how to cite a website in apa in a research paper

Citing a website in APA style

When citing websites in APA style, your citation should follow one of the basic formats below.

Webpage with an individual author 

As is common in APA format, write the title of the webpage in “sentence case.” In other words, capitalize only the first letter, any proper nouns, and the first letter of a subtitle (after a colon).

Author Last Name, First Initial. Middle Initial. (Year, Month Day). Title . Website name. URL

Nadworny, E. (2019, October 5). College students: How to make office hours less scary . NPR. https://www.npr.org/2019/10/05/678815966/college-students-how-to-make-office-hours-less-scary

Webpage with a group author

When the author and site name are the same, you can omit the site name from the citation. In the example below, both the group author and the site name are the CDC, so the citation does not repeat the website name after the title.

Name of group author. (Year, Month Day). Title . Website name. URL

Centers for Disease Control and Prevention. (2021, August 23). Adverse Childhood Experiences (ACEs).   https://www.cdc.gov/vitalsigns/aces/index.html

Webpage with no date

If a publication date cannot be located, use “ n.d. ”, short for “no date”.

Name of group or individual author. (n.d.). Title . Website name. URL

National Nurses United. (n.d.). Medicare for all: It’s time for guaranteed health care for everyone! https://www.nationalnursesunited.org/medicare-for-all

More information

To see more examples and other situations of citing sources in APA style, see the library's online APA Citation guide . You can also find the Publication Manual of the American Psychological Association (7th edition) in the Knowledge Center’s reference collection and the Book Stacks. Purdue’s Online Writing Lab has a comprehensive guide to APA style .

• Bibliography Answers

How to cite a website in APA, MLA, or Harvard style

There are many different ways to cite a website, depending on which citation style you need to format it in.

 The easy way to cite a website in any citation style

Use our citation generator below to automatically cite a website in any style, including APA, MLA 7 and 8, and Harvard. Just select the style you need, copy the URL into the search box, and press search. We’ll do the rest.

 The manual way to cite a website

To cite a website by hand just follow the instructions below. For the 3 most popular styles–APA, MLA 8, and Harvard–this is as follows:

 In APA style

You need to locate these details for the website: page or article author, page or article title, website name, published date, access date, page URL (web address) .

• The author can typically be found on the page, but if there isn’t one listed you can use the website name in its place.
• The page title can be found near the top of the page, and you can also find it by hovering your mouse over the browser tab.
• The website name can usually be found in the web address or by looking for a logo or similar at the very top of the page.
• There often isn’t a publish date , but if there is it’ll be very close to the page title.
• The access date is the date you took information from the article (usually today).
• The page URL can be copied straight from the address bar of your browser and will start with either http:// or https://.

Then use this template, replacing the colored placeholders with the information you found on the page:

Author last name , author first name initial . ( published year , published month and day ). Page title . Retrieved accessed month and day , accessed year , from article URL .

The final formatted citation should look like this:

Ingle, S. (2018, February 11). Winter Olympics was hit by cyber-attack, officials confirm. Retrieved July 24, 2018, from https://www.theguardian.com/sport/2018/feb/11/winter-olympics-was-hit-by-cyber-attack-officials-confirm.

For a more comprehensive guide, including what to do when you can’t find certain details, have a look at our more in-depth guide to citing a website in APA format .

 In MLA 8 style

Here are the specific details you need to find on the page: page or article author, page or article title, website name, published date, access date, page URL (web address) .

Then use this template:

Author last name , author first name . “ Page title .” website name , published date day, month, year , page URL . Accessed accessed date day, month, year .

Ingle, Sean. “Winter Olympics Was Hit by Cyber-Attack, Officials Confirm.” The Guardian , 11 Feb. 2018, https://www.theguardian.com/sport/2018/feb/11/winter-olympics-was-hit-by-cyber-attack-officials-confirm. Accessed 13 July 2018.

For a more comprehensive guide, including what to do when you can’t find certain details, have a look at our more in-depth guide to citing a website in MLA 8 format .

 In Harvard style

First, find these details for the website: page or article author, page or article title, website name, published date, access date, page URL (web address) .

Author last name , author firstname initial ( published date year ). Page title . [online] website name . Available at: page URL [Accessed accessed date day, month, year ].

Ingle, S. (2018). Winter Olympics was hit by cyber-attack, officials confirm . [online] The Guardian. Available at: https://www.theguardian.com/sport/2018/feb/11/winter-olympics-was-hit-by-cyber-attack-officials-confirm [Accessed 13 Jul. 2018].

Daniel is a qualified librarian, former teacher, and citation expert. He has been contributing to MyBib since 2018.

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Research Guides

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APA Style 7th Edition Tutorials for Students in Psychology and Social Work

What is apa style.

• The Importance of Citing

Why is APA Style needed?

How do i get started with apa style, let us practice what we have learned, attribution and acknowledgement.

