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The top list of academic search engines

1. Google Scholar

4. science.gov, 5. semantic scholar, 6. baidu scholar, get the most out of academic search engines, frequently asked questions about academic search engines, related articles.

Academic search engines have become the number one resource to turn to in order to find research papers and other scholarly sources. While classic academic databases like Web of Science and Scopus are locked behind paywalls, Google Scholar and others can be accessed free of charge. In order to help you get your research done fast, we have compiled the top list of free academic search engines.

Google Scholar is the clear number one when it comes to academic search engines. It's the power of Google searches applied to research papers and patents. It not only lets you find research papers for all academic disciplines for free but also often provides links to full-text PDF files.

• Coverage: approx. 200 million articles
• Abstracts: only a snippet of the abstract is available
• Related articles: ✔
• References: ✔
• Cited by: ✔
• Links to full text: ✔
• Export formats: APA, MLA, Chicago, Harvard, Vancouver, RIS, BibTeX

BASE is hosted at Bielefeld University in Germany. That is also where its name stems from (Bielefeld Academic Search Engine).

• Coverage: approx. 136 million articles (contains duplicates)
• Abstracts: ✔
• Related articles: ✘
• References: ✘
• Cited by: ✘
• Export formats: RIS, BibTeX

CORE is an academic search engine dedicated to open-access research papers. For each search result, a link to the full-text PDF or full-text web page is provided.

• Coverage: approx. 136 million articles
• Links to full text: ✔ (all articles in CORE are open access)
• Export formats: BibTeX

Science.gov is a fantastic resource as it bundles and offers free access to search results from more than 15 U.S. federal agencies. There is no need anymore to query all those resources separately!

• Coverage: approx. 200 million articles and reports
• Links to full text: ✔ (available for some databases)
• Export formats: APA, MLA, RIS, BibTeX (available for some databases)

Semantic Scholar is the new kid on the block. Its mission is to provide more relevant and impactful search results using AI-powered algorithms that find hidden connections and links between research topics.

• Coverage: approx. 40 million articles
• Export formats: APA, MLA, Chicago, BibTeX

Although Baidu Scholar's interface is in Chinese, its index contains research papers in English as well as Chinese.

• Coverage: no detailed statistics available, approx. 100 million articles
• Abstracts: only snippets of the abstract are available
• Export formats: APA, MLA, RIS, BibTeX

RefSeek searches more than one billion documents from academic and organizational websites. Its clean interface makes it especially easy to use for students and new researchers.

• Coverage: no detailed statistics available, approx. 1 billion documents
• Abstracts: only snippets of the article are available
• Export formats: not available

Consider using a reference manager like Paperpile to save, organize, and cite your references. Paperpile integrates with Google Scholar and many popular databases, so you can save references and PDFs directly to your library using the Paperpile buttons:

Google Scholar is an academic search engine, and it is the clear number one when it comes to academic search engines. It's the power of Google searches applied to research papers and patents. It not only let's you find research papers for all academic disciplines for free, but also often provides links to full text PDF file.

Semantic Scholar is a free, AI-powered research tool for scientific literature developed at the Allen Institute for AI. Sematic Scholar was publicly released in 2015 and uses advances in natural language processing to provide summaries for scholarly papers.

BASE , as its name suggest is an academic search engine. It is hosted at Bielefeld University in Germany and that's where it name stems from (Bielefeld Academic Search Engine).

CORE is an academic search engine dedicated to open access research papers. For each search result a link to the full text PDF or full text web page is provided.

Science.gov is a fantastic resource as it bundles and offers free access to search results from more than 15 U.S. federal agencies. There is no need any more to query all those resources separately!

“The only truly modern academic research engine”

Oa.mg is a search engine for academic papers, specialising in open access. we have over 250 million papers in our index..

• Corrections

Search Help

Get the most out of Google Scholar with some helpful tips on searches, email alerts, citation export, and more.

Finding recent papers

Your search results are normally sorted by relevance, not by date. To find newer articles, try the following options in the left sidebar:

• click "Since Year" to show only recently published papers, sorted by relevance;
• click "Sort by date" to show just the new additions, sorted by date;
• click the envelope icon to have new results periodically delivered by email.

Locating the full text of an article

Abstracts are freely available for most of the articles. Alas, reading the entire article may require a subscription. Here're a few things to try:

• click a library link, e.g., "FindIt@Harvard", to the right of the search result;
• click a link labeled [PDF] to the right of the search result;
• click "All versions" under the search result and check out the alternative sources;
• click "Related articles" or "Cited by" under the search result to explore similar articles.

If you're affiliated with a university, but don't see links such as "FindIt@Harvard", please check with your local library about the best way to access their online subscriptions. You may need to do search from a computer on campus, or to configure your browser to use a library proxy.

Getting better answers

If you're new to the subject, it may be helpful to pick up the terminology from secondary sources. E.g., a Wikipedia article for "overweight" might suggest a Scholar search for "pediatric hyperalimentation".

If the search results are too specific for your needs, check out what they're citing in their "References" sections. Referenced works are often more general in nature.

Similarly, if the search results are too basic for you, click "Cited by" to see newer papers that referenced them. These newer papers will often be more specific.

Explore! There's rarely a single answer to a research question. Click "Related articles" or "Cited by" to see closely related work, or search for author's name and see what else they have written.

Searching Google Scholar

Use the "author:" operator, e.g., author:"d knuth" or author:"donald e knuth".

