a total of 1,954.4 property crimes per 100,000 people, compared with 380.7 violent crimes per 100,000 people.  

By far the most common form of property crime in 2022 was larceny/theft, followed by motor vehicle theft and burglary. Among violent crimes, aggravated assault was the most common offense, followed by robbery, rape, and murder/nonnegligent manslaughter.

BJS tracks a slightly different set of offenses from the FBI, but it finds the same overall patterns, with theft the most common form of property crime in 2022 and assault the most common form of violent crime.

How have crime rates in the U.S. changed over time?

Both the FBI and BJS data show dramatic declines in U.S. violent and property crime rates since the early 1990s, when crime spiked across much of the nation.

Using the FBI data, the violent crime rate fell 49% between 1993 and 2022, with large decreases in the rates of robbery (-74%), aggravated assault (-39%) and murder/nonnegligent manslaughter (-34%). It’s not possible to calculate the change in the rape rate during this period because the FBI  revised its definition of the offense in 2013 .

The FBI data also shows a 59% reduction in the U.S. property crime rate between 1993 and 2022, with big declines in the rates of burglary (-75%), larceny/theft (-54%) and motor vehicle theft (-53%).

Using the BJS statistics, the declines in the violent and property crime rates are even steeper than those captured in the FBI data. Per BJS, the U.S. violent and property crime rates each fell 71% between 1993 and 2022.

While crime rates have fallen sharply over the long term, the decline hasn’t always been steady. There have been notable increases in certain kinds of crime in some years, including recently.

In 2020, for example, the U.S. murder rate saw its largest single-year increase on record – and by 2022, it remained considerably higher than before the coronavirus pandemic. Preliminary data for 2023, however, suggests that the murder rate fell substantially last year .

How do Americans perceive crime in their country?

Americans tend to believe crime is up, even when official data shows it is down.

In 23 of 27 Gallup surveys conducted since 1993 , at least 60% of U.S. adults have said there is more crime nationally than there was the year before, despite the downward trend in crime rates during most of that period.

While perceptions of rising crime at the national level are common, fewer Americans believe crime is up in their own communities. In every Gallup crime survey since the 1990s, Americans have been much less likely to say crime is up in their area than to say the same about crime nationally.

Public attitudes about crime differ widely by Americans’ party affiliation, race and ethnicity, and other factors . For example, Republicans and Republican-leaning independents are much more likely than Democrats and Democratic leaners to say reducing crime should be a top priority for the president and Congress this year (68% vs. 47%), according to a recent Pew Research Center survey.

How does crime in the U.S. differ by demographic characteristics?

Some groups of Americans are more likely than others to be victims of crime. In the  2022 BJS survey , for example, younger people and those with lower incomes were far more likely to report being the victim of a violent crime than older and higher-income people.

There were no major differences in violent crime victimization rates between male and female respondents or between those who identified as White, Black or Hispanic. But the victimization rate among Asian Americans (a category that includes Native Hawaiians and other Pacific Islanders) was substantially lower than among other racial and ethnic groups.

The same BJS survey asks victims about the demographic characteristics of the offenders in the incidents they experienced.

In 2022, those who are male, younger people and those who are Black accounted for considerably larger shares of perceived offenders in violent incidents than their respective shares of the U.S. population. Men, for instance, accounted for 79% of perceived offenders in violent incidents, compared with 49% of the nation’s 12-and-older population that year. Black Americans accounted for 25% of perceived offenders in violent incidents, about twice their share of the 12-and-older population (12%).

As with all surveys, however, there are several potential sources of error, including the possibility that crime victims’ perceptions about offenders are incorrect.

How does crime in the U.S. differ geographically?

There are big geographic differences in violent and property crime rates.

For example, in 2022, there were more than 700 violent crimes per 100,000 residents in New Mexico and Alaska. That compares with fewer than 200 per 100,000 people in Rhode Island, Connecticut, New Hampshire and Maine, according to the FBI.

The FBI notes that various factors might influence an area’s crime rate, including its population density and economic conditions.

What percentage of crimes are reported to police? What percentage are solved?

Most violent and property crimes in the U.S. are not reported to police, and most of the crimes that  are  reported are not solved.

In its annual survey, BJS asks crime victims whether they reported their crime to police. It found that in 2022, only 41.5% of violent crimes and 31.8% of household property crimes were reported to authorities. BJS notes that there are many reasons why crime might not be reported, including fear of reprisal or of “getting the offender in trouble,” a feeling that police “would not or could not do anything to help,” or a belief that the crime is “a personal issue or too trivial to report.”

Most of the crimes that are reported to police, meanwhile,  are not solved , at least based on an FBI measure known as the clearance rate . That’s the share of cases each year that are closed, or “cleared,” through the arrest, charging and referral of a suspect for prosecution, or due to “exceptional” circumstances such as the death of a suspect or a victim’s refusal to cooperate with a prosecution. In 2022, police nationwide cleared 36.7% of violent crimes that were reported to them and 12.1% of the property crimes that came to their attention.

Which crimes are most likely to be reported to police? Which are most likely to be solved?

Around eight-in-ten motor vehicle thefts (80.9%) were reported to police in 2022, making them by far the most commonly reported property crime tracked by BJS. Household burglaries and trespassing offenses were reported to police at much lower rates (44.9% and 41.2%, respectively), while personal theft/larceny and other types of theft were only reported around a quarter of the time.

Among violent crimes – excluding homicide, which BJS doesn’t track – robbery was the most likely to be reported to law enforcement in 2022 (64.0%). It was followed by aggravated assault (49.9%), simple assault (36.8%) and rape/sexual assault (21.4%).

The list of crimes  cleared  by police in 2022 looks different from the list of crimes reported. Law enforcement officers were generally much more likely to solve violent crimes than property crimes, according to the FBI.

The most frequently solved violent crime tends to be homicide. Police cleared around half of murders and nonnegligent manslaughters (52.3%) in 2022. The clearance rates were lower for aggravated assault (41.4%), rape (26.1%) and robbery (23.2%).

When it comes to property crime, law enforcement agencies cleared 13.0% of burglaries, 12.4% of larcenies/thefts and 9.3% of motor vehicle thefts in 2022.

Are police solving more or fewer crimes than they used to?

Nationwide clearance rates for both violent and property crime are at their lowest levels since at least 1993, the FBI data shows.

Police cleared a little over a third (36.7%) of the violent crimes that came to their attention in 2022, down from nearly half (48.1%) as recently as 2013. During the same period, there were decreases for each of the four types of violent crime the FBI tracks:

• Police cleared 52.3% of reported murders and nonnegligent homicides in 2022, down from 64.1% in 2013.
• They cleared 41.4% of aggravated assaults, down from 57.7%.
• They cleared 26.1% of rapes, down from 40.6%.
• They cleared 23.2% of robberies, down from 29.4%.

The pattern is less pronounced for property crime. Overall, law enforcement agencies cleared 12.1% of reported property crimes in 2022, down from 19.7% in 2013. The clearance rate for burglary didn’t change much, but it fell for larceny/theft (to 12.4% in 2022 from 22.4% in 2013) and motor vehicle theft (to 9.3% from 14.2%).

Note: This is an update of a post originally published on Nov. 20, 2020.

• Criminal Justice

John Gramlich is an associate director at Pew Research Center

8 facts about Black Lives Matter

#blacklivesmatter turns 10, support for the black lives matter movement has dropped considerably from its peak in 2020, fewer than 1% of federal criminal defendants were acquitted in 2022, before release of video showing tyre nichols’ beating, public views of police conduct had improved modestly, most popular.

