what mean by research paper

What Is a Research Paper?

• An Introduction to Punctuation

Olivia Valdes was the Associate Editorial Director for ThoughtCo. She worked with Dotdash Meredith from 2017 to 2021.

• B.A., American Studies, Yale University

A research paper is a common form of academic writing . Research papers require students and academics to locate information about a topic (that is, to conduct research ), take a stand on that topic, and provide support (or evidence) for that position in an organized report.

The term research paper may also refer to a scholarly article that contains the results of original research or an evaluation of research conducted by others. Most scholarly articles must undergo a process of peer review before they can be accepted for publication in an academic journal.

Define Your Research Question

The first step in writing a research paper is defining your research question . Has your instructor assigned a specific topic? If so, great—you've got this step covered. If not, review the guidelines of the assignment. Your instructor has likely provided several general subjects for your consideration. Your research paper should focus on a specific angle on one of these subjects. Spend some time mulling over your options before deciding which one you'd like to explore more deeply.

Try to choose a research question that interests you. The research process is time-consuming, and you'll be significantly more motivated if you have a genuine desire to learn more about the topic. You should also consider whether you have access to all of the resources necessary to conduct thorough research on your topic, such as primary and secondary sources .

Create a Research Strategy 

Approach the research process systematically by creating a research strategy. First, review your library's website. What resources are available? Where will you find them? Do any resources require a special process to gain access? Start gathering those resources—especially those that may be difficult to access—as soon as possible.

Second, make an appointment with a reference librarian . A reference librarian is nothing short of a research superhero. He or she will listen to your research question, offer suggestions for how to focus your research, and direct you toward valuable sources that directly relate to your topic.

Evaluate Sources

Now that you've gathered a wide array of sources, it's time to evaluate them. First, consider the reliability of the information. Where is the information coming from? What is the origin of the source? Second, assess the  relevance  of the information. How does this information relate to your research question? Does it support, refute, or add context to your position? How does it relate to the other sources you'll be using in your paper? Once you have determined that your sources are both reliable and relevant, you can proceed confidently to the writing phase. 

Why Write Research Papers? 

The research process is one of the most taxing academic tasks you'll be asked to complete. Luckily, the value of writing a research paper goes beyond that A+ you hope to receive. Here are just some of the benefits of research papers. 

• Learning Scholarly Conventions:  Writing a research paper is a crash course in the stylistic conventions of scholarly writing. During the research and writing process, you'll learn how to document your research, cite sources appropriately, format an academic paper, maintain an academic tone, and more.
• Organizing Information: In a way, research is nothing more than a massive organizational project. The information available to you is near-infinite, and it's your job to review that information, narrow it down, categorize it, and present it in a clear, relevant format. This process requires attention to detail and major brainpower.
• Managing Time: Research papers put your time management  skills to the test. Every step of the research and writing process takes time, and it's up to you to set aside the time you'll need to complete each step of the task. Maximize your efficiency by creating a research schedule and inserting blocks of "research time" into your calendar as soon as you receive the assignment. 
• Exploring Your Chosen Subject:  We couldn't forget the best part of research papers—learning about something that truly excites you. No matter what topic you choose, you're bound to come away from the research process with new ideas and countless nuggets of fascinating information. 

The best research papers are the result of genuine interest and a thorough research process. With these ideas in mind, go forth and research. Welcome to the scholarly conversation!

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Reference management. Clean and simple.

What is a research paper?

A research paper is a paper that makes an argument about a topic based on research and analysis.

Any paper requiring the writer to research a particular topic is a research paper. Unlike essays, which are often based largely on opinion and are written from the author's point of view, research papers are based in fact.

A research paper requires you to form an opinion on a topic, research and gain expert knowledge on that topic, and then back up your own opinions and assertions with facts found through your thorough research.

➡️ Read more about  different types of research papers .

What is the difference between a research paper and a thesis?

A thesis is a large paper, or multi-chapter work, based on a topic relating to your field of study.

A thesis is a document students of higher education write to obtain an academic degree or qualification. Usually, it is longer than a research paper and takes multiple years to complete.

Generally associated with graduate/postgraduate studies, it is carried out under the supervision of a professor or other academic of the university.

A major difference between a research paper and a thesis is that:

• a research paper presents certain facts that have already been researched and explained by others
• a thesis starts with a certain scholarly question or statement, which then leads to further research and new findings

This means that a thesis requires the author to input original work and their own findings in a certain field, whereas the research paper can be completed with extensive research only.

➡️ Getting ready to start a research paper or thesis? Take a look at our guides on how to start a research paper or how to come up with a topic for your thesis .

Frequently Asked Questions about research papers

Take a look at this list of the top 21 Free Online Journal and Research Databases , such as ScienceOpen , Directory of Open Access Journals , ERIC , and many more.

Mason Porter, Professor at UCLA, explains in this forum post the main reasons to write a research paper:

• To create new knowledge and disseminate it.
• To teach science and how to write about it in an academic style.
• Some practical benefits: prestige, establishing credentials, requirements for grants or to help one get a future grant proposal, and so on.

Generally, people involved in the academia. Research papers are mostly written by higher education students and professional researchers.

Yes, a research paper is the same as a scientific paper. Both papers have the same purpose and format.

A major difference between a research paper and a thesis is that the former presents certain facts that have already been researched and explained by others, whereas the latter starts with a certain scholarly question or statement, which then leads to further research and new findings.

Related Articles

Research Paper

29 December 2023

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A research paper is a product of seeking information, analysis, human thinking, and time. Basically, when scholars want to get answers to questions, they start to search for information to expand, use, approve, or deny findings. In simple words, research papers are results of processes by considering writing works and following specific requirements. Besides, scientists research and expand many theories, developing social or technological aspects of human science. However, in order to write relevant papers, they need to know a definition of the research, structure, characteristics, and types.

Definition of What Is a Research Paper and Its Meaning

A research paper is a common assignment. It comes to a situation when students, scholars, and scientists need to answer specific questions by using sources. Basically, a research paper is one of the types of papers where scholars analyze questions or topics , look for secondary sources , and write papers on defined themes. For example, if an assignment is to write a research paper on some causes of global warming or any other topic, a person must write a research proposal on it, analyzing important points and credible sources . Although essays focus on personal knowledge, writing a research paper means analyzing sources by following academic standards. Moreover, scientists must meet the structure of research papers. Therefore, writers need to analyze their research paper topics , start to research, cover key aspects, process credible articles, and organize final studies properly.

The Structure of a Research Work

The structure of research papers depends on assignment requirements. In fact, when students get their assignments and instructions, they need to analyze specific research questions or topics, find reliable sources , and write final works. Basically, the structure of research papers consists of the abstract , outline , introduction , literature review , methodology, results , discussion, recommendations, limitations, conclusion , acknowledgments , and references. However, students may not include some of these sections because of assigned instructions that they have and specific types of research papers. For instance, if instructions of papers do not suppose to conduct real experiments, the methodology section can be skipped because of the data’s absence. In turn, the structure of the final work consists of:

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🔸 The First Part of a Research Study

Abstract or an executive summary means the first section of a research paper that provides the study’s purpose, research questions or suggestions, main findings with conclusions. Moreover, this paragraph of about 150 words should be written when the whole work is finished already. Hence, abstract sections should describe key aspects of studies, including discussions about the relevance of findings.

Outline serves as a clear map of the structure of a research study.

Introduction provides the main information on problem statements, the indication of methodology, important findings, and principal conclusion. Basically, this section of a research paper covers rationales behind the work or background research, explanation of the importance, defending its relevance, a brief description of experimental designs, defined research questions, hypotheses, or key aspects.

🔸 Literature Review and Research or Experiment

Literature Review is needed for the analysis of past studies or scholarly articles to be familiar with research questions or topics. Hence, this section summarizes and synthesizes arguments and ideas from scholarly sources without adding new contributions. In turn, this part is organized around arguments or ideas, not sources.

Methodology or Materials and Methods covers explanations of research designs. Basically, techniques for gathering information and other aspects related to experiments must be described in a research paper. For instance, students and scholars document all specialized materials and general procedures. In this case, individuals may use some or all of the methods in further studies or judge the scientific merit of the work. Moreover, scientists should explain how they are going to conduct their experiments.

Results mean the gained information or data after the research or experiment. Basically, scholars should present and illustrate their findings. Moreover, this section may include tables or figures.

🔸 Analysis of Findings

Discussion is a section of a research paper where scientists review the information in the introduction part, evaluate gained results, or compare it with past studies. In particular, students and scholars interpret gained data or findings in appropriate depth. For example, if results differ from expectations at the beginning, scientists should explain why that may have happened. However, if results agree with rationales, scientists should describe theories that the evidence is supported.

Recommendations take its roots from a discussion section where scholars propose potential solutions or new ideas based on obtained results in a research paper. In this case, if scientists have any recommendations on how to improve this research so that other scholars can use evidence in further studies, they must write what they think in this section.

Limitations mean a consideration of research weaknesses and results to get new directions. For instance, if researchers found any limitations of studies that could affect experiments, scholars must not use such knowledge because of the same mistakes. Moreover, scientists should avoid contradicting results, and, even more, they must write it in this section.

🔸 The Final Part of a Conducted Research

Conclusion includes final claims of a research paper based on findings. Basically, this section covers final thoughts and the summary of the whole work. Moreover, this section may be used instead of limitations and recommendations that would be too small by themselves. In this case, scientists do not need to use headings for recommendations and limitations. Also, check out conclusion examples .

Acknowledgments or Appendix may take different forms, from paragraphs to charts. In this section, scholars include additional information on a research paper.

References mean a section where students, scholars, or scientists provide all used sources by following the format and academic rules.

Research Characteristics

Any type of work must meet some standards. By considering a research paper, this work must be written accordingly. In this case, the main characteristics of research papers are the length, style, format, and sources. Firstly, the length of research work defines the number of needed sources to analyze. Then, the style must be formal and covers impersonal and inclusive language. In turn, the format means academic standards of how to organize final works, including its structure and norms. Finally, sources and their number define works as research papers because of the volume of analyzed information. Hence, these characteristics must be considered while writing research papers.

Types of Research Papers

In general, the length of assignments can be different because of instructions. For example, there are two main types of research papers, such as typical and serious works. Firstly, a typical research paper may include definitive, argumentative, interpretive, and other works. In this case, typical papers are from 2 to 10 pages, where students analyze research questions or specific topics. Then, a serious research study is the expanded version of typical works. In turn, the length of such a paper is more than 10 pages. Basically, such works cover a serious analysis with many sources. Therefore, typical and serious works are two types of research papers.

Typical Research Papers

Basically, typical research works depend on assignments, the number of sources, and the paper’s length. So, a typical research paper is usually a long essay with the analyzed evidence. For example, students in high school and colleges get such assignments to learn how to research and analyze topics. In this case, they do not need to conduct serious experiments with the analysis and calculation of data. Moreover, students must use the Internet or libraries in searching for credible secondary sources to find potential answers to specific questions. As a result, students gather information on topics and learn how to take defined sides, present unique positions, or explain new directions. Hence, typical research papers require an analysis of primary and secondary sources without serious experiments or data.

Serious Research Studies

Although long papers require a lot of time for finding and analyzing credible sources, real experiments are an integral part of research work. Firstly, scholars at universities need to analyze the information from past studies to expand or disapprove of researched topics. Then, if scholars want to prove specific positions or ideas, they must get real evidence. In this case, experiments can be surveys, calculations, or other types of data that scholars do personally. Moreover, a dissertation is a typical serious research paper that young scientists write based on the research analysis of topics, data from conducted experiments, and conclusions at the end of work. Thus, serious research papers are studies that take a lot of time, analysis of sources with gained data, and interpretation of results.

How To Write A Research Paper

Step-By-Step Tutorial With Examples + FREE Template

By: Derek Jansen (MBA) | Expert Reviewer: Dr Eunice Rautenbach | March 2024

For many students, crafting a strong research paper from scratch can feel like a daunting task – and rightly so! In this post, we’ll unpack what a research paper is, what it needs to do , and how to write one – in three easy steps. 🙂 

Overview: Writing A Research Paper

What (exactly) is a research paper.

• How to write a research paper
• Stage 1 : Topic & literature search
• Stage 2 : Structure & outline
• Stage 3 : Iterative writing
• Key takeaways

Let’s start by asking the most important question, “ What is a research paper? ”.

Simply put, a research paper is a scholarly written work where the writer (that’s you!) answers a specific question (this is called a research question ) through evidence-based arguments . Evidence-based is the keyword here. In other words, a research paper is different from an essay or other writing assignments that draw from the writer’s personal opinions or experiences. With a research paper, it’s all about building your arguments based on evidence (we’ll talk more about that evidence a little later).

Now, it’s worth noting that there are many different types of research papers , including analytical papers (the type I just described), argumentative papers, and interpretative papers. Here, we’ll focus on analytical papers , as these are some of the most common – but if you’re keen to learn about other types of research papers, be sure to check out the rest of the blog .

With that basic foundation laid, let’s get down to business and look at how to write a research paper .

Overview: The 3-Stage Process

While there are, of course, many potential approaches you can take to write a research paper, there are typically three stages to the writing process. So, in this tutorial, we’ll present a straightforward three-step process that we use when working with students at Grad Coach.

These three steps are:

• Finding a research topic and reviewing the existing literature
• Developing a provisional structure and outline for your paper, and
• Writing up your initial draft and then refining it iteratively

Let’s dig into each of these.

Need a helping hand?

Step 1: Find a topic and review the literature

As we mentioned earlier, in a research paper, you, as the researcher, will try to answer a question . More specifically, that’s called a research question , and it sets the direction of your entire paper. What’s important to understand though is that you’ll need to answer that research question with the help of high-quality sources – for example, journal articles, government reports, case studies, and so on. We’ll circle back to this in a minute.

The first stage of the research process is deciding on what your research question will be and then reviewing the existing literature (in other words, past studies and papers) to see what they say about that specific research question. In some cases, your professor may provide you with a predetermined research question (or set of questions). However, in many cases, you’ll need to find your own research question within a certain topic area.

Finding a strong research question hinges on identifying a meaningful research gap – in other words, an area that’s lacking in existing research. There’s a lot to unpack here, so if you wanna learn more, check out the plain-language explainer video below.

Once you’ve figured out which question (or questions) you’ll attempt to answer in your research paper, you’ll need to do a deep dive into the existing literature – this is called a “ literature search ”. Again, there are many ways to go about this, but your most likely starting point will be Google Scholar .

If you’re new to Google Scholar, think of it as Google for the academic world. You can start by simply entering a few different keywords that are relevant to your research question and it will then present a host of articles for you to review. What you want to pay close attention to here is the number of citations for each paper – the more citations a paper has, the more credible it is (generally speaking – there are some exceptions, of course).

Ideally, what you’re looking for are well-cited papers that are highly relevant to your topic. That said, keep in mind that citations are a cumulative metric , so older papers will often have more citations than newer papers – just because they’ve been around for longer. So, don’t fixate on this metric in isolation – relevance and recency are also very important.

Beyond Google Scholar, you’ll also definitely want to check out academic databases and aggregators such as Science Direct, PubMed, JStor and so on. These will often overlap with the results that you find in Google Scholar, but they can also reveal some hidden gems – so, be sure to check them out.

Once you’ve worked your way through all the literature, you’ll want to catalogue all this information in some sort of spreadsheet so that you can easily recall who said what, when and within what context. If you’d like, we’ve got a free literature spreadsheet that helps you do exactly that.

Step 2: Develop a structure and outline

With your research question pinned down and your literature digested and catalogued, it’s time to move on to planning your actual research paper .

It might sound obvious, but it’s really important to have some sort of rough outline in place before you start writing your paper. So often, we see students eagerly rushing into the writing phase, only to land up with a disjointed research paper that rambles on in multiple

Now, the secret here is to not get caught up in the fine details . Realistically, all you need at this stage is a bullet-point list that describes (in broad strokes) what you’ll discuss and in what order. It’s also useful to remember that you’re not glued to this outline – in all likelihood, you’ll chop and change some sections once you start writing, and that’s perfectly okay. What’s important is that you have some sort of roadmap in place from the start.

At this stage you might be wondering, “ But how should I structure my research paper? ”. Well, there’s no one-size-fits-all solution here, but in general, a research paper will consist of a few relatively standardised components:

• Introduction
• Literature review
• Methodology

Let’s take a look at each of these.

First up is the introduction section . As the name suggests, the purpose of the introduction is to set the scene for your research paper. There are usually (at least) four ingredients that go into this section – these are the background to the topic, the research problem and resultant research question , and the justification or rationale. If you’re interested, the video below unpacks the introduction section in more detail. 

The next section of your research paper will typically be your literature review . Remember all that literature you worked through earlier? Well, this is where you’ll present your interpretation of all that content . You’ll do this by writing about recent trends, developments, and arguments within the literature – but more specifically, those that are relevant to your research question . The literature review can oftentimes seem a little daunting, even to seasoned researchers, so be sure to check out our extensive collection of literature review content here .

With the introduction and lit review out of the way, the next section of your paper is the research methodology . In a nutshell, the methodology section should describe to your reader what you did (beyond just reviewing the existing literature) to answer your research question. For example, what data did you collect, how did you collect that data, how did you analyse that data and so on? For each choice, you’ll also need to justify why you chose to do it that way, and what the strengths and weaknesses of your approach were.

Now, it’s worth mentioning that for some research papers, this aspect of the project may be a lot simpler . For example, you may only need to draw on secondary sources (in other words, existing data sets). In some cases, you may just be asked to draw your conclusions from the literature search itself (in other words, there may be no data analysis at all). But, if you are required to collect and analyse data, you’ll need to pay a lot of attention to the methodology section. The video below provides an example of what the methodology section might look like.

By this stage of your paper, you will have explained what your research question is, what the existing literature has to say about that question, and how you analysed additional data to try to answer your question. So, the natural next step is to present your analysis of that data . This section is usually called the “results” or “analysis” section and this is where you’ll showcase your findings.

Depending on your school’s requirements, you may need to present and interpret the data in one section – or you might split the presentation and the interpretation into two sections. In the latter case, your “results” section will just describe the data, and the “discussion” is where you’ll interpret that data and explicitly link your analysis back to your research question. If you’re not sure which approach to take, check in with your professor or take a look at past papers to see what the norms are for your programme.

Alright – once you’ve presented and discussed your results, it’s time to wrap it up . This usually takes the form of the “ conclusion ” section. In the conclusion, you’ll need to highlight the key takeaways from your study and close the loop by explicitly answering your research question. Again, the exact requirements here will vary depending on your programme (and you may not even need a conclusion section at all) – so be sure to check with your professor if you’re unsure.

Step 3: Write and refine

Finally, it’s time to get writing. All too often though, students hit a brick wall right about here… So, how do you avoid this happening to you?

Well, there’s a lot to be said when it comes to writing a research paper (or any sort of academic piece), but we’ll share three practical tips to help you get started.

First and foremost , it’s essential to approach your writing as an iterative process. In other words, you need to start with a really messy first draft and then polish it over multiple rounds of editing. Don’t waste your time trying to write a perfect research paper in one go. Instead, take the pressure off yourself by adopting an iterative approach.

Secondly , it’s important to always lean towards critical writing , rather than descriptive writing. What does this mean? Well, at the simplest level, descriptive writing focuses on the “ what ”, while critical writing digs into the “ so what ” – in other words, the implications. If you’re not familiar with these two types of writing, don’t worry! You can find a plain-language explanation here.

Last but not least, you’ll need to get your referencing right. Specifically, you’ll need to provide credible, correctly formatted citations for the statements you make. We see students making referencing mistakes all the time and it costs them dearly. The good news is that you can easily avoid this by using a simple reference manager . If you don’t have one, check out our video about Mendeley, an easy (and free) reference management tool that you can start using today.

Recap: Key Takeaways

We’ve covered a lot of ground here. To recap, the three steps to writing a high-quality research paper are:

• To choose a research question and review the literature
• To plan your paper structure and draft an outline
• To take an iterative approach to writing, focusing on critical writing and strong referencing

Remember, this is just a b ig-picture overview of the research paper development process and there’s a lot more nuance to unpack. So, be sure to grab a copy of our free research paper template to learn more about how to write a research paper.

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• Academic Writing

What is a Research Paper?

• Steps in Writing a Research Paper
• Critical Reading and Writing
• Punctuation
• Writing Exercises
• ELL/ESL Resources

"Research paper." What image comes into mind as you hear those words: working with stacks of articles and books, hunting the "treasure" of others' thoughts? Whatever image you create, it's a sure bet that you're envisioning sources of information--articles, books, people, artworks. Yet a research paper is more than the sum of your sources, more than a collection of different pieces of information about a topic, and more than a review of the literature in a field. A research paper analyzes a perspective argues a point . Regardless of the type of research paper you are writing, your finished research paper should present your own thinking backed up by others' ideas and information.

To draw a parallel, a lawyer researches and reads about many cases and uses them to support his or her own case. A scientist reads many case studies to support an idea about a scientific principle. In the same way, a history student writing about the Vietnam War might read newspaper articles and books and interview veterans to develop and/or confirm a viewpoint and support it with evidence.

A research paper is an expanded essay that presents your own interpretation or evaluation or argument. When you write an essay, you use everything that you personally know and have thought about a subject. When you write a research paper you build upon what you know about the subject and make a deliberate attempt to find out what experts know. A research paper involves surveying a field of knowledge in order to find the best possible information in that field. And that survey can be orderly and focused, if you know how to approach it. Don't worry--you won't get lost in a sea of sources.

In fact, this guide is designed to help you navigate the research voyage, through developing a research question and thesis, doing the research, writing the paper, and correctly documenting your sources.

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How to read and understand a scientific paper

How to read and understand a scientific paper: a guide for non-scientists, london school of economics and political science, jennifer raff.

From vaccinations to climate change, getting science wrong has very real consequences. But journal articles, a primary way science is communicated in academia, are a different format to newspaper articles or blogs and require a level of skill and undoubtedly a greater amount of patience. Here  Jennifer Raff   has prepared a helpful guide for non-scientists on how to read a scientific paper. These steps and tips will be useful to anyone interested in the presentation of scientific findings and raise important points for scientists to consider with their own writing practice.

My post,  The truth about vaccinations: Your physician knows more than the University of Google  sparked a very lively discussion, with comments from several people trying to persuade me (and the other readers) that  their  paper disproved everything that I’d been saying. While I encourage you to go read the comments and contribute your own, here I want to focus on the much larger issue that this debate raised: what constitutes scientific authority?

It’s not just a fun academic problem. Getting the science wrong has very real consequences. For example, when a community doesn’t vaccinate children because they’re afraid of “toxins” and think that prayer (or diet, exercise, and “clean living”) is enough to prevent infection, outbreaks happen.

“Be skeptical. But when you get proof, accept proof.” –Michael Specter

What constitutes enough proof? Obviously everyone has a different answer to that question. But to form a truly educated opinion on a scientific subject, you need to become familiar with current research in that field. And to do that, you have to read the “primary research literature” (often just called “the literature”). You might have tried to read scientific papers before and been frustrated by the dense, stilted writing and the unfamiliar jargon. I remember feeling this way!  Reading and understanding research papers is a skill which every single doctor and scientist has had to learn during graduate school.  You can learn it too, but like any skill it takes patience and practice.

I want to help people become more scientifically literate, so I wrote this guide for how a layperson can approach reading and understanding a scientific research paper. It’s appropriate for someone who has no background whatsoever in science or medicine, and based on the assumption that he or she is doing this for the purpose of getting a  basic  understanding of a paper and deciding whether or not it’s a reputable study.

The type of scientific paper I’m discussing here is referred to as a  primary research article . It’s a peer-reviewed report of new research on a specific question (or questions). Another useful type of publication is a  review article . Review articles are also peer-reviewed, and don’t present new information, but summarize multiple primary research articles, to give a sense of the consensus, debates, and unanswered questions within a field.  (I’m not going to say much more about them here, but be cautious about which review articles you read. Remember that they are only a snapshot of the research at the time they are published.  A review article on, say, genome-wide association studies from 2001 is not going to be very informative in 2013. So much research has been done in the intervening years that the field has changed considerably).

Before you begin: some general advice

Reading a scientific paper is a completely different process than reading an article about science in a blog or newspaper. Not only do you read the sections in a different order than they’re presented, but you also have to take notes, read it multiple times, and probably go look up other papers for some of the details. Reading a single paper may take you a very long time at first. Be patient with yourself. The process will go much faster as you gain experience.

Most primary research papers will be divided into the following sections: Abstract, Introduction, Methods, Results, and Conclusions/Interpretations/Discussion. The order will depend on which journal it’s published in. Some journals have additional files (called Supplementary Online Information) which contain important details of the research, but are published online instead of in the article itself (make sure you don’t skip these files).

Before you begin reading, take note of the authors and their institutional affiliations. Some institutions (e.g. University of Texas) are well-respected; others (e.g.  the Discovery Institute ) may appear to be legitimate research institutions but are actually agenda-driven.  Tip:  g oogle  “Discovery Institute” to see why you don’t want to use it as a scientific authority on evolutionary theory.

Also take note of the journal in which it’s published. Reputable (biomedical) journals will be indexed by  Pubmed . [EDIT: Several people have reminded me that non-biomedical journals won’t be on Pubmed, and they’re absolutely correct! (thanks for catching that, I apologize for being sloppy here). Check out  Web of Science  for a more complete index of science journals. And please feel free to share other resources in the comments!]  Beware of  questionable journals .

As you read, write down  every single word  that you don’t understand. You’re going to have to look them all up (yes, every one. I know it’s a total pain. But you won’t understand the paper if you don’t understand the vocabulary. Scientific words have extremely precise meanings).

Step-by-step instructions for reading a primary research article

1. Begin by reading the introduction, not the abstract.

The abstract is that dense first paragraph at the very beginning of a paper. In fact, that’s often the only part of a paper that many non-scientists read when they’re trying to build a scientific argument. (This is a terrible practice—don’t do it.).  When I’m choosing papers to read, I decide what’s relevant to my interests based on a combination of the title and abstract. But when I’ve got a collection of papers assembled for deep reading, I always read the abstract last. I do this because abstracts contain a succinct summary of the entire paper, and I’m concerned about inadvertently becoming biased by the authors’ interpretation of the results.

2. Identify the BIG QUESTION.

Not “What is this paper about”, but “What problem is this entire field trying to solve?”

This helps you focus on why this research is being done.  Look closely for evidence of agenda-motivated research.

3. Summarize the background in five sentences or less.

Here are some questions to guide you:

What work has been done before in this field to answer the BIG QUESTION? What are the limitations of that work? What, according to the authors, needs to be done next?

The five sentences part is a little arbitrary, but it forces you to be concise and really think about the context of this research. You need to be able to explain why this research has been done in order to understand it.

4.   Identify the SPECIFIC QUESTION(S)

What  exactly  are the authors trying to answer with their research? There may be multiple questions, or just one. Write them down.  If it’s the kind of research that tests one or more null hypotheses, identify it/them.

Not sure what a null hypothesis is? Go read this one  and try to identify the null hypotheses in it. Keep in mind that not every paper will test a null hypothesis.

5. Identify the approach

What are the authors going to do to answer the SPECIFIC QUESTION(S)?

6. Now read the methods section. Draw a diagram for each experiment, showing exactly what the authors did.

I mean  literally  draw it. Include as much detail as you need to fully understand the work.  As an example, here is what I drew to sort out the methods for a paper I read today ( Battaglia et al. 2013: “The first peopling of South America: New evidence from Y-chromosome haplogroup Q” ). This is much less detail than you’d probably need, because it’s a paper in my specialty and I use these methods all the time.  But if you were reading this, and didn’t happen to know what “process data with reduced-median method using Network” means, you’d need to look that up.

Image credit: author

You don’t need to understand the methods in enough detail to replicate the experiment—that’s something reviewers have to do—but you’re not ready to move on to the results until you can explain the basics of the methods to someone else.

7.   Read the results section. Write one or more paragraphs to summarize the results for each experiment, each figure, and each table. Don’t yet try to decide what the results  mean , just write down what they  are.

You’ll find that, particularly in good papers, the majority of the results are summarized in the figures and tables. Pay careful attention to them!  You may also need to go to the Supplementary Online Information file to find some of the results.

 It is at this point where difficulties can arise if statistical tests are employed in the paper and you don’t have enough of a background to understand them. I can’t teach you stats in this post, but  here , and here   are some basic resources to help you.  I STRONGLY advise you to become familiar with them.

Things to pay attention to in the results section:

• Any time the words “significant” or “non-significant” are used. These have precise statistical meanings. Read more about this  here .
• If there are graphs, do they have  error bars  on them? For certain types of studies, a lack of confidence intervals is a major red flag.
• The sample size. Has the study been conducted on 10, or 10,000 people? (For some research purposes, a sample size of 10 is sufficient, but for most studies larger is better).