Put the paper's title in quotations: "A History of the China Sea".

You'll often get better results if you search only recent articles, but still sort them by relevance, not by date. E.g., click "Since 2018" in the left sidebar of the search results page.

To see the absolutely newest articles first, click "Sort by date" in the sidebar. If you use this feature a lot, you may also find it useful to setup email alerts to have new results automatically sent to you.

Note: On smaller screens that don't show the sidebar, these options are available in the dropdown menu labelled "Year" right below the search button.

Select the "Case law" option on the homepage or in the side drawer on the search results page.

It finds documents similar to the given search result.

It's in the side drawer. The advanced search window lets you search in the author, title, and publication fields, as well as limit your search results by date.

Select the "Case law" option and do a keyword search over all jurisdictions. Then, click the "Select courts" link in the left sidebar on the search results page.

Tip: To quickly search a frequently used selection of courts, bookmark a search results page with the desired selection.

Access to articles

For each Scholar search result, we try to find a version of the article that you can read. These access links are labelled [PDF] or [HTML] and appear to the right of the search result. For example:

A paper that you need to read

Access links cover a wide variety of ways in which articles may be available to you - articles that your library subscribes to, open access articles, free-to-read articles from publishers, preprints, articles in repositories, etc.

When you are on a campus network, access links automatically include your library subscriptions and direct you to subscribed versions of articles. On-campus access links cover subscriptions from primary publishers as well as aggregators.

Off-campus access

Off-campus access links let you take your library subscriptions with you when you are at home or traveling. You can read subscribed articles when you are off-campus just as easily as when you are on-campus. Off-campus access links work by recording your subscriptions when you visit Scholar while on-campus, and looking up the recorded subscriptions later when you are off-campus.

We use the recorded subscriptions to provide you with the same subscribed access links as you see on campus. We also indicate your subscription access to participating publishers so that they can allow you to read the full-text of these articles without logging in or using a proxy. The recorded subscription information expires after 30 days and is automatically deleted.

In addition to Google Scholar search results, off-campus access links can also appear on articles from publishers participating in the off-campus subscription access program. Look for links labeled [PDF] or [HTML] on the right hand side of article pages.

Anne Author , John Doe , Jane Smith , Someone Else

In this fascinating paper, we investigate various topics that would be of interest to you. We also describe new methods relevant to your project, and attempt to address several questions which you would also like to know the answer to. Lastly, we analyze …

You can disable off-campus access links on the Scholar settings page . Disabling off-campus access links will turn off recording of your library subscriptions. It will also turn off indicating subscription access to participating publishers. Once off-campus access links are disabled, you may need to identify and configure an alternate mechanism (e.g., an institutional proxy or VPN) to access your library subscriptions while off-campus.

Email Alerts

Do a search for the topic of interest, e.g., "M Theory"; click the envelope icon in the sidebar of the search results page; enter your email address, and click "Create alert". We'll then periodically email you newly published papers that match your search criteria.

No, you can enter any email address of your choice. If the email address isn't a Google account or doesn't match your Google account, then we'll email you a verification link, which you'll need to click to start receiving alerts.

This works best if you create a public profile , which is free and quick to do. Once you get to the homepage with your photo, click "Follow" next to your name, select "New citations to my articles", and click "Done". We will then email you when we find new articles that cite yours.

Search for the title of your paper, e.g., "Anti de Sitter space and holography"; click on the "Cited by" link at the bottom of the search result; and then click on the envelope icon in the left sidebar of the search results page.

First, do a search for your colleague's name, and see if they have a Scholar profile. If they do, click on it, click the "Follow" button next to their name, select "New articles by this author", and click "Done".

If they don't have a profile, do a search by author, e.g., [author:s-hawking], and click on the mighty envelope in the left sidebar of the search results page. If you find that several different people share the same name, you may need to add co-author names or topical keywords to limit results to the author you wish to follow.

We send the alerts right after we add new papers to Google Scholar. This usually happens several times a week, except that our search robots meticulously observe holidays.

There's a link to cancel the alert at the bottom of every notification email.

If you created alerts using a Google account, you can manage them all here . If you're not using a Google account, you'll need to unsubscribe from the individual alerts and subscribe to the new ones.

Google Scholar library

Google Scholar library is your personal collection of articles. You can save articles right off the search page, organize them by adding labels, and use the power of Scholar search to quickly find just the one you want - at any time and from anywhere. You decide what goes into your library, and we’ll keep the links up to date.

You get all the goodies that come with Scholar search results - links to PDF and to your university's subscriptions, formatted citations, citing articles, and more!

Library help

Find the article you want to add in Google Scholar and click the “Save” button under the search result.

Click “My library” at the top of the page or in the side drawer to view all articles in your library. To search the full text of these articles, enter your query as usual in the search box.

Find the article you want to remove, and then click the “Delete” button under it.

• To add a label to an article, find the article in your library, click the “Label” button under it, select the label you want to apply, and click “Done”.
• To view all the articles with a specific label, click the label name in the left sidebar of your library page.
• To remove a label from an article, click the “Label” button under it, deselect the label you want to remove, and click “Done”.
• To add, edit, or delete labels, click “Manage labels” in the left column of your library page.

Only you can see the articles in your library. If you create a Scholar profile and make it public, then the articles in your public profile (and only those articles) will be visible to everyone.

Your profile contains all the articles you have written yourself. It’s a way to present your work to others, as well as to keep track of citations to it. Your library is a way to organize the articles that you’d like to read or cite, not necessarily the ones you’ve written.