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• Published: 24 April 2024

The impacts of national centralized drug procurement policy on drug utilization of medical institutions: an empirical study in a county-level hospital in China

• Haoye Li 1   na1 ,
• Fanyu Lin 1   na1 ,
• Rui Wang 1 ,
• Chenxuan Zhu 1 ,
• Keyao Cao 1 ,
• Yu Chen 1 ,
• Gang Fang 1 ,
• Jiaming Li 1 ,
• Jinxi Ding 1 , 2   na1 &
• Wei Li 1 , 2   na1  

BMC Health Services Research volume  24 , Article number:  513 ( 2024 ) Cite this article

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Metrics details

Under the background of the regular implementation of the National Centralized Drug Procurement (NCDP) policy, this study aimed to assess the impacts of the NCDP policy on drug utilization of county-level medical institutions, and probe into the influencing factors of the changes in drug utilization.

A pre-post study was applied using inpatient data from a county-level medical institution in Nanjing. Drug utilization behavior of medical institutions of 88 most commonly used policy-related drugs (by generic name, including bid-winning and bid-non-winning brands) was analyzed, and the substitution of bid-winning brands for brand-name drugs after policy intervention was evaluated.

After policy intervention, 43.18% of policy-related drugs realized the substitution of bid-winning brands for bid-non-winning brands (6.82% of complete substitution, 36.36% of partial substitution). Meanwhile, 40.90% of policy-related drugs failed to realize brand substitution. Multiple factors affected brand substitution, including: (1) Policy effect: brand substitution was more obvious after the intervention of the first and third round of NCDP. (2) Drug market competition: the greater the price reduction of bid-non-winning brands, the more the drugs for the same indication, the more likely that medical institutions keep using the same brands as they did before policy intervention. (3) Previous drug utilization of medical institutions: brand substitution was more obvious in drugs with large number of prescriptions and weak preference for brand-name drugs.

The NCDP policy promoted the substitution of bid-winning brands for bid-non-winning brands. However, the NCDP policy remained to be further implemented in county-level medical institutions. Policy implememtation efforts, drug market competition and drug utilization of medical institutions would affect the implementation of the NCDP policy.

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Introduction

National Centralized Drug Procurement (NCDP) policy is one of the supplemental drug procurement policies in China implemented since December 2018. Since 2009, China has initiated healthcare reform, and implemented a province-based, government-led procurement pattern, whereby enterprises negotiate with medical institutions after listing on the provincial-level platform and medical institutions purchase on-demand. In December 2018, the State Council released the Pilot Program for National Centralized Drug Procurement and Utilization , which introduced NCDP policy for the first time, supplementing the existing drug procurement pattern in China. By October 2023, there have been eight rounds of centralized procurement, with an average of 41 policy-related drugs per round and an average price reduction of more than 50% [ 1 ].

NCDP policy is a government-led procurement pattern, which is widely practiced around the world. For example, the UK has a universal health insurance system, with the NHS (National Health Service) leading the centralized procurement of off-patent drugs and generic drugs in public hospitals [ 2 ,  3 ]. In Hong Kong China, drug is centrally procured by the Hospital Authority (HA) of SAR (Special Administrative Region) in conjunction with all the public healthcare institutions [ 4 ].

Led and organized by the National Healthcare Security Administration (NHSA), the NCDP policy is implemented through a comprehensive service platform. Footnote 1 NHSA selects drugs with sufficient market competition and large market scale, negotiates prices with enterprises (no distinction between brand-name drug and generic drug) based on their quoted prices, supply capacity, market recognition and other comprehensive conditions. The bid-winning enterprise reduces its price drastically, and in order to guarantee its benefits, NHSA promises 50%—70% of the total annual drug utilization volume of all public medical institutions in the alliance regions (different proportions are set according to the characteristics of drugs).

The NCDP policy, as a supplementary procurement policy, only covers the most commonly used drugs in the clinical setting, and for the first time, mandates public medical institutions to equip a certain volume of the procured brands within a procurement cycle. In addition, the NCDP policy establishes rewards and penalties for medical institutions' drug utilization. For example, additional incentives may be provided based on the completion status of medical institutions, while those who fail to equip the assigned procurement volume may be criticized and reprimanded.

After policy intervention, bid-winning enterprises exhibit two characteristics. On the one hand, the prices of bid-winning brands significantly decrease. Taking Flurbiprofen Ester Injection as an example, the winning enterprise, Wuhan Da'an Pharmaceutical Co., Ltd., witnessed a 64.46% reduction in DDDc (61.77 vs. 21.95, P  < 0.000), which was significantly lower than bid-non-winning enterprises (21.95 vs. 62.25, Footnote 2 P  < 0.000). Therefore, it is evident that bid-winning enterprises would enjoy a significant pricing advantage.

On the other hand, bid-winning enterprises occupy 50%-70% market share of policy-related drugs in the next procurement cycle. Meanwhile, policy-related drugs also have direct access to medical institutions, which means that after policy intervention, bid-winning enterprises would dominate the market compared to bid-non-winning enterprises.

However, in order to ensure the autonomy of medical institutions in drug procurement and to cope with supply risks, bid-non-winning enterprises would still retain a certain share of the market. Medical institutions can procure drugs from bid-non-winning enterprises under the premise of completing the assigned procurement volume of the bid-winning brands.

Therefore, as a special drug procurement policy, NCDP policy has an impact on the changes of drug utilization of medical institutions in the following three aspects. Firstly, the NCDP policy promoted the substitution of generic drugs for brand-name drugs. Most doctors and pharmacists in China support such substitution based on professional judgment [ 5 ]. And there was a significant increase of substitution of generic drugs for brand-name drugs [ 6 , 7 ]. Secondly, the NCDP policy promoted the substitution of bid-winning brands for bid-non-winning brands. The utilization rate of bid-winning brands in medical institutions increased significantly [ 8 ], thus reducing the average cost of medication [ 9 ]. Thirdly, the NCDP policy increased the utilization volume of bid-winning brands. For example, NCDP policy has improved the utilization volume of antibiotics [ 10 , 11 , 12 ] and drugs for chronic diseases [ 13 , 14 ].

Current research on drug utilization is relatively sufficient. However, research on NCDP policy is still immature due to limited dimension and depth. Firstly, most studies focus on a certain round of NCDP. Secondly, current research on changes of drug utilization of medical institutions using real-world medication data is insufficient. Most studies use purchasing data which cannot reflect the actual using situation. Thirdly, systematic analysis of the causes of changes in drug utilization brought by NCDP policy is lacking.

Therefore, this research focuses on county-level medical institutions that account for 47.3% of all medical institutions in China. By using inpatient drug utilization data to avoid the impact of the COVID-19, the research cycle consists of six months before the intervention and six months after the intervention to avoid the influence of two rounds of policy-related drugs in the same therapeutic field. This research aims to discover changes in physicians’ drug utilization behavior after the NCDP policy implementation by using one county-level medical institutions inpatient drug utilization data, and explores the factors that affect changes in drug utilization.

Data and methods

Target varieties.

As of carrying out this study, eight rounds of NCDP have been implemented in China. Considering that the sixth round of NCDP only included insulin which featured complex drug substitution, and the seventh and eighth rounds were implemented in Jiangsu in November 2022, August 2023 with a short period, respectively this study only involved drugs of the first to fifth round.