8. Do the results answer the SPECIFIC QUESTION(S)? What do you think they mean?

Don’t move on until you have thought about this. It’s okay to change your mind in light of the authors’ interpretation—in fact you probably will if you’re still a beginner at this kind of analysis—but it’s a really good habit to start forming your own interpretations before you read those of others.

9. Read the conclusion/discussion/Interpretation section.

What do the authors think the results mean? Do you agree with them? Can you come up with any alternative way of interpreting them? Do the authors identify any weaknesses in their own study? Do you see any that the authors missed? (Don’t assume they’re infallible!) What do they propose to do as a next step? Do you agree with that?

10. Now, go back to the beginning and read the abstract.

Does it match what the authors said in the paper? Does it fit with your interpretation of the paper?

11. FINAL STEP:  (Don’t neglect doing this)  What do other researchers say about this paper?

Who are the (acknowledged or self-proclaimed) experts in this particular field? Do they have criticisms of the study that you haven’t thought of, or do they generally support it?

Here’s a place where I do recommend you use google! But do it last, so you are better prepared to think critically about what other people say.

(12. This step may be optional for you, depending on why you’re reading a particular paper. But for me, it’s critical! I go through the “Literature cited” section to see what other papers the authors cited. This allows me to better identify the important papers in a particular field, see if the authors cited my own papers (KIDDING!….mostly), and find sources of useful ideas or techniques.)

UPDATE: If you would like to see an example of how to read a science paper using this framework, you can find one  here .

I gratefully acknowledge Professors José Bonner and Bill Saxton for teaching me how to critically read and analyze scientific papers using this method. I’m honored to have the chance to pass along what they taught me.

I’ve written a shorter version of this guide for teachers to hand out to their classes. If you’d like a PDF, shoot me an email: jenniferraff (at) utexas (dot) edu. For further comments and additional questions on this guide, please see the Comments Section on  the original post .

This piece originally appeared on the  author’s personal blog  and is reposted with permission.

Featured image credit:  Scientists in a laboratory of the University of La Rioja  by  Urcomunicacion  (Wikimedia CC BY3.0)

Note: This article gives the views of the authors, and not the position of the LSE Impact blog, nor of the London School of Economics. Please review our  Comments Policy  if you have any concerns on posting a comment below.

Jennifer Raff (Indiana University—dual Ph.D. in genetics and bioanthropology) is an assistant professor in the Department of Anthropology, University of Kansas, director and Principal Investigator of the KU Laboratory of Human Population Genomics, and assistant director of KU’s Laboratory of Biological Anthropology. She is also a research affiliate with the University of Texas anthropological genetics laboratory. She is keenly interested in public outreach and scientific literacy, writing about topics in science and pseudoscience for her blog ( violentmetaphors.com ), the Huffington Post, and for the  Social Evolution Forum .

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Writing Research Papers

• Research Paper Structure

Whether you are writing a B.S. Degree Research Paper or completing a research report for a Psychology course, it is highly likely that you will need to organize your research paper in accordance with American Psychological Association (APA) guidelines.  Here we discuss the structure of research papers according to APA style.

Major Sections of a Research Paper in APA Style

A complete research paper in APA style that is reporting on experimental research will typically contain a Title page, Abstract, Introduction, Methods, Results, Discussion, and References sections. 1  Many will also contain Figures and Tables and some will have an Appendix or Appendices.  These sections are detailed as follows (for a more in-depth guide, please refer to " How to Write a Research Paper in APA Style ”, a comprehensive guide developed by Prof. Emma Geller). 2

What is this paper called and who wrote it? – the first page of the paper; this includes the name of the paper, a “running head”, authors, and institutional affiliation of the authors.  The institutional affiliation is usually listed in an Author Note that is placed towards the bottom of the title page.  In some cases, the Author Note also contains an acknowledgment of any funding support and of any individuals that assisted with the research project.

One-paragraph summary of the entire study – typically no more than 250 words in length (and in many cases it is well shorter than that), the Abstract provides an overview of the study.

Introduction

What is the topic and why is it worth studying? – the first major section of text in the paper, the Introduction commonly describes the topic under investigation, summarizes or discusses relevant prior research (for related details, please see the Writing Literature Reviews section of this website), identifies unresolved issues that the current research will address, and provides an overview of the research that is to be described in greater detail in the sections to follow.

What did you do? – a section which details how the research was performed.  It typically features a description of the participants/subjects that were involved, the study design, the materials that were used, and the study procedure.  If there were multiple experiments, then each experiment may require a separate Methods section.  A rule of thumb is that the Methods section should be sufficiently detailed for another researcher to duplicate your research.

What did you find? – a section which describes the data that was collected and the results of any statistical tests that were performed.  It may also be prefaced by a description of the analysis procedure that was used. If there were multiple experiments, then each experiment may require a separate Results section.

What is the significance of your results? – the final major section of text in the paper.  The Discussion commonly features a summary of the results that were obtained in the study, describes how those results address the topic under investigation and/or the issues that the research was designed to address, and may expand upon the implications of those findings.  Limitations and directions for future research are also commonly addressed.

List of articles and any books cited – an alphabetized list of the sources that are cited in the paper (by last name of the first author of each source).  Each reference should follow specific APA guidelines regarding author names, dates, article titles, journal titles, journal volume numbers, page numbers, book publishers, publisher locations, websites, and so on (for more information, please see the Citing References in APA Style page of this website).

Tables and Figures

Graphs and data (optional in some cases) – depending on the type of research being performed, there may be Tables and/or Figures (however, in some cases, there may be neither).  In APA style, each Table and each Figure is placed on a separate page and all Tables and Figures are included after the References.   Tables are included first, followed by Figures.   However, for some journals and undergraduate research papers (such as the B.S. Research Paper or Honors Thesis), Tables and Figures may be embedded in the text (depending on the instructor’s or editor’s policies; for more details, see "Deviations from APA Style" below).

Supplementary information (optional) – in some cases, additional information that is not critical to understanding the research paper, such as a list of experiment stimuli, details of a secondary analysis, or programming code, is provided.  This is often placed in an Appendix.

Variations of Research Papers in APA Style

Although the major sections described above are common to most research papers written in APA style, there are variations on that pattern.  These variations include: 

• Literature reviews – when a paper is reviewing prior published research and not presenting new empirical research itself (such as in a review article, and particularly a qualitative review), then the authors may forgo any Methods and Results sections. Instead, there is a different structure such as an Introduction section followed by sections for each of the different aspects of the body of research being reviewed, and then perhaps a Discussion section. 
• Multi-experiment papers – when there are multiple experiments, it is common to follow the Introduction with an Experiment 1 section, itself containing Methods, Results, and Discussion subsections. Then there is an Experiment 2 section with a similar structure, an Experiment 3 section with a similar structure, and so on until all experiments are covered.  Towards the end of the paper there is a General Discussion section followed by References.  Additionally, in multi-experiment papers, it is common for the Results and Discussion subsections for individual experiments to be combined into single “Results and Discussion” sections.

Departures from APA Style

In some cases, official APA style might not be followed (however, be sure to check with your editor, instructor, or other sources before deviating from standards of the Publication Manual of the American Psychological Association).  Such deviations may include:

• Placement of Tables and Figures  – in some cases, to make reading through the paper easier, Tables and/or Figures are embedded in the text (for example, having a bar graph placed in the relevant Results section). The embedding of Tables and/or Figures in the text is one of the most common deviations from APA style (and is commonly allowed in B.S. Degree Research Papers and Honors Theses; however you should check with your instructor, supervisor, or editor first). 
• Incomplete research – sometimes a B.S. Degree Research Paper in this department is written about research that is currently being planned or is in progress. In those circumstances, sometimes only an Introduction and Methods section, followed by References, is included (that is, in cases where the research itself has not formally begun).  In other cases, preliminary results are presented and noted as such in the Results section (such as in cases where the study is underway but not complete), and the Discussion section includes caveats about the in-progress nature of the research.  Again, you should check with your instructor, supervisor, or editor first.
• Class assignments – in some classes in this department, an assignment must be written in APA style but is not exactly a traditional research paper (for instance, a student asked to write about an article that they read, and to write that report in APA style). In that case, the structure of the paper might approximate the typical sections of a research paper in APA style, but not entirely.  You should check with your instructor for further guidelines.

Workshops and Downloadable Resources

• For in-person discussion of the process of writing research papers, please consider attending this department’s “Writing Research Papers” workshop (for dates and times, please check the undergraduate workshops calendar).

Downloadable Resources

• How to Write APA Style Research Papers (a comprehensive guide) [ PDF ]
• Tips for Writing APA Style Research Papers (a brief summary) [ PDF ]
• Example APA Style Research Paper (for B.S. Degree – empirical research) [ PDF ]
• Example APA Style Research Paper (for B.S. Degree – literature review) [ PDF ]

Further Resources

How-To Videos     

• Writing Research Paper Videos

APA Journal Article Reporting Guidelines

• Appelbaum, M., Cooper, H., Kline, R. B., Mayo-Wilson, E., Nezu, A. M., & Rao, S. M. (2018). Journal article reporting standards for quantitative research in psychology: The APA Publications and Communications Board task force report . American Psychologist , 73 (1), 3.
• Levitt, H. M., Bamberg, M., Creswell, J. W., Frost, D. M., Josselson, R., & Suárez-Orozco, C. (2018). Journal article reporting standards for qualitative primary, qualitative meta-analytic, and mixed methods research in psychology: The APA Publications and Communications Board task force report . American Psychologist , 73 (1), 26.  

External Resources

• Formatting APA Style Papers in Microsoft Word
• How to Write an APA Style Research Paper from Hamilton University
• WikiHow Guide to Writing APA Research Papers
• Sample APA Formatted Paper with Comments
• Sample APA Formatted Paper
• Tips for Writing a Paper in APA Style

1 VandenBos, G. R. (Ed). (2010). Publication manual of the American Psychological Association (6th ed.) (pp. 41-60).  Washington, DC: American Psychological Association.

2 geller, e. (2018).  how to write an apa-style research report . [instructional materials]. , prepared by s. c. pan for ucsd psychology.

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• Formatting Research Papers
• Using Databases and Finding References
• What Types of References Are Appropriate?
• Evaluating References and Taking Notes
• Citing References
• Writing a Literature Review
• Writing Process and Revising
• Improving Scientific Writing
• Academic Integrity and Avoiding Plagiarism
• Writing Research Papers Videos

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Home » Research Paper Format – Types, Examples and Templates

Research Paper Format – Types, Examples and Templates

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Research paper format is an essential aspect of academic writing that plays a crucial role in the communication of research findings . The format of a research paper depends on various factors such as the discipline, style guide, and purpose of the research. It includes guidelines for the structure, citation style, referencing , and other elements of the paper that contribute to its overall presentation and coherence. Adhering to the appropriate research paper format is vital for ensuring that the research is accurately and effectively communicated to the intended audience. In this era of information, it is essential to understand the different research paper formats and their guidelines to communicate research effectively, accurately, and with the required level of detail. This post aims to provide an overview of some of the common research paper formats used in academic writing.

Research Paper Formats

Research Paper Formats are as follows:

• APA (American Psychological Association) format
• MLA (Modern Language Association) format
• Chicago/Turabian style
• IEEE (Institute of Electrical and Electronics Engineers) format
• AMA (American Medical Association) style
• Harvard style
• Vancouver style
• ACS (American Chemical Society) style
• ASA (American Sociological Association) style
• APSA (American Political Science Association) style

APA (American Psychological Association) Format

Here is a general APA format for a research paper:

• Title Page: The title page should include the title of your paper, your name, and your institutional affiliation. It should also include a running head, which is a shortened version of the title, and a page number in the upper right-hand corner.
• Abstract : The abstract is a brief summary of your paper, typically 150-250 words. It should include the purpose of your research, the main findings, and any implications or conclusions that can be drawn.
• Introduction: The introduction should provide background information on your topic, state the purpose of your research, and present your research question or hypothesis. It should also include a brief literature review that discusses previous research on your topic.
• Methods: The methods section should describe the procedures you used to collect and analyze your data. It should include information on the participants, the materials and instruments used, and the statistical analyses performed.
• Results: The results section should present the findings of your research in a clear and concise manner. Use tables and figures to help illustrate your results.
• Discussion : The discussion section should interpret your results and relate them back to your research question or hypothesis. It should also discuss the implications of your findings and any limitations of your study.
• References : The references section should include a list of all sources cited in your paper. Follow APA formatting guidelines for your citations and references.

Some additional tips for formatting your APA research paper:

• Use 12-point Times New Roman font throughout the paper.
• Double-space all text, including the references.
• Use 1-inch margins on all sides of the page.
• Indent the first line of each paragraph by 0.5 inches.
• Use a hanging indent for the references (the first line should be flush with the left margin, and all subsequent lines should be indented).
• Number all pages, including the title page and references page, in the upper right-hand corner.

APA Research Paper Format Template

APA Research Paper Format Template is as follows:

Title Page:

• Title of the paper
• Author’s name
• Institutional affiliation
• A brief summary of the main points of the paper, including the research question, methods, findings, and conclusions. The abstract should be no more than 250 words.

Introduction:

• Background information on the topic of the research paper
• Research question or hypothesis
• Significance of the study
• Overview of the research methods and design
• Brief summary of the main findings
• Participants: description of the sample population, including the number of participants and their characteristics (age, gender, ethnicity, etc.)
• Materials: description of any materials used in the study (e.g., survey questions, experimental apparatus)
• Procedure: detailed description of the steps taken to conduct the study
• Presentation of the findings of the study, including statistical analyses if applicable
• Tables and figures may be included to illustrate the results

Discussion:

• Interpretation of the results in light of the research question and hypothesis
• Implications of the study for the field
• Limitations of the study
• Suggestions for future research

References:

• A list of all sources cited in the paper, in APA format

Formatting guidelines:

• Double-spaced
• 12-point font (Times New Roman or Arial)
• 1-inch margins on all sides
• Page numbers in the top right corner
• Headings and subheadings should be used to organize the paper
• The first line of each paragraph should be indented
• Quotations of 40 or more words should be set off in a block quote with no quotation marks
• In-text citations should include the author’s last name and year of publication (e.g., Smith, 2019)

APA Research Paper Format Example

APA Research Paper Format Example is as follows:

The Effects of Social Media on Mental Health

University of XYZ

This study examines the relationship between social media use and mental health among college students. Data was collected through a survey of 500 students at the University of XYZ. Results suggest that social media use is significantly related to symptoms of depression and anxiety, and that the negative effects of social media are greater among frequent users.

Social media has become an increasingly important aspect of modern life, especially among young adults. While social media can have many positive effects, such as connecting people across distances and sharing information, there is growing concern about its impact on mental health. This study aims to examine the relationship between social media use and mental health among college students.

Participants: Participants were 500 college students at the University of XYZ, recruited through online advertisements and flyers posted on campus. Participants ranged in age from 18 to 25, with a mean age of 20.5 years. The sample was 60% female, 40% male, and 5% identified as non-binary or gender non-conforming.

Data was collected through an online survey administered through Qualtrics. The survey consisted of several measures, including the Patient Health Questionnaire-9 (PHQ-9) for depression symptoms, the Generalized Anxiety Disorder-7 (GAD-7) for anxiety symptoms, and questions about social media use.

Procedure :

Participants were asked to complete the online survey at their convenience. The survey took approximately 20-30 minutes to complete. Data was analyzed using descriptive statistics, correlations, and multiple regression analysis.

Results indicated that social media use was significantly related to symptoms of depression (r = .32, p < .001) and anxiety (r = .29, p < .001). Regression analysis indicated that frequency of social media use was a significant predictor of both depression symptoms (β = .24, p < .001) and anxiety symptoms (β = .20, p < .001), even when controlling for age, gender, and other relevant factors.

The results of this study suggest that social media use is associated with symptoms of depression and anxiety among college students. The negative effects of social media are greater among frequent users. These findings have important implications for mental health professionals and educators, who should consider addressing the potential negative effects of social media use in their work with young adults.

References :

References should be listed in alphabetical order according to the author’s last name. For example:

• Chou, H. T. G., & Edge, N. (2012). “They are happier and having better lives than I am”: The impact of using Facebook on perceptions of others’ lives. Cyberpsychology, Behavior, and Social Networking, 15(2), 117-121.
• Twenge, J. M., Joiner, T. E., Rogers, M. L., & Martin, G. N. (2018). Increases in depressive symptoms, suicide-related outcomes, and suicide rates among U.S. adolescents after 2010 and links to increased new media screen time. Clinical Psychological Science, 6(1), 3-17.

Note: This is just a sample Example do not use this in your assignment.

MLA (Modern Language Association) Format

MLA (Modern Language Association) Format is as follows:

• Page Layout : Use 8.5 x 11-inch white paper, with 1-inch margins on all sides. The font should be 12-point Times New Roman or a similar serif font.
• Heading and Title : The first page of your research paper should include a heading and a title. The heading should include your name, your instructor’s name, the course title, and the date. The title should be centered and in title case (capitalizing the first letter of each important word).
• In-Text Citations : Use parenthetical citations to indicate the source of your information. The citation should include the author’s last name and the page number(s) of the source. For example: (Smith 23).
• Works Cited Page : At the end of your paper, include a Works Cited page that lists all the sources you used in your research. Each entry should include the author’s name, the title of the work, the publication information, and the medium of publication.
• Formatting Quotations : Use double quotation marks for short quotations and block quotations for longer quotations. Indent the entire quotation five spaces from the left margin.
• Formatting the Body : Use a clear and readable font and double-space your text throughout. The first line of each paragraph should be indented one-half inch from the left margin.

MLA Research Paper Template

MLA Research Paper Format Template is as follows:

• Use 8.5 x 11 inch white paper.
• Use a 12-point font, such as Times New Roman.
• Use double-spacing throughout the entire paper, including the title page and works cited page.
• Set the margins to 1 inch on all sides.
• Use page numbers in the upper right corner, beginning with the first page of text.
• Include a centered title for the research paper, using title case (capitalizing the first letter of each important word).
• Include your name, instructor’s name, course name, and date in the upper left corner, double-spaced.

In-Text Citations

• When quoting or paraphrasing information from sources, include an in-text citation within the text of your paper.
• Use the author’s last name and the page number in parentheses at the end of the sentence, before the punctuation mark.
• If the author’s name is mentioned in the sentence, only include the page number in parentheses.

Works Cited Page

• List all sources cited in alphabetical order by the author’s last name.
• Each entry should include the author’s name, title of the work, publication information, and medium of publication.
• Use italics for book and journal titles, and quotation marks for article and chapter titles.
• For online sources, include the date of access and the URL.

Here is an example of how the first page of a research paper in MLA format should look:

Headings and Subheadings

• Use headings and subheadings to organize your paper and make it easier to read.
• Use numerals to number your headings and subheadings (e.g. 1, 2, 3), and capitalize the first letter of each word.
• The main heading should be centered and in boldface type, while subheadings should be left-aligned and in italics.
• Use only one space after each period or punctuation mark.
• Use quotation marks to indicate direct quotes from a source.
• If the quote is more than four lines, format it as a block quote, indented one inch from the left margin and without quotation marks.
• Use ellipses (…) to indicate omitted words from a quote, and brackets ([…]) to indicate added words.

Works Cited Examples

• Book: Last Name, First Name. Title of Book. Publisher, Publication Year.
• Journal Article: Last Name, First Name. “Title of Article.” Title of Journal, volume number, issue number, publication date, page numbers.
• Website: Last Name, First Name. “Title of Webpage.” Title of Website, publication date, URL. Accessed date.

Here is an example of how a works cited entry for a book should look:

Smith, John. The Art of Writing Research Papers. Penguin, 2021.

MLA Research Paper Example

MLA Research Paper Format Example is as follows:

Your Professor’s Name

Course Name and Number

Date (in Day Month Year format)

Word Count (not including title page or Works Cited)

Title: The Impact of Video Games on Aggression Levels

Video games have become a popular form of entertainment among people of all ages. However, the impact of video games on aggression levels has been a subject of debate among scholars and researchers. While some argue that video games promote aggression and violent behavior, others argue that there is no clear link between video games and aggression levels. This research paper aims to explore the impact of video games on aggression levels among young adults.

Background:

The debate on the impact of video games on aggression levels has been ongoing for several years. According to the American Psychological Association, exposure to violent media, including video games, can increase aggression levels in children and adolescents. However, some researchers argue that there is no clear evidence to support this claim. Several studies have been conducted to examine the impact of video games on aggression levels, but the results have been mixed.

Methodology:

This research paper used a quantitative research approach to examine the impact of video games on aggression levels among young adults. A sample of 100 young adults between the ages of 18 and 25 was selected for the study. The participants were asked to complete a questionnaire that measured their aggression levels and their video game habits.

The results of the study showed that there was a significant correlation between video game habits and aggression levels among young adults. The participants who reported playing violent video games for more than 5 hours per week had higher aggression levels than those who played less than 5 hours per week. The study also found that male participants were more likely to play violent video games and had higher aggression levels than female participants.

The findings of this study support the claim that video games can increase aggression levels among young adults. However, it is important to note that the study only examined the impact of video games on aggression levels and did not take into account other factors that may contribute to aggressive behavior. It is also important to note that not all video games promote violence and aggression, and some games may have a positive impact on cognitive and social skills.

Conclusion :

In conclusion, this research paper provides evidence to support the claim that video games can increase aggression levels among young adults. However, it is important to conduct further research to examine the impact of video games on other aspects of behavior and to explore the potential benefits of video games. Parents and educators should be aware of the potential impact of video games on aggression levels and should encourage young adults to engage in a variety of activities that promote cognitive and social skills.

Works Cited:

• American Psychological Association. (2017). Violent Video Games: Myths, Facts, and Unanswered Questions. Retrieved from https://www.apa.org/news/press/releases/2017/08/violent-video-games
• Ferguson, C. J. (2015). Do Angry Birds make for angry children? A meta-analysis of video game influences on children’s and adolescents’ aggression, mental health, prosocial behavior, and academic performance. Perspectives on Psychological Science, 10(5), 646-666.
• Gentile, D. A., Swing, E. L., Lim, C. G., & Khoo, A. (2012). Video game playing, attention problems, and impulsiveness: Evidence of bidirectional causality. Psychology of Popular Media Culture, 1(1), 62-70.
• Greitemeyer, T. (2014). Effects of prosocial video games on prosocial behavior. Journal of Personality and Social Psychology, 106(4), 530-548.

Chicago/Turabian Style

Chicago/Turabian Formate is as follows:

• Margins : Use 1-inch margins on all sides of the paper.
• Font : Use a readable font such as Times New Roman or Arial, and use a 12-point font size.
• Page numbering : Number all pages in the upper right-hand corner, beginning with the first page of text. Use Arabic numerals.
• Title page: Include a title page with the title of the paper, your name, course title and number, instructor’s name, and the date. The title should be centered on the page and in title case (capitalize the first letter of each word).
• Headings: Use headings to organize your paper. The first level of headings should be centered and in boldface or italics. The second level of headings should be left-aligned and in boldface or italics. Use as many levels of headings as necessary to organize your paper.
• In-text citations : Use footnotes or endnotes to cite sources within the text of your paper. The first citation for each source should be a full citation, and subsequent citations can be shortened. Use superscript numbers to indicate footnotes or endnotes.
• Bibliography : Include a bibliography at the end of your paper, listing all sources cited in your paper. The bibliography should be in alphabetical order by the author’s last name, and each entry should include the author’s name, title of the work, publication information, and date of publication.
• Formatting of quotations: Use block quotations for quotations that are longer than four lines. Indent the entire quotation one inch from the left margin, and do not use quotation marks. Single-space the quotation, and double-space between paragraphs.
• Tables and figures: Use tables and figures to present data and illustrations. Number each table and figure sequentially, and provide a brief title for each. Place tables and figures as close as possible to the text that refers to them.
• Spelling and grammar : Use correct spelling and grammar throughout your paper. Proofread carefully for errors.

Chicago/Turabian Research Paper Template

Chicago/Turabian Research Paper Template is as folows:

Title of Paper

Name of Student

Professor’s Name

I. Introduction

A. Background Information

B. Research Question

C. Thesis Statement

II. Literature Review

A. Overview of Existing Literature

B. Analysis of Key Literature

C. Identification of Gaps in Literature

III. Methodology

A. Research Design

B. Data Collection

C. Data Analysis

IV. Results

A. Presentation of Findings

B. Analysis of Findings

C. Discussion of Implications

V. Conclusion

A. Summary of Findings

B. Implications for Future Research

C. Conclusion

VI. References

A. Bibliography

B. In-Text Citations

VII. Appendices (if necessary)

A. Data Tables

C. Additional Supporting Materials

Chicago/Turabian Research Paper Example

Title: The Impact of Social Media on Political Engagement

Name: John Smith

Class: POLS 101

Professor: Dr. Jane Doe

Date: April 8, 2023

I. Introduction:

Social media has become an integral part of our daily lives. People use social media platforms like Facebook, Twitter, and Instagram to connect with friends and family, share their opinions, and stay informed about current events. With the rise of social media, there has been a growing interest in understanding its impact on various aspects of society, including political engagement. In this paper, I will examine the relationship between social media use and political engagement, specifically focusing on how social media influences political participation and political attitudes.

II. Literature Review:

There is a growing body of literature on the impact of social media on political engagement. Some scholars argue that social media has a positive effect on political participation by providing new channels for political communication and mobilization (Delli Carpini & Keeter, 1996; Putnam, 2000). Others, however, suggest that social media can have a negative impact on political engagement by creating filter bubbles that reinforce existing beliefs and discourage political dialogue (Pariser, 2011; Sunstein, 2001).

III. Methodology:

To examine the relationship between social media use and political engagement, I conducted a survey of 500 college students. The survey included questions about social media use, political participation, and political attitudes. The data was analyzed using descriptive statistics and regression analysis.

Iv. Results:

The results of the survey indicate that social media use is positively associated with political participation. Specifically, respondents who reported using social media to discuss politics were more likely to have participated in a political campaign, attended a political rally, or contacted a political representative. Additionally, social media use was found to be associated with more positive attitudes towards political engagement, such as increased trust in government and belief in the effectiveness of political action.

V. Conclusion:

The findings of this study suggest that social media has a positive impact on political engagement, by providing new opportunities for political communication and mobilization. However, there is also a need for caution, as social media can also create filter bubbles that reinforce existing beliefs and discourage political dialogue. Future research should continue to explore the complex relationship between social media and political engagement, and develop strategies to harness the potential benefits of social media while mitigating its potential negative effects.

Vii. References:

• Delli Carpini, M. X., & Keeter, S. (1996). What Americans know about politics and why it matters. Yale University Press.
• Pariser, E. (2011). The filter bubble: What the Internet is hiding from you. Penguin.
• Putnam, R. D. (2000). Bowling alone: The collapse and revival of American community. Simon & Schuster.
• Sunstein, C. R. (2001). Republic.com. Princeton University Press.

IEEE (Institute of Electrical and Electronics Engineers) Format

IEEE (Institute of Electrical and Electronics Engineers) Research Paper Format is as follows:

• Title : A concise and informative title that accurately reflects the content of the paper.
• Abstract : A brief summary of the paper, typically no more than 250 words, that includes the purpose of the study, the methods used, the key findings, and the main conclusions.
• Introduction : An overview of the background, context, and motivation for the research, including a clear statement of the problem being addressed and the objectives of the study.
• Literature review: A critical analysis of the relevant research and scholarship on the topic, including a discussion of any gaps or limitations in the existing literature.
• Methodology : A detailed description of the methods used to collect and analyze data, including any experiments or simulations, data collection instruments or procedures, and statistical analyses.
• Results : A clear and concise presentation of the findings, including any relevant tables, graphs, or figures.
• Discussion : A detailed interpretation of the results, including a comparison of the findings with previous research, a discussion of the implications of the results, and any recommendations for future research.
• Conclusion : A summary of the key findings and main conclusions of the study.
• References : A list of all sources cited in the paper, formatted according to IEEE guidelines.

In addition to these elements, an IEEE research paper should also follow certain formatting guidelines, including using 12-point font, double-spaced text, and numbered headings and subheadings. Additionally, any tables, figures, or equations should be clearly labeled and referenced in the text.

AMA (American Medical Association) Style

AMA (American Medical Association) Style Research Paper Format:

• Title Page: This page includes the title of the paper, the author’s name, institutional affiliation, and any acknowledgments or disclaimers.
• Abstract: The abstract is a brief summary of the paper that outlines the purpose, methods, results, and conclusions of the study. It is typically limited to 250 words or less.
• Introduction: The introduction provides a background of the research problem, defines the research question, and outlines the objectives and hypotheses of the study.
• Methods: The methods section describes the research design, participants, procedures, and instruments used to collect and analyze data.
• Results: The results section presents the findings of the study in a clear and concise manner, using graphs, tables, and charts where appropriate.
• Discussion: The discussion section interprets the results, explains their significance, and relates them to previous research in the field.
• Conclusion: The conclusion summarizes the main points of the paper, discusses the implications of the findings, and suggests future research directions.
• References: The reference list includes all sources cited in the paper, listed in alphabetical order by author’s last name.