Citation Export

Click the "Cite" button under the search result and then select your bibliography manager at the bottom of the popup. We currently support BibTeX, EndNote, RefMan, and RefWorks.

Err, no, please respect our robots.txt when you access Google Scholar using automated software. As the wearers of crawler's shoes and webmaster's hat, we cannot recommend adherence to web standards highly enough.

Sorry, we're unable to provide bulk access. You'll need to make an arrangement directly with the source of the data you're interested in. Keep in mind that a lot of the records in Google Scholar come from commercial subscription services.

Sorry, we can only show up to 1,000 results for any particular search query. Try a different query to get more results.

Content Coverage

Google Scholar includes journal and conference papers, theses and dissertations, academic books, pre-prints, abstracts, technical reports and other scholarly literature from all broad areas of research. You'll find works from a wide variety of academic publishers, professional societies and university repositories, as well as scholarly articles available anywhere across the web. Google Scholar also includes court opinions and patents.

We index research articles and abstracts from most major academic publishers and repositories worldwide, including both free and subscription sources. To check current coverage of a specific source in Google Scholar, search for a sample of their article titles in quotes.

While we try to be comprehensive, it isn't possible to guarantee uninterrupted coverage of any particular source. We index articles from sources all over the web and link to these websites in our search results. If one of these websites becomes unavailable to our search robots or to a large number of web users, we have to remove it from Google Scholar until it becomes available again.

Our meticulous search robots generally try to index every paper from every website they visit, including most major sources and also many lesser known ones.

That said, Google Scholar is primarily a search of academic papers. Shorter articles, such as book reviews, news sections, editorials, announcements and letters, may or may not be included. Untitled documents and documents without authors are usually not included. Website URLs that aren't available to our search robots or to the majority of web users are, obviously, not included either. Nor do we include websites that require you to sign up for an account, install a browser plugin, watch four colorful ads, and turn around three times and say coo-coo before you can read the listing of titles scanned at 10 DPI... You get the idea, we cover academic papers from sensible websites.

That's usually because we index many of these papers from other websites, such as the websites of their primary publishers. The "site:" operator currently only searches the primary version of each paper.

It could also be that the papers are located on examplejournals.gov, not on example.gov. Please make sure you're searching for the "right" website.

That said, the best way to check coverage of a specific source is to search for a sample of their papers using the title of the paper.

Ahem, we index papers, not journals. You should also ask about our coverage of universities, research groups, proteins, seminal breakthroughs, and other dimensions that are of interest to users. All such questions are best answered by searching for a statistical sample of papers that has the property of interest - journal, author, protein, etc. Many coverage comparisons are available if you search for [allintitle:"google scholar"], but some of them are more statistically valid than others.

Currently, Google Scholar allows you to search and read published opinions of US state appellate and supreme court cases since 1950, US federal district, appellate, tax and bankruptcy courts since 1923 and US Supreme Court cases since 1791. In addition, it includes citations for cases cited by indexed opinions or journal articles which allows you to find influential cases (usually older or international) which are not yet online or publicly available.

Legal opinions in Google Scholar are provided for informational purposes only and should not be relied on as a substitute for legal advice from a licensed lawyer. Google does not warrant that the information is complete or accurate.

We normally add new papers several times a week. However, updates to existing records take 6-9 months to a year or longer, because in order to update our records, we need to first recrawl them from the source website. For many larger websites, the speed at which we can update their records is limited by the crawl rate that they allow.

Inclusion and Corrections

We apologize, and we assure you the error was unintentional. Automated extraction of information from articles in diverse fields can be tricky, so an error sometimes sneaks through.

Please write to the owner of the website where the erroneous search result is coming from, and encourage them to provide correct bibliographic data to us, as described in the technical guidelines . Once the data is corrected on their website, it usually takes 6-9 months to a year or longer for it to be updated in Google Scholar. We appreciate your help and your patience.

If you can't find your papers when you search for them by title and by author, please refer your publisher to our technical guidelines .

You can also deposit your papers into your institutional repository or put their PDF versions on your personal website, but please follow your publisher's requirements when you do so. See our technical guidelines for more details on the inclusion process.

We normally add new papers several times a week; however, it might take us some time to crawl larger websites, and corrections to already included papers can take 6-9 months to a year or longer.

Google Scholar generally reflects the state of the web as it is currently visible to our search robots and to the majority of users. When you're searching for relevant papers to read, you wouldn't want it any other way!

If your citation counts have gone down, chances are that either your paper or papers that cite it have either disappeared from the web entirely, or have become unavailable to our search robots, or, perhaps, have been reformatted in a way that made it difficult for our automated software to identify their bibliographic data and references. If you wish to correct this, you'll need to identify the specific documents with indexing problems and ask your publisher to fix them. Please refer to the technical guidelines .

Please do let us know . Please include the URL for the opinion, the corrected information and a source where we can verify the correction.

We're only able to make corrections to court opinions that are hosted on our own website. For corrections to academic papers, books, dissertations and other third-party material, click on the search result in question and contact the owner of the website where the document came from. For corrections to books from Google Book Search, click on the book's title and locate the link to provide feedback at the bottom of the book's page.

General Questions

These are articles which other scholarly articles have referred to, but which we haven't found online. To exclude them from your search results, uncheck the "include citations" box on the left sidebar.

First, click on links labeled [PDF] or [HTML] to the right of the search result's title. Also, check out the "All versions" link at the bottom of the search result.