• Basics of APA Style Tutorial
• Reference Entry Elements
• Reference Examples
• Reference List
• In-Text Citations
• Student Paper Format
• Managing References - Zotero

Origination of APA Style

• Where did APA Style come from?

Commonly Used APA Related Terms

Abstract : Abstract is a brief synopses of article. It provides a brief but comprehensive summary of the article. 

Citing : In the context of academic writing, citing is the act of acknowledging the sources of information you have used when writing your work.

Citation:  A citation gives credit to a source, and contains publication information such as author(s), title and date.

DOI (digital object identifier): It is a unique alphanumeric string assigned to a digital object, mainly a scholarly article, to provide a persistent link to its location on the internet. 

In-Text Citation : It is a brief note that appears within the body of the paper and briefly identifies the cited work by its author and date of publication. An in-text citation should always match the corresponding entry in the reference list at the end of paper.

Paraphrasing : A paraphrase restates another’s idea (or your own previously published idea) in your own words. 

Plagiarism : It is the act of presenting the words, ideas, or images of another as your own; it denies creators of content the credit they are due. 

Quoting : It is the act of reproducing the exact wording used by the original author. Direct quotations appear within quotation marks and end with a citation.

Reference : It contains details about one cited work, generally including four elements:  author, date, title, and source.  

Reference List : It identifies all the sources you cited in the text of your paper. It generally is at the end of the paper and definitely on a new page after the text of your paper. 

APA Style is the most common writing style used in college and career. Its purpose is to promote excellence in communication by helping writers create clear, precise, and inclusive sentences with a straightforward scholarly tone. It addresses areas of writing such as how to

• format a paper so it looks professional;
• credit other people’s words and ideas via citations and references to avoid plagiarism; and
• describe other people with dignity and respect using inclusive, bias-free language.

APA Style is primarily used in the behavioral sciences, which are subjects related to people, such as psychology, education, and nursing. It is also used by students in business, engineering, communications, and other classes. Students use it to write academic essays and research papers in college, and professionals use it to conduct, report, and publish scientific research.

In addition, APA Style provides you with a powerful tool that will hep you avoid deliberate or unintentional plagiarism. Please review the Avoiding Plagiarism Guide created by the APA experts to understand what two common types of plagiarism are and how to avoid them. 

Why is learning citations important? Citations help readers understand where the information used in your paper comes from, enabling them to trace the path of that information. When readers wish to explore a specific point or reference cited in the text, citations make it easier by providing information about your sources in a standardized format.

Besides showing readers where you obtained information, using citations also has a strong ethical purpose. In academic writing, it is important to credit ideas that are not your own. Citations allow you to integrate the ideas of others with your own thoughts in a fair and honest way.

The reference formats for APA Style manuals are as follows:

APA Style provides a foundation for effective scholarly communication because it helps authors present their ideas in a clear and concise, and organized manner.  Uniformity and consistency enable readers to (a) focus on the ideas being presented rather than formatting and (b) scan works quickly for key points, findings, and sources. When style works best, ideas flow logically, sources are credited appropriately, and papers are organized predictably and consistently. 

Students are encouraged to first learn about APA Style by reading works written in APA Style. A couple of guides created by APA experts from the American Psychological Association can help you with that:

Anatomy of a Journal Article   https://apastyle.apa.org/instructional-aids/anatomy-journal-article.pdf

Scholarly journal articles share a common anatomy or structure. Each part of an article serves a specific purpose. The handout of  Anatomy of a Journal Article explains how journal articles are structured and how to become more efficient at reading and understanding them. Understanding the structure of a scholarly article and the purpose of each part helps you grasp a strategy called targeted reading. Targeted reading means to read specific sections of research articles first to determine if the article seems useful for your research topic. This way you will save time, find useful article faster, and choose which articles to read in full.

Reading and Understanding Abstracts https://apastyle.apa.org/instructional-aids/reading-abstracts.pdf

Abstracts are short summaries of scientific research articles. The handout of Reading & Understanding Abstracts explains the definition and purpose of abstracts and the benefits of reading them, including analysis of a sample abstract. The skill of reading and understanding abstracts of scholarly articles not only saves time but also helps you conduct better research and write more effectively.

APA Style Writing Principles https://apastyle.apa.org/instructional-aids/writing-principles.pdf

The poster created by APA experts shows the three main principles of APA Style: clarity, precision, and inclusion and lists steps on how to achieve them. As a student writer, you always should write your academic paper with clarity, precision, and inclusion. 

Research Article Activity https://apastyle.apa.org/instructional-aids/apa-style-research-activity.pdf

Reading research articles is not an easy task for you as a student. The Research Article Activity designed by APA Style experts aims to make it easy to read and understand a scholarly article. This activity worksheet helps you find, cite, analyze, and summarize a research article. Completing this activity breaks down a lengthy research article into easily understandable chunks. This way helps you better understand the study in the article before you write about it. 