In addition to these sections, the AMA format requires that authors follow specific guidelines for citing sources in the text and formatting their references. The AMA style uses a superscript number system for in-text citations and provides specific formats for different types of sources, such as books, journal articles, and websites.

Harvard Style

Harvard Style Research Paper format is as follows:

• Title page: This should include the title of your paper, your name, the name of your institution, and the date of submission.
• Abstract : This is a brief summary of your paper, usually no more than 250 words. It should outline the main points of your research and highlight your findings.
• Introduction : This section should introduce your research topic, provide background information, and outline your research question or thesis statement.
• Literature review: This section should review the relevant literature on your topic, including previous research studies, academic articles, and other sources.
• Methodology : This section should describe the methods you used to conduct your research, including any data collection methods, research instruments, and sampling techniques.
• Results : This section should present your findings in a clear and concise manner, using tables, graphs, and other visual aids if necessary.
• Discussion : This section should interpret your findings and relate them to the broader research question or thesis statement. You should also discuss the implications of your research and suggest areas for future study.
• Conclusion : This section should summarize your main findings and provide a final statement on the significance of your research.
• References : This is a list of all the sources you cited in your paper, presented in alphabetical order by author name. Each citation should include the author’s name, the title of the source, the publication date, and other relevant information.

In addition to these sections, a Harvard Style research paper may also include a table of contents, appendices, and other supplementary materials as needed. It is important to follow the specific formatting guidelines provided by your instructor or academic institution when preparing your research paper in Harvard Style.

Vancouver Style

Vancouver Style Research Paper format is as follows:

The Vancouver citation style is commonly used in the biomedical sciences and is known for its use of numbered references. Here is a basic format for a research paper using the Vancouver citation style:

• Title page: Include the title of your paper, your name, the name of your institution, and the date.
• Abstract : This is a brief summary of your research paper, usually no more than 250 words.
• Introduction : Provide some background information on your topic and state the purpose of your research.
• Methods : Describe the methods you used to conduct your research, including the study design, data collection, and statistical analysis.
• Results : Present your findings in a clear and concise manner, using tables and figures as needed.
• Discussion : Interpret your results and explain their significance. Also, discuss any limitations of your study and suggest directions for future research.
• References : List all of the sources you cited in your paper in numerical order. Each reference should include the author’s name, the title of the article or book, the name of the journal or publisher, the year of publication, and the page numbers.

ACS (American Chemical Society) Style

ACS (American Chemical Society) Style Research Paper format is as follows:

The American Chemical Society (ACS) Style is a citation style commonly used in chemistry and related fields. When formatting a research paper in ACS Style, here are some guidelines to follow:

• Paper Size and Margins : Use standard 8.5″ x 11″ paper with 1-inch margins on all sides.
• Font: Use a 12-point serif font (such as Times New Roman) for the main text. The title should be in bold and a larger font size.
• Title Page : The title page should include the title of the paper, the authors’ names and affiliations, and the date of submission. The title should be centered on the page and written in bold font. The authors’ names should be centered below the title, followed by their affiliations and the date.
• Abstract : The abstract should be a brief summary of the paper, no more than 250 words. It should be on a separate page and include the title of the paper, the authors’ names and affiliations, and the text of the abstract.
• Main Text : The main text should be organized into sections with headings that clearly indicate the content of each section. The introduction should provide background information and state the research question or hypothesis. The methods section should describe the procedures used in the study. The results section should present the findings of the study, and the discussion section should interpret the results and provide conclusions.
• References: Use the ACS Style guide to format the references cited in the paper. In-text citations should be numbered sequentially throughout the text and listed in numerical order at the end of the paper.
• Figures and Tables: Figures and tables should be numbered sequentially and referenced in the text. Each should have a descriptive caption that explains its content. Figures should be submitted in a high-quality electronic format.
• Supporting Information: Additional information such as data, graphs, and videos may be included as supporting information. This should be included in a separate file and referenced in the main text.
• Acknowledgments : Acknowledge any funding sources or individuals who contributed to the research.

ASA (American Sociological Association) Style

ASA (American Sociological Association) Style Research Paper format is as follows:

• Title Page: The title page of an ASA style research paper should include the title of the paper, the author’s name, and the institutional affiliation. The title should be centered and should be in title case (the first letter of each major word should be capitalized).
• Abstract: An abstract is a brief summary of the paper that should appear on a separate page immediately following the title page. The abstract should be no more than 200 words in length and should summarize the main points of the paper.
• Main Body: The main body of the paper should begin on a new page following the abstract page. The paper should be double-spaced, with 1-inch margins on all sides, and should be written in 12-point Times New Roman font. The main body of the paper should include an introduction, a literature review, a methodology section, results, and a discussion.
• References : The reference section should appear on a separate page at the end of the paper. All sources cited in the paper should be listed in alphabetical order by the author’s last name. Each reference should include the author’s name, the title of the work, the publication information, and the date of publication.
• Appendices : Appendices are optional and should only be included if they contain information that is relevant to the study but too lengthy to be included in the main body of the paper. If you include appendices, each one should be labeled with a letter (e.g., Appendix A, Appendix B, etc.) and should be referenced in the main body of the paper.

APSA (American Political Science Association) Style

APSA (American Political Science Association) Style Research Paper format is as follows:

• Title Page: The title page should include the title of the paper, the author’s name, the name of the course or instructor, and the date.
• Abstract : An abstract is typically not required in APSA style papers, but if one is included, it should be brief and summarize the main points of the paper.
• Introduction : The introduction should provide an overview of the research topic, the research question, and the main argument or thesis of the paper.
• Literature Review : The literature review should summarize the existing research on the topic and provide a context for the research question.
• Methods : The methods section should describe the research methods used in the paper, including data collection and analysis.
• Results : The results section should present the findings of the research.
• Discussion : The discussion section should interpret the results and connect them back to the research question and argument.
• Conclusion : The conclusion should summarize the main findings and implications of the research.
• References : The reference list should include all sources cited in the paper, formatted according to APSA style guidelines.

In-text citations in APSA style use parenthetical citation, which includes the author’s last name, publication year, and page number(s) if applicable. For example, (Smith 2010, 25).

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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• v.16(7); 2020 Jul

Ten simple rules for reading a scientific paper

Maureen a. carey.

Division of Infectious Diseases and International Health, Department of Medicine, University of Virginia School of Medicine, Charlottesville, Virginia, United States of America

Kevin L. Steiner

William a. petri, jr, introduction.

“There is no problem that a library card can't solve” according to author Eleanor Brown [ 1 ]. This advice is sound, probably for both life and science, but even the best tool (like the library) is most effective when accompanied by instructions and a basic understanding of how and when to use it.

For many budding scientists, the first day in a new lab setting often involves a stack of papers, an email full of links to pertinent articles, or some promise of a richer understanding so long as one reads enough of the scientific literature. However, the purpose and approach to reading a scientific article is unlike that of reading a news story, novel, or even a textbook and can initially seem unapproachable. Having good habits for reading scientific literature is key to setting oneself up for success, identifying new research questions, and filling in the gaps in one’s current understanding; developing these good habits is the first crucial step.

Advice typically centers around two main tips: read actively and read often. However, active reading, or reading with an intent to understand, is both a learned skill and a level of effort. Although there is no one best way to do this, we present 10 simple rules, relevant to novices and seasoned scientists alike, to teach our strategy for active reading based on our experience as readers and as mentors of undergraduate and graduate researchers, medical students, fellows, and early career faculty. Rules 1–5 are big picture recommendations. Rules 6–8 relate to philosophy of reading. Rules 9–10 guide the “now what?” questions one should ask after reading and how to integrate what was learned into one’s own science.

Rule 1: Pick your reading goal

What you want to get out of an article should influence your approach to reading it. Table 1 includes a handful of example intentions and how you might prioritize different parts of the same article differently based on your goals as a reader.

1 Yay! Welcome!

2 A journal club is when a group of scientists get together to discuss a paper. Usually one person leads the discussion and presents all of the data. The group discusses their own interpretations and the authors’ interpretation.

Rule 2: Understand the author’s goal

In written communication, the reader and the writer are equally important. Both influence the final outcome: in this case, your scientific understanding! After identifying your goal, think about the author’s goal for sharing this project. This will help you interpret the data and understand the author’s interpretation of the data. However, this requires some understanding of who the author(s) are (e.g., what are their scientific interests?), the scientific field in which they work (e.g., what techniques are available in this field?), and how this paper fits into the author’s research (e.g., is this work building on an author’s longstanding project or controversial idea?). This information may be hard to glean without experience and a history of reading. But don’t let this be a discouragement to starting the process; it is by the act of reading that this experience is gained!

A good step toward understanding the goal of the author(s) is to ask yourself: What kind of article is this? Journals publish different types of articles, including methods, review, commentary, resources, and research articles as well as other types that are specific to a particular journal or groups of journals. These article types have different formatting requirements and expectations for content. Knowing the article type will help guide your evaluation of the information presented. Is the article a methods paper, presenting a new technique? Is the article a review article, intended to summarize a field or problem? Is it a commentary, intended to take a stand on a controversy or give a big picture perspective on a problem? Is it a resource article, presenting a new tool or data set for others to use? Is it a research article, written to present new data and the authors’ interpretation of those data? The type of paper, and its intended purpose, will get you on your way to understanding the author’s goal.

Rule 3: Ask six questions

When reading, ask yourself: (1) What do the author(s) want to know (motivation)? (2) What did they do (approach/methods)? (3) Why was it done that way (context within the field)? (4) What do the results show (figures and data tables)? (5) How did the author(s) interpret the results (interpretation/discussion)? (6) What should be done next? (Regarding this last question, the author(s) may provide some suggestions in the discussion, but the key is to ask yourself what you think should come next.)

Each of these questions can and should be asked about the complete work as well as each table, figure, or experiment within the paper. Early on, it can take a long time to read one article front to back, and this can be intimidating. Break down your understanding of each section of the work with these questions to make the effort more manageable.

Rule 4: Unpack each figure and table

Scientists write original research papers primarily to present new data that may change or reinforce the collective knowledge of a field. Therefore, the most important parts of this type of scientific paper are the data. Some people like to scrutinize the figures and tables (including legends) before reading any of the “main text”: because all of the important information should be obtained through the data. Others prefer to read through the results section while sequentially examining the figures and tables as they are addressed in the text. There is no correct or incorrect approach: Try both to see what works best for you. The key is making sure that one understands the presented data and how it was obtained.

For each figure, work to understand each x- and y-axes, color scheme, statistical approach (if one was used), and why the particular plotting approach was used. For each table, identify what experimental groups and variables are presented. Identify what is shown and how the data were collected. This is typically summarized in the legend or caption but often requires digging deeper into the methods: Do not be afraid to refer back to the methods section frequently to ensure a full understanding of how the presented data were obtained. Again, ask the questions in Rule 3 for each figure or panel and conclude with articulating the “take home” message.

Rule 5: Understand the formatting intentions

Just like the overall intent of the article (discussed in Rule 2), the intent of each section within a research article can guide your interpretation. Some sections are intended to be written as objective descriptions of the data (i.e., the Results section), whereas other sections are intended to present the author’s interpretation of the data. Remember though that even “objective” sections are written by and, therefore, influenced by the authors interpretations. Check out Table 2 to understand the intent of each section of a research article. When reading a specific paper, you can also refer to the journal’s website to understand the formatting intentions. The “For Authors” section of a website will have some nitty gritty information that is less relevant for the reader (like word counts) but will also summarize what the journal editors expect in each section. This will help to familiarize you with the goal of each article section.

Research articles typically contain each of these sections, although sometimes the “results” and “discussion” sections (or “discussion” and “conclusion” sections) are merged into one section. Additional sections may be included, based on request of the journal or the author(s). Keep in mind: If it was included, someone thought it was important for you to read.

Rule 6: Be critical

Published papers are not truths etched in stone. Published papers in high impact journals are not truths etched in stone. Published papers by bigwigs in the field are not truths etched in stone. Published papers that seem to agree with your own hypothesis or data are not etched in stone. Published papers that seem to refute your hypothesis or data are not etched in stone.

Science is a never-ending work in progress, and it is essential that the reader pushes back against the author’s interpretation to test the strength of their conclusions. Everyone has their own perspective and may interpret the same data in different ways. Mistakes are sometimes published, but more often these apparent errors are due to other factors such as limitations of a methodology and other limits to generalizability (selection bias, unaddressed, or unappreciated confounders). When reading a paper, it is important to consider if these factors are pertinent.

Critical thinking is a tough skill to learn but ultimately boils down to evaluating data while minimizing biases. Ask yourself: Are there other, equally likely, explanations for what is observed? In addition to paying close attention to potential biases of the study or author(s), a reader should also be alert to one’s own preceding perspective (and biases). Take time to ask oneself: Do I find this paper compelling because it affirms something I already think (or wish) is true? Or am I discounting their findings because it differs from what I expect or from my own work?

The phenomenon of a self-fulfilling prophecy, or expectancy, is well studied in the psychology literature [ 2 ] and is why many studies are conducted in a “blinded” manner [ 3 ]. It refers to the idea that a person may assume something to be true and their resultant behavior aligns to make it true. In other words, as humans and scientists, we often find exactly what we are looking for. A scientist may only test their hypotheses and fail to evaluate alternative hypotheses; perhaps, a scientist may not be aware of alternative, less biased ways to test her or his hypothesis that are typically used in different fields. Individuals with different life, academic, and work experiences may think of several alternative hypotheses, all equally supported by the data.

Rule 7: Be kind

The author(s) are human too. So, whenever possible, give them the benefit of the doubt. An author may write a phrase differently than you would, forcing you to reread the sentence to understand it. Someone in your field may neglect to cite your paper because of a reference count limit. A figure panel may be misreferenced as Supplemental Fig 3E when it is obviously Supplemental Fig 4E. While these things may be frustrating, none are an indication that the quality of work is poor. Try to avoid letting these minor things influence your evaluation and interpretation of the work.

Similarly, if you intend to share your critique with others, be extra kind. An author (especially the lead author) may invest years of their time into a single paper. Hearing a kindly phrased critique can be difficult but constructive. Hearing a rude, brusque, or mean-spirited critique can be heartbreaking, especially for young scientists or those seeking to establish their place within a field and who may worry that they do not belong.

Rule 8: Be ready to go the extra mile

To truly understand a scientific work, you often will need to look up a term, dig into the supplemental materials, or read one or more of the cited references. This process takes time. Some advisors recommend reading an article three times: The first time, simply read without the pressure of understanding or critiquing the work. For the second time, aim to understand the paper. For the third read through, take notes.

Some people engage with a paper by printing it out and writing all over it. The reader might write question marks in the margins to mark parts (s)he wants to return to, circle unfamiliar terms (and then actually look them up!), highlight or underline important statements, and draw arrows linking figures and the corresponding interpretation in the discussion. Not everyone needs a paper copy to engage in the reading process but, whatever your version of “printing it out” is, do it.

Rule 9: Talk about it

Talking about an article in a journal club or more informal environment forces active reading and participation with the material. Studies show that teaching is one of the best ways to learn and that teachers learn the material even better as the teaching task becomes more complex [ 4 – 5 ]; anecdotally, such observations inspired the phrase “to teach is to learn twice.”

Beyond formal settings such as journal clubs, lab meetings, and academic classes, discuss papers with your peers, mentors, and colleagues in person or electronically. Twitter and other social media platforms have become excellent resources for discussing papers with other scientists, the public or your nonscientist friends, or even the paper’s author(s). Describing a paper can be done at multiple levels and your description can contain all of the scientific details, only the big picture summary, or perhaps the implications for the average person in your community. All of these descriptions will solidify your understanding, while highlighting gaps in your knowledge and informing those around you.

Rule 10: Build on it

One approach we like to use for communicating how we build on the scientific literature is by starting research presentations with an image depicting a wall of Lego bricks. Each brick is labeled with the reference for a paper, and the wall highlights the body of literature on which the work is built. We describe the work and conclusions of each paper represented by a labeled brick and discuss each brick and the wall as a whole. The top brick on the wall is left blank: We aspire to build on this work and label this brick with our own work. We then delve into our own research, discoveries, and the conclusions it inspires. We finish our presentations with the image of the Legos and summarize our presentation on that empty brick.

Whether you are reading an article to understand a new topic area or to move a research project forward, effective learning requires that you integrate knowledge from multiple sources (“click” those Lego bricks together) and build upwards. Leveraging published work will enable you to build a stronger and taller structure. The first row of bricks is more stable once a second row is assembled on top of it and so on and so forth. Moreover, the Lego construction will become taller and larger if you build upon the work of others, rather than using only your own bricks.

Build on the article you read by thinking about how it connects to ideas described in other papers and within own work, implementing a technique in your own research, or attempting to challenge or support the hypothesis of the author(s) with a more extensive literature review. Integrate the techniques and scientific conclusions learned from an article into your own research or perspective in the classroom or research lab. You may find that this process strengthens your understanding, leads you toward new and unexpected interests or research questions, or returns you back to the original article with new questions and critiques of the work. All of these experiences are part of the “active reading”: process and are signs of a successful reading experience.

In summary, practice these rules to learn how to read a scientific article, keeping in mind that this process will get easier (and faster) with experience. We are firm believers that an hour in the library will save a week at the bench; this diligent practice will ultimately make you both a more knowledgeable and productive scientist. As you develop the skills to read an article, try to also foster good reading and learning habits for yourself (recommendations here: [ 6 ] and [ 7 ], respectively) and in others. Good luck and happy reading!

Acknowledgments

Thank you to the mentors, teachers, and students who have shaped our thoughts on reading, learning, and what science is all about.

Funding Statement

MAC was supported by the PhRMA Foundation's Postdoctoral Fellowship in Translational Medicine and Therapeutics and the University of Virginia's Engineering-in-Medicine seed grant, and KLS was supported by the NIH T32 Global Biothreats Training Program at the University of Virginia (AI055432). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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13.1 Formatting a Research Paper

Learning objectives.

• Identify the major components of a research paper written using American Psychological Association (APA) style.
• Apply general APA style and formatting conventions in a research paper.

In this chapter, you will learn how to use APA style , the documentation and formatting style followed by the American Psychological Association, as well as MLA style , from the Modern Language Association. There are a few major formatting styles used in academic texts, including AMA, Chicago, and Turabian:

• AMA (American Medical Association) for medicine, health, and biological sciences
• APA (American Psychological Association) for education, psychology, and the social sciences
• Chicago—a common style used in everyday publications like magazines, newspapers, and books
• MLA (Modern Language Association) for English, literature, arts, and humanities
• Turabian—another common style designed for its universal application across all subjects and disciplines

While all the formatting and citation styles have their own use and applications, in this chapter we focus our attention on the two styles you are most likely to use in your academic studies: APA and MLA.

If you find that the rules of proper source documentation are difficult to keep straight, you are not alone. Writing a good research paper is, in and of itself, a major intellectual challenge. Having to follow detailed citation and formatting guidelines as well may seem like just one more task to add to an already-too-long list of requirements.

Following these guidelines, however, serves several important purposes. First, it signals to your readers that your paper should be taken seriously as a student’s contribution to a given academic or professional field; it is the literary equivalent of wearing a tailored suit to a job interview. Second, it shows that you respect other people’s work enough to give them proper credit for it. Finally, it helps your reader find additional materials if he or she wishes to learn more about your topic.

Furthermore, producing a letter-perfect APA-style paper need not be burdensome. Yes, it requires careful attention to detail. However, you can simplify the process if you keep these broad guidelines in mind:

• Work ahead whenever you can. Chapter 11 “Writing from Research: What Will I Learn?” includes tips for keeping track of your sources early in the research process, which will save time later on.
• Get it right the first time. Apply APA guidelines as you write, so you will not have much to correct during the editing stage. Again, putting in a little extra time early on can save time later.
• Use the resources available to you. In addition to the guidelines provided in this chapter, you may wish to consult the APA website at http://www.apa.org or the Purdue University Online Writing lab at http://owl.english.purdue.edu , which regularly updates its online style guidelines.

General Formatting Guidelines

This chapter provides detailed guidelines for using the citation and formatting conventions developed by the American Psychological Association, or APA. Writers in disciplines as diverse as astrophysics, biology, psychology, and education follow APA style. The major components of a paper written in APA style are listed in the following box.

These are the major components of an APA-style paper:

Body, which includes the following:

• Headings and, if necessary, subheadings to organize the content
• In-text citations of research sources
• References page

All these components must be saved in one document, not as separate documents.

The title page of your paper includes the following information:

• Title of the paper
• Author’s name
• Name of the institution with which the author is affiliated
• Header at the top of the page with the paper title (in capital letters) and the page number (If the title is lengthy, you may use a shortened form of it in the header.)

List the first three elements in the order given in the previous list, centered about one third of the way down from the top of the page. Use the headers and footers tool of your word-processing program to add the header, with the title text at the left and the page number in the upper-right corner. Your title page should look like the following example.

The next page of your paper provides an abstract , or brief summary of your findings. An abstract does not need to be provided in every paper, but an abstract should be used in papers that include a hypothesis. A good abstract is concise—about one hundred fifty to two hundred fifty words—and is written in an objective, impersonal style. Your writing voice will not be as apparent here as in the body of your paper. When writing the abstract, take a just-the-facts approach, and summarize your research question and your findings in a few sentences.

In Chapter 12 “Writing a Research Paper” , you read a paper written by a student named Jorge, who researched the effectiveness of low-carbohydrate diets. Read Jorge’s abstract. Note how it sums up the major ideas in his paper without going into excessive detail.

Write an abstract summarizing your paper. Briefly introduce the topic, state your findings, and sum up what conclusions you can draw from your research. Use the word count feature of your word-processing program to make sure your abstract does not exceed one hundred fifty words.

Depending on your field of study, you may sometimes write research papers that present extensive primary research, such as your own experiment or survey. In your abstract, summarize your research question and your findings, and briefly indicate how your study relates to prior research in the field.

Margins, Pagination, and Headings

APA style requirements also address specific formatting concerns, such as margins, pagination, and heading styles, within the body of the paper. Review the following APA guidelines.

Use these general guidelines to format the paper:

• Set the top, bottom, and side margins of your paper at 1 inch.
• Use double-spaced text throughout your paper.
• Use a standard font, such as Times New Roman or Arial, in a legible size (10- to 12-point).
• Use continuous pagination throughout the paper, including the title page and the references section. Page numbers appear flush right within your header.
• Section headings and subsection headings within the body of your paper use different types of formatting depending on the level of information you are presenting. Additional details from Jorge’s paper are provided.

Begin formatting the final draft of your paper according to APA guidelines. You may work with an existing document or set up a new document if you choose. Include the following:

• Your title page
• The abstract you created in Note 13.8 “Exercise 1”
• Correct headers and page numbers for your title page and abstract

APA style uses section headings to organize information, making it easy for the reader to follow the writer’s train of thought and to know immediately what major topics are covered. Depending on the length and complexity of the paper, its major sections may also be divided into subsections, sub-subsections, and so on. These smaller sections, in turn, use different heading styles to indicate different levels of information. In essence, you are using headings to create a hierarchy of information.

The following heading styles used in APA formatting are listed in order of greatest to least importance:

• Section headings use centered, boldface type. Headings use title case, with important words in the heading capitalized.
• Subsection headings use left-aligned, boldface type. Headings use title case.
• The third level uses left-aligned, indented, boldface type. Headings use a capital letter only for the first word, and they end in a period.
• The fourth level follows the same style used for the previous level, but the headings are boldfaced and italicized.
• The fifth level follows the same style used for the previous level, but the headings are italicized and not boldfaced.

Visually, the hierarchy of information is organized as indicated in Table 13.1 “Section Headings” .

Table 13.1 Section Headings

A college research paper may not use all the heading levels shown in Table 13.1 “Section Headings” , but you are likely to encounter them in academic journal articles that use APA style. For a brief paper, you may find that level 1 headings suffice. Longer or more complex papers may need level 2 headings or other lower-level headings to organize information clearly. Use your outline to craft your major section headings and determine whether any subtopics are substantial enough to require additional levels of headings.

Working with the document you developed in Note 13.11 “Exercise 2” , begin setting up the heading structure of the final draft of your research paper according to APA guidelines. Include your title and at least two to three major section headings, and follow the formatting guidelines provided above. If your major sections should be broken into subsections, add those headings as well. Use your outline to help you.

Because Jorge used only level 1 headings, his Exercise 3 would look like the following:

Citation Guidelines

In-text citations.

Throughout the body of your paper, include a citation whenever you quote or paraphrase material from your research sources. As you learned in Chapter 11 “Writing from Research: What Will I Learn?” , the purpose of citations is twofold: to give credit to others for their ideas and to allow your reader to follow up and learn more about the topic if desired. Your in-text citations provide basic information about your source; each source you cite will have a longer entry in the references section that provides more detailed information.

In-text citations must provide the name of the author or authors and the year the source was published. (When a given source does not list an individual author, you may provide the source title or the name of the organization that published the material instead.) When directly quoting a source, it is also required that you include the page number where the quote appears in your citation.

This information may be included within the sentence or in a parenthetical reference at the end of the sentence, as in these examples.

Epstein (2010) points out that “junk food cannot be considered addictive in the same way that we think of psychoactive drugs as addictive” (p. 137).

Here, the writer names the source author when introducing the quote and provides the publication date in parentheses after the author’s name. The page number appears in parentheses after the closing quotation marks and before the period that ends the sentence.

Addiction researchers caution that “junk food cannot be considered addictive in the same way that we think of psychoactive drugs as addictive” (Epstein, 2010, p. 137).

Here, the writer provides a parenthetical citation at the end of the sentence that includes the author’s name, the year of publication, and the page number separated by commas. Again, the parenthetical citation is placed after the closing quotation marks and before the period at the end of the sentence.

As noted in the book Junk Food, Junk Science (Epstein, 2010, p. 137), “junk food cannot be considered addictive in the same way that we think of psychoactive drugs as addictive.”

Here, the writer chose to mention the source title in the sentence (an optional piece of information to include) and followed the title with a parenthetical citation. Note that the parenthetical citation is placed before the comma that signals the end of the introductory phrase.

David Epstein’s book Junk Food, Junk Science (2010) pointed out that “junk food cannot be considered addictive in the same way that we think of psychoactive drugs as addictive” (p. 137).

Another variation is to introduce the author and the source title in your sentence and include the publication date and page number in parentheses within the sentence or at the end of the sentence. As long as you have included the essential information, you can choose the option that works best for that particular sentence and source.

Citing a book with a single author is usually a straightforward task. Of course, your research may require that you cite many other types of sources, such as books or articles with more than one author or sources with no individual author listed. You may also need to cite sources available in both print and online and nonprint sources, such as websites and personal interviews. Chapter 13 “APA and MLA Documentation and Formatting” , Section 13.2 “Citing and Referencing Techniques” and Section 13.3 “Creating a References Section” provide extensive guidelines for citing a variety of source types.

Writing at Work

APA is just one of several different styles with its own guidelines for documentation, formatting, and language usage. Depending on your field of interest, you may be exposed to additional styles, such as the following:

• MLA style. Determined by the Modern Languages Association and used for papers in literature, languages, and other disciplines in the humanities.
• Chicago style. Outlined in the Chicago Manual of Style and sometimes used for papers in the humanities and the sciences; many professional organizations use this style for publications as well.
• Associated Press (AP) style. Used by professional journalists.

References List

The brief citations included in the body of your paper correspond to the more detailed citations provided at the end of the paper in the references section. In-text citations provide basic information—the author’s name, the publication date, and the page number if necessary—while the references section provides more extensive bibliographical information. Again, this information allows your reader to follow up on the sources you cited and do additional reading about the topic if desired.

The specific format of entries in the list of references varies slightly for different source types, but the entries generally include the following information:

• The name(s) of the author(s) or institution that wrote the source
• The year of publication and, where applicable, the exact date of publication
• The full title of the source
• For books, the city of publication
• For articles or essays, the name of the periodical or book in which the article or essay appears
• For magazine and journal articles, the volume number, issue number, and pages where the article appears
• For sources on the web, the URL where the source is located

The references page is double spaced and lists entries in alphabetical order by the author’s last name. If an entry continues for more than one line, the second line and each subsequent line are indented five spaces. Review the following example. ( Chapter 13 “APA and MLA Documentation and Formatting” , Section 13.3 “Creating a References Section” provides extensive guidelines for formatting reference entries for different types of sources.)

In APA style, book and article titles are formatted in sentence case, not title case. Sentence case means that only the first word is capitalized, along with any proper nouns.