Second, if you're affiliated with a university, using a computer on campus will often let you access your library's online subscriptions. Look for links labeled with your library's name to the right of the search result's title. Also, see if there's a link to the full text on the publisher's page with the abstract.

Keep in mind that final published versions are often only available to subscribers, and that some articles are not available online at all. Good luck!

Technically, your web browser remembers your settings in a "cookie" on your computer's disk, and sends this cookie to our website along with every search. Check that your browser isn't configured to discard our cookies. Also, check if disabling various proxies or overly helpful privacy settings does the trick. Either way, your settings are stored on your computer, not on our servers, so a long hard look at your browser's preferences or internet options should help cure the machine's forgetfulness.

Not even close. That phrase is our acknowledgement that much of scholarly research involves building on what others have already discovered. It's taken from Sir Isaac Newton's famous quote, "If I have seen further, it is by standing on the shoulders of giants."

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Stay Connected With Semantic Scholar Sign Up What Is Semantic Scholar? Semantic Scholar is a free, AI-powered research tool for scientific literature, based at the Allen Institute for AI.

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How to Write and Publish a Research Paper for a Peer-Reviewed Journal

• Open access
• Published: 30 April 2020
• Volume 36 , pages 909–913, ( 2021 )

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• Clara Busse   ORCID: orcid.org/0000-0002-0178-1000 1 &
• Ella August   ORCID: orcid.org/0000-0001-5151-1036 1 , 2  

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Communicating research findings is an essential step in the research process. Often, peer-reviewed journals are the forum for such communication, yet many researchers are never taught how to write a publishable scientific paper. In this article, we explain the basic structure of a scientific paper and describe the information that should be included in each section. We also identify common pitfalls for each section and recommend strategies to avoid them. Further, we give advice about target journal selection and authorship. In the online resource 1 , we provide an example of a high-quality scientific paper, with annotations identifying the elements we describe in this article.

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Ehsan Roohi & Omid Mahian

Avoid common mistakes on your manuscript.

Introduction

Writing a scientific paper is an important component of the research process, yet researchers often receive little formal training in scientific writing. This is especially true in low-resource settings. In this article, we explain why choosing a target journal is important, give advice about authorship, provide a basic structure for writing each section of a scientific paper, and describe common pitfalls and recommendations for each section. In the online resource 1 , we also include an annotated journal article that identifies the key elements and writing approaches that we detail here. Before you begin your research, make sure you have ethical clearance from all relevant ethical review boards.

Select a Target Journal Early in the Writing Process

We recommend that you select a “target journal” early in the writing process; a “target journal” is the journal to which you plan to submit your paper. Each journal has a set of core readers and you should tailor your writing to this readership. For example, if you plan to submit a manuscript about vaping during pregnancy to a pregnancy-focused journal, you will need to explain what vaping is because readers of this journal may not have a background in this topic. However, if you were to submit that same article to a tobacco journal, you would not need to provide as much background information about vaping.

Information about a journal’s core readership can be found on its website, usually in a section called “About this journal” or something similar. For example, the Journal of Cancer Education presents such information on the “Aims and Scope” page of its website, which can be found here: https://www.springer.com/journal/13187/aims-and-scope .

Peer reviewer guidelines from your target journal are an additional resource that can help you tailor your writing to the journal and provide additional advice about crafting an effective article [ 1 ]. These are not always available, but it is worth a quick web search to find out.

Identify Author Roles Early in the Process

Early in the writing process, identify authors, determine the order of authors, and discuss the responsibilities of each author. Standard author responsibilities have been identified by The International Committee of Medical Journal Editors (ICMJE) [ 2 ]. To set clear expectations about each team member’s responsibilities and prevent errors in communication, we also suggest outlining more detailed roles, such as who will draft each section of the manuscript, write the abstract, submit the paper electronically, serve as corresponding author, and write the cover letter. It is best to formalize this agreement in writing after discussing it, circulating the document to the author team for approval. We suggest creating a title page on which all authors are listed in the agreed-upon order. It may be necessary to adjust authorship roles and order during the development of the paper. If a new author order is agreed upon, be sure to update the title page in the manuscript draft.

In the case where multiple papers will result from a single study, authors should discuss who will author each paper. Additionally, authors should agree on a deadline for each paper and the lead author should take responsibility for producing an initial draft by this deadline.

Structure of the Introduction Section

The introduction section should be approximately three to five paragraphs in length. Look at examples from your target journal to decide the appropriate length. This section should include the elements shown in Fig.  1 . Begin with a general context, narrowing to the specific focus of the paper. Include five main elements: why your research is important, what is already known about the topic, the “gap” or what is not yet known about the topic, why it is important to learn the new information that your research adds, and the specific research aim(s) that your paper addresses. Your research aim should address the gap you identified. Be sure to add enough background information to enable readers to understand your study. Table 1 provides common introduction section pitfalls and recommendations for addressing them.

The main elements of the introduction section of an original research article. Often, the elements overlap

Methods Section

The purpose of the methods section is twofold: to explain how the study was done in enough detail to enable its replication and to provide enough contextual detail to enable readers to understand and interpret the results. In general, the essential elements of a methods section are the following: a description of the setting and participants, the study design and timing, the recruitment and sampling, the data collection process, the dataset, the dependent and independent variables, the covariates, the analytic approach for each research objective, and the ethical approval. The hallmark of an exemplary methods section is the justification of why each method was used. Table 2 provides common methods section pitfalls and recommendations for addressing them.