The information in this Guide   is courtesy of   the official APA Style website by the American Psychological Association.

Source Credit: Information on this LibGuide comes from APA Style website https://apastyle.apa.org/ This website has a wealth of free and authoritative resources designed to help anyone new to APA Style.

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• Last Updated: Apr 6, 2024 12:06 PM
• URL: https://research.ewu.edu/APAStyleTutorial

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How to Cite a Research Paper in APA

Last Updated: October 19, 2022 Fact Checked

This article was co-authored by wikiHow Staff . Our trained team of editors and researchers validate articles for accuracy and comprehensiveness. wikiHow's Content Management Team carefully monitors the work from our editorial staff to ensure that each article is backed by trusted research and meets our high quality standards. There are 12 references cited in this article, which can be found at the bottom of the page. This article has been fact-checked, ensuring the accuracy of any cited facts and confirming the authority of its sources. This article has been viewed 159,148 times. Learn more...

If you’re citing a research article or paper in APA style, you’ll need to use a specific citation format that varies depending on the source. Assess whether your source is an article or report published in an academic journal or book, or whether it is an unpublished research paper, such as a print-only thesis or dissertation. Either way, your in-text citations will need to include information about the author (if available) and the date when your source was published or written.

Sample Citations

Writing an In-Text Citation

• For example, you may write, “Gardener (2008) notes, ‘There are several factors to consider about lobsters’ (p. 199).”

• For example, you may write, “‘There are several factors to consider about lobsters’ (Gardner, 2008, p. 199).” Or, “The paper claims, ‘The fallen angel trope is common in religious and non-religious texts’ (Meek & Hill, 2015, p.13-14).”
• For articles with 3-5 authors, write out the names of all the authors the first time you cite the source. For example: (Hammett, Wooster, Smith, & Charles, 1928). In subsequent citations, write only the first author’s name, followed by et al.: (Hammett et al., 1928).
• If there are 6 or more authors for the paper, include the last name of the first author listed and then write "et al." to indicate that there are more than 5 authors.
• For example, you may write, "'This is a quote' (Minaj et al., 1997, p. 45)."

• For example, you may write, “‘The risk of cervical cancer in women is rising’ (American Cancer Society, 2012, p. 2).”

• For example, you may write, “‘Shakespeare may have been a woman’ (“Radical English Literature,” 2004, p. 45).” Or, “The paper notes, ‘There is a boom in Virgin Mary imagery’ (“Art History in Italy,” 2011, p. 32).”

• For example, you may write, “‘There are several factors to consider about lobsters’ (Gardner, 2008, p. 199).” Or, “The paper claims, ‘The fallen angel trope is common in religious and non-religious texts’ (“Iconography in Italian Frescos,” 2015, p.13-14).”

• For example, you may write, “‘There are several factors to consider about lobsters’ (Gardner, 2008, p. 199).” Or, “The paper claims, ‘The fallen angel trope is common in religious and non-religious texts’ (“Iconography in Italian Frescos,” 2015, p.145-146).”

• For example, you may write, “‘The effects of food deprivation are long-term’ (Mett, 2005, para. 18).”

Creating a Reference List Citation for a Published Source

• Material on websites is also considered “published,” even if it’s not peer-reviewed or associated with a formal publishing company.
• While academic dissertations or theses that are print-only are considered unpublished, these types of documents are considered published if they’re included in an online database (such as ProQuest) or incorporated into an institutional repository.

• For example, you may write, “Gardner, L. M.” Or, “Meek, P. Q., Kendrick, L. H., & Hill, R. W.”
• If there is no author, you can list the name of the organization that published the research paper. For example, you may write, “American Cancer Society” or “The Reading Room.”
• Formally published documents that don’t list an author or that have a corporate author are typically reports or white papers .

• For example, you may write, “Gardner, L. M. (2008).” Or, “American Cancer Society. (2015).”

• For example, you may write, “Gardner, L. M. (2008). Crustaceans: Research and data.” Or, “American Cancer Society. (2015). Cervical cancer rates in women ages 20-45.”

• For example, for a journal article, you may write, “Gardner, L. M. (2008). Crustaceans: Research and data. Modern Journal of Malacostracan Research, 25, 150-305.”
• For a book chapter, you could write: “Wooster, B. W. (1937). A comparative study of modern Dutch cow creamers. In T. E. Travers (Ed.), A Detailed History of Tea Serviceware (pp. 127-155). London: Wimble Press."