Key Takeaways

• Following proper citation and formatting guidelines helps writers ensure that their work will be taken seriously, give proper credit to other authors for their work, and provide valuable information to readers.
• Working ahead and taking care to cite sources correctly the first time are ways writers can save time during the editing stage of writing a research paper.
• APA papers usually include an abstract that concisely summarizes the paper.
• APA papers use a specific headings structure to provide a clear hierarchy of information.
• In APA papers, in-text citations usually include the name(s) of the author(s) and the year of publication.
• In-text citations correspond to entries in the references section, which provide detailed bibliographical information about a source.

Writing for Success Copyright © 2015 by University of Minnesota is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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Organizing Your Social Sciences Research Paper

• 8. The Discussion
• Purpose of Guide
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The purpose of the discussion section is to interpret and describe the significance of your findings in relation to what was already known about the research problem being investigated and to explain any new understanding or insights that emerged as a result of your research. The discussion will always connect to the introduction by way of the research questions or hypotheses you posed and the literature you reviewed, but the discussion does not simply repeat or rearrange the first parts of your paper; the discussion clearly explains how your study advanced the reader's understanding of the research problem from where you left them at the end of your review of prior research.

Annesley, Thomas M. “The Discussion Section: Your Closing Argument.” Clinical Chemistry 56 (November 2010): 1671-1674; Peacock, Matthew. “Communicative Moves in the Discussion Section of Research Articles.” System 30 (December 2002): 479-497.

Importance of a Good Discussion

The discussion section is often considered the most important part of your research paper because it:

• Most effectively demonstrates your ability as a researcher to think critically about an issue, to develop creative solutions to problems based upon a logical synthesis of the findings, and to formulate a deeper, more profound understanding of the research problem under investigation;
• Presents the underlying meaning of your research, notes possible implications in other areas of study, and explores possible improvements that can be made in order to further develop the concerns of your research;
• Highlights the importance of your study and how it can contribute to understanding the research problem within the field of study;
• Presents how the findings from your study revealed and helped fill gaps in the literature that had not been previously exposed or adequately described; and,
• Engages the reader in thinking critically about issues based on an evidence-based interpretation of findings; it is not governed strictly by objective reporting of information.

Annesley Thomas M. “The Discussion Section: Your Closing Argument.” Clinical Chemistry 56 (November 2010): 1671-1674; Bitchener, John and Helen Basturkmen. “Perceptions of the Difficulties of Postgraduate L2 Thesis Students Writing the Discussion Section.” Journal of English for Academic Purposes 5 (January 2006): 4-18; Kretchmer, Paul. Fourteen Steps to Writing an Effective Discussion Section. San Francisco Edit, 2003-2008.

Structure and Writing Style

I.  General Rules

These are the general rules you should adopt when composing your discussion of the results :

• Do not be verbose or repetitive; be concise and make your points clearly
• Avoid the use of jargon or undefined technical language
• Follow a logical stream of thought; in general, interpret and discuss the significance of your findings in the same sequence you described them in your results section [a notable exception is to begin by highlighting an unexpected result or a finding that can grab the reader's attention]
• Use the present verb tense, especially for established facts; however, refer to specific works or prior studies in the past tense
• If needed, use subheadings to help organize your discussion or to categorize your interpretations into themes

II.  The Content

The content of the discussion section of your paper most often includes :

• Explanation of results : Comment on whether or not the results were expected for each set of findings; go into greater depth to explain findings that were unexpected or especially profound. If appropriate, note any unusual or unanticipated patterns or trends that emerged from your results and explain their meaning in relation to the research problem.
• References to previous research : Either compare your results with the findings from other studies or use the studies to support a claim. This can include re-visiting key sources already cited in your literature review section, or, save them to cite later in the discussion section if they are more important to compare with your results instead of being a part of the general literature review of prior research used to provide context and background information. Note that you can make this decision to highlight specific studies after you have begun writing the discussion section.
• Deduction : A claim for how the results can be applied more generally. For example, describing lessons learned, proposing recommendations that can help improve a situation, or highlighting best practices.
• Hypothesis : A more general claim or possible conclusion arising from the results [which may be proved or disproved in subsequent research]. This can be framed as new research questions that emerged as a consequence of your analysis.

III.  Organization and Structure

Keep the following sequential points in mind as you organize and write the discussion section of your paper:

• Think of your discussion as an inverted pyramid. Organize the discussion from the general to the specific, linking your findings to the literature, then to theory, then to practice [if appropriate].
• Use the same key terms, narrative style, and verb tense [present] that you used when describing the research problem in your introduction.
• Begin by briefly re-stating the research problem you were investigating and answer all of the research questions underpinning the problem that you posed in the introduction.
• Describe the patterns, principles, and relationships shown by each major findings and place them in proper perspective. The sequence of this information is important; first state the answer, then the relevant results, then cite the work of others. If appropriate, refer the reader to a figure or table to help enhance the interpretation of the data [either within the text or as an appendix].
• Regardless of where it's mentioned, a good discussion section includes analysis of any unexpected findings. This part of the discussion should begin with a description of the unanticipated finding, followed by a brief interpretation as to why you believe it appeared and, if necessary, its possible significance in relation to the overall study. If more than one unexpected finding emerged during the study, describe each of them in the order they appeared as you gathered or analyzed the data. As noted, the exception to discussing findings in the same order you described them in the results section would be to begin by highlighting the implications of a particularly unexpected or significant finding that emerged from the study, followed by a discussion of the remaining findings.
• Before concluding the discussion, identify potential limitations and weaknesses if you do not plan to do so in the conclusion of the paper. Comment on their relative importance in relation to your overall interpretation of the results and, if necessary, note how they may affect the validity of your findings. Avoid using an apologetic tone; however, be honest and self-critical [e.g., in retrospect, had you included a particular question in a survey instrument, additional data could have been revealed].
• The discussion section should end with a concise summary of the principal implications of the findings regardless of their significance. Give a brief explanation about why you believe the findings and conclusions of your study are important and how they support broader knowledge or understanding of the research problem. This can be followed by any recommendations for further research. However, do not offer recommendations which could have been easily addressed within the study. This would demonstrate to the reader that you have inadequately examined and interpreted the data.

IV.  Overall Objectives

The objectives of your discussion section should include the following: I.  Reiterate the Research Problem/State the Major Findings

Briefly reiterate the research problem or problems you are investigating and the methods you used to investigate them, then move quickly to describe the major findings of the study. You should write a direct, declarative, and succinct proclamation of the study results, usually in one paragraph.

II.  Explain the Meaning of the Findings and Why They are Important

No one has thought as long and hard about your study as you have. Systematically explain the underlying meaning of your findings and state why you believe they are significant. After reading the discussion section, you want the reader to think critically about the results and why they are important. You don’t want to force the reader to go through the paper multiple times to figure out what it all means. If applicable, begin this part of the section by repeating what you consider to be your most significant or unanticipated finding first, then systematically review each finding. Otherwise, follow the general order you reported the findings presented in the results section.

III.  Relate the Findings to Similar Studies

No study in the social sciences is so novel or possesses such a restricted focus that it has absolutely no relation to previously published research. The discussion section should relate your results to those found in other studies, particularly if questions raised from prior studies served as the motivation for your research. This is important because comparing and contrasting the findings of other studies helps to support the overall importance of your results and it highlights how and in what ways your study differs from other research about the topic. Note that any significant or unanticipated finding is often because there was no prior research to indicate the finding could occur. If there is prior research to indicate this, you need to explain why it was significant or unanticipated. IV.  Consider Alternative Explanations of the Findings

It is important to remember that the purpose of research in the social sciences is to discover and not to prove . When writing the discussion section, you should carefully consider all possible explanations for the study results, rather than just those that fit your hypothesis or prior assumptions and biases. This is especially important when describing the discovery of significant or unanticipated findings.

V.  Acknowledge the Study’s Limitations

It is far better for you to identify and acknowledge your study’s limitations than to have them pointed out by your professor! Note any unanswered questions or issues your study could not address and describe the generalizability of your results to other situations. If a limitation is applicable to the method chosen to gather information, then describe in detail the problems you encountered and why. VI.  Make Suggestions for Further Research

You may choose to conclude the discussion section by making suggestions for further research [as opposed to offering suggestions in the conclusion of your paper]. Although your study can offer important insights about the research problem, this is where you can address other questions related to the problem that remain unanswered or highlight hidden issues that were revealed as a result of conducting your research. You should frame your suggestions by linking the need for further research to the limitations of your study [e.g., in future studies, the survey instrument should include more questions that ask..."] or linking to critical issues revealed from the data that were not considered initially in your research.

NOTE: Besides the literature review section, the preponderance of references to sources is usually found in the discussion section . A few historical references may be helpful for perspective, but most of the references should be relatively recent and included to aid in the interpretation of your results, to support the significance of a finding, and/or to place a finding within a particular context. If a study that you cited does not support your findings, don't ignore it--clearly explain why your research findings differ from theirs.

V.  Problems to Avoid

• Do not waste time restating your results . Should you need to remind the reader of a finding to be discussed, use "bridge sentences" that relate the result to the interpretation. An example would be: “In the case of determining available housing to single women with children in rural areas of Texas, the findings suggest that access to good schools is important...," then move on to further explaining this finding and its implications.
• As noted, recommendations for further research can be included in either the discussion or conclusion of your paper, but do not repeat your recommendations in the both sections. Think about the overall narrative flow of your paper to determine where best to locate this information. However, if your findings raise a lot of new questions or issues, consider including suggestions for further research in the discussion section.
• Do not introduce new results in the discussion section. Be wary of mistaking the reiteration of a specific finding for an interpretation because it may confuse the reader. The description of findings [results section] and the interpretation of their significance [discussion section] should be distinct parts of your paper. If you choose to combine the results section and the discussion section into a single narrative, you must be clear in how you report the information discovered and your own interpretation of each finding. This approach is not recommended if you lack experience writing college-level research papers.
• Use of the first person pronoun is generally acceptable. Using first person singular pronouns can help emphasize a point or illustrate a contrasting finding. However, keep in mind that too much use of the first person can actually distract the reader from the main points [i.e., I know you're telling me this--just tell me!].

Analyzing vs. Summarizing. Department of English Writing Guide. George Mason University; Discussion. The Structure, Format, Content, and Style of a Journal-Style Scientific Paper. Department of Biology. Bates College; Hess, Dean R. "How to Write an Effective Discussion." Respiratory Care 49 (October 2004); Kretchmer, Paul. Fourteen Steps to Writing to Writing an Effective Discussion Section. San Francisco Edit, 2003-2008; The Lab Report. University College Writing Centre. University of Toronto; Sauaia, A. et al. "The Anatomy of an Article: The Discussion Section: "How Does the Article I Read Today Change What I Will Recommend to my Patients Tomorrow?” The Journal of Trauma and Acute Care Surgery 74 (June 2013): 1599-1602; Research Limitations & Future Research . Lund Research Ltd., 2012; Summary: Using it Wisely. The Writing Center. University of North Carolina; Schafer, Mickey S. Writing the Discussion. Writing in Psychology course syllabus. University of Florida; Yellin, Linda L. A Sociology Writer's Guide . Boston, MA: Allyn and Bacon, 2009.

Writing Tip

Don’t Over-Interpret the Results!

Interpretation is a subjective exercise. As such, you should always approach the selection and interpretation of your findings introspectively and to think critically about the possibility of judgmental biases unintentionally entering into discussions about the significance of your work. With this in mind, be careful that you do not read more into the findings than can be supported by the evidence you have gathered. Remember that the data are the data: nothing more, nothing less.

MacCoun, Robert J. "Biases in the Interpretation and Use of Research Results." Annual Review of Psychology 49 (February 1998): 259-287; Ward, Paulet al, editors. The Oxford Handbook of Expertise . Oxford, UK: Oxford University Press, 2018.

Another Writing Tip

Don't Write Two Results Sections!

One of the most common mistakes that you can make when discussing the results of your study is to present a superficial interpretation of the findings that more or less re-states the results section of your paper. Obviously, you must refer to your results when discussing them, but focus on the interpretation of those results and their significance in relation to the research problem, not the data itself.

Azar, Beth. "Discussing Your Findings."  American Psychological Association gradPSYCH Magazine (January 2006).

Yet Another Writing Tip

Avoid Unwarranted Speculation!

The discussion section should remain focused on the findings of your study. For example, if the purpose of your research was to measure the impact of foreign aid on increasing access to education among disadvantaged children in Bangladesh, it would not be appropriate to speculate about how your findings might apply to populations in other countries without drawing from existing studies to support your claim or if analysis of other countries was not a part of your original research design. If you feel compelled to speculate, do so in the form of describing possible implications or explaining possible impacts. Be certain that you clearly identify your comments as speculation or as a suggestion for where further research is needed. Sometimes your professor will encourage you to expand your discussion of the results in this way, while others don’t care what your opinion is beyond your effort to interpret the data in relation to the research problem.

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More From Forbes

5 tips to enhance your research paper’s visibility and altmetric score.

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US evangelist Billy Graham addresses a crowd of football supporters at Stamford Bridge, London, ... [+] during half-time at the match between Chelsea and Newcastle United. (Photo by Edward Miller/Getty Images)

I previously wrote about the importance of attracting public attention to scientific research . In today’s world, where billions of people are attached to their digital devices watching the very addictive but often useless TikTok content or receiving instant gratification by engaging in meaningless debates about celebrities, scientists need to find creative ways to have their research noticed. Popularizing scientific research helps inspire the younger generations to go into science and provide the general public with a sense of optimism enabling the government to channel more resources into science. People do need inspiration. But very often, even very important scientific breakthroughs requiring many years, hard work, skill, funding, and genuine serendipity go largely unnoticed by the general public.

One of the best ways to measure expert and public attention is the cumulative Altmetric Attention Score , originally developed by Digital Science and adopted by many prestigious publishers, including Nature Publishing Group. Every Nature paper and the papers published by pretty much every credible publisher are tracked by Digital Science by the Document Object Identification (DOI) or the Unique Resource Locator (URL) . While Altmetric has many limitations, for example, it does not track LinkedIn posts and may not adequately cover the impact of top-tier media coverage, at the moment it is the blueprint for tracking attention.

Altmetric Score in The Age of Generative AI

Media attention is likely to be very important in the age of generative AI. Many modern generative systems, such as ChatGPT, Claude, Mistral, and Gemini, as well as hundreds of Large Language Models (LLMs) in China, use the data from the same sources referenced in Altmetric to learn. The more times generative systems see the same concept presented in different contexts, the better they learn. So if you want to contribute to the training of AI systems that may thank you for it in the future - Altmetric is the way to go.

So what can a research group do to ensure they are communicating their findings effectively and increasing the visibility of their research to ensure it gets reflected in the Altmetric Attention Score?

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Altmetric openly discloses the weights of the various sources and the scoring algorithm is relatively straightforward. It is easy to learn, and there are multiple online resources providing advice on how to share your research in ways that will be captured by Altmetric. Cambridge University Press published a guideline to Altmetric for the authors on how to popularize their research with Altmetric in mind. Wolters Kluwer put out a guide and the editor of Toxicology and Pathology wrote a comprehensive overview of Altmetric and how to use it. Surprisingly, this overview got an Altmetric Attention Score of only 4 at the time of the writing, but was cited 137 times according to Google Scholar .

Altmetric monitors social networks, including X (formerly Twitter), Facebook, and Reddit; all major top-tier mainstream media, mainstream science blogs, policy documents, patents, Wikipedia articles, peer review websites, F1000, Syllabi, X (formerly Twitter), tracked Facebook pages, Reddit, one of the Stack Exchange sites, and Youtube. Unfortunately, several powerful platforms, including LinkedIn, are not currently tracked.

The popularity of the paper depends on many factors. Firstly, it has to be novel, trendy, and newsworthy. You are unlikely to get high Altmetric Score with a boring topic. Secondly, papers coming out of popular labs in top-tier academic institutions and in top journals are likely to attract more attention. Often, the communications officers in these academic institutions work closely with the media to amplify notable research. Celebrity companies, for example, Google DeepMind, consistently get higher coverage.

Screenshot of the Altmetric Attention Score "Flower" showing several tracked sources

Here are the five tips for increasing the visibility of your work and ensuring that reach is tracked and reflected by Altmetric:

1. Understand How Altmetric System Works

Congratulations, if you read this article and looked at what sources are tracked by Altmetric. Most likely, you got the basics and will be able to get a “balanced flower” by making a press release, tweeting the DOI of the paper on X, posting a video overview of your paper on Youtube, announcing on Reddit (I still need to learn how to do this).

To understand how Altmetric works, I emailed a few questions to Miguel Garcia, Director of Product and Data Analytics Hub at Digital Science and my first question was wether the Altmetric algorithm is open source. “The Altmetric Attention Score's calculation is not open source but we try to provide as much information as possible around how we calculate it here, and are currently considering what steps we might take to make our algorithms more transparent.” He also provided a link to how the Altmetric Attention Score is calculated.

Many professionals use LinkedIn as the primary social media resource and I was wondering why Altmetric stopped tracking it. Bad news - technical reasons prevent tracking DOIs on LinkedIn. Good news - they are actively seeking ways to appropriately track mentions on LinkedIn and we may see some news toward the end of the year.

My other big question was how does Altmetric count tweets and retweets on X. What if there are many posts from the same account? Miguel’s response was: “Re-tweets count less than original tweets. In addition to that, modifiers are applied to the type of account that is tweeting in order to reduce the weight of the tweet in situations where we find signals of bias or promiscuity (for example a journal publisher only tweeting their own articles). Besides that, we have conditions around the maximum number of retweets in order to limit the maximum impact they would have.”

So tweeting the article many times will not help you. But if other scientists tweet you paper with a DOI - these tweets will get counted. So tweet others as you would like to be tweeted.

2. Make a Press Release and Distribute to Science-focused Media

If your paper is significant, for example, you elucidated novel disease biology, discovered a new drug, developed a new fancy algorithm, designed a new material, or developed a new application for a quantum computer, it is worthwhile investing some time and resources in writing a press release. If you are working for an academic institution, most likely they have a communications office that will help you. If you do not have this luxury, you will need to learn how to write a press release. Plenty of free online guides cover the basics of press release writing. And press releases are one area where ChatGPT and other generative tools do surprisingly well. Upload your paper and ask it to write a press release, check for errors or exaggerations, edit, and you are ready to go. Just make sure to include the DOI and the URL of your paper. A proper business press release on BusinessWire or PRNewswire may cost several thousand dollars. In my opinion, these resources are dramatically overcharging while providing little service. I don't remember a case where a journalist picked up our news based on a commercial press release. But these releases are often reposted by other online press release distributors and the boost to Altmetric may be considerable. The default news release distribution service for research news is EurekAlert. This resource may sometimes result in journalistic coverage as many reporters are using it for science news. There are many free resources you can use if you do not have any budget.

Once the press release is issued, share it with the media. Share the resulting news coverage via your social networks and contacts. Many journalists track the popularity of their news articles and giving them several thousand extra views from professional audience and increasing their social following increases the chances that they will cover the next important research paper.

3. Make a Blog Post

Writing a blog post can be longer and more comprehensive than the press release. Make sure to add fancy diagrams and graphical explainers. You can share the blog post with the journalists at the same time as the press release. Your blog may serve as a source of inspiration for third party news coverage. Make sure to reference the DOI and URL of your paper.

If your paper is in one of the Nature journals, consider writing a “Behind the Paper" blog post on Nature Bioengineering Community. Surprisingly, these blogs are rarely picked up by Altmetric but may serve as a source of inspiration for the journalists and social media influencers. Plus, it is a resource by the Nature Publishing Group.

4. Tweet and Ask Your Team Members to Tweet

Each post on X gives you a quarter of an Altmetric point. If your paper goes viral on X, your Altmetric score can be considerable. Plus, once journalists notice that it went viral, they will be more likely to cover the story, further increasing the score.

Try to choose the time of the post, the hashtags, and the images wisely. Since Elon Musk took over X and opened the algorithm it became very transparent and easy to optimize for. Here are the top 10 tips for boosting attention for a post on X. Make sure to include the DOI or the URL of the paper for Altmetric to find the post.

5. Experiment, Learn, Repeat

My highest Altmetric Attention Score core to date was around 1,500 for a paper in Nature Biotechnology published in 2019, where we used a novel method for designing small molecules called Generative Tensorial Reinforcement Learning (GENTRL) to generate new molecules with druglike properties that got synthesized and tested all the way into mice. In 2024, we went further and showed that an AI-generated molecule for an AI-discovered target was tested all the way up to Phase II human trials, but the paper published in Nature Biotechnology, let’s call it the TNIK paper , has achieved a score ofjust over 600 to date. So what has changed and what can we learn from these two papers?

The popularity of the paper depends on many factors. Ones which capture the public imagination or have widespread appeal are of course, much more likely to gain traction online. When we published the GENTRL paper in 2019, Generative AI was in its infancy, and there are pretty much no other companies that I heard of at the intersection of generative AI and drug discovery. We also published multiple articles in this field in the years leading to that paper and many key opinion leaders (KOLs) followed us. That following included a small army of generative AI skeptics who not only contributed to multiple rejections in peer-reviewed journals but also openly criticized this approach in social networks. This criticism also helped boost the Altmetric Score and bring more attention to the study. So first learning from this exercise - negative publicity helps overall publicity. As long as you are certain that your research results are honest - leave room for criticism and even help expose your paper’s weaknesses. Critics are your greatest Altmetric boosters. Since readers and, by extension journalists, react to negative news and drama stronger than to positive news, critical reviews will boost your Altmetric as long as the DOI or URL of the paper is properly referenced.

Secondly, papers coming out of popular labs in top-tier academic institutions and in top journals are likely to attract more attention. Often, the communications officers in these academic institutions work closely with the media to amplify notable research. Celebrity companies, for example, Google DeepMind, always get a higher level of coverage. For example, the AlphaFold paper published in July 2021 in Nature got an Altmetric Attention Score of over 3,500 . Even though I have not seen any drugs out of AlphaFold reaching preclinical candidate status, I predict the popularity of this tool will result in the first Nobel Prize in this area. Therefore, in order to become famous and popularize your research more effectively, it is a good idea to build up the public profile of yourself and your work. For example, Kardashians are famous for being famous .

Be careful with Wikipedia. I made a mistake explaining the importance of Wikipedia to students when lecturing on the future of generative AI, and one or two of them got banned for expanding the articles with paper references. Wikipedia requires that these are added by independent editors rather than the authors of papers themselves, but if some editors do not like it, they will not go deep or investigate - they will assume wrongdoing. So it is better to avoid even talking about Wikipedia. References there should happen naturally and often some of the more popular papers get picked up and referenced by veteran editors.

Experimenting with Altmetric will also help you explore new strategies for popularizing scientific research and develop new strategies for inspiring people to learn or even get into the new exciting field. UNESCO estimates that there was just over 8 million full-time equivalent (FTE) researchers in 2018 globally. Only a fraction of these are in biotechnology - less than 0.01% of the global population. If you motivate a million students to go into biotechnology by popularizing your research, you double this number.

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What the U.K.’s explosive Cass Review means for gender medicine in the U.S.

The report is a gauntlet thrown down to the biden administration and organizations supporting controversial treatments for children.

By Valerie Hudson

A 388-page bomb just dropped in the U.K., and reverberations will be felt around the world. The long-awaited final Cass Review — commissioned by the National Health Service on gender-related medical treatment — has just been published. Dr. Hilary Cass, the author of this independent review, is one of Britain’s preeminent pediatricians and formerly the president of the Royal College of Paediatrics and Child Health.

The Cass Review is painstaking in its detail and comprehensive in its scope. Its findings have already caused the U.K.’s Council for Psychotherapy to cease its advocacy for an uncritically affirming stance for those with gender dysphoria. In anticipation of the final report, last month the U.K. banned the NHS from providing puberty blockers, cross-sex hormones or surgery to minors. A law prohibiting private clinics from offering these practices is also in the works.

What does the Cass Review say?

Overall, it finds the evidence for the use of puberty blockers and cross-sex hormones as treatment for gender dysphoria to be quite weak.

With regard to puberty blockers, the review “found no evidence that puberty blockers improve body image or dysphoria, and very limited evidence for positive mental health outcomes, which without a control group could be due to placebo effect or concomitant psychological support.”

Additionally, the use of puberty blockers was not only associated with significant loss in bone density, but the review found evidence that “brain maturation may be temporarily or permanently disrupted by the use of puberty blockers, which could have a significant impact on the young person’s ability to make complex risk-laden decisions, as well as having possible longer-term neuropsychological consequences.”

The effects of puberty blockers may not, then, be reversible. In fact, the review notes, “given that the vast majority of young people started on puberty blockers proceed from puberty blockers to masculinising/ feminising hormones, there is no evidence that puberty blockers buy time to think, and some concern that they may change the trajectory of psychosexual and gender identity development.”

With regard to the use of cross-sex hormones, similar conclusions are reached: “There is a lack of high-quality research assessing the outcomes of hormone interventions in adolescents with gender dysphoria/incongruence, and few studies that undertake long-term follow up. No conclusions can be drawn about the effect on gender dysphoria, body satisfaction, psychosocial health, cognitive development, or fertility. Uncertainty remains about the outcomes for height/growth, cardiometabolic and bone health.”

Noting the lack of evidence as to benefits and harms, the author concludes that it is unethical to prescribe these medications to anyone under the age of 18, and possibly unethical to prescribe them to anyone younger than their mid-20s, when full executive reasoning has been achieved.

Proponents of gender-altering medical treatment have argued that treatment lowers the risk of suicide among gender dysphoric young people but Cass does not find this to be the case. The report says: “[I]t is well established that children and young people with gender dysphoria are at increased risk of suicide, but suicide risk appears to be comparable to other young people with a similar range of mental health and psychosocial challenges. Some clinicians feel under pressure to support a medical pathway based on widespread reporting that gender-affirming treatment reduces suicide risk. This conclusion was not supported by the systematic review. In summary, the evidence does not adequately support the claim that gender-affirming treatment reduces suicide risk.”

Given no real evidence of any improvement with use of puberty blockers and cross-sex hormones in gender dysphoric children, and given the clear gaps in the research literature, the review concludes that there can be no informed consent on the part of either parents or patients to this treatment. Without the possibility of informed consent, it is patently unethical for doctors to prescribe such treatments.

The Cass Review also weighs in on the issue of social transition, which has been a source of conflict between schools and parents in the U.K.

While U.K. schools are prepared to socially transition a child — and to do so without informing parents — the Cass Review asserts that social transition is consequential, especially for younger children. The review notes, “sex of rearing seems to have some influence on eventual gender outcome, and it is possible that social transition in childhood may change the trajectory of gender identity development for children with early gender incongruence. For this reason, a more cautious approach needs to be taken for children than for adolescents.” For this reason, the U.K. government has recently issued guidance to stop schools from socially transitioning children.

The concept of “conversion therapy” also needs to be rethought, according to the Cass Review. Given the significantly higher rate of mental health comorbidities of gender dysphoric children compared to controls, it is important that mental health professionals be allowed to investigate whether a child’s gender dysphoria may be relieved through psychological interventions. Proposed bans on “conversion therapy” might stifle such needed therapy.

Furthermore, the review insists that detransitioning support also be provided by the NHS since, according to Cass, the number of detransitioners appears to be increasing.

All in all, the Cass Review is an important achievement. It will be the foundation for an almost 180-degree turn in how the National Health Service treats gender dysphoric children. It is also a massive repudiation of the care guidelines put forward by WPATH, the World Professional Association of Transgender Healthcare. The guidelines have been unjustifiably influential given their “lack [of] developmental rigour,” as the review politely puts it.

But the report represents more, at least to Americans. It is a gauntlet thrown down to U.S. professional organizations, such as the American Medical Association, the American Academy of Pediatrics and the American Psychological Association, all of which have uncritically adopted the clearly unethical WPATH approach. It is also a gauntlet thrown down to the Biden administration, which has followed suit.

With the publication of the Cass Review, American institutions must rethink their approach to the treatment of gender dysphoric children. That approach is now clearly seen to be wrong, and can no longer be ethically justified.

I’m planning on mailing a copy of the review to the U.S. Department of Health and Human Services, care of Dr. Rachel Levine.

Valerie M. Hudson is a university distinguished professor at the Bush School of Government and Public Service at Texas A&M University and a Deseret News contributor. Her views are her own.

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Six Things to Know About ‘Forever Chemicals’

The federal government is ordering the removal of PFAS, a class of chemicals that poses serious health risks, from drinking water systems across the country.

By Lisa Friedman

Almost half the tap water in the United States contains PFAS, a class of chemicals linked to serious health problems. On Wednesday, the Environmental Protection Agency announced that, for the first time, municipal utilities will have to detect and remove PFAS from drinking water.

Here’s what you need to know.

What are PFAS?

In 1938 a young chemist working on refrigerants for Dupont accidentally discovered a new compound that was remarkably resistant to water and grease, a finding that would lead to the creation of the Teflon brand of nonstick cookware.

Today there are nearly 15,000 per- and polyfluoroalkyl substances, which collectively go by the acronym PFAS, according to a database maintained by the E.P.A.