Results Section

The focus of the results section should be associations, or lack thereof, rather than statistical tests. Two considerations should guide your writing here. First, the results should present answers to each part of the research aim. Second, return to the methods section to ensure that the analysis and variables for each result have been explained.

Begin the results section by describing the number of participants in the final sample and details such as the number who were approached to participate, the proportion who were eligible and who enrolled, and the number of participants who dropped out. The next part of the results should describe the participant characteristics. After that, you may organize your results by the aim or by putting the most exciting results first. Do not forget to report your non-significant associations. These are still findings.

Tables and figures capture the reader’s attention and efficiently communicate your main findings [ 3 ]. Each table and figure should have a clear message and should complement, rather than repeat, the text. Tables and figures should communicate all salient details necessary for a reader to understand the findings without consulting the text. Include information on comparisons and tests, as well as information about the sample and timing of the study in the title, legend, or in a footnote. Note that figures are often more visually interesting than tables, so if it is feasible to make a figure, make a figure. To avoid confusing the reader, either avoid abbreviations in tables and figures, or define them in a footnote. Note that there should not be citations in the results section and you should not interpret results here. Table 3 provides common results section pitfalls and recommendations for addressing them.

Discussion Section

Opposite the introduction section, the discussion should take the form of a right-side-up triangle beginning with interpretation of your results and moving to general implications (Fig.  2 ). This section typically begins with a restatement of the main findings, which can usually be accomplished with a few carefully-crafted sentences.

Major elements of the discussion section of an original research article. Often, the elements overlap

Next, interpret the meaning or explain the significance of your results, lifting the reader’s gaze from the study’s specific findings to more general applications. Then, compare these study findings with other research. Are these findings in agreement or disagreement with those from other studies? Does this study impart additional nuance to well-accepted theories? Situate your findings within the broader context of scientific literature, then explain the pathways or mechanisms that might give rise to, or explain, the results.

Journals vary in their approach to strengths and limitations sections: some are embedded paragraphs within the discussion section, while some mandate separate section headings. Keep in mind that every study has strengths and limitations. Candidly reporting yours helps readers to correctly interpret your research findings.

The next element of the discussion is a summary of the potential impacts and applications of the research. Should these results be used to optimally design an intervention? Does the work have implications for clinical protocols or public policy? These considerations will help the reader to further grasp the possible impacts of the presented work.

Finally, the discussion should conclude with specific suggestions for future work. Here, you have an opportunity to illuminate specific gaps in the literature that compel further study. Avoid the phrase “future research is necessary” because the recommendation is too general to be helpful to readers. Instead, provide substantive and specific recommendations for future studies. Table 4 provides common discussion section pitfalls and recommendations for addressing them.

Follow the Journal’s Author Guidelines

After you select a target journal, identify the journal’s author guidelines to guide the formatting of your manuscript and references. Author guidelines will often (but not always) include instructions for titles, cover letters, and other components of a manuscript submission. Read the guidelines carefully. If you do not follow the guidelines, your article will be sent back to you.

Finally, do not submit your paper to more than one journal at a time. Even if this is not explicitly stated in the author guidelines of your target journal, it is considered inappropriate and unprofessional.

Your title should invite readers to continue reading beyond the first page [ 4 , 5 ]. It should be informative and interesting. Consider describing the independent and dependent variables, the population and setting, the study design, the timing, and even the main result in your title. Because the focus of the paper can change as you write and revise, we recommend you wait until you have finished writing your paper before composing the title.

Be sure that the title is useful for potential readers searching for your topic. The keywords you select should complement those in your title to maximize the likelihood that a researcher will find your paper through a database search. Avoid using abbreviations in your title unless they are very well known, such as SNP, because it is more likely that someone will use a complete word rather than an abbreviation as a search term to help readers find your paper.

After you have written a complete draft, use the checklist (Fig. 3 ) below to guide your revisions and editing. Additional resources are available on writing the abstract and citing references [ 5 ]. When you feel that your work is ready, ask a trusted colleague or two to read the work and provide informal feedback. The box below provides a checklist that summarizes the key points offered in this article.

Checklist for manuscript quality

Data Availability

Michalek AM (2014) Down the rabbit hole…advice to reviewers. J Cancer Educ 29:4–5

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International Committee of Medical Journal Editors. Defining the role of authors and contributors: who is an author? http://www.icmje.org/recommendations/browse/roles-and-responsibilities/defining-the-role-of-authosrs-and-contributors.html . Accessed 15 January, 2020

Vetto JT (2014) Short and sweet: a short course on concise medical writing. J Cancer Educ 29(1):194–195

Brett M, Kording K (2017) Ten simple rules for structuring papers. PLoS ComputBiol. https://doi.org/10.1371/journal.pcbi.1005619

Lang TA (2017) Writing a better research article. J Public Health Emerg. https://doi.org/10.21037/jphe.2017.11.06

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Acknowledgments

Ella August is grateful to the Sustainable Sciences Institute for mentoring her in training researchers on writing and publishing their research.

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Busse, C., August, E. How to Write and Publish a Research Paper for a Peer-Reviewed Journal. J Canc Educ 36 , 909–913 (2021). https://doi.org/10.1007/s13187-020-01751-z

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Social Media Use and Its Connection to Mental Health: A Systematic Review

Fazida karim.