• For example, you may write, “Kotb, M. A., Kamal, A. M., Aldossary, N. M., & Bedewi, M. A. (2019). Effect of vitamin D replacement on depression in multiple sclerosis patients. Multiple Sclerosis and Related Disorders, 29, 111-117. Retrieved from PubMed, https://www.ncbi.nlm.nih.gov/pubmed/30708308.
• If you’re citing a paper or article that was published online but did not come from an academic journal or database, provide information about the author (if known), the date of publication (if available), and the website where you found the article. For example: “Hill, M. (n.d.). Egypt in the Ptolemaic Period. Retrieved from https://www.metmuseum.org/toah/hd/ptol/hd_ptol.htm”

Citing Unpublished Sources in Your Reference List

• Print-only dissertations or theses.
• Articles or book chapters that are in press or have been recently prepared or submitted for publication.
• Papers that have been rejected for publication or were never intended for publication (such as student research papers or unpublished conference papers).

• If the paper is currently being prepared for publication, include the author’s name, the year when the current draft was completed, and the title of the article in italics, followed by “Manuscript in preparation.” For example: Wooster, B. W. (1932). What the well-dressed man is wearing. Manuscript in preparation.
• If the paper has been submitted for publication, format the citation the same way as if it were in preparation, but instead follow the title with “Manuscript submitted for publication.” For example: Wooster, B. W. (1932). What the well-dressed man is wearing. Manuscript submitted for publication.
• If the paper has been accepted for publication but is not yet published, replace the date with “in press.” Do not italicize the paper title, but do include the title of the periodical or book in which it will be published and italicize that. For example: Wooster, B. W. (in press). What the well-dressed man is wearing. Milady’s Boudoir.

• If the paper was written for a conference but never published, your citation should look like this: Riker, W. T. (2019, March). Traditional methods for the preparation of spiny lobe-fish. Paper presented at the 325th Annual Intergalactic Culinary Conference, San Francisco, CA.
• For an unpublished paper written by a student for a class, include details about the institution where the paper was written. For example: Crusher, B. H. (2019). A typology of Cardassian skin diseases. Unpublished manuscript, Department of External Medicine, Starfleet Academy, San Francisco, CA.

• For example, you may write, “Pendlebottom, R. H. (2011). Iconography in Italian Frescos (Unpublished doctoral dissertation). New York University, New York, United States.”

Community Q&A

• If you want certain information to stand out in the research paper, then you can consider using a block quote. Thanks Helpful 0 Not Helpful 0

You Might Also Like

• ↑ https://libraryguides.vu.edu.au/apa-referencing/7JournalArticles
• ↑ https://owl.purdue.edu/owl/research_and_citation/apa_style/apa_formatting_and_style_guide/in_text_citations_author_authors.html
• ↑ https://bowvalleycollege.libguides.com/c.php?g=714519&p=5093747
• ↑ https://guides.libraries.psu.edu/apaquickguide/intext
• ↑ https://owl.purdue.edu/owl/research_and_citation/apa_style/apa_formatting_and_style_guide/in_text_citations_the_basics.html
• ↑ https://libguides.southernct.edu/c.php?g=7125&p=34582#1951239
• ↑ https://owl.purdue.edu/owl/research_and_citation/apa_style/apa_formatting_and_style_guide/reference_list_electronic_sources.html
• ↑ https://owl.purdue.edu/owl/research_and_citation/apa_style/apa_formatting_and_style_guide/reference_list_articles_in_periodicals.html
• ↑ https://owl.purdue.edu/owl/research_and_citation/apa_style/apa_formatting_and_style_guide/reference_list_books.html
• ↑ https://morlingcollege.libguides.com/apareferencing/unpublished-or-informally-published-work
• ↑ https://owl.purdue.edu/owl/research_and_citation/apa_style/apa_formatting_and_style_guide/general_apa_faqs.html
• ↑ https://owl.purdue.edu/owl/research_and_citation/apa_style/apa_formatting_and_style_guide/reference_list_other_print_sources.html

About This Article

To cite a research paper in-text in APA, name the author in the text to introduce the quote and put the publication date for the text in parentheses. At the end of your quote, put the page number in parentheses. If you don’t mention the author in your prose, include them in the citation. Start the citation, which should come at the end of the quote, by listing the author’s last name, the year of publication, and the page number. Make sure to put all of this information in parentheses. If there’s no author, use the name of the organization that published the paper or the first few words from the title. To learn how to cite published and unpublished sources in your reference list, keep reading! Did this summary help you? Yes No

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Home / Guides / Citation Guides / How to Cite Sources

How to Cite Sources

Here is a complete list for how to cite sources. Most of these guides present citation guidance and examples in MLA, APA, and Chicago.

If you’re looking for general information on MLA or APA citations , the EasyBib Writing Center was designed for you! It has articles on what’s needed in an MLA in-text citation , how to format an APA paper, what an MLA annotated bibliography is, making an MLA works cited page, and much more!

MLA Format Citation Examples

The Modern Language Association created the MLA Style, currently in its 9th edition, to provide researchers with guidelines for writing and documenting scholarly borrowings.  Most often used in the humanities, MLA style (or MLA format ) has been adopted and used by numerous other disciplines, in multiple parts of the world.