The common link is that they have a special bond of carbon and fluorine atoms, making them incredibly strong and resistant to heat, water, oil and dirt. For that reason, PFAS is used for everyday items as varied as microwave popcorn bags, water-repellent clothing and stain-resistant carpets. PFAS are also in firefighting foam, cosmetics, shampoos, toys and even dental floss.

Where are PFAS?

Everywhere, including drinking water. The indestructible nature that makes PFAS useful in some products also makes them harmful to human health. The chemicals are virtually indestructible and do not fully degrade, accumulating in the environment and the human body.

The chemicals are so ubiquitous that they can be found in the blood of almost every person in the country. One recent government study detected PFAS chemicals in nearly half of the nation’s tap water . A global study of more than 45,000 water samples around the world found that about 31 percent of tested groundwater samples that weren’t near any obvious source of contamination had PFAS levels considered harmful to human health.

What does PFAS do to the body?

According to the E.P.A., exposure to PFAS can cause damage to the liver and immune system and also has been linked to low birth weight, birth defects and developmental delays as well as increased risk of some prostate, kidney and testicular cancers. New research published in the past year found links between PFAS exposure and a delay in the onset of puberty in girls, leading to a higher incidence of breast cancer, renal disease and thyroid disease; a decrease in bone density in teenagers, potentially leading to osteoporosis; and an increased risk of Type 2 diabetes in women.

Why didn’t the E.P.A. regulate PFAS in water sooner?

Many environmental advocates argue that PFAS contamination should have been dealt with long ago.

“For generations, PFAS chemicals slid off every federal environmental law like a fried egg off a Teflon pan,” said Ken Cook, president and co-founder of the Environmental Working Group, a nonprofit advocacy group.

Activists blame chemical companies, which for decades hid evidence of the dangers of PFAS, according to lawsuits and a peer-reviewed study , published in the Annals of Global Health, of previously secret industry documents.

The new E.P.A. rule requires utilities to reduce PFAS in drinking water to near-zero levels.

How can I get rid of PFAS?

Not easily. In homes, filters attached to faucets or in pitchers generally do not remove PFAS substances. Under-sink reverse-osmosis systems have been shown to remove most but not all PFAS in studies performed by scientists at Duke University and North Carolina State University.

Municipal water systems can install one of several technologies including carbon filtration or a reverse-osmosis water filtration system that can reduce levels of the chemicals.

Now that limits have been set, when will PFAS disappear from tap water?

It could take years. Under the rule, a water system has three years to monitor and report its PFAS levels. Then, if the levels exceed the E.P.A.’s new standard, the utility will have another two years to purchase and install filtration technology.

But trade groups and local governments are expected to mount legal challenges against the regulation, potentially delaying it even before a court makes a final ruling. And if former President Donald J. Trump were to retake the White House in November, his administration could also reverse or weaken the rule.

An earlier version of this article described incorrectly the molecular structure of PFAS compounds. They have carbon and fluorine atoms, not carbon and fluoride.

How we handle corrections

Lisa Friedman is a Times reporter who writes about how governments are addressing climate change and the effects of those policies on communities. More about Lisa Friedman

The Proliferation of ‘Forever Chemicals’

Pfas, or per- and polyfluoroalkyl substances, are hazardous compounds that pose a global threat to human health..

For the first time, the U.S. government is requiring municipal water systems to detect and remove PFAS from drinking water .

A global study found harmful levels of PFAS  in water samples taken far from any obvious source of contamination.

Virtually indestructible, PFAS are used in fast-food packaging and countless household items .

PFAS lurk in much of what we eat, drink and use, but scientists are only beginning to understand how they affect our health .

Though no one can avoid forever chemicals entirely, Wirecutter offers tips on how to limit your exposure .

Scientists have spent years searching for ways to destroy forever chemicals. In 2022, a team of chemists found a cheap, effective method to break them down .

Biostatistics Graduate Program

Yeji ko is first author of annals of epidemiology paper.

Posted by duthip1 on Thursday, April 18, 2024 in News .

Congratulations to PhD student Yeji Ko on the publication of Adjustment for duration of employment in occupational epidemiology in the June 2024 issue of Annals of Epidemiology  (appearing online ahead of print this week). Professor Ben French , who was r ecently elected to the National Council for Radiation Protection and Measurements , is the paper’s corresponding author. Ko, French, and colleagues at Oak Ridge Associated Universities examined the healthy worker survivor effect in relation to radiation risk among nuclear workers, using simulation studies to arrive at reliable results and conclude that “it is crucial to flexibly adjust for duration of employment to account for confounding arising from the healthy worker survivor effect in occupational epidemiology.” The work was made possible by the Oak Ridge Associated Universities (ORAU) Directed Research and Development Grant, which promotes collaborations between universities and ORAU scientists for foundational research efforts.

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Methodology

Research Methods | Definitions, Types, Examples

Research methods are specific procedures for collecting and analyzing data. Developing your research methods is an integral part of your research design . When planning your methods, there are two key decisions you will make.

First, decide how you will collect data . Your methods depend on what type of data you need to answer your research question :

• Qualitative vs. quantitative : Will your data take the form of words or numbers?
• Primary vs. secondary : Will you collect original data yourself, or will you use data that has already been collected by someone else?
• Descriptive vs. experimental : Will you take measurements of something as it is, or will you perform an experiment?

Second, decide how you will analyze the data .

• For quantitative data, you can use statistical analysis methods to test relationships between variables.
• For qualitative data, you can use methods such as thematic analysis to interpret patterns and meanings in the data.

Table of contents

Methods for collecting data, examples of data collection methods, methods for analyzing data, examples of data analysis methods, other interesting articles, frequently asked questions about research methods.

Data is the information that you collect for the purposes of answering your research question . The type of data you need depends on the aims of your research.

Qualitative vs. quantitative data

Your choice of qualitative or quantitative data collection depends on the type of knowledge you want to develop.

For questions about ideas, experiences and meanings, or to study something that can’t be described numerically, collect qualitative data .

If you want to develop a more mechanistic understanding of a topic, or your research involves hypothesis testing , collect quantitative data .

You can also take a mixed methods approach , where you use both qualitative and quantitative research methods.

Primary vs. secondary research

Primary research is any original data that you collect yourself for the purposes of answering your research question (e.g. through surveys , observations and experiments ). Secondary research is data that has already been collected by other researchers (e.g. in a government census or previous scientific studies).

If you are exploring a novel research question, you’ll probably need to collect primary data . But if you want to synthesize existing knowledge, analyze historical trends, or identify patterns on a large scale, secondary data might be a better choice.

Descriptive vs. experimental data

In descriptive research , you collect data about your study subject without intervening. The validity of your research will depend on your sampling method .

In experimental research , you systematically intervene in a process and measure the outcome. The validity of your research will depend on your experimental design .

To conduct an experiment, you need to be able to vary your independent variable , precisely measure your dependent variable, and control for confounding variables . If it’s practically and ethically possible, this method is the best choice for answering questions about cause and effect.

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Your data analysis methods will depend on the type of data you collect and how you prepare it for analysis.

Data can often be analyzed both quantitatively and qualitatively. For example, survey responses could be analyzed qualitatively by studying the meanings of responses or quantitatively by studying the frequencies of responses.

Qualitative analysis methods

Qualitative analysis is used to understand words, ideas, and experiences. You can use it to interpret data that was collected:

• From open-ended surveys and interviews , literature reviews , case studies , ethnographies , and other sources that use text rather than numbers.
• Using non-probability sampling methods .

Qualitative analysis tends to be quite flexible and relies on the researcher’s judgement, so you have to reflect carefully on your choices and assumptions and be careful to avoid research bias .

Quantitative analysis methods

Quantitative analysis uses numbers and statistics to understand frequencies, averages and correlations (in descriptive studies) or cause-and-effect relationships (in experiments).

You can use quantitative analysis to interpret data that was collected either:

• During an experiment .
• Using probability sampling methods .

Because the data is collected and analyzed in a statistically valid way, the results of quantitative analysis can be easily standardized and shared among researchers.

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If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.

• Chi square test of independence
• Statistical power
• Descriptive statistics
• Degrees of freedom
• Pearson correlation
• Null hypothesis
• Double-blind study
• Case-control study
• Research ethics
• Data collection
• Hypothesis testing
• Structured interviews

Research bias

• Hawthorne effect
• Unconscious bias
• Recall bias
• Halo effect
• Self-serving bias
• Information bias

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

Quantitative methods allow you to systematically measure variables and test hypotheses . Qualitative methods allow you to explore concepts and experiences in more detail.

In mixed methods research , you use both qualitative and quantitative data collection and analysis methods to answer your research question .

A sample is a subset of individuals from a larger population . Sampling means selecting the group that you will actually collect data from in your research. For example, if you are researching the opinions of students in your university, you could survey a sample of 100 students.

In statistics, sampling allows you to test a hypothesis about the characteristics of a population.

The research methods you use depend on the type of data you need to answer your research question .

• If you want to measure something or test a hypothesis , use quantitative methods . If you want to explore ideas, thoughts and meanings, use qualitative methods .
• If you want to analyze a large amount of readily-available data, use secondary data. If you want data specific to your purposes with control over how it is generated, collect primary data.
• If you want to establish cause-and-effect relationships between variables , use experimental methods. If you want to understand the characteristics of a research subject, use descriptive methods.

Methodology refers to the overarching strategy and rationale of your research project . It involves studying the methods used in your field and the theories or principles behind them, in order to develop an approach that matches your objectives.

Methods are the specific tools and procedures you use to collect and analyze data (for example, experiments, surveys , and statistical tests ).

In shorter scientific papers, where the aim is to report the findings of a specific study, you might simply describe what you did in a methods section .

In a longer or more complex research project, such as a thesis or dissertation , you will probably include a methodology section , where you explain your approach to answering the research questions and cite relevant sources to support your choice of methods.

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This paper is in the following e-collection/theme issue:

Published on 17.4.2024 in Vol 26 (2024)

Digital Interventions for Recreational Cannabis Use Among Young Adults: Systematic Review, Meta-Analysis, and Behavior Change Technique Analysis of Randomized Controlled Studies

Authors of this article:

• José Côté 1, 2, 3 , RN, PhD   ; 
• Gabrielle Chicoine 3, 4 , RN, PhD   ; 
• Billy Vinette 1, 3 , RN, MSN   ; 
• Patricia Auger 2, 3 , MSc   ; 
• Geneviève Rouleau 3, 5, 6 , RN, PhD   ; 
• Guillaume Fontaine 7, 8, 9 , RN, PhD   ; 
• Didier Jutras-Aswad 2, 10 , MSc, MD  

1 Faculty of Nursing, Université de Montréal, Montreal, QC, Canada

2 Research Centre of the Centre Hospitalier de l’Université de Montréal, Montreal, QC, Canada

3 Research Chair in Innovative Nursing Practices, Montreal, QC, Canada

4 Knowledge Translation Program, Li Ka Shing Knowledge Institute, St. Michael’s Hospital, Toronto, ON, Canada

5 Department of Nursing, Université du Québec en Outaouais, Saint-Jérôme, QC, Canada

6 Women's College Hospital Institute for Health System Solutions and Virtual Care, Women's College Hospital, Toronto, ON, Canada

7 Ingram School of Nursing, Faculty of Medicine and Health Sciences, McGill University, Montreal, QC, Canada

8 Centre for Clinical Epidemiology, Lady Davis Institute for Medical Research, Sir Mortimer B. Davis Jewish General Hospital, Montreal, QC, Canada

9 Kirby Institute, University of New South Wales, Sydney, Australia

10 Department of Psychiatry and Addictology, Faculty of Medicine, Université de Montréal, Montreal, QC, Canada

Corresponding Author:

José Côté, RN, PhD

Research Centre of the Centre Hospitalier de l’Université de Montréal

850 Saint-Denis

Montreal, QC, H2X 0A9

Phone: 1 514 890 8000

Email: [email protected]

Background: The high prevalence of cannabis use among young adults poses substantial global health concerns due to the associated acute and long-term health and psychosocial risks. Digital modalities, including websites, digital platforms, and mobile apps, have emerged as promising tools to enhance the accessibility and availability of evidence-based interventions for young adults for cannabis use. However, existing reviews do not consider young adults specifically, combine cannabis-related outcomes with those of many other substances in their meta-analytical results, and do not solely target interventions for cannabis use.

Objective: We aimed to evaluate the effectiveness and active ingredients of digital interventions designed specifically for cannabis use among young adults living in the community.

Methods: We conducted a systematic search of 7 databases for empirical studies published between database inception and February 13, 2023, assessing the following outcomes: cannabis use (frequency, quantity, or both) and cannabis-related negative consequences. The reference lists of included studies were consulted, and forward citation searching was also conducted. We included randomized studies assessing web- or mobile-based interventions that included a comparator or control group. Studies were excluded if they targeted other substance use (eg, alcohol), did not report cannabis use separately as an outcome, did not include young adults (aged 16-35 y), had unpublished data, were delivered via teleconference through mobile phones and computers or in a hospital-based setting, or involved people with mental health disorders or substance use disorders or dependence. Data were independently extracted by 2 reviewers using a pilot-tested extraction form. Authors were contacted to clarify study details and obtain additional data. The characteristics of the included studies, study participants, digital interventions, and their comparators were summarized. Meta-analysis results were combined using a random-effects model and pooled as standardized mean differences.

Results: Of 6606 unique records, 19 (0.29%) were included (n=6710 participants). Half (9/19, 47%) of these articles reported an intervention effect on cannabis use frequency. The digital interventions included in the review were mostly web-based. A total of 184 behavior change techniques were identified across the interventions (range 5-19), and feedback on behavior was the most frequently used (17/19, 89%). Digital interventions for young adults reduced cannabis use frequency at the 3-month follow-up compared to control conditions (including passive and active controls) by −6.79 days of use in the previous month (95% CI −9.59 to −4.00; P <.001).

Conclusions: Our results indicate the potential of digital interventions to reduce cannabis use in young adults but raise important questions about what optimal exposure dose could be more effective, both in terms of intervention duration and frequency. Further high-quality research is still needed to investigate the effects of digital interventions on cannabis use among young adults.

Trial Registration: PROSPERO CRD42020196959; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=196959

Introduction

Cannabis use among young adults is recognized as a public health concern.

Young adulthood (typically the ages of 18-30 y) is a critical developmental stage characterized by a peak prevalence of substance use [ 1 , 2 ]. Worldwide, cannabis is a substance frequently used for nonmedical purposes due in part to its high availability in some regions and enhanced product variety and potency [ 3 , 4 ]. The prevalence of cannabis use (CU) among young adults is high [ 5 , 6 ], and its rates have risen in recent decades [ 7 ]. In North America and Oceania, the estimated past-year prevalence of CU is ≥25% among young adults [ 8 , 9 ].

While the vast majority of cannabis users do not experience severe problems from their use [ 4 ], the high prevalence of CU among young adults poses substantial global health concerns due to the associated acute and long-term health and psychosocial risks [ 10 , 11 ]. These include impairment of cognitive function, memory, and psychomotor skills during acute intoxication; increased engagement in behaviors with a potential for injury and fatality (eg, driving under the influence); socioeconomic problems; and diminished social functioning [ 4 , 12 - 14 ]. Importantly, an extensive body of literature reveals that subgroups engaging in higher-risk use, such as intensive or repeated use, are more prone to severe and chronic consequences, including physical ailments (eg, respiratory illness and reproductive dysfunction), mental health disorders (eg, psychosis, depression, and suicidal ideation or attempts), and the potential development of CU disorder [ 4 , 15 - 17 ].

Interventions to Reduce Public Health Impact of Young Adult CU

Given the increased prevalence of lifetime and daily CU among young adults and the potential negative impact of higher-risk CU, various prevention and intervention programs have been implemented to help users reduce or cease their CU. These programs primarily target young adults regardless of their CU status [ 2 , 18 ]. In this context, many health care organizations and international expert panels have developed evidence-based lower-risk CU guidelines to promote safer CU and intervention options to help reduce risks of adverse health outcomes from nonmedical CU [ 4 , 16 , 17 , 19 ]. Lower-risk guidance-oriented interventions for CU are based on concepts of health promotion [ 20 - 22 ] and health behavior change [ 23 - 26 ] and on other similar harm reduction interventions implemented in other areas of population health (eg, lower-risk drinking guidelines, supervised consumption sites and services, and sexual health) [ 27 , 28 ]. These interventions primarily aim to raise awareness of negative mental, physical, and social cannabis-related consequences to modify individual-level behavior-related risk factors.

Meta-analyses have shown that face-to-face prevention and treatment interventions are generally effective in reducing CU in young adults [ 18 , 29 - 32 ]. However, as the proportion of professional help seeking for CU concerns among young adults remains low (approximately 15%) [ 33 , 34 ], alternative strategies that consider the limited capacities and access-related barriers of traditional face-to-face prevention and treatment facilities are needed. Digital interventions, including websites, digital platforms, and mobile apps, have emerged as promising tools to enhance the accessibility and availability of evidence-based programs for young adult cannabis users. These interventions address barriers such as long-distance travel, concerns about confidentiality, stigma associated with seeking treatment, and the cost of traditional treatments [ 35 - 37 ]. By overcoming these barriers, digital interventions have the potential to have a stronger public health impact [ 18 , 38 ].

State of Knowledge of Digital Interventions for CU and Young Adults

The literature regarding digital interventions for substance use has grown rapidly in the past decade, as evidenced by several systematic reviews and meta-analyses of randomized controlled trial (RCT) studies on the efficacy or effectiveness of these interventions in preventing or reducing harmful substance use [ 2 , 39 - 41 ]. However, these reviews do not focus on young adults specifically. In addition, they combine CU-related outcomes with those of many other substances in their meta-analytical results. Finally, they do not target CU interventions exclusively.

In total, 4 systematic reviews and meta-analyses of digital interventions for CU among young people have reported mixed results [ 42 - 45 ]. In their systematic review (10 studies of 5 prevention and 5 treatment interventions up to 2012), Tait et al [ 44 ] concluded that digital interventions effectively reduced CU among adolescents and adults at the posttreatment time point. Olmos et al [ 43 ] reached a similar conclusion in their meta-analysis of 9 RCT studies (2 prevention and 7 treatment interventions). In their review, Hoch et al [ 42 ] reported evidence of small effects at the 3-month follow-up based on 4 RCTs of brief motivational interventions and cognitive behavioral therapy (CBT) delivered on the web. In another systematic review and meta-analysis, Beneria et al [ 45 ] found that web-based CU interventions did not significantly reduce consumption. However, these authors indicated that the programs tested varied significantly across the studies considered and that statistical heterogeneity was attributable to the inclusion of studies of programs targeting more than one substance (eg, alcohol and cannabis) and both adolescents and young adults. Beneria et al [ 45 ] recommend that future work “establish the effectiveness of the newer generation of interventions as well as the key ingredients” of effective digital interventions addressing CU by young people. This is of particular importance because behavior change interventions tend to be complex as they consist of multiple interactive components [ 46 ].

Behavior change interventions refer to “coordinated sets of activities designed to change specified behavior patterns” [ 47 ]. Their interacting active ingredients can be conceptualized as behavior change techniques (BCTs) [ 48 ]. BCTs are specific and irreducible. Each BCT has its own individual label and definition, which can be used when designing and reporting complex interventions and as a nomenclature system when coding interventions for their content [ 47 ]. The Behavior Change Technique Taxonomy version 1 (BCTTv1) [ 48 , 49 ] was developed to provide a shared, standardized terminology for characterizing complex behavior change interventions and their active ingredients. Several systematic reviews with meta-regressions that used the BCTTv1 have found interventions with certain BCTs to be more effective than those without [ 50 - 53 ]. A better understanding of the BCTs used in digital interventions for young adult cannabis users would help not only to establish the key ingredients of such interventions but also develop and evaluate effective interventions.

In the absence of any systematic review of the effectiveness and active ingredients of digital interventions designed specifically for CU among community-living young adults, we set out to achieve the following:

• conduct a comprehensive review of digital interventions for preventing, reducing, or ceasing CU among community-living young adults,
• describe the active ingredients (ie, BCTs) in these interventions from the perspective of behavior change science, and
• analyze the effectiveness of these interventions on CU outcomes.

Protocol Registration

We followed the Cochrane Handbook for Systematic Reviews of Interventions [ 54 ] in designing this systematic review and meta-analysis and the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2020 guidelines in reporting our findings (see Multimedia Appendix 1 [ 55 ] for the complete PRISMA checklist). This review was registered in PROSPERO (CRD42020196959).

Search Strategy

The search strategy was designed by a health information specialist together with the research team and peer reviewed by another senior information specialist before execution using Peer Review of Electronic Search Strategies for systematic reviews [ 56 ]. The search strategy revolved around three concepts:

• CU (eg, “cannabis,” “marijuana,” and “hashish”)
• Digital interventions (eg, “telehealth,” “website,” “mobile applications,” and “computer”)
• Young adults (eg, “emerging adults” and “students”)

The strategy was initially implemented on March 18, 2020, and again on October 13, 2021, and February 13, 2023. The full, detailed search strategies for each database are presented in Multimedia Appendix 2 .

Information Sources

We searched 7 electronic databases of published literature: CINAHL Complete, Cochrane Database of Systematic Reviews, Cochrane Central Register of Controlled Trials, Embase, MEDLINE, PubMed, and PsycINFO. No publication date filters or language restrictions were applied. A combination of free-text keywords and Medical Subject Headings was tailored to the conventions of each database for optimal electronic searching. The research team also manually screened the reference lists of the included articles and the bibliographies of existing systematic reviews [ 18 , 31 , 42 - 45 ] to identify additional relevant studies (snowballing). Finally, a forward citation tracking procedure (ie, searching for articles that cited the included studies) was carried out in Google Scholar.

Inclusion Criteria

The population, intervention, comparison, outcome, and study design process is presented in Multimedia Appendix 3 . The inclusion criteria were as follows: (1) original research articles published in peer-reviewed journals; (2) use of an experimental study design (eg, RCT, cluster RCT, or pilot RCT); (3) studies evaluating the effectiveness (or efficacy) of digital interventions designed specifically to prevent, reduce, or cease CU as well as promote CU self-management or address cannabis-related harm and having CU as an outcome measure; (4) studies targeting young adults, including active and nonactive cannabis users; (5) cannabis users and nonusers not under substance use treatment used as controls in comparator, waitlist, or delayed-treatment groups offered another type of intervention (eg, pharmacotherapy or psychosocial) different from the one being investigated or participants assessed only for CU; and (6) quantitative CU outcomes (frequency and quantity) or cannabis abstinence. Given the availability of numerous CU screening and assessment tools with adequate psychometric properties and the absence of a gold standard in this regard [ 57 ], any instrument capturing aspects of CU was considered. CU outcome measures could be subjective (eg, self-reported number of CU days or joints in the previous 3 months) or objective (eg, drug screening test). CU had to be measured before the intervention (baseline) and at least once after.

Digital CU interventions were defined as web- or mobile-based interventions that included one or more activities (eg, self-directed or interactive psychoeducation or therapy, personalized feedback, peer-to-peer contact, and patient-to-expert communication) aimed at changing CU [ 58 ]. Mobile-based interventions were defined as interventions delivered via mobile phone through SMS text message, multimedia messaging service (ie, SMS text messages that include　multimedia content, such as pictures, videos, or emojis), or mobile apps, whereas web-based interventions (eg, websites and digital platforms) were defined as interventions designed to be accessed on the web (ie, the internet), mainly via computers. Interventions could include self-directed and web-based interventions with human support. We defined young adults as aged 16 to 35 years and included students and nonstudents. While young adulthood is typically defined as covering the ages of 18 to 30 years [ 59 ], we broadened the range given that the age of majority and legal age to purchase cannabis differs across countries and jurisdictions. This was also in line with the age range targeted by several digital CU interventions (college or university students or emerging adults aged 15-24 years) [ 31 , 45 ]. Given the language expertise of the research team members and the available resources, only English- and French-language articles were retained.

Exclusion Criteria

Knowledge synthesis articles, study protocols, and discussion papers or editorials were excluded, as were articles with cross-sectional, cohort, case study or report, pretest-posttest, quasi-experimental, or qualitative designs. Mixed methods designs were included only if the quantitative component was an RCT. We excluded studies if (1) use of substances other than cannabis (eg, alcohol, opioids, or stimulants) was the focus of the digital intervention (though studies that included polysubstance users were retained if CU was assessed and reported separately); (2) CU was not reported separately as an outcome or only attitudes or beliefs regarding, knowledge of, intention to reduce, or readiness or motivation to change CU was measured; and (3) the data reported were unpublished (eg, conferences and dissertations). Studies of traditional face-to-face therapy delivered via teleconference on mobile phones and computers or in a hospital-based setting and informational campaigns (eg, web-based poster presentations or pamphlets) were excluded as well. Studies with samples with a maximum age of <15 years and a minimum age of >35 years were also excluded. Finally, we excluded studies that focused exclusively on people with a mental health disorder or substance use disorder or dependence or on adolescents owing to the particular health care needs of these populations, which may differ from those of young adults [ 1 ].

Data Collection

Selection of studies.

Duplicates were removed from the literature search results in EndNote (version X9.3.3; Clarivate Analytics) using the Bramer method for deduplication of database search results for systematic reviews [ 60 ]. The remaining records were uploaded to Covidence (Veritas Health Innovation), a web-based systematic review management system. A reviewer guide was developed that included screening questions and a detailed description of each inclusion and exclusion criterion based on PICO (population, intervention, comparator, and outcome), and a calibration exercise was performed before each stage of the selection process to maximize consistency between reviewers. Titles and abstracts of studies flagged for possible inclusion were screened first by 2 independent reviewers (GC, BV, PA, and GR; 2 per article) against the eligibility criteria (stage 1). Articles deemed eligible for full-text review were then retrieved and screened for inclusion (stage 2). Full texts were assessed in detail against the eligibility criteria again by 2 reviewers independently. Disagreements between reviewers were resolved through consensus or by consulting a third reviewer.

Data Extraction Process

In total, 2 reviewers (GC, BV, PA, GR, and GF; 2 per article) independently extracted relevant data (or informal evidence) using a data extraction form developed specifically for this review and integrated into Covidence. The form was pilot-tested on 2 randomly selected studies and refined accordingly. Data pertaining to the following domains were extracted from the included studies: (1) Study characteristics included information on the first and corresponding authors, publication year, country of origin, aims and hypotheses, study period, design (including details on randomization and blinding), follow-up times, data collection methods, and types of statistical analysis. (2) Participant characteristics included study target population, participant inclusion and exclusion criteria, sex or gender, mean age, and sample sizes at each data collection time point. (3) Intervention characteristics, for which the research team developed a matrix inspired by the template for intervention description and replication 12-item checklist [ 61 ] to extract informal evidence (ie, intervention descriptions) from the included studies under the headings name of intervention, purpose, underpinning theory of design elements, treatment approach, type of technology (ie, web or mobile) and software used, delivery format (ie, self-directed, human involvement, or both), provider characteristics (if applicable), intervention duration (ie, length of treatment and number of sessions or modules), material and procedures (ie, tools or activities offered, resources provided, and psychoeducational content), tailoring, and unplanned modifications. (4) Comparator characteristics were details of the control or comparison group or groups, including nature (passive vs active), number of groups or clusters (if applicable), type and length of the intervention (if applicable), and number of participants at each data collection time point. (5) Outcome variables, including the primary outcome variable examined in this systematic review, that is, the mean difference in CU frequency before and after the intervention and between the experimental and control or comparison groups. When possible, we examined continuous variables, including CU frequency means and SDs at the baseline and follow-up time points, and standardized regression coefficients (ie, β coefficients and associated 95% CIs). The secondary outcomes examined included other CU outcome variables (eg, quantity of cannabis used and abstinence) and cannabis-related negative consequences (or problems). Details on outcome variables (ie, definition, data time points, and missing data) and measurements (ie, instruments, measurement units, and scales) were also extracted.

In addition, data on user engagement and use of the digital intervention and study attrition rates (ie, dropouts and loss to follow-up) were extracted. When articles had missing data, we contacted the corresponding authors via email (2 attempts were made over a 2-month period) to obtain missing information. Disagreements over the extracted data were limited and resolved through discussion.

Data Synthesis Methods

Descriptive synthesis.

The characteristics of the included studies, study participants, interventions, and comparators were summarized in narrative and table formats. The template for intervention description and replication 12-item checklist [ 61 ] was used to summarize and organize intervention characteristics and assess to what extent the interventions were appropriately described in the included articles. As not all studies had usable data for meta-analysis purposes and because of heterogeneity, we summarized the main findings (ie, intervention effects) of the included studies in narrative and table formats for each outcome of interest in this review.