During the defined research cycle, the target medical institution used 103 policy-related drugs, accounting for 47.48% of policy-related drugs involved in the five rounds of NCDP, which was highly representative. However, of the 103 policy-related drugs, 15 had less than 20 prescription records. Such small data volume may result in extreme values, therefore, they were excluded from analysis. Thus, 88 drugs were included, and their brand substitution was analyzed.

Research cycle

This research used inpatient data of a county-level medical institution in Nanjing from 1st January 2019 to 31st December 2021. The interval between two rounds of NCDP is about 6 months. Besides, therapeutic areas of policy-related varieties between rounds may be overlapped. Therefore, the research cycle of this study is 12 months for each round, consisting of 6 months before and 6 months after policy implementation, so that interruption between rounds would be avoided (Table  1 Inpatient drug utilization information).

Target stata

As this study was launched amid the period of Covid-19, outpatient service in some medical institutions was closed Footnote 3   Footnote 4 , while inpatient service was impacted to a less degree. Therefore, outpatient data was not included in order to maintain the integrity of data. Besides, there is possibility that outpatient patients choose not to purchase drugs in hospital pharmacy, substituting bid-winning drugs for brand-name drugs. Therefore, only inpatient data was used for analysis so that the result could be ensured to reflect the real-world situation.

After desensitizing the patients' personal information and deleting incomplete and abnormal records (volume or amount ≤ 0), a total number of 2,190,677 medication records of 76,284 patients were preserved, including 167,116 records of policy-related drugs (Table 2 Inpatient drug utilization information).

Statistical analysis

This study focused on the change in price and volume of policy-related drugs after policy intervention.

Drug price was evaluated by Defined Daily Dose Cost (DDDc). DDDc takes DDD as the unit of measurement to reflect the average daily medication cost. The larger the DDDc, the higher the price.

① Unit price: sales price of the target drug per package size.

② Package size: the minimum quantity of measurement units included in the package unit.

③ Unit strength: the content of active ingredients in the minimum unit of measurement of the target drug

④ DDD: Defined Daily Dose, that is, the average daily maintenance dose for adults, determined according to the Guidelines for ATC Classification and DDD Assignment 2021 issued by WHO and the package insert.

Take Acarbose (the second round) for example. Its DDDc of 2.46 is calculated based on the unit price of 36.9 CNY/box, the package size of 30 tablets/box, the unit strength of 0.25ug, and the DDD of 0.5ug.

Drug volume was evaluated by Defined Daily Dose (DDDs). DDDs takes DDD as the unit of measurement to reflect days of application. The larger the DDDs, the larger the volume.

⑤ Drug volume: the total volume of the target drug by patient in a certain visit.

Take Acarbose (the second round) for example. The DDDs of 30 is calculated by the DDD of 0.5ug and the drug volume of 0.25ug*30 tablets/box*2 boxes.

Analytical method

For one thing, the data of this study is not linearly distributed, and it is difficult to choose the control group because NCDP is a nationwide policy. So ITS or DID analysis is not suitable. Eventually, through pre-post study, interrupted by the time of NCDP implementation, this study applied the descriptive statistics to analyze the change in target indexes, and applied rank-sum test or unpaired t test for statistics test.

For another, after grouping the results through descriptive statistics, this study applied rank-Sum test of categorical variables and one-way Anova of continuous variables to launch the between-group test of influencing factors (see Influencing factors of drug utilization change section) so that whether the difference between situations was large could be investigated.

This study used Microsoft Excel 2019 to establish database and used the statistical data analysis software Stata 16.0 to complete the analysis. p  < 0.05 was considered statistically significant.

Based on the medication data of 88 policy-related drugs commonly used in medical institutions, this study analyzed the substitution of bid-winning brands for bid-non-winning brands.

Drug utilization analysis

Through detailed analysis of 167,116 medication data of 88 commonly-used policy-related drugs, Footnote 5 this study summarized the patterns of brand substitution after policy intervention: 43.18% varieties have achieved brand substitution, including high-intensity substitution (complete substitution) and middle-intensity substitution (partial substitution); 40.90% varieties have not achieved brand substitution; 15.91% have achieved alternation of varieties (Table  3 Summary of the substitution of policy-related drugs).

Situation 1: brand substitution

High-intensity substitution.

High-intensity substitution (complete substitution) referred to the partial or complete utilization of bid-non-winning brands before policy intervention, and complete utilization of bid-winning brands after policy intervention. 6 (6/88, 6.81%) policy-related drugs realized complete substitution (Table  4 Drugs of complete substitution).

Among the 6 drugs of complete substitution, the DDDs of 3 (3/6, 50%) bid-winning brands increased significantly. Among them, the growth rate of the DDDs of ticagrelor tablets for cardiovascular system was the largest, which was 34.14% (the average value of the six months before and after policy intervention).

It was worth noting that after complete substitution, the DDDs of docetaxel injection decreased significantly while the DDDs of montelukast sodium oral granules observed no significant change. Two reasons were at play based on on-site interviews in the medical institution: For one thing, efficacy became unstable after brand substitution, therefore, doctors switched to other varieties, such as docetaxel injection; For another, the mutual substitution of policy-related drugs lead to the decrease of DDDs of bid-winning brands. Take montelukast sodium oral granules of the third round as an example, the tablets and chewable tablets of the same generic name were procured in the first and third round respectively. Within six months after policy intervention, the DDDs of these two increased by 13.22% and 24.39% respectively, which had a substitution effect on montelukast sodium oral granules.

Middle-intensity substitution

Middle-intensity substitution (Partial substitution) referred to that the utilization volume of bid-winning brands increased after policy intervention, gradually substituting bid-non-winning brands. In the analyzed samples, 32 drugs (32/88, 36.36%) realized partial substitution, which was the mainstream situation (Table  5 Drugs of partial substitution).

Among the 32 drugs of partial substitution, the bid-winning brands of 27 drugs (27/32, 84.37%) were not used before policy intervention. After policy intervention, medical institutions started using these brands. The bid-winning brands of 5 drugs (5/32, 18.75%) were seldom used before policy intervention. After policy intervention, their utilization volume significantly increased, gradually took the share of bid-non-winning brands.

Situation 2: no substitution

No substitution was another mainstream type of brand substitutions in the medical institution, including two situations:

Bid-winning brands were used both before and after policy intervention

Bid-winning brands were used both before and after policy intervention, but their DDDc and DDDs changed. This was the case for 5 (5/88, 5.68%) policy-related drugs (Table  6 Bid-winning brands were used both before and after policy intervention). Except that the DDDc of alfacalcidol tablets remained unchanged, the DDDc of other drugs all decreased significantly, the NCDP policy lowered drug prices. The DDDs of acarbose capsules and letrozole tablets decreased significantly, while other varieties observed no significant change. The possible reasons were as followed:

First, there could be mutual substitution between drugs for the same indication. Acarbose capsules and letrozole tablets had the same indication with many other policy-related drugs. For example, acarbose capsules was selected in the second round of NCDP. However, 15 more antidiabetic drugs were selected in the third to fifth round, which caused varying degrees of substitution for acarbose capsules. This caused the reduction of its DDDs.

Second, the drug demand has weak correlation to its price. For example, iohexol injection is a contrast medium, the demand of which is directly influenced by the number of patients rather than its price. As a result, the utilization volume of iohexol injection did not significantly increase after policy intervention.

① Bid-non-winning brands were used both before and after policy intervention

Bid-non-winning brands were used both before and after policy intervention, with the DDDc of bid-non-winning brands decreased. The share of bid-winning brands in the medical institution did not increase (no substitution). This was the case for 31 (31/88, 35.22%) policy-related drugs (Table  7 Bid-non-winning brands were used both before and after policy intervention).