1 Psychology, California Institute of Behavioral Neurosciences and Psychology, Fairfield, USA

2 Business & Management, University Sultan Zainal Abidin, Terengganu, MYS

Azeezat A Oyewande

3 Family Medicine, California Institute of Behavioral Neurosciences and Psychology, Fairfield, USA

4 Family Medicine, Lagos State Health Service Commission/Alimosho General Hospital, Lagos, NGA

Lamis F Abdalla

5 Internal Medicine, California Institute of Behavioral Neurosciences and Psychology, Fairfield, USA

Reem Chaudhry Ehsanullah

Safeera khan.

Social media are responsible for aggravating mental health problems. This systematic study summarizes the effects of social network usage on mental health. Fifty papers were shortlisted from google scholar databases, and after the application of various inclusion and exclusion criteria, 16 papers were chosen and all papers were evaluated for quality. Eight papers were cross-sectional studies, three were longitudinal studies, two were qualitative studies, and others were systematic reviews. Findings were classified into two outcomes of mental health: anxiety and depression. Social media activity such as time spent to have a positive effect on the mental health domain. However, due to the cross-sectional design and methodological limitations of sampling, there are considerable differences. The structure of social media influences on mental health needs to be further analyzed through qualitative research and vertical cohort studies.

Introduction and background

Human beings are social creatures that require the companionship of others to make progress in life. Thus, being socially connected with other people can relieve stress, anxiety, and sadness, but lack of social connection can pose serious risks to mental health [ 1 ].

Social media

Social media has recently become part of people's daily activities; many of them spend hours each day on Messenger, Instagram, Facebook, and other popular social media. Thus, many researchers and scholars study the impact of social media and applications on various aspects of people’s lives [ 2 ]. Moreover, the number of social media users worldwide in 2019 is 3.484 billion, up 9% year-on-year [ 3 - 5 ]. A statistic in Figure  1  shows the gender distribution of social media audiences worldwide as of January 2020, sorted by platform. It was found that only 38% of Twitter users were male but 61% were using Snapchat. In contrast, females were more likely to use LinkedIn and Facebook. There is no denying that social media has now become an important part of many people's lives. Social media has many positive and enjoyable benefits, but it can also lead to mental health problems. Previous research found that age did not have an effect but gender did; females were much more likely to experience mental health than males [ 6 , 7 ].

Impact on mental health

Mental health is defined as a state of well-being in which people understand their abilities, solve everyday life problems, work well, and make a significant contribution to the lives of their communities [ 8 ]. There is debated presently going on regarding the benefits and negative impacts of social media on mental health [ 9 , 10 ]. Social networking is a crucial element in protecting our mental health. Both the quantity and quality of social relationships affect mental health, health behavior, physical health, and mortality risk [ 9 ]. The Displaced Behavior Theory may help explain why social media shows a connection with mental health. According to the theory, people who spend more time in sedentary behaviors such as social media use have less time for face-to-face social interaction, both of which have been proven to be protective against mental disorders [ 11 , 12 ]. On the other hand, social theories found how social media use affects mental health by influencing how people view, maintain, and interact with their social network [ 13 ]. A number of studies have been conducted on the impacts of social media, and it has been indicated that the prolonged use of social media platforms such as Facebook may be related to negative signs and symptoms of depression, anxiety, and stress [ 10 - 15 ]. Furthermore, social media can create a lot of pressure to create the stereotype that others want to see and also being as popular as others.

The need for a systematic review

Systematic studies can quantitatively and qualitatively identify, aggregate, and evaluate all accessible data to generate a warm and accurate response to the research questions involved [ 4 ]. In addition, many existing systematic studies related to mental health studies have been conducted worldwide. However, only a limited number of studies are integrated with social media and conducted in the context of social science because the available literature heavily focused on medical science [ 6 ]. Because social media is a relatively new phenomenon, the potential links between their use and mental health have not been widely investigated.

This paper attempt to systematically review all the relevant literature with the aim of filling the gap by examining social media impact on mental health, which is sedentary behavior, which, if in excess, raises the risk of health problems [ 7 , 9 , 12 ]. This study is important because it provides information on the extent of the focus of peer review literature, which can assist the researchers in delivering a prospect with the aim of understanding the future attention related to climate change strategies that require scholarly attention. This study is very useful because it provides information on the extent to which peer review literature can assist researchers in presenting prospects with a view to understanding future concerns related to mental health strategies that require scientific attention. The development of the current systematic review is based on the main research question: how does social media affect mental health?

Research strategy

The research was conducted to identify studies analyzing the role of social media on mental health. Google Scholar was used as our main database to find the relevant articles. Keywords that were used for the search were: (1) “social media”, (2) “mental health”, (3) “social media” AND “mental health”, (4) “social networking” AND “mental health”, and (5) “social networking” OR “social media” AND “mental health” (Table  1 ).

Out of the results in Table  1 , a total of 50 articles relevant to the research question were selected. After applying the inclusion and exclusion criteria, duplicate papers were removed, and, finally, a total of 28 articles were selected for review (Figure  2 ).

PRISMA, Preferred Reporting Items for Systematic Reviews and Meta-Analyses

Inclusion and exclusion criteria

Peer-reviewed, full-text research papers from the past five years were included in the review. All selected articles were in English language and any non-peer-reviewed and duplicate papers were excluded from finally selected articles.