The BCTs used in the digital interventions were identified from the descriptions of the interventions (ie, experimental groups) provided in the articles as well as any supplementary material and previously published research protocols. A BCT was defined as “an observable, replicable, and irreducible component of an intervention designed to alter or redirect causal processes that regulate behavior” [ 48 ]. The target behavior in this review was the cessation or reduction of CU by young adults. BCTs were identified and coded using the BCTTv1 [ 48 , 49 ], a taxonomy of 93 BCTs organized into 16 hierarchical thematic clusters or categories. Applying the BCTTv1 in a systematic review allows for the comparison and synthesis of evidence across studies in a structured manner. This analysis allows for the identification of the explicit mechanisms underlying the reported behavior change induced by interventions, successful or not, and, thus, avoids making implicit assumptions about what works [ 62 ].

BCT coding was performed by 2 reviewers independently—BV coded all studies, and GC and GF coded a subset of the studies. All reviewers completed web-based training on the BCTTv1, and GF is an experienced implementation scientist who had used the BCTTv1 in prior work [ 63 - 65 ]. The descriptions of the interventions in the articles were read line by line and analyzed for the clear presence of BCTs using the guidelines developed by Michie et al [ 48 ]. For each article, the BCTs identified were documented and categorized using supporting textual evidence. They were coded only once per article regardless of how many times they came up in the text. Disagreements about including a BCT were resolved through discussion. If there was uncertainty about whether a BCT was present, it was coded as absent. Excel (Microsoft Corp) was used to compare the reviewers’ independent BCT coding and generate an overall descriptive synthesis of the BCTs identified. The BCTs were summarized by study and BCT cluster.

Statistical Analysis

Meta-analyses were conducted to estimate the size of the effect of the digital interventions for young adult CU on outcomes of interest at the posttreatment and follow-up assessments compared with control or alternative intervention conditions. The outcome variables considered were (1) CU frequency and other CU outcome variables (eg, quantity of cannabis used and abstinence) at baseline and the posttreatment time point or follow-up measured using standardized instruments of self-reported CU (eg, the timeline followback [TLFB] method) [ 66 ] and (2) cannabis-related negative consequences measured using standardized instruments (eg, the Marijuana Problems Scale) [ 67 ].

Under our systematic review protocol, ≥2 studies were needed for a meta-analysis. On the basis of previous systematic reviews and meta-analyses in the field of digital CU interventions [ 31 , 42 - 45 ], we expected between-study heterogeneity regarding outcome assessment. To minimize heterogeneity, we chose to pool studies with similar outcomes of interest based on four criteria: (1) definition of outcome (eg, CU frequency, quantity consumed, and abstinence), (2) type of outcome variable (eg, days of CU in the previous 90 days, days high per week in the previous 30 days, and number of CU events in the previous month) and measure (ie, instruments or scales), (3) use of validated instruments, and (4) posttreatment or follow-up time points (eg, 2 weeks or 1 month after the baseline or 3, 6, and 12 months after the baseline).

Only articles that reported sufficient statistics to compute a valid effect size with 95% CIs were included in the meta-analyses. In the case of articles that were not independent (ie, more than one published article reporting data from the same clinical trial), only 1 was included, and it was represented only once in the meta-analysis for a given outcome variable regardless of whether the data used to compute the effect size were extracted from the original paper or a secondary analysis paper. We made sure that the independence of the studies included in the meta-analysis of each outcome was respected. In the case of studies that had more than one comparator, we used the effect size for each comparison between the intervention and control groups.

Meta-analyses were conducted only for mean differences based on the change from baseline in CU frequency at 3 months after the baseline as measured using the number of self-reported days of use in the previous month. As the true value of the estimated effect size for outcome variables might vary across different trials and samples, we used a random-effects model given that the studies retained did not have identical target populations. The random-effects model incorporates between-study variation in the study weights and estimated effect size [ 68 ]. In addition, statistical heterogeneity across studies was assessed using I 2 , which measures the proportion of heterogeneity to the total observed dispersion; 25% was considered low, 50% was considered moderate, and 75% was considered high [ 69 ]. Because only 3 studies were included in the meta-analysis [ 70 - 72 ], publication bias could not be assessed. All analyses were completed using Stata (version 18; StataCorp) [ 73 ].

Risk-of-Bias Assessment

The risk of bias (RoB) of the included RCTs was assessed using the Cochrane RoB 2 tool at the outcome level [ 74 ]. Each distinct risk domain (ie, randomization process, deviations from the intended intervention, missing outcome data, measurement of the outcome, and selection of the reported results) was assessed as “low,” “some concerns,” or “high” based on the RoB 2 criteria. In total, 2 reviewers (GC and BV) conducted the assessments independently. Disagreements were discussed, and if not resolved consensually by the 2, the matter was left for a third reviewer (GF) to settle. The assessments were summarized by risk domain and outcome and converted into figures using the RoB visualization tool robvis [ 75 ].

Search Results

The database search generated a total of 13,232 citations, of which 7822 (59.11%) were from the initial search on March 18, 2020, and 2805 (21.2%) and 2605 (19.69%) were from the updates on October 13, 2021, and February 13, 2023, respectively. Figure 1 presents the PRISMA study flow diagram [ 76 ]. Of the 6606 unique records, 6484 (98.15%) were excluded based on title and abstract screening. Full texts of the remaining 1.85% (122/6606) of the records were examined, as were those of 25 more reports found through hand searching. Of these 147 records, 128 (87.1%) were excluded after 3 rounds of full-text screening. Of these 128 records, 39 (30.5%) were excluded for not being empirical research articles (eg, research protocols). Another 28.1% (36/128) were excluded for not meeting our definition of digital CU intervention. The remaining records were excluded for reasons that occurred with a frequency of ≤14%, including young adults not being the target population and the study not meeting our study design criteria (ie, RCT, cluster RCT, or pilot RCT). Excluded studies and reasons for exclusion are listed in Multimedia Appendix 4 . Finally, 19 articles detailing the results of 19 original studies were included.

Description of Studies

Study characteristics.

Multimedia Appendix 5 [ 70 - 72 , 77 - 92 ] describes the general characteristics of the 19 included studies. The studies were published between 2010 and 2023, with 58% (11/19) published in 2018 or later. A total of 53% (10/19) of the studies were conducted in the United States [ 77 - 86 ], 11% (2/19) were conducted in Canada [ 87 , 88 ], 11% (2/19) were conducted in Australia [ 71 , 89 ], 11% (2/19) were conducted in Germany [ 72 , 90 ], 11% (2/19) were conducted in Switzerland [ 70 , 91 ], and 5% (1/19) were conducted in Sweden [ 92 ]. A total of 79% (15/19) were RCTs [ 70 - 72 , 77 , 79 , 81 - 83 , 86 - 92 ], and 21% (4/19) were pilot RCTs [ 78 , 80 , 84 , 85 ].

Participant Characteristics

The studies enrolled a total of 6710 participants—3229 (48.1%) in the experimental groups, 3358 (50%) in the control groups, and the remaining 123 (1.8%) from 1 study [ 82 ] where participant allocation to the intervention condition was not reported. Baseline sample sizes ranged from 49 [ 81 ] to 1292 [ 72 ] (mean 352.89, SD 289.50), as shown in Multimedia Appendix 5 . Participant mean ages ranged from 18.03 (SD 0.31) [ 79 ] to 35.3 (SD 12.6) years [ 88 ], and the proportion of participants who identified as female ranged from 24.7% [ 91 ] to 84.1% [ 80 ].

Of the 19 included studies, 10 (53%) targeted adults aged ≥18 years, of which 7 (70%) studies focused on adults who had engaged in past-month CU [ 70 , 71 , 80 , 84 , 85 , 90 , 91 ], 2 (20%) studies included adults who wished to reduce or cease CU [ 72 , 89 ], and 1 (10%) study focused on noncollege adults with a moderate risk associated with CU [ 88 ]. Sinadinovic et al [ 92 ] targeted young adults aged ≥16 years who had used cannabis at least once a week in the previous 6 months. The remaining 8 studies targeted college or university students (aged ≥17 y) specifically, of which 7 (88%) studies focused solely on students who reported using cannabis [ 78 , 79 , 81 - 83 , 86 , 87 ] and 1 (12%) study focused solely on students who did not report past-month CU (ie, abstainers) [ 77 ].

Intervention Characteristics

The 19 included studies assessed nine different digital interventions: (1) 5 (26%) evaluated Marijuana eCHECKUP TO GO (e-TOKE), a commercially available electronic intervention used at colleges throughout the United States and Canada [ 77 , 78 , 81 - 83 ]; (2) 2 (11%) examined the internationally known CANreduce program [ 70 , 91 ]; (3) 2 (11%) evaluated the German Quit the Shit program [ 72 , 90 ]; (4) 2 (11%) assessed a social media–delivered, physical activity–focused cannabis intervention [ 84 , 85 ]; (5) 1 (5%) investigated the Swedish Cannabishjälpen intervention [ 92 ]; (6) 1 (5%) evaluated the Australian Grassessment: Evaluate Your Use of Cannabis website program [ 89 ]; (7) 1 (5%) assessed the Canadian Ma réussite, mon choix intervention [ 87 ]; (8) 1 (5%) examined the Australian Reduce Your Use: How to Break the Cannabis Habit program [ 71 ]; and (9) 4 (21%) each evaluated a unique no-name intervention described as a personalized feedback intervention (PFI) [ 79 , 80 , 86 , 88 ]. Detailed information regarding the characteristics of all interventions as reported in each included study is provided in Multimedia Appendix 6 [ 70 - 72 , 77 - 113 ] and summarized in the following paragraphs.

In several studies (8/19, 42%), the interventions were designed to support cannabis users in reducing or ceasing their consumption [ 70 , 72 , 80 , 87 , 89 - 92 ]. In 37% (7/19) of the studies, the interventions aimed at reducing both CU and cannabis-related consequences [ 79 , 81 - 85 , 88 ]. Other interventions focused on helping college students think carefully about the decision to use cannabis [ 77 , 78 ] and on reducing either cannabis-related problems among undergraduate students [ 86 ] or symptoms associated with CU disorder in young adults [ 71 ].

In 26% (5/19) of the studies, theory was used to inform intervention design along with a clear rationale for theory use. Of these 5 articles, only 1 (20%) [ 87 ] reported using a single theory of behavior change, the theory of planned behavior [ 114 ]. A total of 21% (4/19) of the studies selected only constructs of theories (or models) for their intervention design. Of these 4 studies, 2 (50%) evaluated the same intervention [ 72 , 90 ], which focused on principles of self-regulation and self-control theory [ 93 ]; 1 (25%) [ 70 ] used the concept of adherence-focused guidance enhancement based on the supportive accountability model of guidance [ 94 ]; and 1 (25%) [ 71 ] reported that intervention design was guided by the concept of self-behavioral management.

The strategies (or approaches) used in the delivery of the digital interventions were discussed in greater detail in 84% (16/19) of the articles [ 70 - 72 , 79 - 81 , 83 - 92 ]. Many of these articles (9/19, 47%) reported using a combination of approaches based on CBT or motivational interviewing (MI) [ 70 , 71 , 79 , 83 - 85 , 90 - 92 ]. PFIs were also often mentioned as an approach to inform intervention delivery [ 7 , 71 , 79 , 86 - 88 ].

More than half (13/19, 68%) of all the digital interventions were asynchronous and based on a self-guided approach without support from a counselor or therapist. The study by Côté et al [ 87 ] evaluated the efficacy of a web-based tailored intervention focused on reinforcing a positive attitude toward and a sense of control over cannabis abstinence through psychoeducational messages delivered by a credible character in short video clips and personalized reinforcement messages. Lee et al [ 79 ] evaluated a brief, web-based personalized feedback selective intervention based on the PFI approach pioneered by Marlatt et al [ 95 ] for alcohol use prevention and on the MI approach described by Miller and Rollnick [ 96 ]. Similarly, Rooke et al [ 71 ] combined principles of MI and CBT to develop a web-based intervention delivered via web modules, which were informed by previous automated feedback interventions targeting substance use. The study by Copeland et al [ 89 ] assessed the short-term effectiveness of Grassessment: Evaluate Your Use of Cannabis, a brief web-based, self-complete intervention based on motivational enhancement therapy that included personalized feedback messages and psychoeducational material. In the studies by Buckner et al [ 80 ], Cunningham et al [ 88 ], and Walukevich-Dienst et al [ 86 ], experimental groups received a brief web-based PFI available via a computer. A total of 16% (3/19) of the studies [ 77 , 78 , 82 ] applied a program called the Marijuana eCHECKUP TO GO (e-TOKE) for Universities and Colleges, which was presented as a web-based, norm-correcting, brief preventive and intervention education program designed to prompt self-reflection on consequences and consideration of decreasing CU among students. Riggs et al [ 83 ] developed and evaluated an adapted version of e-TOKE that provided participants with university-specific personalized feedback and normative information based on protective behavioral strategies for CU [ 97 ]. Similarly, Goodness and Palfai [ 81 ] tested the efficacy of eCHECKUP TO GO-cannabis, a modified version of e-TOKE combining personalized feedback, norm correction, and a harm and frequency reduction strategy where a “booster” session was provided at 3 months to allow participants to receive repeated exposure to the intervention.

In the remaining 32% (6/19) of the studies, which examined 4 different interventions, the presence of a therapist guide was reported. The intervention evaluated by Sinadinovic et al [ 92 ] combined principles of psychoeducation, MI, and CBT organized into 13 web-based modules and a calendar involving therapist guidance, recommendations, and personal feedback. In total, 33% (2/6) of these studies evaluated a social media–delivered intervention with e-coaches that combined principles of MI and CBT and a harm reduction approach for risky CU [ 84 , 85 ]. Schaub et al [ 91 ] evaluated the efficacy of CANreduce, a web-based self-help intervention based on both MI and CBT approaches, using automated motivational and feedback emails, chat with a counselor, and web-based psychoeducational modules. Similarly, Baumgartner et al [ 70 ] investigated the effectiveness of CANreduce 2.0, a modified version of CANreduce, using semiautomated motivational and adherence-focused guidance-based email feedback with or without a personal online coach. The studies by Tossman et al [ 72 ] and Jonas et al [ 90 ] used a solution-focused approach and MI to evaluate the effectiveness of the German Quit the Shit web-based program that involves weekly feedback provided by counselors.

In addition to using different intervention strategies or approaches, the interventions were diverse in terms of the duration and frequency of the program (eg, web-based activities, sessions, or modules). Of the 12 articles that provided details in this regard, 2 (17%) on the same intervention described it as a brief 20- to 45-minute web-based program [ 77 , 78 ], 2 (17%) on 2 different interventions reported including 1 or 2 modules per week for a duration of 6 weeks [ 71 , 92 ], and 7 (58%) on 4 different interventions described them as being available over a longer period ranging from 6 weeks to 3 months [ 70 , 72 , 79 , 84 , 85 , 87 , 90 , 91 ].

Comparator Types

A total of 42% (8/19) of the studies [ 72 , 77 - 80 , 85 , 87 , 92 ] used a passive comparator only, namely, a waitlist control group ( Multimedia Appendix 5 ). A total of 26% (5/19) of the studies used an active comparator only where participants were provided with minimal general health feedback regarding recommended guidelines for sleep, exercise, and nutrition [ 81 , 82 ]; strategies for healthy stress management [ 83 ]; educational materials about risky CU [ 88 ]; or access to a website containing information about cannabis [ 71 ]. In another 21% (4/19) of the studies, which used an active comparator, participants received the same digital intervention minus a specific component: a personal web-based coach [ 70 ], extended personalized feedback [ 89 ], web-based chat counseling [ 91 ], or information on risks associated with CU [ 86 ]. A total of 21% (4/19) of the studies had more than one control group [ 70 , 84 , 90 , 91 ].

Outcome Variable Assessment and Summary of Main Findings of the Studies

The methodological characteristics and major findings of the included studies (N=19) are presented in Multimedia Appendix 7 [ 67 , 70 - 72 , 77 - 92 , 115 - 120 ] and summarized in the following sections for each outcome of interest in this review (ie, CU and cannabis-related consequences). Of the 19 studies, 11 (58%) were reported as efficacy trials [ 7 , 77 , 79 , 81 - 83 , 86 - 88 , 91 , 92 ], and 8 (42%) were reported as effectiveness trials [ 70 - 72 , 78 , 84 , 85 , 89 , 90 ].

Across all the included studies (19/19, 100%), participant attrition rates ranged from 1.6% at 1 month after the baseline [ 77 , 78 ] to 75.1% at the 3-month follow-up [ 70 ]. A total of 37% (7/19) of the studies assessed and reported results regarding user engagement [ 71 , 78 , 84 , 85 , 90 - 92 ] using different types of metrics. In one article on the Marijuana eCHECKUP TO GO (e-TOKE) web-based program [ 78 ], the authors briefly reported that participation was confirmed for 98.1% (158/161) of participants in the intervention group. In 11% (2/19) of the studies, which were on a similar social media–delivered intervention [ 84 , 85 ], user engagement was quantified by tallying the number of comments or posts and reactions (eg, likes and hearts) left by participants. In both studies [ 84 , 85 ], the intervention group, which involved a CU-related Facebook page, displayed greater interactions than the control groups, which involved a Facebook page unrelated to CU. One article [ 84 ] reported that 80% of participants in the intervention group posted at least once (range 0-60) and 50% posted at least weekly. In the other study [ 85 ], the results showed that intervention participants engaged (ie, posting or commenting or clicking reactions) on average 47.9 times each over 8 weeks. In total, 11% (2/19) of the studies [ 90 , 91 ] on 2 different web-based intervention programs, both consisting of web documentation accompanied by chat-based counseling, measured user engagement either by average duration or average number of chat sessions. Finally, 16% (3/19) of the studies [ 71 , 91 , 92 ], which involved 3 different web-based intervention programs, characterized user engagement by the mean number of web modules completed per participant. Overall, the mean number of web modules completed reported in these articles was quite similar: 3.9 out of 13 [ 92 ] and 3.2 [ 91 ] and 3.5 [ 71 ] out of 6.

Assessment of CU

As presented in Multimedia Appendix 7 , the included studies differed in terms of how they assessed CU, although all used at least one self-reported measure of frequency. Most studies (16/19, 84%) measured frequency by days of use, including days of use in the preceding week [ 91 ] or 2 [ 80 ], days of use in the previous 30 [ 70 - 72 , 78 , 84 - 86 , 88 - 90 ] or 90 days [ 79 , 81 , 82 ], and days high per week [ 83 ]. Other self-reported measures of CU frequency included (1) number of CU events in the previous month [ 87 , 90 ], (2) cannabis initiation or use in the previous month (ie, yes or no) [ 77 ], and (3) days without CU in the previous 7 days [ 92 ]. In addition to measuring CU frequency, 42% (8/19) of the studies also assessed CU via self-reported measures of quantity used, including estimated grams consumed in the previous week [ 92 ] or 30 days [ 72 , 85 , 90 ] and the number of standard-sized joints consumed in the previous 7 days [ 91 ] or the previous month [ 70 , 71 , 89 ].

Of the 19 articles included, 10 (53%) [ 70 - 72 , 80 , 84 - 86 , 89 , 90 , 92 ] reported using a validated instrument to measure CU frequency or quantity, including the TLFB instrument [ 66 ] (n=9, 90% of the studies) and the Marijuana Use Form (n=1, 10% of the studies); 1 (10%) [ 79 ] reported using CU-related questions from an adaptation of the Global Appraisal of Individual Needs–Initial instrument [ 115 ]; and 30% (3/10) [ 81 , 82 , 91 ] reported using a questionnaire accompanied by a calendar or a diary of consumption. The 19 studies also differed with regard to their follow-up time measurements for assessing CU, ranging from 2 weeks after the baseline [ 80 ] to 12 months after randomization [ 90 ], although 12 (63%) of the studies included a 3-month follow-up assessment [ 70 - 72 , 79 , 81 , 82 , 84 , 85 , 88 , 90 - 92 ].

Of all studies assessing and reporting change in CU frequency from baseline to follow-up assessments (19/19, 100%), 47% (9/19) found statistically significant differences between the experimental and control groups [ 70 - 72 , 80 , 81 , 83 , 85 , 87 , 91 ]. Importantly, 67% (6/9) of these studies showed that participants in the experimental groups exhibited greater decreases in CU frequency 3 months following the baseline assessment compared with participants in the control groups [ 70 - 72 , 81 , 85 , 91 ], 22% (2/9) of the studies showed greater decreases in CU frequency at 6 weeks after the baseline assessment [ 71 , 83 ], 22% (2/9) of the studies showed greater decreases in CU frequency at 6 months following the baseline assessment [ 81 , 85 ], 11% (1/9) of the studies showed greater decreases in CU frequency at 2 weeks after the baseline [ 80 ], and 11% (1/9) of the studies showed greater decreases in CU frequency at 2 months after treatment [ 87 ].

In the study by Baumgartner et al [ 70 ], a reduction in CU days was observed in all groups, but the authors reported that the difference was statistically significant only between the intervention group with the service team and the control group (the reduction in the intervention group with social presence was not significant). In the study by Bonar et al [ 85 ], the only statistically significant difference between the intervention and control groups at the 3- and 6-month follow-ups involved total days of cannabis vaping in the previous 30 days. Finally, in the study by Buckner et al [ 80 ], the intervention group had less CU than the control group 2 weeks after the baseline; however, this was statistically significant only for participants with moderate or high levels of social anxiety.

Assessment of Cannabis-Related Negative Consequences

A total of 53% (10/19) of the studies also assessed cannabis-related negative consequences [ 78 - 84 , 86 , 88 , 92 ]. Of these 10 articles, 8 (80%) reported using a validated self-report instrument: 4 (50%) [ 81 , 82 , 86 , 88 ] used the 19-item Marijuana Problems Scale [ 67 ], 2 (25%) [ 78 , 79 ] used the 18-item Rutgers Marijuana Problem Index [ 121 , 122 ], and 2 (25%) [ 80 , 84 ] used the Brief Marijuana Consequences Questionnaire [ 116 ]. Only 10% (1/10) of the studies [ 92 ] used a screening tool, the Cannabis Abuse Screening Test [ 117 , 118 ]. None of these 10 studies demonstrated a statistically significant difference between the intervention and control groups. Of note, Walukevich-Dienst et al [ 86 ] found that women (but not men) who received an web-based PFI with additional information on CU risks reported significantly fewer cannabis-related problems than did women in the control group at 1 month after the intervention ( B =−1.941; P =.01).

Descriptive Summary of BCTs Used in Intervention Groups

After the 19 studies included in this review were coded, a total of 184 individual BCTs targeting CU in young adults were identified. Of these 184 BCTs, 133 (72.3% ) were deemed to be present beyond a reasonable doubt, and 51 (27.7%) were deemed to be present in all probability. Multimedia Appendix 8 [ 48 , 70 - 72 , 77 - 92 ] presents all the BCTs coded for each included study summarized by individual BCT and BCT cluster.

The 184 individual BCTs coded covered 38% (35/93) of the BCTs listed in the BCTTv1 [ 48 ]. The number of individual BCTs identified per study ranged from 5 to 19, with two-thirds of the 19 studies (12/19, 63%) using ≤9 BCTs (mean 9.68). As Multimedia Appendix 8 shows, at least one BCT fell into 13 of the 16 possible BCT clusters. The most frequent clusters were feedback monitoring , natural consequences , goal planning , and comparison of outcomes .

The most frequently coded BCTs were (1) feedback on behavior (BCT 2.2; 17/19, 89% of the studies; eg, “Once a week, participants receive detailed feedback by their counselor on their entries in diary and exercises. Depending on the involvement of each participant, up to seven feedbacks are given” [ 90 ]), (2) social support (unspecified) (BCT 3.1; 15/19, 79% of the studies; eg, “The website also features [...] blogs from former cannabis users, quick assist links, and weekly automatically generated encouragement emails” [ 71 ]), and (3) pros and cons (BCT 9.2; 14/19, 74% of the studies; eg, “participants are encouraged to state their personal reasons for and against their cannabis consumption, which they can review at any time, so they may reflect on what they could gain by successfully completing the program” [ 70 ]). Other commonly identified BCTs included social comparison (BCT 6.2; 12/19, 63% of the studies) and information about social and environmental consequences (BCT 5.3; 11/19, 58% of the studies), followed by problem solving (BCT 2.1; 10/19, 53% of the studies) and information about health consequences (BCT 5.1; 10/19, 53% of the studies).

RoB Assessment

Figure 2 presents the overall assessment of risk in each domain for all the included studies, whereas Figure 3 [ 70 - 72 , 77 - 92 ] summarizes the assessment of each study at the outcome level for each domain in the Cochrane RoB 2 [ 74 ].

Figure 2 shows that, of the included studies, 93% (27/29) were rated as having a “low” RoB arising from the randomization process (ie, selection bias) and 83% (24/29) were rated as having a “low” RoB due to missing data (ie, attrition bias). For bias due to deviations from the intended intervention (ie, performance bias), 72% (21/29) were rated as having a “low” risk, and for selective reporting of results, 59% (17/29) were rated as having a “low” risk. In the remaining domain regarding bias in measurement of the outcome (ie, detection bias), 48% (14/29) of the studies were deemed to present “some concerns,” mainly owing to the outcome assessment not being blinded (eg, self-reported outcome measure of CU). Finally, 79% (15/19) of the included studies were deemed to present “some concerns” or were rated as having a “high” RoB at the outcome level ( Figure 3 [ 70 - 72 , 77 - 92 ]). The RoB assessment for CU and cannabis consequences of each included study is presented in Multimedia Appendix 9 [ 70 - 72 , 77 - 92 ].

Meta-Analysis Results

Due to several missing data points and despite contacting the authors, we were able to carry out only 1 meta-analysis of our primary outcome, CU frequency. Usable data were retrieved from only 16% (3/19) [ 70 - 72 ] of the studies included in this review. These 3 studies provided sufficient information to calculate an effect size, including mean differences based on change-from-baseline measurements and associated 95% CIs (or SE of the mean difference) and sample sizes per intervention and comparison conditions. The reasons for excluding the other 84% (16/19) of the studies included heterogeneity in outcome variables or measurements, inconsistent results, and missing data ( Multimedia Appendix 10 [ 77 - 92 ]).

Figure 4 [ 70 - 72 ] illustrates the mean differences and associated 95% CIs of 3 unique RCTs [ 70 - 72 ] that provided sufficient information to allow for the measurement of CU frequency at 3 months after the baseline relative to a comparison condition in terms of the number of self-reported days of use in the previous month using the TLFB method. Overall, the synthesized effect of digital interventions for young adult cannabis users on CU frequency, as measured using days of use in the previous month, was −6.79 (95% CI −9.59 to −4.00). This suggests that digital CU interventions had a statistically significant effect ( P <.001) on reducing CU frequency at the 3-month follow-up compared with the control conditions (both passive and active controls). The results of the meta-analysis also showed low between-study heterogeneity ( I 2 =48.3%; P =.12) across the 3 included studies.

The samples of the 3 studies included in the meta-analysis varied in size from 225 to 1292 participants (mean 697.33, SD 444.11), and the mean age ranged from 24.7 to 31.88 years (mean 26.38, SD 3.58 years). These studies involved 3 different digital interventions and used different design approaches to assess intervention effectiveness. One study assessed the effectiveness of a web-based counseling program (ie, Quit the Shit) against a waitlist control [ 72 ], another examined the effectiveness of a fully self-guided web-based treatment program for CU and related problems (ie, Reduce Your Use: How to Break the Cannabis Habit) against a control condition website consisting of basic educational information on cannabis [ 71 ], and the third used a 3-arm RCT design to investigate whether the effectiveness of a minimally guided internet-based self-help intervention (ie, CANreduce 2.0) might be enhanced by implementing adherence-focused guidance and emphasizing the social presence factor of a personal e-coach [ 70 ].

Summary of Principal Findings

The primary aim of this systematic review was to evaluate the effectiveness of digital interventions in addressing CU among community-living young adults. We included 19 randomized controlled studies representing 9 unique digital interventions aimed at preventing, reducing, or ceasing CU and evaluated the effects of 3 different digital interventions on CU. In summary, the 3 digital interventions included in the meta-analysis proved superior to control conditions in reducing the number of days of CU in the previous month at the 3-month follow-up.

Our findings are consistent with those of 2 previous meta-analyses by Olmos et al [ 43 ] and Tait et al [ 44 ] and with the findings of a recently published umbrella review of systematic reviews and meta-analyses of RCTs [ 123 ], all of which revealed a positive effect of internet- and computer-based interventions on CU. However, a recent systematic review and meta-analysis by Beneria et al [ 45 ] found that web-based CU interventions did not significantly reduce CU. Beneria et al [ 45 ] included studies with different intervention programs that targeted diverse population groups (both adolescents and young adults) and use of more than one substance (eg, alcohol and cannabis). In our systematic review, a more conservative approach was taken—we focused specifically on young adults and considered interventions targeting CU only. Although our results indicate that digital interventions hold great promise in terms of effectiveness, an important question that remains unresolved is whether there is an optimal exposure dose in terms of both duration and frequency that might be more effective. Among the studies included in this systematic review, interventions varied considerably in terms of the number of psychoeducational modules offered (from 2 to 13), time spent reviewing the material, and duration (from a single session to a 12-week spread period). Our results suggest that an intervention duration of at least 6 weeks yields better results.