Among the 31 drugs, the bid-non-winning brands of 27 drugs (27/31, 87.10%) were used both before and after policy intervention, and the DDDc of them showed a downward trend after policy intervention. Of the 27 drugs, the DDDc of 22 drugs decreased significantly, the average decrease was 39.26%. The DDDc of moxifloxacin hydrochloride tablets, donepezil hydrochloride tablets and ambroxol hydrochloride injection decreased by more than 80.00%. Moreover, the bid-non-winning brands of one drug (mosapride citrate tablets) came into use after policy intervention, causing the DDDs of the bid-winning brands decreased by 16.34%. And the DDDs of 3 drugs (iodixanol injection, rivaroxaban tablets and ropivacaine hydrochloride for injection) decreased, the DDDs reduction of their bid-winning brands was even greater than that of their bid-non-winning brands.

Situation 3: Alternation of varieties

Policy-related drugs came into use after policy intervention.

Policy-related drugs came into use after policy intervention referred to drugs that were not used before policy intervention and started being used after policy intervention. This was the case for 8 (8/88, 9.10%) policy-related drugs (Table  8 Policy-related drugs used after policy intervention). The medical institution did not report the volume indicator of the bid-winning brands of azithromycin tablets and levocetirizine dihydrochloride tablets, thus keeping using the bid-non-winning brands. The bid-winning brands of other drugs were used after policy intervention.

Policy-related drugs no longer used after policy intervention

Six (6/88, 6.82%) policy-related drugs were no longer used by the medical institution after policy intervention (Table  9 Policy-related drugs no longer used after policy intervention). According to our analysis, three following reasons are responsible for that:

First, the number of medication cases of these drugs was relatively small. Voriconazole tablets, nateglinide tablets, tinidazole tablets, linezolid, and glucose injection all had less than 50 prescriptions records, which revealed that these drugs were not commonly used in the medical institution. Second, there could be mutual substitution between drugs of the same indication. For example, etoricoxib tablets was selected in the third round. Three commonly used drugs of the same indication including celecoxib capsule and paracetamol tablets were selected before or together with etoricoxib tablets, which had substitution effect on etoricoxib tablets. Third, some of these drugs became more out-patiently used rather than in-patiently used. For example, palonosetron hydrochloride injection is primarily used for preventing nausea and vomiting caused by chemotherapy. Due to the continuous improvement of the treatment level of outpatient service in China, cancer patients can apply for medical insurance reimbursement for radiotherapy, chemotherapy, and pain treatment, leading to the decrease of in-patient use of palonosetron hydrochloride injection.

Influencing factors of drug utilization change

To probe into the influencing factors of brand substitution, three types of factors were analyzed based on literature review and field research, including policy effect, drug market condition, and previous drug utilization of the medical institution(Table 10 Influencing factors of brand substitution).

Categorical variable “indication” was assigned as below (Table  11 Influencing factors of brand utilization (indication type)):

According to results, six factors had significant influence on all situations, as shown in Table 12 (Results of parametric/non-parametric analysis) Results of parametric/non-parametric analysis:

Policy effect

In the analysis of policy effect, political factor (the order of inclusion in the NCDP) played a significant role ( P  = 0.0049). In the first and third round of NCDP, 85.71% and 69.57% policy-related drugs realized brand substitution respectively (complete substitution & partial substitution). By contrast, in the second and fourth round of NCDP, only 7.14% policy-related drugs realized brand substitution, respectively.

Our study proposed that the number of substituted drugs was positively correlated with the efforts made by government at all levels in policy promotion (Fig.  1 Summary of brand substitution in each round of NCDP).

Summary of brand substitution in each round of NCDP

In the first round of NCDP, of which the brand substitution rate was the highest, press conference was held to promote the pilot program before policy intervention. Policy interpretation of the NCDP implementing scheme and Q&A of rational clinical use of both bid-winning and bid-non-winning drugs were released after policy intervention. The policymakers also launched training programs on the settlement of policy-related drugs. All these efforts promoted the brand substitution in medical institutions.

For example, on January 17, 2020, Jiangsu Provincial Medical Insurance Bureau released Notice on Issues Related to the Reasonable Clinical Use of Bid-winning and Bid-non-winning Drugs in the National Centralized Drug Procurement to guide drug alternation. And a training meeting was held with relevant leaders from major medical institutions in Jiangsu Province, providing guidance from aspects of "priority substitution, reasonable substitution, and strengthened publicity", which helped medical institutions implement the NCDP policy.

② Drug market competition

In the analysis of drug market competition, average price reduction of bid-non-winning brands ( P  = 0.0004), indication type of bid-winning brands ( P  = 0.0154) played significant roles.

For one thing, the tendency of brand substitution was negatively correlated with the average price reduction of bid-non-winning brands. In the case of partial substitution, the average price reduction of bid-non-winning brands was 14.29%, among which the price reduction of bid-non-winning brands of 9 drugs (27.27%, 9/33) was over 20%. By contrast, in the case of no substitution, the average price reduction of bid-non-winning brands used after policy intervention Footnote 6 was 28.82%, among which the price reduction of bid-non-winning brands of 13 drugs (43.33%, 13/20) was over 20%. Significant difference was observed between the two situations. When bid-non-winning brands realized a relatively high price reduction, the corresponding bid-winning brands were more likely to not be substituted at all (Fig.  2 Substitution type and price reduction of bid-non-winning brands).

Substitution type and price reduction of bid-non-winning brands

For another, the tendency of brand substitution was negatively correlated with the number of drugs of the same indication before policy intervention. By sorting policy-related drugs of the same indication, it was observed that for the 6 policy-related drugs no longer used after policy intervention, each of them had averagely 10.17 drugs of the same indication already included in the NCDP before. Additionally, for the 35 drugs of no substitution, each of them had averagely 4.94 drugs of the same indication already included in the NCDP before. Therefore, when medical institutions had a wide selection of drugs, they tended to simplify drugs or brands (Fig.  3 Summary of substitution type and indication type).

Summary of substitution type and indication type

Previous drug utilization of the medical institution

In the analysis of previous drug utilization of the medical institution, the number of prescriptions was positively correlated with the tendency of brand substitution ( P  = 0.0002).

Drugs with large number of prescriptions were more likely to realize partial substitution. Because relatively larger utilization volume and higher frequency of use allowed new brands to enter the market or change the original market share. In our study, 33 drugs (33/88, 37.50%) realized partial substitution, their average number of prescriptions was 3,034.

However, drugs with relatively moderate utilization volume and frequency of use were more likely to realize complete or no substitution. To drugs of complete and no substitution, the average number of prescriptions was 1,608 and 1,518 respectively, about 50% of partial substitution. For these drugs, medical institutions preferred to choose a specific brand, resulting in complete or no substitution.

Apart from the number of prescriptions, our study found in the exploratory interview that the tendency of brand substitution was negatively correlated with the preference for brand-name drugs, in other words, the proportion of brand-name prescriptions was relatively large after policy intervention. Drugs with weaker preference for brand-name drugs were more likely to realize brand substitution. In the 6 types of brand substitution, 32 drugs (32/88, 36.36%) had used brand-name drugs before policy intervention, 2 of which (2/32, 6.25%) realized complete substitution. The proportion of brand-name drug prescriptions of these 2 drugs turned from 78.26% to 0% after policy intervention, which showed extremely weak preference for brand-name drugs.

Fourteen drugs (14/32,43.75%) realized partial substitution. The proportion of brand-name drug prescriptions of these 14 drugs dramatically decreased after policy intervention, turning from 78.15% to 31.17%, which showed relatively weak preference for brand-name drugs.