MLA provides standard rules to follow so that most research papers are formatted in a similar manner. This makes it easier for readers to comprehend the information. The MLA in-text citation guidelines, MLA works cited standards, and MLA annotated bibliography instructions provide scholars with the information they need to properly cite sources in their research papers, articles, and assignments.

• Book Chapter
• Conference Paper
• Documentary
• Encyclopedia
• Google Images
• Kindle Book
• Memorial Inscription
• Museum Exhibit
• Painting or Artwork
• PowerPoint Presentation
• Sheet Music
• Thesis or Dissertation
• YouTube Video

APA Format Citation Examples

The American Psychological Association created the APA citation style in 1929 as a way to help psychologists, anthropologists, and even business managers establish one common way to cite sources and present content.

APA is used when citing sources for academic articles such as journals, and is intended to help readers better comprehend content, and to avoid language bias wherever possible. The APA style (or APA format ) is now in its 7th edition, and provides citation style guides for virtually any type of resource.

Chicago Style Citation Examples

The Chicago/Turabian style of citing sources is generally used when citing sources for humanities papers, and is best known for its requirement that writers place bibliographic citations at the bottom of a page (in Chicago-format footnotes ) or at the end of a paper (endnotes).

The Turabian and Chicago citation styles are almost identical, but the Turabian style is geared towards student published papers such as theses and dissertations, while the Chicago style provides guidelines for all types of publications. This is why you’ll commonly see Chicago style and Turabian style presented together. The Chicago Manual of Style is currently in its 17th edition, and Turabian’s A Manual for Writers of Research Papers, Theses, and Dissertations is in its 8th edition.

Citing Specific Sources or Events

• Declaration of Independence
• Gettysburg Address
• Martin Luther King Jr. Speech
• President Obama’s Farewell Address
• President Trump’s Inauguration Speech
• White House Press Briefing

Additional FAQs

• Citing Archived Contributors
• Citing a Blog
• Citing a Book Chapter
• Citing a Source in a Foreign Language
• Citing an Image
• Citing a Song
• Citing Special Contributors
• Citing a Translated Article
• Citing a Tweet

6 Interesting Citation Facts

The world of citations may seem cut and dry, but there’s more to them than just specific capitalization rules, MLA in-text citations , and other formatting specifications. Citations have been helping researches document their sources for hundreds of years, and are a great way to learn more about a particular subject area.

Ever wonder what sets all the different styles apart, or how they came to be in the first place? Read on for some interesting facts about citations!

1. There are Over 7,000 Different Citation Styles

You may be familiar with MLA and APA citation styles, but there are actually thousands of citation styles used for all different academic disciplines all across the world. Deciding which one to use can be difficult, so be sure to ask you instructor which one you should be using for your next paper.

2. Some Citation Styles are Named After People

While a majority of citation styles are named for the specific organizations that publish them (i.e. APA is published by the American Psychological Association, and MLA format is named for the Modern Language Association), some are actually named after individuals. The most well-known example of this is perhaps Turabian style, named for Kate L. Turabian, an American educator and writer. She developed this style as a condensed version of the Chicago Manual of Style in order to present a more concise set of rules to students.

3. There are Some Really Specific and Uniquely Named Citation Styles

How specific can citation styles get? The answer is very. For example, the “Flavour and Fragrance Journal” style is based on a bimonthly, peer-reviewed scientific journal published since 1985 by John Wiley & Sons. It publishes original research articles, reviews and special reports on all aspects of flavor and fragrance. Another example is “Nordic Pulp and Paper Research,” a style used by an international scientific magazine covering science and technology for the areas of wood or bio-mass constituents.

4. More citations were created on  EasyBib.com  in the first quarter of 2018 than there are people in California.

The US Census Bureau estimates that approximately 39.5 million people live in the state of California. Meanwhile, about 43 million citations were made on EasyBib from January to March of 2018. That’s a lot of citations.

5. “Citations” is a Word With a Long History

The word “citations” can be traced back literally thousands of years to the Latin word “citare” meaning “to summon, urge, call; put in sudden motion, call forward; rouse, excite.” The word then took on its more modern meaning and relevance to writing papers in the 1600s, where it became known as the “act of citing or quoting a passage from a book, etc.”

6. Citation Styles are Always Changing

The concept of citations always stays the same. It is a means of preventing plagiarism and demonstrating where you relied on outside sources. The specific style rules, however, can and do change regularly. For example, in 2018 alone, 46 new citation styles were introduced , and 106 updates were made to exiting styles. At EasyBib, we are always on the lookout for ways to improve our styles and opportunities to add new ones to our list.

Why Citations Matter

Here are the ways accurate citations can help your students achieve academic success, and how you can answer the dreaded question, “why should I cite my sources?”