Another important finding of this review is that, although almost half (9/19, 47%) of the included studies observed an intervention effect on CU frequency, none reported a statistically significant improvement in cannabis-related negative consequences, which may be considered a more distal indicator. More than half (10/19, 53%) of the included studies investigated this outcome. It seems normal to expect to find an effect on CU frequency given that reducing CU is often the primary objective of interventions and because the motivation of users’ is generally focused on changing consumption behavior. It is plausible to think that the change in behavior at the consumption level must be maintained over time before an effect on cannabis-related negative consequences can be observed. However, our results showed that, in all the included studies, cannabis-related negative consequences and change in behavior (CU frequency) were measured at the same time point, namely, 3 months after the baseline. Moreover, Grigsby et al [ 124 ] conducted a scoping review of risk and protective factors for CU and suggested that interventions to reduce negative CU consequences should prioritize multilevel methods or strategies “to attenuate the cumulative risk from a combination of psychological, contextual, and social influences.”

A secondary objective of this systematic review was to describe the active ingredients used in digital interventions for CU among young adults. The vast majority of the interventions were based on either a theory or an intervention approach derived from theories such as CBT, MI, and personalized feedback. From these theories and approaches stem behavior change strategies or techniques, commonly known as BCTs. Feedback on behavior , included in the feedback monitoring BCT cluster, was the most common BCT used in the included studies. This specific BCT appears to be a core strategy in behavior change interventions [ 125 , 126 ]. In their systematic review of remotely delivered alcohol or substance misuse interventions for adults, Howlett et al [ 53 ] found that feedback on behavior , problem solving , and goal setting were the most frequently used BCTs in the included studies. In addition, this research group noted that the most promising BCTs for alcohol misuse were avoidance/reducing exposure to cues for behavior , pros and cons , and self-monitoring of behavior, whereas 2 very promising strategies for substance misuse in general were problem solving and self-monitoring of behavior . In our systematic review, in addition to feedback on behavior , the 6 most frequently used BCTs in the included studies were social support , pros and cons , social comparison , problem solving , information about social and environmental consequences , and information about health consequences . Although pros and cons and problem solving were present in all 3 studies of digital interventions included in our meta-analysis, avoidance/reducing exposure to cues for behavior was reported in only 5% (1/19) of the articles, and feedback on behavior was more frequently used than self-monitoring of behavior. However, it should be noted that the review by Howlett et al [ 53 ] examined digital interventions for participants with alcohol or substance misuse problems, whereas in this review, we focused on interventions that targeted CU from a harm reduction perspective. In this light, avoidance/reducing exposure to cues for behavior may be a BCT better suited to populations with substance misuse problems. Lending support to this, a meta-regression by Garnett et al [ 127 ] and a Cochrane systematic review by Kaner et al [ 128 ] both found interventions that used behavior substitution and credible source to be associated with greater reduction in excessive alcohol consumption compared with interventions that used other BCTs.

Beyond the number and types of BCTs used, reflecting on the extent to which each BCT in a given intervention suits (or does not suit) the targeted determinants (ie, behavioral and environmental causes) is crucial for planning intervention programs [ 26 ]. It is important when designing digital CU interventions not merely to pick a combination of BCTs that have been associated with effectiveness. Rather, the active ingredients must fit the determinants that the interventionists seek to influence. For example, action planning would be more relevant as a BCT for young adults highly motivated and ready to take action on their CU than would pros and cons , which aims instead to bolster motivation. Given that more than half of all digital interventions are asynchronous and based on a self-guided approach and do not offer counselor or therapist support, a great deal of motivation is required to engage in intervention and behavior change. Therefore, it is essential that developers consider the needs and characteristics of the targeted population to tailor intervention strategies (ie, BCTs) for successful behavior change (eg, tailored to the participant’s stage of change). In most of the digital interventions included in this systematic review, personalization was achieved through feedback messages about CU regarding descriptive norms, motives, risks and consequences, and costs, among other things.

Despite the high number of recent studies conducted in the field of digital CU interventions, most of the included articles in our review (17/19, 89%) reported on the development and evaluation of web-based intervention programs. A new generation of health intervention modalities such as mobile apps and social media has drawn the attention of researchers in the past decade and is currently being evaluated. In this regard, the results from a recently published scoping review [ 129 ], which included 5 studies of mobile apps for nonmedical CU, suggested that these novel modes of intervention delivery demonstrated adequate feasibility and acceptability. Nevertheless, the internet remains a powerful and convenient medium for reaching young adults with digital interventions intended to support safe CU behaviors [ 123 , 130 ].

Quality of Evidence

The GRADE (Grading of Recommendations Assessment, Development, and Evaluation) approach [ 131 - 133 ] was used to assess the quality of the evidence reviewed. It was deemed to be moderate for the primary outcome of this review, that is, CU frequency in terms of days of use in the previous month (see the summary of evidence in Multimedia Appendix 11 [ 70 , 72 ]). The direction of evidence was broadly consistent—in all 3 RCT studies [ 70 - 72 ] included in the meta-analysis, participants who received digital CU interventions reduced their consumption compared with those who received no or minimal interventions. The 3 RCTs were similar in that they all involved a web-based, multicomponent intervention program aimed at reducing or ceasing CU. However, the interventions did differ or vary in terms of several characteristics, including the strategies used, content, frequency, and duration. Given the small number of studies included in the meta-analysis, we could not conclude with certainty which intervention components, if any, contributed to the effect estimate observed.

Although inconsistency, indirectness, and imprecision were not major issues in the body of evidence, we downgraded the evidence from high to moderate quality on account of RoB assessments at the outcome level. The 3 RCT studies included in the meta-analysis were rated as having “some concerns” of RoB, mainly due to lack of blinding, which significantly reduced our certainty relative to subjective outcomes (ie, self-reported measures of CU frequency). A positive feature of these digital intervention trials is that most procedures are fully automated, and so there was typically a low RoB regarding randomization procedures, allocation to different conditions, and intervention delivery. It is impossible to blind participants to these types of behavior change interventions, and although some researchers have made attempts to counter the impact of this risk, performance bias is an inescapable issue in RCT studies of this kind. Blinding of intervention providers was not an issue in the 3 RCTs included in the meta-analysis because outcome data collection was automated. However, this same automated procedure made it very difficult to ensure follow‐up. Consequently, attrition was another source of bias in these RCT studies [ 70 - 72 ]. The participants lost to follow-up likely stopped using the intervention. However, there is no way of determining whether these people would have benefited more or less than the completers if they had seen the trial through.

The 3 RCTs included in the meta-analysis relied on subjective self-reported measures of CU at baseline and follow‐up, which are subject to recall and social desirability bias. However, all 3 studies used a well-validated instrument of measurement to determine frequency of CU, the TLFB [ 66 ]. This is a widely used, subjective self-report tool for measuring frequency (or quantity) of substance use (or abstinence). It is considered a reliable measure of CU [ 134 , 135 ]. Finally, it should be pointed out that any potential bias related to self‐reported CU frequency would have affected both the intervention and control groups (particularly in cases in which control groups received cannabis‐related information), and thus, it was unlikely to account for differential intervention effects. Moreover, we found RoB due to selective reporting in some studies owing mainly to the absence of any reference to a protocol. Ultimately, these limitations may have biased the results of the meta-analysis. Consequently, future research is likely to further undermine our confidence in the effect estimate we observed and report considerably different estimates.

Strengths and Limitations

Our systematic review and meta-analysis has a number of strengths: (1) we included only randomized controlled studies to ensure that the included studies possessed a rigorous research design, (2) we focused specifically on cannabis (rather than combining multiple substances), (3) we assessed the effectiveness of 3 different digital interventions on CU frequency among community-living young adults, and (4) we performed an exhaustive synthesis and comparison of the BCTs used in the 9 digital interventions examined in the 19 studies included in our review based on the BCTTv1.

Admittedly, this systematic review and meta-analysis has limitations that should be recognized. First, although we searched a range of bibliographic databases, the review was limited to articles published in peer-reviewed journals in English or French. This may have introduced publication bias given that articles reporting positive effects are more likely to be published than those with negative or equivocal results. Consequently, the studies included in this review may have overrepresented the statistically significant effects of digital CU interventions.

Second, only a small number of studies were included in the meta-analyses because many studies did not provide adequate statistical information for calculating and synthesizing effect sizes, although significant efforts were made to contact the authors in case of missing data. Because of the small sample size used in the meta-analysis, the effect size estimates may not be highly reflective of the true effects of digital interventions on CU frequency among young adults. Furthermore, synthesizing findings across studies that evaluated different modalities of web-based intervention programs (eg, fully self-guided vs with therapist guidance) and types of intervention approaches (eg, CBT, MI, and personalized feedback) may have introduced bias in the meta-analytical results due to the heterogeneity of the included studies, although heterogeneity was controlled for using a random-effects model and our results indicated low between-study heterogeneity.

Third, we took various measures to ensure that BCT coding was carried out rigorously throughout the data extraction and analysis procedures: (1) all coders received training on how to use the BCTTv1; (2) all the included articles were read line by line so that coders became familiar with intervention descriptions before initiating BCT coding; (3) the intervention description of each included article was double coded after a pilot calibration exercise with all coders, and any disagreements regarding the presence or absence of a BCT were discussed and resolved with a third party; and (4) we contacted the article authors when necessary and possible for further details on the BCTs they used. However, incomplete reporting of intervention content is a recognized issue [ 136 ], which may have resulted in our coding BCTs incorrectly as present or absent. Reliably specifying the BCTs used in interventions allows their active ingredients to be identified, their evidence to be synthesized, and interventions to be replicated, thereby providing tangible guidance to programmers and researchers to develop more effective interventions.

Finally, although this review identified the BCTs used in digital interventions, our approach did not allow us to draw conclusions regarding their effectiveness. Coding BCTs simply as present or absent does not consider the frequency, intensity, and quality with which they were delivered. For example, it is unclear how many individuals should self‐monitor their CU. In addition, the quality of BCT implementation may be critical in digital interventions where different graphics and interface designs and the usability of the BCTs used can have considerable influence on the level of user engagement [ 137 ]. In the future, it may be necessary to develop new methods to evaluate the dosage of individual BCTs in digital health interventions and characterize their implementation quality to assess their effectiveness [ 128 , 138 ]. Despite its limitations, this review suggests that digital interventions represent a promising avenue for preventing, reducing, or ceasing CU among community-living young adults.

Conclusions

The results of this systematic review and meta-analysis lend support to the promise of digital interventions as an effective means of reducing recreational CU frequency among young adults. Despite the advent and popularity of smartphones, web-based interventions remain the most common mode of delivery for digital interventions. The active ingredients of digital interventions are varied and encompass a number of clusters of the BCTTv1, but a significant number of BCTs remain underused. Additional research is needed to further investigate the effectiveness of these interventions on CU and key outcomes at later time points. Finally, a detailed assessment of user engagement with digital interventions for CU and understanding which intervention components are the most effective remain important research gaps.

Acknowledgments

The authors would like to thank Bénédicte Nauche, Miguel Chagnon, and Paul Di Biase for their valuable support with the search strategy development, statistical analysis, and linguistic revision, respectively. This work was supported by the Ministère de la Santé et des Services sociaux du Québec as part of a broader study aimed at developing and evaluating a digital intervention for young adult cannabis users. Additional funding was provided by the Research Chair in Innovative Nursing Practices. The views and opinions expressed in this manuscript do not necessarily reflect those of these funding entities.

Data Availability

The data sets generated and analyzed during this study are available from the corresponding author on reasonable request.

Authors' Contributions

JC contributed to conceptualization, methodology, formal analysis, writing—original draft, supervision, and funding acquisition. GC contributed to conceptualization, methodology, formal analysis, investigation, data curation, writing—original draft, visualization, and project administration. BV contributed to conceptualization, methodology, formal analysis, investigation, data curation, writing—original draft, and visualization. PA contributed to conceptualization, methodology, formal analysis, investigation, data curation, writing—original draft, visualization, and project administration. GR contributed to conceptualization, methodology, formal analysis, investigation, data curation, and writing—review and editing. GF contributed to conceptualization, methodology, formal analysis, investigation, data curation, and writing—review and editing. DJA contributed to conceptualization, methodology, formal analysis, writing—review and editing, and funding acquisition.

Conflicts of Interest

None declared.

PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) checklist.

Detailed search strategies for each database.

Population, intervention, comparison, outcome, and study design strategy.

Excluded studies and reasons for exclusion.

Study and participant characteristics.

Description of intervention characteristics in the included articles.

Summary of methodological characteristics and major findings of the included studies categorized by intervention name.

Behavior change techniques (BCTs) coded in each included study summarized by individual BCT and BCT cluster.

Risk-of-bias assessment of each included study for cannabis use and cannabis consequences.

Excluded studies and reasons for exclusion from the meta-analysis.

Summary of evidence according to the Grading of Recommendations Assessment, Development, and Evaluation tool.