Fifteen drugs (15/32, 46.87%) realized no substitution (bid-non-winning brands were used both before and after policy intervention). Footnote 7 The proportion of brand-name drug prescriptions of these 15 drugs turned from 92.13% to 70.01% after policy intervention. Among them, esomeprazole magnesium enteric-coated tablets, finasteride tablets, and other 8 drugs still only used brand-name drugs after policy intervention, showing strong preference for brand-name drugs. To conclude, in actual medication, some drugs had strong preference for brand-name drugs, directly weakening the substitution of bid-winning brands (Fig.  4 Relation between substitution intensity and preference for brand-name drugs).

Relation between substitution intensity and preference for brand-name drugs

The NCDP policy influenced the medication selection of medical institutions

The NCDP policy altered the medication behavior of medical institutions through the substitution of bid-winning brands for bid-non-winning brands. 43.18% of the 88 policy-related drugs realized brand substitution after policy intervention (6.82% of complete substitution and 36.36% of partial substitution). The NCDP policy effectively promoted brand substitution in medical institutions.

Meanwhile, 39.77% policy-related drugs realized no substitution. Our study proposed that it was due to the following reasons:

First, the price of bid-non-winning brands dropped significantly. The average price reduction was 28.82%, and for some drugs it exceeded 60%. For example, prices of hydrotalcite chewable tablets and donepezil hydrochloride tablets dropped by 69.33% and 89.03% respectively. As a result, medical institutions maintained the original brand selection. Second, field research found that the target medical institution did not report the quantity demand of some policy-related drugs, thus being free from the assessment pressure of using bid-winning brands. For example, among drugs of no substitution, 4 drugs (thioctic acid injection, fluconazole and sodium chloride injection, desloratadine tablets, esomeprazole magnesium enteric-coated tablets) did not have the indicator for the utilization volume of bid-winning brands. Therefore, the medical institution did not change its brand selection into bid-winning brands.

Multiple factors influenced the substitution of bid-winning brands for bid-non-winning brands

According to analysis, three kinds of factors had significant impact on the substitution of bid-winning brands for bid-non-winning brands: (1) policy effect, including round of the NCDP, (2) drug market competition, including price reduction of bid-non-winning brands and indication type, (3) previous drug utilization of the medical institution, including number of prescriptions and the preference for brand-name drugs.

From the perspective of policy effect, the efforts made by government at all levels in policy implementation could influence brand substitution, which was obvious in the first and third round. However, because the NCDP policy is directed by the NHSA while medical institutions are appraised by the NHC, we suggest that the coordination between the NHSA and the NHC should be strengthened. Enough time should be secured for policy implementation, and the NCDP policy appraisal system implemented by NHSA should be coordinated with the medical institutions appraisal system implemented by NHC. That is, the two appraisal systems are used together to evaluate the effect of the NCDP policy, urging medical institutions to give priority to using policy-related drugs and bid-winning brands, thus lightening the medication burden of patients.

From the perspective of drug market competition, the greater the price reduction of bid-non-winning brands, the more the drugs of the same indication selected before, the more likely that medical institutions tended to use previous brands.

For one thing, policy-related drugs whose bid-non-winning brands’ prices reduced significantly were less likely to realize brand substitution. Thus, it can be seen, the NCDP policy featured strong positive externality. It promoted the gradient price reduction of bid-non-winning brands, in the long term, the NCDP policy could help reduce sales expenses and purify market environment.

For another, the indications of policy-related drugs showed high degree of repetition. Therefore, our study suggested that the selection of policy-related drugs should be guided by clinical need and give priority to diseases with relatively fewer policy-related drugs, such as ophthalmology and cerebrovascular diseases. In this way, the scope of diseases covered by policy-related drugs could be expanded, thus benefiting wider patient groups.

From the perspective of previous drug utilization of the medical institution, brand substitution was more obvious in drugs with less brand-name preference and larger utilization volume.

Brand-name preference was an important influencing factor of brand substitution. For policy-related drugs of no substitution, brand-name drug prescriptions accounted for 92.31% before policy intervention and 70.01% after policy intervention. By contrast, for policy-related drugs of partial substitution, brand-name drug prescriptions accounted for 78.15% before policy intervention and dropped to 31.17% after policy intervention. Therefore, although the NCDP policy improved the substitution rate of generic drugs, certain policy-related drugs with strong brand-name preference still failed to realize the substitution of generic drugs.

Advantages and limitations

Our study had the following limitations due to its design. First, our study was based on one county-level medical institution. Considering the differences of economic level among regions, the differences of drug utilization habits among medical departments and drug market competition, our study results could not represent the overall situation of county-level medical institutions in China. Second, our study only used inpatient data, excluding outpatient information, which posed limitations as policy-related drugs were used in both settings.

Despite the abovementioned limitations, our study built up connections between multiple rounds of NCDP and the drug utilization of medical institutions, evaluated whether the utilization volume of policy-related drugs and different brands of the target medical institution changed after the implementation of multiple rounds of NCDP.

Furthermore, our study was based on a county-level medical institution. County-level medical institutions have the widest distribution in China, thus reflecting the influence of the NCDP policy on brand substitution and the policy effect on an universal basis. Therefore, our study has reference value for the quantitative study of the NCDP policy and further policy improvement.

The NCDP policy promoted the substitution of bid-winning brands and increased their utilization volume, lowered overall drug prices, benefited pharmaceutical companies and patients, realized the initial intention of exchanging quantity for low prices and lightening patient burden. However, the NCDP policy remained to be further implemented in county-level medical institutions. Policy enforcement, drug market competition and drug utilization of medical institutions would affect the implementation of the NCDP policy.

Availability of data and materials

The datasets analyzed during the current study are not publicly available because they were obtained from Hospital Information System, but they are available from the corresponding author on reasonable request. And the raw data did not require any administrative permission.

It refers to a management platform established by the National Healthcare Security Administration (NHSA)( https://pub.smpaa.cn/login?rn=1 ). This platform is responsible for managing the entire process of procurement, including tasks such as the submission of procurement requirements from healthcare institutions, prequalification of enterprises, the bidding process and so on.

The price of the bid-non-winning drug is the average DDDc of all non-winning brands in the target medical institutions during research cycle.

West China Hospital of Sichuan University: remaining at its post to fight Covid 19, Anesthesia Surgery Center is in action[EB\OL] http://www.wchscu.cn/detail/65199.html

Published by Taizhou High-tech District: notice of suspending the service of medical institutions including outpatient departments and clinics[EB\OL] https://mp.weixin.qq.com/s?__biz=MzI2NzA5NDk2Ng==&mid=2657311916&idx=4&sn=af74bcce6a9b23dec019d7bf7689b977&chksm=f113e275c6646b63a308fc2762a12820ec6c9c9cccac80d6df878d3f5b235c2238ce4a543dc2&scene=27

commonly-used policy-related drugs: policy-relates drugs whose number of prescription in the research cycle is greater than 20.

Because in the situation of “bid-winning brands were used both before and after policy intervention”, price data of bid-non-winning brands were unavailable. To ensure that the result was reliable, only the price reduction of bid-non-winning brands in the situation of “bid-non-winning brands were used both before and after policy intervention” was evaluated.

Because during the study period, the 5 drugs of “policy-related drugs were used both before and after policy intervention” used bid-winning generic drugs only. Therefore, to ensure that the result was reliable, only the situation of “bid-non-winning brands were used both before and after policy intervention” of no substitution was used to evaluate the preference for brand-name drugs.