They Give Credit to the Right People

Citing their sources makes sure that the reader can differentiate the student’s original thoughts from those of other researchers. Not only does this make sure that the sources they use receive proper credit for their work, it ensures that the student receives deserved recognition for their unique contributions to the topic. Whether the student is citing in MLA format , APA format , or any other style, citations serve as a natural way to place a student’s work in the broader context of the subject area, and serve as an easy way to gauge their commitment to the project.

They Provide Hard Evidence of Ideas

Having many citations from a wide variety of sources related to their idea means that the student is working on a well-researched and respected subject. Citing sources that back up their claim creates room for fact-checking and further research . And, if they can cite a few sources that have the converse opinion or idea, and then demonstrate to the reader why they believe that that viewpoint is wrong by again citing credible sources, the student is well on their way to winning over the reader and cementing their point of view.

They Promote Originality and Prevent Plagiarism

The point of research projects is not to regurgitate information that can already be found elsewhere. We have Google for that! What the student’s project should aim to do is promote an original idea or a spin on an existing idea, and use reliable sources to promote that idea. Copying or directly referencing a source without proper citation can lead to not only a poor grade, but accusations of academic dishonesty. By citing their sources regularly and accurately, students can easily avoid the trap of plagiarism , and promote further research on their topic.

They Create Better Researchers

By researching sources to back up and promote their ideas, students are becoming better researchers without even knowing it! Each time a new source is read or researched, the student is becoming more engaged with the project and is developing a deeper understanding of the subject area. Proper citations demonstrate a breadth of the student’s reading and dedication to the project itself. By creating citations, students are compelled to make connections between their sources and discern research patterns. Each time they complete this process, they are helping themselves become better researchers and writers overall.

When is the Right Time to Start Making Citations?

Make in-text/parenthetical citations as you need them.

As you are writing your paper, be sure to include references within the text that correspond with references in a works cited or bibliography. These are usually called in-text citations or parenthetical citations in MLA and APA formats. The most effective time to complete these is directly after you have made your reference to another source. For instance, after writing the line from Charles Dickens’ A Tale of Two Cities : “It was the best of times, it was the worst of times…,” you would include a citation like this (depending on your chosen citation style):

(Dickens 11).

This signals to the reader that you have referenced an outside source. What’s great about this system is that the in-text citations serve as a natural list for all of the citations you have made in your paper, which will make completing the works cited page a whole lot easier. After you are done writing, all that will be left for you to do is scan your paper for these references, and then build a works cited page that includes a citation for each one.

Need help creating an MLA works cited page ? Try the MLA format generator on EasyBib.com! We also have a guide on how to format an APA reference page .

2. Understand the General Formatting Rules of Your Citation Style Before You Start Writing

While reading up on paper formatting may not sound exciting, being aware of how your paper should look early on in the paper writing process is super important. Citation styles can dictate more than just the appearance of the citations themselves, but rather can impact the layout of your paper as a whole, with specific guidelines concerning margin width, title treatment, and even font size and spacing. Knowing how to organize your paper before you start writing will ensure that you do not receive a low grade for something as trivial as forgetting a hanging indent.

Don’t know where to start? Here’s a formatting guide on APA format .

3. Double-check All of Your Outside Sources for Relevance and Trustworthiness First

Collecting outside sources that support your research and specific topic is a critical step in writing an effective paper. But before you run to the library and grab the first 20 books you can lay your hands on, keep in mind that selecting a source to include in your paper should not be taken lightly. Before you proceed with using it to backup your ideas, run a quick Internet search for it and see if other scholars in your field have written about it as well. Check to see if there are book reviews about it or peer accolades. If you spot something that seems off to you, you may want to consider leaving it out of your work. Doing this before your start making citations can save you a ton of time in the long run.

Finished with your paper? It may be time to run it through a grammar and plagiarism checker , like the one offered by EasyBib Plus. If you’re just looking to brush up on the basics, our grammar guides  are ready anytime you are.

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Cite a Website

Don't let plagiarism errors spoil your paper, citing a website in apa.

Once you’ve identified a credible website to use, create a citation and begin building your reference list. Citation Machine citing tools can help you create references for online news articles, government websites, blogs, and many other website! Keeping track of sources as you research and write can help you stay organized and ethical. If you end up not using a source, you can easily delete it from your bibliography. Ready to create a citation? Enter the website’s URL into the search box above. You’ll get a list of results, so you can identify and choose the correct source you want to cite. It’s that easy to begin!

If you’re wondering how to cite a website in APA, use the structure below.

Author Last Name, First initial. (Year, Month Date Published). Title of web page . Name of Website. URL

Example of an APA format website:

Austerlitz, S. (2015, March 3). How long can a spinoff like ‘Better Call Saul’ last? FiveThirtyEight. http://fivethirtyeight.com/features/how-long-can-a-spinoff-like-better-call-saul-last/

Keep in mind that not all information found on a website follows the structure above. Only use the Website format above if your online source does not fit another source category. For example, if you’re looking at a video on YouTube, refer to the ‘YouTube Video’ section. If you’re citing a newspaper article found online, refer to ‘Newspapers Found Online’ section. Again, an APA website citation is strictly for web pages that do not fit better with one of the other categories on this page.