Of the 16 selected research papers, there were a research focus on adults, gender, and preadolescents [ 10 - 19 ]. In the design, there were qualitative and quantitative studies [ 15 , 16 ]. There were three systematic reviews and one thematic analysis that explored the better or worse of using social media among adolescents [ 20 - 23 ]. In addition, eight were cross-sectional studies and only three were longitudinal studies [ 24 - 29 ].The meta-analyses included studies published beyond the last five years in this population. Table  2  presents a selection of studies from the review.

IGU, internet gaming disorder; PSMU, problematic social media use

This study has attempted to systematically analyze the existing literature on the effect of social media use on mental health. Although the results of the study were not completely consistent, this review found a general association between social media use and mental health issues. Although there is positive evidence for a link between social media and mental health, the opposite has been reported.

For example, a previous study found no relationship between the amount of time spent on social media and depression or between social media-related activities, such as the number of online friends and the number of “selfies”, and depression [ 29 ]. Similarly, Neira and Barber found that while higher investment in social media (e.g. active social media use) predicted adolescents’ depressive symptoms, no relationship was found between the frequency of social media use and depressed mood [ 28 ].

In the 16 studies, anxiety and depression were the most commonly measured outcome. The prominent risk factors for anxiety and depression emerging from this study comprised time spent, activity, and addiction to social media. In today's world, anxiety is one of the basic mental health problems. People liked and commented on their uploaded photos and videos. In today's age, everyone is immune to the social media context. Some teens experience anxiety from social media related to fear of loss, which causes teens to try to respond and check all their friends' messages and messages on a regular basis.

On the contrary, depression is one of the unintended significances of unnecessary use of social media. In detail, depression is limited not only to Facebooks but also to other social networking sites, which causes psychological problems. A new study found that individuals who are involved in social media, games, texts, mobile phones, etc. are more likely to experience depression.

The previous study found a 70% increase in self-reported depressive symptoms among the group using social media. The other social media influence that causes depression is sexual fun [ 12 ]. The intimacy fun happens when social media promotes putting on a facade that highlights the fun and excitement but does not tell us much about where we are struggling in our daily lives at a deeper level [ 28 ]. Another study revealed that depression and time spent on Facebook by adolescents are positively correlated [ 22 ]. More importantly, symptoms of major depression have been found among the individuals who spent most of their time in online activities and performing image management on social networking sites [ 14 ].

Another study assessed gender differences in associations between social media use and mental health. Females were found to be more addicted to social media as compared with males [ 26 ]. Passive activity in social media use such as reading posts is more strongly associated with depression than doing active use like making posts [ 23 ]. Other important findings of this review suggest that other factors such as interpersonal trust and family functioning may have a greater influence on the symptoms of depression than the frequency of social media use [ 28 , 29 ].

Limitation and suggestion

The limitations and suggestions were identified by the evidence involved in the study and review process. Previously, 7 of the 16 studies were cross-sectional and slightly failed to determine the causal relationship between the variables of interest. Given the evidence from cross-sectional studies, it is not possible to conclude that the use of social networks causes mental health problems. Only three longitudinal studies examined the causal relationship between social media and mental health, which is hard to examine if the mental health problem appeared more pronounced in those who use social media more compared with those who use it less or do not use at all [ 19 , 20 , 24 ]. Next, despite the fact that the proposed relationship between social media and mental health is complex, a few studies investigated mediating factors that may contribute or exacerbate this relationship. Further investigations are required to clarify the underlying factors that help examine why social media has a negative impact on some peoples’ mental health, whereas it has no or positive effect on others’ mental health.

Conclusions

Social media is a new study that is rapidly growing and gaining popularity. Thus, there are many unexplored and unexpected constructive answers associated with it. Lately, studies have found that using social media platforms can have a detrimental effect on the psychological health of its users. However, the extent to which the use of social media impacts the public is yet to be determined. This systematic review has found that social media envy can affect the level of anxiety and depression in individuals. In addition, other potential causes of anxiety and depression have been identified, which require further exploration.

The importance of such findings is to facilitate further research on social media and mental health. In addition, the information obtained from this study can be helpful not only to medical professionals but also to social science research. The findings of this study suggest that potential causal factors from social media can be considered when cooperating with patients who have been diagnosed with anxiety or depression. Also, if the results from this study were used to explore more relationships with another construct, this could potentially enhance the findings to reduce anxiety and depression rates and prevent suicide rates from occurring.

The content published in Cureus is the result of clinical experience and/or research by independent individuals or organizations. Cureus is not responsible for the scientific accuracy or reliability of data or conclusions published herein. All content published within Cureus is intended only for educational, research and reference purposes. Additionally, articles published within Cureus should not be deemed a suitable substitute for the advice of a qualified health care professional. Do not disregard or avoid professional medical advice due to content published within Cureus.

The authors have declared that no competing interests exist.

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Title: mm1: methods, analysis & insights from multimodal llm pre-training.

Abstract: In this work, we discuss building performant Multimodal Large Language Models (MLLMs). In particular, we study the importance of various architecture components and data choices. Through careful and comprehensive ablations of the image encoder, the vision language connector, and various pre-training data choices, we identified several crucial design lessons. For example, we demonstrate that for large-scale multimodal pre-training using a careful mix of image-caption, interleaved image-text, and text-only data is crucial for achieving state-of-the-art (SOTA) few-shot results across multiple benchmarks, compared to other published pre-training results. Further, we show that the image encoder together with image resolution and the image token count has substantial impact, while the vision-language connector design is of comparatively negligible importance. By scaling up the presented recipe, we build MM1, a family of multimodal models up to 30B parameters, including both dense models and mixture-of-experts (MoE) variants, that are SOTA in pre-training metrics and achieve competitive performance after supervised fine-tuning on a range of established multimodal benchmarks. Thanks to large-scale pre-training, MM1 enjoys appealing properties such as enhanced in-context learning, and multi-image reasoning, enabling few-shot chain-of-thought prompting.