Abbreviations

Antibiotics Use Density

Chinese Yuan

Differences-in-differences model

Defined Daily Doses

Defined Daily Dose Cost

Interrupted Time Series

National Centralized Drug Procurement

National Healthcare Security Administration

National Health Commission

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Acknowledgements

Not applicable.

This work was supported by Pharmaceutical Market Access Policy Research Center, China Pharmaceutical University, China. The role of the funding body included designing the study, the analysis and interpretation of data, and writing the manuscript.

Author information

Haoye Li and Fanyu Lin  contributed equally to this work and should be considered co-first authors.

Jinxi Ding and Wei Li contributed equally to this work.

Authors and Affiliations

School of International Pharmaceutical Business, China Pharmaceutical University, Nanjing, China

Haoye Li, Fanyu Lin, Rui Wang, Chenxuan Zhu, Keyao Cao, Yu Chen, Gang Fang, Jiaming Li, Jinxi Ding & Wei Li

Pharmaceutical Market Access Policy Research Center, China Pharmaceutical University, Nanjing, China

Jinxi Ding & Wei Li

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Contributions

Haoye Li and Fanyu Lin wrote the main manuscript. Rui Wang, Chenxuan Zhu, Yu Chen and Keyao Cao analyzed data. Gang Fang and Jiaming Li collected and corrected data. Jinxi Ding and Wei Li reviewed manuscripts and made suggestions. All authors reviewed the manuscript.

Corresponding authors

Correspondence to Jinxi Ding or Wei Li .

Ethics declarations

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Our study only used desensitized drug utilization data from medical institutions, which is anonymous and retrospective data obtained through observation that does not interfere with public behavior, involving no data of diagnosis and treatment behavior, or drug efficacy. Therefore, our study meets the conditions described in the regulation and is eligible for the exemption of ethical review/ approval and informed consent for the study according to Measures for Ethical Review of Life Sciences and Medical Research Involving Human Article 32 by Nanjing LuHe People’s Hospital Ethics Committee.

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How bad are invasive plants for birds? Research suggests large-scale removal may not have intended benefits

by Great Hollow Nature Preserve & Ecological Research Center

A prevailing opinion in land management is that non-native invasive plants are of no ecological value and they significantly diminish habitat quality for wildlife. Conservation practitioners allocate significant resources to invasive plant removal, often relying on surrounding native plants to passively fill the void. However, evidence that this practice improves food abundance or quality for wildlife is surprisingly limited.

In a new study published in the journal Biological Invasions , researchers in Connecticut, U.S. show that some of the most vilified invasive plants in northeastern U.S. forests may actually be of comparable value to native plants as foraging resources for insectivorous birds, and large-scale invasive plant removal on behalf of these birds may not have the intended benefits.

The research team from Great Hollow Nature Preserve and Ecological Research Center (New Fairfield, CT, U.S.) and Wesleyan University (Middletown, CT, U.S.) conducted a large-scale bird-exclusion experiment in which they compared arthropod biomass and bird foraging intensity among four species of non-native, invasive woody plants and six of the most dominant native species in an 800-acre forest preserve in western Connecticut.

They also measured the protein content (percent elemental nitrogen) of the arthropods on these plants as an indicator of food quality since protein strongly mediates food selection by breeding birds and is critical to offspring development. The study involved the collection, identification, and isotopic analysis of more than 17,000 arthropods from the branches of 240 trees and shrubs, half of which were covered with bird-exclusion netting.

The non-native invasive plants in the study included Japanese barberry, Morrow's honeysuckle, burning bush, and autumn olive while the natives included striped maple, shadbush, musclewood, witch-hazel, sweet birch, and American beech. In the common stewardship practice of removing invasives without actively planting and fostering natives afterwards, these six native species are among those most likely to fill the void left by invasive plant removal in secondary growth forests in southern New England.

They are therefore among the most realistic alternatives to invasive plants facing managers of such forests, as opposed to oaks, which are generally considered high-quality sources of insect prey for wildlife, but have been regenerating poorly and steeply declining in the eastern U.S. for nearly a century.

Unexpectedly, all lines of evidence in the study suggested the invasive plants were comparable to the natives in their value as foraging resources for birds. Arthropod biomass and protein content were broadly similar between the native and non-native species, and in turn, the birds foraged just as intensively on the non-native plants as they did on the natives.

Non-native honeysuckle stood out as having particularly high prey biomass and quality and frequent visitation by foraging birds, while Japanese barberry generally ranked the lowest.

"Our results indicate that it should first be demonstrated, not assumed, that invasive plants are inferior resources for birds compared to the dominant native plants in the community before land managers undertake costly removal efforts," said Dr. Chad Seewagen, one of the study's authors.

"Clearly some invasives are worse than others and it's not as simple as all invasive plants must go. While we certainly do not suggest that invasive plants have no negative ecological impacts, our study shows that coexisting native plants are not always superior resources for wildlife and that context is important.

"Managers need to know whether the native plants that are most likely to replace removed invasives are really of greater value to the wildlife for which they are managing the habitat, and if that effort is worth the cost and disturbance."

The study recommends a more nuanced approach to invasive plant management in eastern North American forests, where the services provided by non- native plants are considered against the backdrop of the native plant community in which they have become established.

Journal information: Biological Invasions

Provided by Great Hollow Nature Preserve & Ecological Research Center

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• Open access
• Published: 24 April 2024

Comparing PrEP initiation rates by service delivery models among high risk adolescent boys and young men in KwaZulu-Natal, South Africa: findings from a population-based prospective study

• Mbuzeleni Hlongwa 1 , 2 ,
• Wisdom Basera 3 , 4 &
• Edward Nicol 3 , 5  

BMC Public Health volume  24 , Article number:  1151 ( 2024 ) Cite this article

143 Accesses

Metrics details

Introduction

Pre-exposure prophylaxis (PrEP) is an HIV prevention strategy that can reduce the risk of HIV acquisition by more than 90% if taken consistently. Although South Africa has been implementing PrEP since 2016, initially for selected population groups before expanding access to more people, there is a dearth of research focused on PrEP among adolescent boys and young men (ABYM), despite them experiencing high rates of HIV infection. To address this gap, we compared PrEP initiation rates by service delivery points (SDPs) among ABYM in KwaZulu-Natal, South Africa.

We conducted a population-based prospective study in 22 SDPs from July 2021 to July 2022 in KwaZulu-Natal, South Africa. Sexually active ABYM aged 15–35 years who tested HIV negative were recruited at purposively selected PrEP SDPs (i.e., healthcare facilities, secondary schools and Technical Vocational Education and Training (TVET) colleges, and community-based youth zones). We collected baseline quantitative data from each participant using self-administered electronic questionnaires built into REDCap, including demographic information such as age, sex, employment status and level of education, as well as PrEP initiation outcomes. We extracted data from REDCap and exported it to Stata version 17.0 for analysis, and then eliminated discrepancies and removed duplicates. We described baseline characteristics using summary and descriptive statistics (median, interquartile range [IQR] and proportions) and reported PrEP initiation proportions overall and by SDPs.

The study included 1104 ABYM, with a median age of 24 years (interquartile range (IQR): 21–28)). Almost all participants were black African ( n  = 1090, 99%), with more than half aged 15–24 years ( n  = 603, 55%) and 45% ( n  = 501) aged 25–35 years. The majority ( n  = 963; 87%) had attained a secondary level of education. Overall PREP initiation rate among adolescent boys and young men was low: among 1078 participants who were eligible for PrEP, 13% ( n  = 141) were started on PrEP. Among the participants who were initiated on PrEP, over three quarters (78%, n  = 58) were initiated from high schools, compared with community-based youth zones (40%, n  = 37), TVET colleges (26%, n  = 16) and healthcare facilities (4%, n  = 30).