Social media:

When adding the text of a post, keep the original capitalization, spelling, hashtags, emojis (if possible), and links within the text.

Facebook posts:

Structure: Facebook user’s Last name, F. M. (Year, Monday Day of Post). Up to the first 20 words of Facebook post [Source type if attached] [Post type]. Facebook. URL

Source type examples: [Video attached], [Image attached]

Post type examples: [Status update], [Video], [Image], [Infographic]

Gomez, S. (2020, February 4). Guys, I’ve been working on this special project for two years and can officially say Rare Beauty is launching in [Video]. Facebook. https://www.facebook.com/Selena/videos/1340031502835436/

Life at Chegg. (2020, February 7) It breaks our heart that 50% of college students right here in Silicon Valley are hungry. That’s why Chegg has [Images attached] [Status update]. Facebook. https://www.facebook.com/LifeAtChegg/posts/1076718522691591

Twitter posts:

Structure: Account holder’s Last name, F. M. [Twitter Handle]. (Year, Month Day of Post). Up to the first 20 words of tweet [source type if attached] [Tweet]. Twitter. URL

Source type examples: [Video attached], [Image attached], [Poll attached]

Example: Edelman, J. [Edelman11]. (2018, April 26). Nine years ago today my life changed forever. New England took a chance on a long shot and I’ve worked [Video attached] [Tweet]. Twitter. https://twitter.com/Edelman11/status/989652345922473985

Instagram posts:

APA citation format: Account holder’s Last name, F. M. [@Instagram handle]. (Year, Month Day). Up to the first 20 words of caption [Photograph(s) and/or Video(s)]. Instagram. URL

Example: Portman, N. [@natalieportman]. (2019, January 5). Many of my best experiences last year were getting to listen to and learn from so many incredible people through [Videos]. Instagram. https://www.instagram.com/p/BsRD-FBB8HI/?utm_source=ig_web_copy_link

If this guide hasn’t helped solve all of your referencing questions, or if you’re still feeling the need to type “how to cite a website APA” into Google, then check out our APA citation generator on CitationMachine.com, which can build your references for you!

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• How to Paraphrase | Step-by-Step Guide & Examples

How to Paraphrase | Step-by-Step Guide & Examples

Published on April 8, 2022 by Courtney Gahan and Jack Caulfield. Revised on June 1, 2023.

Paraphrasing means putting someone else’s ideas into your own words. Paraphrasing a source involves changing the wording while preserving the original meaning.

Paraphrasing is an alternative to  quoting (copying someone’s exact words and putting them in quotation marks ). In academic writing, it’s usually better to integrate sources by paraphrasing instead of quoting. It shows that you have understood the source, reads more smoothly, and keeps your own voice front and center.

Every time you paraphrase, it’s important to cite the source . Also take care not to use wording that is too similar to the original. Otherwise, you could be at risk of committing plagiarism .

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Table of contents

How to paraphrase in five easy steps, how to paraphrase correctly, examples of paraphrasing, how to cite a paraphrase, paraphrasing vs. quoting, paraphrasing vs. summarizing, avoiding plagiarism when you paraphrase, other interesting articles, frequently asked questions about paraphrasing.

If you’re struggling to get to grips with the process of paraphrasing, check out our easy step-by-step guide in the video below.

Prevent plagiarism. Run a free check.

Putting an idea into your own words can be easier said than done. Let’s say you want to paraphrase the text below, about population decline in a particular species of sea snails.

Incorrect paraphrasing

You might make a first attempt to paraphrase it by swapping out a few words for  synonyms .

Like other sea creatures inhabiting the vicinity of highly populated coasts, horse conchs have lost substantial territory to advancement and contamination , including preferred breeding grounds along mud flats and seagrass beds. Their Gulf home is also heating up due to global warming , which scientists think further puts pressure on the creatures , predicated upon the harmful effects extra warmth has on other large mollusks (Barnett, 2022).

This attempt at paraphrasing doesn’t change the sentence structure or order of information, only some of the word choices. And the synonyms chosen are poor:

• “Advancement and contamination” doesn’t really convey the same meaning as “development and pollution.”
• Sometimes the changes make the tone less academic: “home” for “habitat” and “sea creatures” for “marine animals.”
• Adding phrases like “inhabiting the vicinity of” and “puts pressure on” makes the text needlessly long-winded.
• Global warming is related to climate change, but they don’t mean exactly the same thing.

Because of this, the text reads awkwardly, is longer than it needs to be, and remains too close to the original phrasing. This means you risk being accused of plagiarism .