• Arnett JJ. The developmental context of substance use in emerging adulthood. J Drug Issues. 2005;35(2):235-254. [ CrossRef ]
• Stockings E, Hall WD, Lynskey M, Morley KI, Reavley N, Strang J, et al. Prevention, early intervention, harm reduction, and treatment of substance use in young people. Lancet Psychiatry. Mar 2016;3(3):280-296. [ CrossRef ] [ Medline ]
• ElSohly MA, Chandra S, Radwan M, Majumdar CG, Church JC. A comprehensive review of cannabis potency in the United States in the last decade. Biol Psychiatry Cogn Neurosci Neuroimaging. Jun 2021;6(6):603-606. [ CrossRef ] [ Medline ]
• Fischer B, Robinson T, Bullen C, Curran V, Jutras-Aswad D, Medina-Mora ME, et al. Lower-Risk Cannabis Use Guidelines (LRCUG) for reducing health harms from non-medical cannabis use: a comprehensive evidence and recommendations update. Int J Drug Policy. Jan 2022;99:103381. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Rotermann M. What has changed since cannabis was legalized? Health Rep. Feb 19, 2020;31(2):11-20. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Degenhardt L, Stockings E, Patton G, Hall WD, Lynskey M. The increasing global health priority of substance use in young people. Lancet Psychiatry. Mar 2016;3(3):251-264. [ CrossRef ] [ Medline ]
• Buckner JD, Bonn-Miller MO, Zvolensky MJ, Schmidt NB. Marijuana use motives and social anxiety among marijuana-using young adults. Addict Behav. Oct 2007;32(10):2238-2252. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Carliner H, Brown QL, Sarvet AL, Hasin DS. Cannabis use, attitudes, and legal status in the U.S.: a review. Prev Med. Nov 2017;104:13-23. [ FREE Full text ] [ CrossRef ] [ Medline ]
• World drug report 2020. United Nations Office on Drugs and Crime. 2020. URL: https://wdr.unodc.org/wdr2020/index2020.html [accessed 2023-11-28]
• National Academies of Sciences, Engineering, and Medicine, Health and Medicine Division, Board on Population Health and Public Health Practice, Committee on the Health Effects of Marijuana: An Evidence Review and Research Agenda. The Health Effects of Cannabis and Cannabinoids: The Current State of Evidence and Recommendations for Research. Washington, DC. The National Academies Press; 2017.
• Hall WD, Patton G, Stockings E, Weier M, Lynskey M, Morley KI, et al. Why young people's substance use matters for global health. Lancet Psychiatry. Mar 2016;3(3):265-279. [ CrossRef ] [ Medline ]
• Cohen K, Weizman A, Weinstein A. Positive and negative effects of cannabis and cannabinoids on health. Clin Pharmacol Ther. May 2019;105(5):1139-1147. [ CrossRef ] [ Medline ]
• Memedovich KA, Dowsett LE, Spackman E, Noseworthy T, Clement F. The adverse health effects and harms related to marijuana use: an overview review. CMAJ Open. Aug 16, 2018;6(3):E339-E346. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Teeters JB, Armstrong NM, King SA, Hubbard SM. A randomized pilot trial of a mobile phone-based brief intervention with personalized feedback and interactive text messaging to reduce driving after cannabis use and riding with a cannabis impaired driver. J Subst Abuse Treat. Nov 2022;142:108867. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Chan GC, Becker D, Butterworth P, Hines L, Coffey C, Hall W, et al. Young-adult compared to adolescent onset of regular cannabis use: a 20-year prospective cohort study of later consequences. Drug Alcohol Rev. May 2021;40(4):627-636. [ CrossRef ] [ Medline ]
• Hall W, Stjepanović D, Caulkins J, Lynskey M, Leung J, Campbell G, et al. Public health implications of legalising the production and sale of cannabis for medicinal and recreational use. Lancet. Oct 26, 2019;394(10208):1580-1590. [ CrossRef ] [ Medline ]
• The health and social effects of nonmedical cannabis use. World Health Organization. 2016. URL: https://apps.who.int/iris/handle/10665/251056 [accessed 2023-11-28]
• Boumparis N, Loheide-Niesmann L, Blankers M, Ebert DD, Korf D, Schaub MP, et al. Short- and long-term effects of digital prevention and treatment interventions for cannabis use reduction: a systematic review and meta-analysis. Drug Alcohol Depend. Jul 01, 2019;200:82-94. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Jutras-Aswad D, Le Foll B, Bruneau J, Wild TC, Wood E, Fischer B. Thinking beyond legalization: the case for expanding evidence-based options for cannabis use disorder treatment in Canada. Can J Psychiatry. Feb 2019;64(2):82-87. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Garnett CV, Crane D, Brown J, Kaner EF, Beyer FR, Muirhead CR, et al. Behavior change techniques used in digital behavior change interventions to reduce excessive alcohol consumption: a meta-regression. Ann Behav Med. May 18, 2018;52(6):530-543. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Glanz K, Rimer BK, Viswanath K. Health Behavior: Theory, Research, and Practice, 5th Edition. Hoboken, NJ. Jossey-Bass; Jul 2015.
• Prestwich A, Webb TL, Conner M. Using theory to develop and test interventions to promote changes in health behaviour: evidence, issues, and recommendations. Curr Opin Psychol. Oct 2015;5:1-5. [ CrossRef ]
• Webb TL, Sniehotta FF, Michie S. Using theories of behaviour change to inform interventions for addictive behaviours. Addiction. Nov 2010;105(11):1879-1892. [ CrossRef ] [ Medline ]
• Cilliers F, Schuwirth L, van der Vleuten C. Health behaviour theories: a conceptual lens to explore behaviour change. In: Cleland J, Durning SJ, editors. Researching Medical Education. Hoboken, NJ. Wiley; 2015.
• Davis R, Campbell R, Hildon Z, Hobbs L, Michie S. Theories of behaviour and behaviour change across the social and behavioural sciences: a scoping review. Health Psychol Rev. 2015;9(3):323-344. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Eldredge LK, Markham CM, Ruiter RA, Fernández ME, Kok G, Parcel GS. Planning Health Promotion Programs: An Intervention Mapping Approach, 4th Edition. Hoboken, NJ. John Wiley & Sons; Feb 2016.
• Marlatt GA, Blume AW, Parks GA. Integrating harm reduction therapy and traditional substance abuse treatment. J Psychoactive Drugs. 2001;33(1):13-21. [ CrossRef ] [ Medline ]
• Adams A, Ferguson M, Greer AM, Burmeister C, Lock K, McDougall J, et al. Guideline development in harm reduction: considerations around the meaningful involvement of people who access services. Drug Alcohol Depend Rep. Aug 12, 2022;4:100086. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Davis ML, Powers MB, Handelsman P, Medina JL, Zvolensky M, Smits JA. Behavioral therapies for treatment-seeking cannabis users: a meta-analysis of randomized controlled trials. Eval Health Prof. Mar 2015;38(1):94-114. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Gates PJ, Sabioni P, Copeland J, Le Foll B, Gowing L. Psychosocial interventions for cannabis use disorder. Cochrane Database Syst Rev. May 05, 2016;2016(5):CD005336. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Halladay J, Scherer J, MacKillop J, Woock R, Petker T, Linton V, et al. Brief interventions for cannabis use in emerging adults: a systematic review, meta-analysis, and evidence map. Drug Alcohol Depend. Nov 01, 2019;204:107565. [ CrossRef ] [ Medline ]
• Imtiaz S, Roerecke M, Kurdyak P, Samokhvalov AV, Hasan OS, Rehm J. Brief interventions for cannabis use in healthcare settings: systematic review and meta-analyses of randomized trials. J Addict Med. 2020;14(1):78-88. [ CrossRef ] [ Medline ]
• Standeven LR, Scialli A, Chisolm MS, Terplan M. Trends in cannabis treatment admissions in adolescents/young adults: analysis of TEDS-A 1992 to 2016. J Addict Med. 2020;14(4):e29-e36. [ CrossRef ] [ Medline ]
• Montanari L, Guarita B, Mounteney J, Zipfel N, Simon R. Cannabis use among people entering drug treatment in europe: a growing phenomenon? Eur Addict Res. 2017;23(3):113-121. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Kerridge BT, Mauro PM, Chou SP, Saha TD, Pickering RP, Fan AZ, et al. Predictors of treatment utilization and barriers to treatment utilization among individuals with lifetime cannabis use disorder in the United States. Drug Alcohol Depend. Dec 01, 2017;181:223-228. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Gates P, Copeland J, Swift W, Martin G. Barriers and facilitators to cannabis treatment. Drug Alcohol Rev. May 2012;31(3):311-319. [ CrossRef ] [ Medline ]
• Hammarlund RA, Crapanzano KA, Luce L, Mulligan L, Ward KM. Review of the effects of self-stigma and perceived social stigma on the treatment-seeking decisions of individuals with drug- and alcohol-use disorders. Subst Abuse Rehabil. Nov 23, 2018;9:115-136. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Bedrouni W. On the use of digital technologies to reduce the public health impacts of cannabis legalization in Canada. Can J Public Health. Dec 2018;109(5-6):748-751. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Perski O, Hébert ET, Naughton F, Hekler EB, Brown J, Businelle MS. Technology-mediated just-in-time adaptive interventions (JITAIs) to reduce harmful substance use: a systematic review. Addiction. May 2022;117(5):1220-1241. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Kazemi DM, Borsari B, Levine MJ, Li S, Lamberson KA, Matta LA. A systematic review of the mHealth interventions to prevent alcohol and substance abuse. J Health Commun. May 2017;22(5):413-432. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Nesvåg S, McKay JR. Feasibility and effects of digital interventions to support people in recovery from substance use disorders: systematic review. J Med Internet Res. Aug 23, 2018;20(8):e255. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Hoch E, Preuss UW, Ferri M, Simon R. Digital interventions for problematic cannabis users in non-clinical settings: findings from a systematic review and meta-analysis. Eur Addict Res. 2016;22(5):233-242. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Olmos A, Tirado-Muñoz J, Farré M, Torrens M. The efficacy of computerized interventions to reduce cannabis use: a systematic review and meta-analysis. Addict Behav. Apr 2018;79:52-60. [ CrossRef ] [ Medline ]
• Tait RJ, Spijkerman R, Riper H. Internet and computer based interventions for cannabis use: a meta-analysis. Drug Alcohol Depend. Dec 01, 2013;133(2):295-304. [ CrossRef ] [ Medline ]
• Beneria A, Santesteban-Echarri O, Daigre C, Tremain H, Ramos-Quiroga JA, McGorry PD, et al. Online interventions for cannabis use among adolescents and young adults: systematic review and meta-analysis. Early Interv Psychiatry. Aug 2022;16(8):821-844. [ CrossRef ] [ Medline ]
• Craig P, Dieppe P, Macintyre S, Michie S, Nazareth I, Petticrew M. Developing and evaluating complex interventions: the new Medical Research Council guidance. Int J Nurs Stud. May 2013;50(5):587-592. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Michie S, Abraham C, Eccles MP, Francis JJ, Hardeman W, Johnston M. Strengthening evaluation and implementation by specifying components of behaviour change interventions: a study protocol. Implement Sci. Feb 07, 2011;6:10. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Michie S, Richardson M, Johnston M, Abraham C, Francis J, Hardeman W, et al. The behavior change technique taxonomy (v1) of 93 hierarchically clustered techniques: building an international consensus for the reporting of behavior change interventions. Ann Behav Med. Aug 2013;46(1):81-95. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Michie S, Johnston M, Francis J, Hardeman W, Eccles M. From theory to intervention: mapping theoretically derived behavioural determinants to behaviour change techniques. Appl Psychol. Oct 2008;57(4):660-680. [ CrossRef ]
• Scott C, de Barra M, Johnston M, de Bruin M, Scott N, Matheson C, et al. Using the behaviour change technique taxonomy v1 (BCTTv1) to identify the active ingredients of pharmacist interventions to improve non-hospitalised patient health outcomes. BMJ Open. Sep 15, 2020;10(9):e036500. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Dombrowski SU, Sniehotta FF, Avenell A, Johnston M, MacLennan G, Araújo-Soares V. Identifying active ingredients in complex behavioural interventions for obese adults with obesity-related co-morbidities or additional risk factors for co-morbidities: a systematic review. Health Psychol Rev. 2012;6(1):7-32. [ CrossRef ]
• Michie S, Abraham C, Whittington C, McAteer J, Gupta S. Effective techniques in healthy eating and physical activity interventions: a meta-regression. Health Psychol. Nov 2009;28(6):690-701. [ CrossRef ] [ Medline ]
• Howlett N, García-Iglesias J, Bontoft C, Breslin G, Bartington S, Freethy I, et al. A systematic review and behaviour change technique analysis of remotely delivered alcohol and/or substance misuse interventions for adults. Drug Alcohol Depend. Oct 01, 2022;239:109597. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Higgins JP, Thomas J, Chandler J, Cumpston M, Li T, Page MJ, et al. Cochrane Handbook for Systematic Reviews of Interventions Version 6.4. London, UK. The Cochrane Collaboration; 2023.
• Page MJ, Moher D, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. PRISMA 2020 explanation and elaboration: updated guidance and exemplars for reporting systematic reviews. BMJ. Mar 29, 2021;372:n160. [ FREE Full text ] [ CrossRef ] [ Medline ]
• McGowan J, Sampson M, Salzwedel DM, Cogo E, Foerster V, Lefebvre C. PRESS peer review of electronic search strategies: 2015 guideline statement. J Clin Epidemiol. Jul 2016;75:40-46. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Halladay J, Petker T, Fein A, Munn C, MacKillop J. Brief interventions for cannabis use in emerging adults: protocol for a systematic review, meta-analysis, and evidence map. Syst Rev. Jul 25, 2018;7(1):106. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Michie S, van Stralen MM, West R. The behaviour change wheel: a new method for characterising and designing behaviour change interventions. Implement Sci. Apr 23, 2011;6:42. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Arnett JJ. Emerging adulthood. A theory of development from the late teens through the twenties. Am Psychol. May 2000;55(5):469-480. [ Medline ]
• Bramer WM, Giustini D, de Jonge GB, Holland L, Bekhuis T. De-duplication of database search results for systematic reviews in EndNote. J Med Libr Assoc. Jul 2016;104(3):240-243. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Hoffmann TC, Glasziou PP, Boutron I, Milne R, Perera R, Moher D, et al. Better reporting of interventions: template for intervention description and replication (TIDieR) checklist and guide. BMJ. Mar 07, 2014;348:g1687. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Presseau J, Ivers NM, Newham JJ, Knittle K, Danko KJ, Grimshaw JM. Using a behaviour change techniques taxonomy to identify active ingredients within trials of implementation interventions for diabetes care. Implement Sci. Apr 23, 2015;10:55. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Fontaine G, Cossette S, Maheu-Cadotte MA, Deschênes MF, Rouleau G, Lavallée A, et al. Effect of implementation interventions on nurses' behaviour in clinical practice: a systematic review, meta-analysis and meta-regression protocol. Syst Rev. Dec 05, 2019;8(1):305. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Fontaine G, Cossette S. A theory-based adaptive E-learning program aimed at increasing intentions to provide brief behavior change counseling: randomized controlled trial. Nurse Educ Today. Dec 2021;107:105112. [ CrossRef ] [ Medline ]
• Fontaine G, Cossette S. Development and design of E_MOTIV: a theory-based adaptive e-learning program to support nurses' provision of brief behavior change counseling. Comput Inform Nurs. Mar 01, 2023;41(3):130-141. [ CrossRef ] [ Medline ]
• Sobell LC, Sobell MB. Timeline follow-back: a technique for assessing self-reported alcohol consumption. In: Litten RZ, Allen JP, editors. Measuring Alcohol Consumption. Totowa, NJ. Humana Press; 1992.
• Stephens RS, Roffman RA, Simpson EE. Treating adult marijuana dependence: a test of the relapse prevention model. J Consult Clin Psychol. 1994;62(1):92-99. [ CrossRef ]
• Harris RJ, Deeks JJ, Altman DG, Bradburn MJ, Harbord RM, Sterne JA. Metan: fixed- and random-effects meta-analysis. Stata J. 2008;8(1):3-28. [ CrossRef ]
• Higgins JP, Thompson SG, Deeks JJ, Altman DG. Measuring inconsistency in meta-analyses. BMJ. Sep 06, 2003;327(7414):557-560. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Baumgartner C, Schaub MP, Wenger A, Malischnig D, Augsburger M, Walter M, et al. CANreduce 2.0 adherence-focused guidance for internet self-help among cannabis users: three-arm randomized controlled trial. J Med Internet Res. Apr 30, 2021;23(4):e27463. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Rooke S, Copeland J, Norberg M, Hine D, McCambridge J. Effectiveness of a self-guided web-based cannabis treatment program: randomized controlled trial. J Med Internet Res. Feb 15, 2013;15(2):e26. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Tossmann HP, Jonas B, Tensil MD, Lang P, Strüber E. A controlled trial of an internet-based intervention program for cannabis users. Cyberpsychol Behav Soc Netw. Nov 2011;14(11):673-679. [ CrossRef ] [ Medline ]
• StataCorp. Stata statistical software: release 18. StataCorp LLC. College Station, TX. StataCorp LLC; 2023. URL: https://www.stata.com/ [accessed 2023-11-28]
• Sterne JA, Savović J, Page MJ, Elbers RG, Blencowe NS, Boutron I, et al. RoB 2: a revised tool for assessing risk of bias in randomised trials. BMJ. Aug 28, 2019;366:l4898. [ FREE Full text ] [ CrossRef ] [ Medline ]
• McGuinness LA, Higgins JP. Risk-of-bias VISualization (robvis): an R package and Shiny web app for visualizing risk-of-bias assessments. Res Synth Methods. Jan 2021;12(1):55-61. [ CrossRef ] [ Medline ]
• Haddaway NR, Page MJ, Pritchard CC, McGuinness LA. PRISMA2020: an R package and Shiny app for producing PRISMA 2020-compliant flow diagrams, with interactivity for optimised digital transparency and open synthesis. Campbell Syst Rev. Mar 27, 2022;18(2):e1230. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Elliott JC, Carey KB. Correcting exaggerated marijuana use norms among college abstainers: a preliminary test of a preventive intervention. J Stud Alcohol Drugs. Nov 2012;73(6):976-980. [ CrossRef ] [ Medline ]
• Elliott JC, Carey KB, Vanable PA. A preliminary evaluation of a web-based intervention for college marijuana use. Psychol Addict Behav. Mar 2014;28(1):288-293. [ CrossRef ] [ Medline ]
• Lee CM, Neighbors C, Kilmer JR, Larimer ME. A brief, web-based personalized feedback selective intervention for college student marijuana use: a randomized clinical trial. Psychol Addict Behav. Jun 2010;24(2):265-273. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Buckner JD, Zvolensky MJ, Lewis EM. On-line personalized feedback intervention for negative affect and cannabis: a pilot randomized controlled trial. Exp Clin Psychopharmacol. Apr 2020;28(2):143-149. [ CrossRef ] [ Medline ]
• Goodness TM, Palfai TP. Electronic screening and brief intervention to reduce cannabis use and consequences among graduate students presenting to a student health center: a pilot study. Addict Behav. Jul 2020;106:106362. [ CrossRef ] [ Medline ]
• Palfai TP, Saitz R, Winter M, Brown TA, Kypri K, Goodness TM, et al. Web-based screening and brief intervention for student marijuana use in a university health center: pilot study to examine the implementation of eCHECKUP TO GO in different contexts. Addict Behav. Sep 2014;39(9):1346-1352. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Riggs NR, Conner BT, Parnes JE, Prince MA, Shillington AM, George MW. Marijuana eCHECKUPTO GO: effects of a personalized feedback plus protective behavioral strategies intervention for heavy marijuana-using college students. Drug Alcohol Depend. Sep 01, 2018;190:13-19. [ CrossRef ] [ Medline ]
• Bonar EE, Chapman L, Pagoto S, Tan CY, Duval ER, McAfee J, et al. Social media interventions addressing physical activity among emerging adults who use cannabis: a pilot trial of feasibility and acceptability. Drug Alcohol Depend. Jan 01, 2023;242:109693. [ CrossRef ] [ Medline ]
• Bonar EE, Goldstick JE, Chapman L, Bauermeister JA, Young SD, McAfee J, et al. A social media intervention for cannabis use among emerging adults: randomized controlled trial. Drug Alcohol Depend. Mar 01, 2022;232:109345. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Walukevich-Dienst K, Neighbors C, Buckner JD. Online personalized feedback intervention for cannabis-using college students reduces cannabis-related problems among women. Addict Behav. Nov 2019;98:106040. [ CrossRef ] [ Medline ]
• Côté J, Tessier S, Gagnon H, April N, Rouleau G, Chagnon M. Efficacy of a web-based tailored intervention to reduce cannabis use among young people attending adult education centers in Quebec. Telemed J E Health. Nov 2018;24(11):853-860. [ CrossRef ] [ Medline ]
• Cunningham JA, Schell C, Bertholet N, Wardell JD, Quilty LC, Agic B, et al. Online personalized feedback intervention to reduce risky cannabis use. Randomized controlled trial. Internet Interv. Nov 14, 2021;26:100484. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Copeland J, Rooke S, Rodriquez D, Norberg MM, Gibson L. Comparison of brief versus extended personalised feedback in an online intervention for cannabis users: short-term findings of a randomised trial. J Subst Abuse Treat. May 2017;76:43-48. [ CrossRef ] [ Medline ]
• Jonas B, Tensil MD, Tossmann P, Strüber E. Effects of treatment length and chat-based counseling in a web-based intervention for cannabis users: randomized factorial trial. J Med Internet Res. May 08, 2018;20(5):e166. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Schaub MP, Wenger A, Berg O, Beck T, Stark L, Buehler E, et al. A web-based self-help intervention with and without chat counseling to reduce cannabis use in problematic cannabis users: three-arm randomized controlled trial. J Med Internet Res. Oct 13, 2015;17(10):e232. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Sinadinovic K, Johansson M, Johansson AS, Lundqvist T, Lindner P, Hermansson U. Guided web-based treatment program for reducing cannabis use: a randomized controlled trial. Addict Sci Clin Pract. Feb 18, 2020;15(1):9. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Kanfer FH. Implications of a self-regulation model of therapy for treatment of addictive behaviors. In: Miller WR, Heather N, editors. Treating Addictive Behaviors. Boston, MA. Springer; 1986;29-47.
• Mohr DC, Cuijpers P, Lehman K. Supportive accountability: a model for providing human support to enhance adherence to eHealth interventions. J Med Internet Res. Mar 10, 2011;13(1):e30. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Marlatt GA, Baer JS, Kivlahan DR, Dimeff LA, Larimer ME, Quigley LA, et al. Screening and brief intervention for high-risk college student drinkers: results from a 2-year follow-up assessment. J Consult Clin Psychol. Aug 1998;66(4):604-615. [ CrossRef ]
• Miller WR, Rollnick S. Motivational Interviewing: Preparing People for Change. New York, NY. Guilford Press; 2002.
• Prince MA, Carey KB, Maisto SA. Protective behavioral strategies for reducing alcohol involvement: a review of the methodological issues. Addict Behav. Jul 2013;38(7):2343-2351. [ CrossRef ] [ Medline ]
• Lundqvist TN. Cognitive Dysfunctions in Chronic Cannabis Users Observed During Treatment: An Integrative Approach. Stockholm, Sweden. Almqvist & Wiksell; 1997.
• Kanter JW, Puspitasari AJ, Santos MM, Nagy GA. Behavioural activation: history, evidence and promise. Br J Psychiatry. May 2012;200(5):361-363. [ CrossRef ] [ Medline ]
• Jaffee WB, D'Zurilla TJ. Personality, problem solving, and adolescent substance use. Behav Ther. Mar 2009;40(1):93-101. [ CrossRef ] [ Medline ]
• Miller W, Rollnick S. Motivational Interviewing: Preparing People to Change Addictive Behavior. New York, NY. The Guilford Press; 1991.
• Gordon JR, Marlatt GA. Relapse Prevention: Maintenance Strategies in the Treatment of Addictive Behaviors. 2nd edition. New York, NY. The Guilford Press; 2005.
• Platt JJ, Husband SD. An overview of problem-solving and social skills approaches in substance abuse treatment. Psychotherapy (Chic). 1993;30(2):276-283. [ FREE Full text ]
• Steinberg KL, Roffman R, Carroll K, McRee B, Babor T, Miller M. Brief counseling for marijuana dependence: a manual for treating adults. Center for Substance Abuse Treatment, Substance Abuse and Mental Health Services Administration, US Department of Health and Human Services. URL: https:/​/store.​samhsa.gov/​product/​brief-counseling-marijuana-dependence-manual-treating-adults/​sma15-4211 [accessed 2024-03-23]
• de Shazer S, Dolan Y. More Than Miracles: The State of the Art of Solution-Focused Brief Therapy. Oxfordshire, UK. Routledge; 2007.
• Copeland J, Swift W, Roffman R, Stephens R. A randomized controlled trial of brief cognitive-behavioral interventions for cannabis use disorder. J Subst Abuse Treat. Sep 2001;21(2):55-65. [ CrossRef ] [ Medline ]
• Linke S, McCambridge J, Khadjesari Z, Wallace P, Murray E. Development of a psychologically enhanced interactive online intervention for hazardous drinking. Alcohol Alcohol. 2008;43(6):669-674. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Wang ML, Waring ME, Jake-Schoffman DE, Oleski JL, Michaels Z, Goetz JM, et al. Clinic versus online social network-delivered lifestyle interventions: protocol for the get social noninferiority randomized controlled trial. JMIR Res Protoc. Dec 11, 2017;6(12):e243. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Sepah SC, Jiang L, Peters AL. Translating the diabetes prevention program into an online social network: validation against CDC standards. Diabetes Educ. Jul 2014;40(4):435-443. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Cunningham JA, van Mierlo T. The check your cannabis screener: a new online personalized feedback tool. Open Med Inform J. May 07, 2009;3:27-31. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Bertholet N, Cunningham JA, Faouzi M, Gaume J, Gmel G, Burnand B, et al. Internet-based brief intervention for young men with unhealthy alcohol use: a randomized controlled trial in a general population sample. Addiction. Nov 2015;110(11):1735-1743. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Walker DD, Roffman RA, Stephens RS, Wakana K, Berghuis J, Kim W. Motivational enhancement therapy for adolescent marijuana users: a preliminary randomized controlled trial. J Consult Clin Psychol. Jun 2006;74(3):628-632. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Miller MB, Leffingwell T, Claborn K, Meier E, Walters S, Neighbors C. Personalized feedback interventions for college alcohol misuse: an update of Walters and Neighbors (2005). Psychol Addict Behav. Dec 2013;27(4):909-920. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Ajzen I. From intentions to actions: a theory of planned behavior. In: Kuhl J, Beckmann J, editors. Action Control. Berlin, Germany. Springer; 1985;11-39.
• Dennis M, Titus JC, Diamond G, Donaldson J, Godley SH, Tims FM, et al. The Cannabis Youth Treatment (CYT) experiment: rationale, study design and analysis plans. Addiction. Dec 11, 2002;97 Suppl 1(s1):16-34. [ CrossRef ] [ Medline ]
• Simons JS, Dvorak RD, Merrill JE, Read JP. Dimensions and severity of marijuana consequences: development and validation of the Marijuana Consequences Questionnaire (MACQ). Addict Behav. May 2012;37(5):613-621. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Legleye S. The Cannabis Abuse Screening Test and the DSM-5 in the general population: optimal thresholds and underlying common structure using multiple factor analysis. Int J Methods Psychiatr Res. Jun 10, 2018;27(2):e1597. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Legleye S, Karila LM, Beck F, Reynaud M. Validation of the CAST, a general population Cannabis Abuse Screening Test. J Subst Use. Jul 12, 2009;12(4):233-242. [ CrossRef ]
• Sobell LC, Sobell MB. Timeline follow back. In: Litten RZ, Allen JP, editors. Measuring Alcohol Consumption: Psychosocial and Biochemical Methods. Totowa, NJ. Humana Press; 1992;41-72.
• White HR, Labouvie EW, Papadaratsakis V. Changes in substance use during the transition to adulthood: a comparison of college students and their noncollege age peers. J Drug Issues. Aug 03, 2016;35(2):281-306. [ CrossRef ]
• White HR, Labouvie EW. Towards the assessment of adolescent problem drinking. J Stud Alcohol. Jan 1989;50(1):30-37. [ CrossRef ] [ Medline ]
• Cloutier RM, Natesan Batley P, Kearns NT, Knapp AA. A psychometric evaluation of the Marijuana Problems Index among college students: confirmatory factor analysis and measurement invariance by gender. Exp Clin Psychopharmacol. Dec 2022;30(6):907-917. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Guo H, Yang H, Yuan G, Zhu Z, Zhang K, Zhang X, et al. Effectiveness of information and communication technology (ICT) for addictive behaviors: an umbrella review of systematic reviews and meta-analysis of randomized controlled trials. Comput Hum Behav. Oct 2023;147:107843. [ CrossRef ]
• Grigsby TJ, Lopez A, Albers L, Rogers CJ, Forster M. A scoping review of risk and protective factors for negative cannabis use consequences. Subst Abuse. Apr 07, 2023;17:11782218231166622. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Harkin B, Webb TL, Chang BP, Prestwich A, Conner M, Kellar I, et al. Does monitoring goal progress promote goal attainment? A meta-analysis of the experimental evidence. Psychol Bull. Feb 2016;142(2):198-229. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Samdal GB, Eide GE, Barth T, Williams G, Meland E. Effective behaviour change techniques for physical activity and healthy eating in overweight and obese adults; systematic review and meta-regression analyses. Int J Behav Nutr Phys Act. Mar 28, 2017;14(1):42. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Garnett C, Crane D, Brown J, Kaner E, Beyer F, Muirhead C. Behavior Change Techniques Used in Digital Behavior Change Interventions to Reduce Excessive Alcohol Consumption: A Meta-regression. Ann Behav Med May 18. 2018;52(6):A. [ CrossRef ]
• Kaner EF, Beyer FR, Muirhead C, Campbell F, Pienaar ED, Bertholet N, et al. Effectiveness of brief alcohol interventions in primary care populations. Cochrane Database Syst Rev. Feb 24, 2018;2(2):CD004148. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Sedrati H, Belrhiti Z, Nejjari C, Ghazal H. Evaluation of mobile health apps for non-medical cannabis use: a scoping review. Procedia Comput Sci. 2022;196:581-589. [ CrossRef ]
• Curtis BL, Ashford RD, Magnuson KI, Ryan-Pettes SR. Comparison of smartphone ownership, social media use, and willingness to use digital interventions between generation Z and millennials in the treatment of substance use: cross-sectional questionnaire study. J Med Internet Res. Apr 17, 2019;21(4):e13050. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Schünemann H, Brożek J, Guyatt G, Oxman A. The GRADE Handbook. London, UK. The Cochrane Collaboration; 2013.
• Guyatt GH, Oxman AD, Schünemann HJ, Tugwell P, Knottnerus A. GRADE guidelines: a new series of articles in the Journal of Clinical Epidemiology. J Clin Epidemiol. Apr 2011;64(4):380-382. [ CrossRef ] [ Medline ]
• Guyatt GH, Oxman AD, Vist GE, Kunz R, Falck-Ytter Y, Alonso-Coello P, et al. GRADE: an emerging consensus on rating quality of evidence and strength of recommendations. BMJ. Apr 26, 2008;336(7650):924-926. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Hjorthøj CR, Hjorthøj AR, Nordentoft M. Validity of Timeline Follow-Back for self-reported use of cannabis and other illicit substances--systematic review and meta-analysis. Addict Behav. Mar 2012;37(3):225-233. [ CrossRef ] [ Medline ]
• Robinson SM, Sobell LC, Sobell MB, Leo GI. Reliability of the Timeline Followback for cocaine, cannabis, and cigarette use. Psychol Addict Behav. Mar 2014;28(1):154-162. [ CrossRef ] [ Medline ]
• Abraham C, Michie S. A taxonomy of behavior change techniques used in interventions. Health Psychol. May 2008;27(3):379-387. [ CrossRef ] [ Medline ]
• Garrett JJ. The Elements of User Experience: User-Centered Design for the Web and Beyond. London, UK. Pearson Education; 2010.
• Lorencatto F, West R, Bruguera C, Brose LS, Michie S. Assessing the quality of goal setting in behavioural support for smoking cessation and its association with outcomes. Ann Behav Med. Apr 24, 2016;50(2):310-318. [ FREE Full text ] [ CrossRef ] [ Medline ]

Abbreviations

Edited by T Leung, G Eysenbach; submitted 30.11.23; peer-reviewed by H Sedrati; comments to author 02.01.24; revised version received 09.01.24; accepted 08.03.24; published 17.04.24.

©José Côté, Gabrielle Chicoine, Billy Vinette, Patricia Auger, Geneviève Rouleau, Guillaume Fontaine, Didier Jutras-Aswad. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 17.04.2024.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well as this copyright and license information must be included.

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Resolving Workforce Skills Gaps with AI-Powered Insights

Ongoing digital transformation requires a workforce that is proficient in a wide variety of new skills. This briefing explores the use of AI in quantifying such proficiency, through a process known as skills inference. We introduce this concept by means of a case study of Johnson & Johnson, showing how skills inference can provide detailed insight into workforce skills gaps and thereby guide employees’ career development and leaders’ strategic workforce planning.

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Digital transformation is a continuous journey, with new technologies emerging on an ongoing basis. Yet for organizations to harness these technologies, their workforce needs to develop an increasingly expanding variety of skills. Many organizations struggle here: leaders responding to a 2022 MIT CISR survey[foot]MIT CISR 2022 Decision Rights for the Digital Era Survey (N=342).[/foot] estimated that on average 38 percent of their organization’s workforce required fundamental retraining or replacement within three years to address workforce skills gaps.[foot]Workforce skills gaps are the discrepancy between the collective skills proficiency that an organization requires to achieve its strategic objectives and the current skills proficiency of its workforce.[/foot]

To make evidence-based decisions on how to best resolve such skills gaps, however, organizations first need to move beyond estimates. What’s required is precise insight into their workforce’s current skills and how proficiency in these skills differs from that needed for future success. Functional competency models often fall short in this regard, as they need to be validated for each job and thus can’t keep pace with rapid technological change. Relying on employee or manager feedback from interviews and surveys may lead to inaccuracies because of inherent biases. And active assessment of an entire workforce across a wide range of skills is both impractical and costly.

Artificial intelligence (AI) offers a new and scalable alternative to such approaches by enabling skills inference , which we define as the process of analyzing employee data to quantify skills proficiency. This allows for detailed insight into workforce skills gaps, which can, for instance, be broken down by line of business and geography. In this briefing we explore the AI-powered skills inference process, and illustrate how resulting insights can help resolve workforce skills gaps by drawing on lessons learned from a case study of global healthcare company Johnson & Johnson (J&J).

Digital Talent Transformation at J&J

J&J’s mission is to profoundly impact health for humanity. As the trajectory of health and wellbeing is increasingly determined by emerging technology and a growth in data and computing power, J&J’s Technology group has become a cornerstone for the organization’s future success. It drives technological innovation at J&J and modernizes the organization’s tech ecosystem. More importantly, however, the Technology group is enabling J&J to evolve as a digital organization by helping to develop the digital acumen of its global workforce of over 130,000 employees.[foot]This case study of J&J draws from N. van der Meulen, O. Tona, I. A. Someh, B. H. Wixom, and D. E. Leidner, “Developing a Digital-First Workforce: AI-Driven Skills Enablement at Johnson & Johnson,” MIT CISR Working Paper No. 461, November 2023, https://cisr.mit.edu/publication/MIT_CISRwp461_JohnsonandJohnsonAIDrivenSkills_VanderMeulenTonaSomehWixomLeidner .[/foot]

To build a digital organization, you’ve got to take people’s amazing talents and create an “ and ” strategy for technology. To be relevant and future ready, you for instance need to have your commercial expertise and digital expertise. Scientific expertise and digital. You can have the best technology, but without that integrated way of thinking, it won’t transform anything.

Jim Swanson, Executive Vice President and Chief Information Officer, Johnson & Johnson

In early 2020, J&J’s Technology group began its journey of building the organization’s digital acumen with the help of AI-powered skills inference, starting with its own workforce of 4,000 technologists. By the time the group introduced skills inference to other parts of J&J in 2021, it had successfully put in place a three-step process, as illustrated in figure 1. First, it created a skills taxonomy , defining what skills would be required across the organization to reimagine business processes and develop future digital offerings. Second, the group gathered skills evidence by selecting and preparing employee data sources to analyze. And third, it conducted a passive skills assessment , for which it trained a machine learning model to measure the skills proficiencies of each employee. The result was workforce insights that guided employees’ personal development and enhanced leaders’ strategic workforce planning, both of which reduced skills gaps at J&J.[foot]J&J used skills insights only as a guide for employees’ own development; the insights did not factor into employees’ performance reviews. The organization used deidentified insights at an aggregate level to support strategic workforce planning.[/foot]

Figure 1: The Three Steps of the Skills Inference Process

Skills inference involves (1) defining a taxonomy of skills required to realize your organization’s purpose and strategic objectives, (2) gathering employee data as evidence of these skills, and (3) conducting an assessment of this evidence to quantify employees’ skill proficiency.

Defining a Skills Taxonomy

The journey of J&J’s Technology group began with figuring out what future skills J&J would need. Guided by industry benchmarks, its Digital Talent team—a team dedicated to driving the organization’s transformation with the best and most diverse talent—examined strategic plans throughout the organization to create a J&J-specific skills taxonomy. This taxonomy comprised a list of forty-one skills the team referred to as “future ready” (e.g., master data management, robotic process automation) grouped into eleven capabilities (e.g., “Scientific & Digital Health Technology”) that would be required to realize the organization’s purpose and strategic objectives.

To ensure the taxonomy’s accuracy and gain broad support for it, the Digital Talent team asked over one hundred senior leaders from across the company to validate the list. Each indicated whether the taxonomy reflected the needs of their area of business—both at that moment and in the long term—and offered their perception of the current and required state of the listed skills. Given the diversity of J&J’s operations, required proficiency levels naturally varied by functional area. For instance, employees in Innovative Medicine might need stronger capabilities in data engineering and analytics, whereas those in MedTech might need to be especially skilled in software engineering.

Additional tailoring of the taxonomy’s skill and proficiency definitions to J&J’s unique context and terminology fell to subject matter experts (SMEs), employees known for their expertise and thought leadership in a particular future-ready skill. These SMEs crafted current, precise, and yet broadly applicable definitions that novices and experts alike could understand. The result was a skills taxonomy that clearly communicated to every employee what future-ready skills were considered top priorities for J&J’s leadership. Moreover, the taxonomy specified how skills would manifest in employees’ data.

Gathering Skills Evidence

As a machine learning algorithm can only learn from provided data, the quality of chosen data sources is key to the overall skills inference process. As such, the Digital Talent team collaborated with HR data experts to identify data sources that were used across most of the organization yet also provided enough semantic data to calculate skill proficiency, ideally providing evidence for 60 to 70 percent of each employee’s skills. Four of J&J’s data sources fit these criteria: the organization’s HR information system, recruiting database, and learning management system, and one of its project management platforms.

To improve data quality, leaders encouraged employees to update the data fields in those systems that the algorithm would use to infer their skill proficiency. For instance, J&J’s HR information system allowed employees to showcase their experiences and accomplishments by sharing information about their job history, education, certifications, recognitions, goals, personal interests, and volunteering activities. If these fields were missing or incomplete, the algorithm could not infer from them. The Digital Talent team therefore also illustrated how employees could update their data most effectively by providing examples of rich statements that the algorithm could pick up on in gradations of good, better, and best quality.

For employees to be willing to provide additional data for the AI to infer from, however, they first had to trust the skills inference initiative and the intended purpose of the AI model. In accordance with J&J’s commitment to the transparent use of AI, the Digital Talent team and senior leaders communicated early and often with employees—both electronically and in person. They explained how the skills inference process could help employees identify their current skills proficiency and discover new development opportunities. They also gave them the option to opt out at any time. In addition, the Digital Talent team enhanced employee trust and engagement by establishing strict norms of acceptable data use with the help of HR data experts, multiple oversight functions at J&J, and external partners. These norms safeguarded compliance, but also respected employee privacy and reduced the risk of bias by maximizing accountability, explainability, fairness, privacy, and transparency regarding the skills inference process.

Conducting a Skills Assessment

To measure employees’ skills proficiency, the Digital Talent team relied on a proven machine learning model augmented by human input. An experienced solution provider supported the team and provided the model, which used natural language processing to generate proficiency scores for each of the forty-one future-ready skills in J&J’s taxonomy.[foot]Looking ahead, the Digital Talent team is now exploring whether generative AI can further enhance the skills inference process at J&J.[/foot] These scores ranged from zero (no skill detected) to five (thought leadership).

To improve the accuracy and reliability of the inferred scores, the Digital Talent team asked employees to self-assess their skills proficiency and managers to evaluate that of their direct reports. To avoid bias, the solution showed the proficiency scores inferred by the AI only after the participants submitted their perceptions of proficiency levels. With this input, the model generated an “agreement score” that quantified the consistency between the perceived levels and inferred scores. The goal was not to achieve perfect agreement, but rather directional accuracy: the Digital Talent team considered the inferred scores usable if they deviated by at most one point (out of five) from the perceived proficiency levels.

Limit Use Cases for Workforce Insights

Skill proficiency data has many potential uses. Yet, for employees to trust the skills inference process and not opt out of it or otherwise skew the data, it is important to limit what this data is used for. J&J therefore only used skills inference to provide more personalized career development journeys for employees, and (at an aggregate level) to support leaders’ strategic workforce planning efforts. Other use cases were not permitted by J&J’s Privacy function.

With a detailed understanding of their skills proficiency, employees could chart personalized career paths, supported by learning and development opportunities uniquely tailored to their skill proficiency levels. After the first round of skills inference, J&J saw a 20 percent uptick in participants’ voluntary learning activities. These activities not only enhanced practical expertise but also fostered habits of continuous learning and increased knowledge sharing within the organization. In subsequent years, these habits of continuous learning have only become more ingrained, as demonstrated by strong adoption of J&J Learn, the organization’s global, AI-powered learning and development ecosystem that offers training programs, growth assignments, and mentoring opportunities. By March 2024, over 90 percent of employees in J&J’s Technology group had accessed J&J Learn.

Leaders used an executive dashboard to gauge aggregated employee skills proficiency, with insights broken down by geographic region and line of business. This dashboard, displayed as a heat map, resulted in more informed hiring processes, enhanced retention efforts, and improved talent movement and advancement across J&J. The executive committee used a scorecard to track key performance indicators related to these outcomes, while each operating company and supporting function devised its own metrics based on its strategic plans and the capabilities it had to develop.

Skills Inference: People + Technology = Workforce Insights

Resolving skills gaps no longer falls to human resources or learning and development functions alone. Instead, it has become a strategic imperative, reshaping organizational capabilities based on workforce insights. AI emerged as a powerful tool in this endeavor, enabling skills inference at a scale previously unimaginable. However, the success of this process hinges on more than just advanced technologies. It continuously requires collective effort, trust, and support of stakeholders—including employees—across many organizational levels and functions. Just as digital transformation is an ongoing journey, so too is the need to regularly (re)define the skills taxonomy, gather new skills evidence, and conduct skills assessments as required skills evolve.

For those looking to embark on their own skills inference journey today, we suggest you first focus on these inherently human success factors. Begin by generating employee support with a bounded use case that embraces your workforce’s potential and signals a commitment to developing employee skills. Then gather broad input from experts to declare your desired workforce capabilities in the form of a skills taxonomy that is aligned with your purpose and strategic objectives. That way, your employees can focus their development efforts while simultaneously providing more informed input for an eventual AI to process. Start by laying this groundwork today, so that your organization may reap the rewards of AI-powered workforce insights in the future.

© 2024 MIT Center for Information Systems Research, van der Meulen, Tona, and Leidner. MIT CISR Research Briefings are published monthly to update the center’s member organizations on current research projects.

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Ai-powered skills inference.

Working Paper: Case Study

Developing a digital-first workforce: ai-driven skills enablement at johnson & johnson.

About the Researchers

Nick van der Meulen, Research Scientist, MIT Center for Information Systems Research (CISR)

Olgerta Tona, Lecturer, University of Gothenburg and Academic Research Fellow, MIT CISR

Dorothy E. Leidner, Professor, University of Virginia and Academic Research Fellow, MIT CISR

Mit center for information systems research (cisr).

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