Conclusions

This study provided evidence suggesting that expanding PrEP services to non-traditional settings, such as high schools, TVET colleges, and community-based organizations, may have a potential to increase PrEP access among ABYM in South Africa.

Peer Review reports

Human immunodeficiency virus (HIV) continues to be a significant public health concern in many parts of the world, consisting of more than 37 million people diagnosed with HIV in year 2020 [ 1 ]. South Africa has a high HIV prevalence, with more than seven million people estimated to be living with HIV [ 2 ]. Adolescent boys and young men (ABYM) are a vulnerable group affected by HIV in South Africa, as they account for a substantial proportion of people newly infected with HIV in South Africa [ 3 ]. In South Africa, ABYM are increasingly getting recognised as a vulnerable population group due to the disproportionately high burden of HIV infection, underscoring the urgent need to address the risk factors, including high-risk sexual behaviours and prioritizing AYBM in HIV prevention strategies. Pre-exposure prophylaxis (PrEP) is an HIV prevention strategy that can reduce the risk of HIV acquisition by more than 90% if taken consistently [ 4 , 5 ]. Although this is the case, ABYM continue to experience high rates of HIV infection in South Africa, despite many efforts designed to address their HIV prevention care and needs [ 6 ]. HIV prevalence is 3.1 among males aged 15–19, 4.0 in 20–24 years, 6.3 in 25–29 years, 10.8 in 30–34 years and 16.9 in 35–39 years [ 7 , 8 ]). Data from the HIV incidence study conducted in uMgungundlovu, and published in 2019 showed that among men aged 15–19, 20–24, 25–29 and 30–35 the HIV incidence rates were 0.24, 1.18, 2.84 and 1.45 per 100 person-years, respectively [ 7 ]. In South Africa, the rollout of oral PrEP started in 2016 with 11 sites in five provinces. An additional site was added in November, to create a total of 12 implementing sites in 2016 [ 9 , 10 ]. Initially, PrEP was implemented among selected key population groups (for example, sex workers) as well as to men who have sex with men; and adolescent girls and young women at primary healthcare facilities, before expanding access to more people, including ABYM. However, there is a dearth of research focused on PrEP among ABYM, despite them experiencing high rates of HIV infection.

In order to improve the rates of PrEP initiation among ABYM, it is imperative that we understand which service delivery models may be effective to ensure that men have appropriate access to PrEP services. It is also important that we understand which service delivery models may contribute to low PrEP initiation rates. One potential factor for PrEP initiation is the service delivery model used to provide PrEP services. For example, traditional facility-based healthcare models may not effectively reach ABYM, due to several barriers men face to accessing healthcare services, including stigma, lack of privacy, long waiting queues, unfriendly healthcare environments and concerns about confidentiality [ 11 , 12 ]. These challenges facing public healthcare facilities have led to the growing appetite for alternative models, including decentralizing models, that are aimed at improving the rates of PrEP initiation, such as community-based service delivery models. Community-based service delivery models may be more acceptable and accessible to AYBM compared to the traditional public healthcare facility-based models [ 13 ]. Research demonstrates that community-based ART service delivery and initiation are successful approaches for increasing HIV treatment access in SSA because they address a number of distinctive barriers related to receiving HIV treatment from clinic settings, including stigma and discrimination, long waiting times, confidentiality concerns, and transport costs [ 11 , 14 , 15 , 16 ].

This study aimed to compare PrEP initiation rates by service delivery models among ABYM in KwaZulu-Natal, South Africa. Our study targeted adolescent boys and young men, a population that is at a greater risk for new HIV infections [ 6 ]. Specifically, this study assessed PrEP initiation rates among ABYM who accessed PrEP through high schools, technical and vocational education and training (TVET) colleges, community-based youth zones (i.e., spaces within communities dedicated to young people providing services focused on sexual and reproductive health and HIV-related services), and public healthcare facilities.

Study setting

This study was conducted in uMgungundlovu district in KwaZulu-Natal province, South Africa (Fig.  1 ). We selected participating facilities in consultation with provincial and district Department of Health. Overall HIV prevalence is high in uMgungundlovu district, accounting for 31% overall among 15–59 years, and 23% among men 15–49 years [ 17 ]. The population of uMgungundlovu is predominantly poor and rural, with the majority using public health services [ 18 ].

Sub-districts of uMgungundlovu District, KwaZulu-Natal, South Africa

Study design

We conducted a population-based prospective study in 22 SDPs over 13 months (July 2021 to July 2022). Adolescent boys and young men were purposively selected (those who visited the SDP while study staff were around) from 22 service delivery points (SDPs) (i.e., healthcare facilities ( n  = 11), High schools ( n  = 2) and Technical Vocational Education and Training (TVET) colleges ( n  = 4), and community-based youth zones( n  = 5). We defined PrEP initiation according to national guidelines [ 10 ]. We administered questionnaires and accessed routine healthcare service records at enrolment to obtain and verify HIV test results and PrEP initiation outcomes among participants. The protocol for this study has been previously published [ 19 ].

Population and recruitment

The target population for this study comprised sexually active ABYM aged 15–35 years, who test HIV negative during the routine healthcare facility-based, school-based, and community-based HIV testing services at 22 selected SDPs, in each of the seven sub-districts (strata) (namely, UMshwathi, Umgeni, Mpofana, Impendle, Msunduzi, Mkhambathini and Richmond) in the uMgungundlovu district. Participants were recruited and tracked through surveys using questionnaires and routine pharmaceutical records of PrEP pill collection, and SDP records. The inclusion criteria were: (a) having accepted an HIV test in one of the participating SDPs during the data collection, (b) having access to a cell phone and willingness to provide contact details, (c) be aged 15–35 years, (d) be sexually active and at high risk for HIV (identified by a set of risk assessment questions), (e) be seronegative based on HIV rapid test results on the day of recruitment, and (f) be able and willing to provide informed consent. Potential participants who were diagnosed with TB were excluded in the study.

Data collection and management

Male clients that presented at the 22 SDPs for routine HIV test were approached before the test and recruited into the study. We collected baseline quantitative data from each participant using self-administered electronic questionnaires built into REDCap, including demographic information such as age, sex, employment status and level of education, as well as PrEP initiation outcomes, in addition to a HIV risk assessment test. Participants who had a negative HIV test and were substantially at risk were offered PrEP by staff at the SDPs. The risk assessment tool with the higher HIV risk stated in the parenthesis included a past six [ 6 ] months recall on (a) the number of people one had vaginal or anal sex with (2+), (b) frequency of condom use (no & don’t know), (c) reward based sexual experiences (yes), (d) having a sexually transmitted infection (yes & don’t know), (e) sharing of needles during intravenous drug use (yes) and (f) having a partner who is HIV infected (yes & don’t know). Any higher HIV risk response to one of the questions denoted PrEP eligibility. We also used secondary data sources, including the district health information system to extract information on PrEP initiation in the district and facilities where this project was implemented. Trained and competent facility-based data champions, working together with the project coordinator conducted daily quality checks on completeness of REDCap records on the tablets, before uploading data over 3G or Wi-Fi to the REDCap folder stored securely on the SAMRC’s server. Any data inconsistencies and/or errors were flagged, discussed and rectified at regular quality control meetings.