Correct paraphrasing

Let’s look at a more effective way of paraphrasing the same text.

Here, we’ve:

• Only included the information that’s relevant to our argument (note that the paraphrase is shorter than the original)
• Introduced the information with the signal phrase “Scientists believe that …”
• Retained key terms like “development and pollution,” since changing them could alter the meaning
• Structured sentences in our own way instead of copying the structure of the original
• Started from a different point, presenting information in a different order

Because of this, we’re able to clearly convey the relevant information from the source without sticking too close to the original phrasing.

Explore the tabs below to see examples of paraphrasing in action.

• Journal article
• Newspaper article
• Magazine article

Once you have your perfectly paraphrased text, you need to ensure you credit the original author. You’ll always paraphrase sources in the same way, but you’ll have to use a different type of in-text citation depending on what citation style you follow.

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It’s a good idea to paraphrase instead of quoting in most cases because:

• Paraphrasing shows that you fully understand the meaning of a text
• Your own voice remains dominant throughout your paper
• Quotes reduce the readability of your text

But that doesn’t mean you should never quote. Quotes are appropriate when:

• Giving a precise definition
• Saying something about the author’s language or style (e.g., in a literary analysis paper)
• Providing evidence in support of an argument
• Critiquing or analyzing a specific claim

A paraphrase puts a specific passage into your own words. It’s typically a similar length to the original text, or slightly shorter.

When you boil a longer piece of writing down to the key points, so that the result is a lot shorter than the original, this is called summarizing .

Paraphrasing and quoting are important tools for presenting specific information from sources. But if the information you want to include is more general (e.g., the overarching argument of a whole article), summarizing is more appropriate.

When paraphrasing, you have to be careful to avoid accidental plagiarism .

This can happen if the paraphrase is too similar to the original quote, with phrases or whole sentences that are identical (and should therefore be in quotation marks). It can also happen if you fail to properly cite the source.

Paraphrasing tools are widely used by students, and can be especially useful for non-native speakers who may find academic writing particularly challenging. While these can be helpful for a bit of extra inspiration, use these tools sparingly, keeping academic integrity in mind.

To make sure you’ve properly paraphrased and cited all your sources, you could elect to run a plagiarism check before submitting your paper. And of course, always be sure to read your source material yourself and take the first stab at paraphrasing on your own.

If you want to know more about ChatGPT, AI tools , citation , and plagiarism , make sure to check out some of our other articles with explanations and examples.

• ChatGPT vs human editor
• ChatGPT citations
• Is ChatGPT trustworthy?
• Using ChatGPT for your studies
• What is ChatGPT?
• Chicago style
• Critical thinking

 Plagiarism

• Types of plagiarism
• Self-plagiarism
• Avoiding plagiarism
• Academic integrity
• Consequences of plagiarism
• Common knowledge

To paraphrase effectively, don’t just take the original sentence and swap out some of the words for synonyms. Instead, try:

• Reformulating the sentence (e.g., change active to passive , or start from a different point)
• Combining information from multiple sentences into one
• Leaving out information from the original that isn’t relevant to your point
• Using synonyms where they don’t distort the meaning

The main point is to ensure you don’t just copy the structure of the original text, but instead reformulate the idea in your own words.

Paraphrasing without crediting the original author is a form of plagiarism , because you’re presenting someone else’s ideas as if they were your own.

However, paraphrasing is not plagiarism if you correctly cite the source . This means including an in-text citation and a full reference, formatted according to your required citation style .

As well as citing, make sure that any paraphrased text is completely rewritten in your own words.

Plagiarism means using someone else’s words or ideas and passing them off as your own. Paraphrasing means putting someone else’s ideas in your own words.

So when does paraphrasing count as plagiarism?

• Paraphrasing is plagiarism if you don’t properly credit the original author.
• Paraphrasing is plagiarism if your text is too close to the original wording (even if you cite the source). If you directly copy a sentence or phrase, you should quote it instead.
• Paraphrasing  is not plagiarism if you put the author’s ideas completely in your own words and properly cite the source .

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To present information from other sources in academic writing , it’s best to paraphrase in most cases. This shows that you’ve understood the ideas you’re discussing and incorporates them into your text smoothly.

It’s appropriate to quote when:

• Changing the phrasing would distort the meaning of the original text
• You want to discuss the author’s language choices (e.g., in literary analysis )
• You’re presenting a precise definition
• You’re looking in depth at a specific claim

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If you want to cite this source, you can copy and paste the citation or click the “Cite this Scribbr article” button to automatically add the citation to our free Citation Generator.

Gahan, C. & Caulfield, J. (2023, June 01). How to Paraphrase | Step-by-Step Guide & Examples. Scribbr. Retrieved April 15, 2024, from https://www.scribbr.com/working-with-sources/how-to-paraphrase/

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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.

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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.

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