Data analysis

We extracted data from REDCap and exported it to Stata version 17.0 for analysis, and then eliminated discrepancies and removed duplicates. We dropped 23 participants from our analysis because they did not have PrEP initiation outcomes.

We described baseline characteristics using summary and descriptive statistics (median, interquartile range [IQR] and proportions) and reported PrEP initiation proportions overall and by SDPs.

Ethical considerations

The SAMRC Research Ethics Committee gave its clearance for this project (Ref: EC051-11/2020). Gatekeeper approvals were also obtained from the districts, facilities, and collaborating Provincial Departments of Health (Ref: KZ_202010_033). Prior to their involvement, we sought both verbal and written informed consent from all eligible study participants. Participants were informed throughout recruitment that participation was completely voluntary and that they were free to withdraw their participation at any time without facing any repercussions from the research team or the facilities they use.

The study included 1104 ABYM recruited from 22 SDPs (Fig.  2 ), with a median age of 24 years (interquartile range (IQR): 21–28)) (Table  1 ). Almost all participants were black African ( n  = 1090, 99%), with more than half aged 15–24 years ( n  = 603, 55%) and 45% ( n  = 501) aged 25–35 years. The majority ( n  = 963; 87%) had attained a secondary level of education.

Consort diagram detailing the recruitment of study participants into the PrEP initiation in uMgungundlovu district

PrEP initiation rates among adolescent boys and young men

Overall, PrEP initiation rate among adolescent boys and young men was low: among 1078 participants who were eligible for PrEP, 13% ( n  = 141) were started on PrEP (Table  2 ). Twenty-six (2%) participants were diagnosed with HIV, with 89% ( n  = 23) reactive participants coming from clinics and 11% ( n  = 3) from TVET colleges.

Another notable finding in our study is the disparities in PrEP initiation rates among different types of service delivery points. For example, among the participants who were initiated on PrEP, over three quarters (78%, n  = 58) were initiated from high schools, compared with community-based youth zones (40%, n  = 37), TVET colleges (26%, n  = 16) and healthcare facilities/clinics (4%, n  = 30).

Over three quarters (79%, n  = 849) of the participants had a high risk profile of HIV infection based on the risk screening tool and were eligible for PrEP. A high proportion (61%, n  = 661) of participants self-reported as willing to consider taking PrEP, with 16% ( n  = 107) of those who went on to initiate it. Amongst the reasons cited by those at a higher HIV risk profile ( n  = 849) for non willingness to consider PrEP, the top three were – I don’t want to be taking drugs for a long time (13%, n  = 112), I fear side effects (11%, n  = 91) and I do not think I am at risk of acquiring HIV (10%, n  = 84).

This study aimed to compare PrEP initiation rates by service delivery models among ABYM in KwaZulu-Natal, South Africa. Similar to our study, PrEP initiation rates among men were reported to be low in Eswatini [ 20 ]. This supports the notion that PrEP access and uptake is a widespread challenge in the region, given the several factors and barriers identified to be affecting men’s access and initiation to PrEP in SSA, including stigma, discrimination, lack of knowledge and awareness of PrEP, inaccessibility of PrEP services, misinformation, fear of side effects and PrEP pill burden [ 21 , 22 , 23 ]. These findings suggest that there is a need for targeted educational interventions aimed to promote PrEP awareness and improve PrEP initiation rates among ABYM in KwaZulu-Natal, and in similar settings elsewhere.

Specifically, our study found that healthcare facilities had lower rates of PrEP initiation compared to high schools and TVET colleges, and community-based youth zones. This result suggests that the traditional facility-based may not be the most effective approach for reaching adolescent boys and young men with PrEP services. Instead, our study findings suggest that the community-based youth zones and high schools and TVET colleges may be promising additional models to traditional healthcare facilities for reaching men through distributing PrEP services.

Our finding reporting low rates of PrEP initiation from healthcare facilities, compared to community-based youth zones and high schools and TVET colleges was not surprising, given the well documented barriers deterring men from accessing services from the healthcare facilities in SSA [ 11 ]. In South Africa, for example, compared with women, men are less likely to access healthcare services, due to many factors including stigma, long waiting queues, masculinity and unfriendly healthcare environments [ 12 ]. However, our findings are consistent with global efforts to decentralize HIV prevention and treatment services to community-based settings in an effort to improve access to HIV treatment.

Evidence shows that community-based HIV services are an effective strategy for improving access to HIV treatment in SSA, as it addresses several distinctive barriers associated with accessing HIV treatment from clinic settings [ 14 , 15 , 16 ]. Therefore, in order to address the low rates of PrEP initiation among ABYM in KwaZulu-Natal, our findings suggest that there may be a need to adopt a multi-pronged approach that may include targeted outreach and education interventions, as well as decentralizing PrEP services to non-traditional healthcare settings. This may include strengthening and expanding partnering with high schools and TVET colleges, as well as community-based organisations to provide education and counselling, as well as improving PrEP access for men. This could involve developing and/or strengthening tailored educational materials, peer-led counselling sessions, and targeted outreach initiatives to increase knowledge of PrEP among males who might not be currently receiving these services.

A key limitation for this study relates to the fact that this paper does not address the factors influencing PrEP initiation rates among ABYM. Instead, these are currently being analyzed qualitatively, and will be discussed in a separate publication.

In conclusion, the findings from this study have important indications for efforts to improve PrEP access among ABYM in KwaZulu-Natal, South Africa. By expanding PrEP services to non-traditional settings, such as high schools, TVET colleges, and community-based organizations, there is potential to increase PrEP access and reduce the burden of HIV among men. These efforts may be particularly important in the context of the ongoing HIV epidemic in South Africa.

Data availability

The datasets used and/or analysed during the current study available from the corresponding author on reasonable request.

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Acknowledgements

Not applicable.

This work was supported by the U.S. President’s Emergency Plan for AIDS Relief (PEPFAR) through the Centers for Disease Control and Prevention, under the terms of Cooperative Agreement Number 1 NU2GGH002193-01-00.

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Public Health, Societies and Belonging, Human Sciences Research Council, Pretoria, South Africa

Mbuzeleni Hlongwa

School of Nursing and Public Health, University of KwaZulu-Natal, Durban, South Africa

Burden of Disease Research Unit, South African Medical Research Council, Cape Town, South Africa

Wisdom Basera & Edward Nicol

School of Public Health and Family Medicine, University of Cape Town, Cape Town, South Africa

Wisdom Basera

Division of Health Systems and Public Health, Stellenbosch University, Cape Town, South Africa

Edward Nicol

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MH drafted the first draft of the manuscript. EN and WB provided critical contributions towards developing and refining the manuscript. All authors read and approved the final manuscript.

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Correspondence to Mbuzeleni Hlongwa .

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The South African Medical Research Council (SA MRC) Ethics Committee approved this study. Prior to their involvement, we sought both verbal and written informed consent from all eligible study participants. All procedures performed in studies involving human participants adhered to the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. Informed consent was obtained from a parent and/or legal guardian for participants below 16 years of age.

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Hlongwa, M., Basera, W. & Nicol, E. Comparing PrEP initiation rates by service delivery models among high risk adolescent boys and young men in KwaZulu-Natal, South Africa: findings from a population-based prospective study. BMC Public Health 24 , 1151 (2024). https://doi.org/10.1186/s12889-024-18660-1

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Received : 07 June 2023

Accepted : 18 April 2024

Published : 24 April 2024

DOI : https://doi.org/10.1186/s12889-024-18660-1

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• PrEP initiation rates
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• South Africa

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