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• 27 March 2024

Tweeting your research paper boosts engagement but not citations

• Bianca Nogrady

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Even before complaints about X’s declining quality, posting a paper on the social-media platform did not lead to a boost in citations. Credit: Matt Cardy/Getty

Posting about a research paper on social-media platform X (formerly known as Twitter) doesn’t translate into a bump in citations, according to a study that looked at 550 papers.

The finding comes as scientists are moving away from the platform in the wake of changes after its 2022 purchase by entrepreneur Elon Musk.

An international group of 11 researchers, who by the end of the experiment had between them nearly 230,000 followers on X, examined whether there was evidence that posting about a paper would increase its citation rate.

“There certainly is a correlation, and that’s been found in a lot of papers. But very few people have ever looked to see whether there’s any experimental causation,” says Trevor Branch, a marine ecologist at the University of Washington in Seattle and lead author on the paper, published in PLoS ONE last week 1 .

Every month for ten months, each researcher was allocated a randomly selected primary research article or review from a journal of their choice to post about on their personal account. Four randomly chosen articles from the same edition of the journal served as controls, which the researchers did not post about. They conducted the experiment in the period before Elon Musk took ownership of what was then known as Twitter and complaints of its declining quality increased.

‘Nail in the coffin’

Three years after the initial posts, the team compared the citation rates for the 110 posted articles with those of the 440 control articles, and found no significant difference. The researchers did acknowledge that their followers might not have been numerous enough to detect a statistically significant effect on citations.

The rate of daily downloads for the posted papers was nearly fourfold higher on the day that they were shared, compared with controls. Shared papers also had significantly higher accumulated Altmetric scores both 30 days and three years after the initial post. Calculated by London-based technology company Digital Science, an Altmetric score, says Branch, is a measure of how many people have looked at a paper and are talking about it, but it’s not a reliable indicator of a paper’s scientific worth. “It’s thoroughly biased by how many people with large followings tweet about it,” he says.

The findings echo those of information scientist Stefanie Haustein at the University of Ottawa, whose 2013 study 2 found a low correlation between posts and citations.

Haustein says the problem with using posts as a metric is that, even a decade ago, there was a lot of noise in the signal.

“We actually showed that a lot of the counts on Twitter you would get were bots, it wasn’t even humans,” says Haustein, who wasn’t involved in the new study.

She says the more recent departure of scientists from the platform has been the final nail in the coffin of the idea that posting could increase citations.

doi: https://doi.org/10.1038/d41586-024-00922-y

Branch, T. A. et al. PLoS ONE 19 , e0292201 (2024).

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Haustein, S., Peters, I., Sugimoto, C. R., Thelwall, M. & Larivière, V. J. Assoc. Inf. Sci. Technol. 65, 656–669 (2014).

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Will Knight

Apple’s MM1 AI Model Shows a Sleeping Giant Is Waking Up

While the tech industry went gaga for generative artificial intelligence , one giant has held back: Apple. The company has yet to introduce so much as an AI-generated emoji, and according to a New York Times report today and earlier reporting from Bloomberg, it is in preliminary talks with Google about adding the search company’s Gemini AI model to iPhones .

Yet a research paper quietly posted online last Friday by Apple engineers suggests that the company is making significant new investments into AI that are already bearing fruit. It details the development of a new generative AI model called MM1 capable of working with text and images. The researchers show it answering questions about photos and displaying the kind of general knowledge skills shown by chatbots like ChatGPT. The model’s name is not explained but could stand for MultiModal 1. MM1 appears to be similar in design and sophistication to a variety of recent AI models from other tech giants, including Meta’s open source Llama 2 and Google’s Gemini . Work by Apple’s rivals and academics shows that models of this type can be used to power capable chatbots or build “agents” that can solve tasks by writing code and taking actions such as using computer interfaces or websites. That suggests MM1 could yet find its way into Apple’s products.

“The fact that they’re doing this, it shows they have the ability to understand how to train and how to build these models,” says Ruslan Salakhutdinov , a professor at Carnegie Mellon who led AI research at Apple several years ago. “It requires a certain amount of expertise.”

MM1 is a multimodal large language model, or MLLM, meaning it is trained on images as well as text. This allows the model to respond to text prompts and also answer complex questions about particular images.

One example in the Apple research paper shows what happened when MM1 was provided with a photo of a sun-dappled restaurant table with a couple of beer bottles and also an image of the menu. When asked how much someone would expect to pay for “all the beer on the table,” the model correctly reads off the correct price and tallies up the cost.

When ChatGPT launched in November 2022, it could only ingest and generate text, but more recently its creator OpenAI and others have worked to expand the underlying large language model technology to work with other kinds of data. When Google launched Gemini (the model that now powers its answer to ChatGPT ) last December, the company touted its multimodal nature as beginning an important new direction in AI. “After the rise of LLMs, MLLMs are emerging as the next frontier in foundation models,” Apple’s paper says.

MM1 is a relatively small model as measured by its number of “parameters,” or the internal variables that get adjusted as a model is trained. Kate Saenko , a professor at Boston University who specializes in computer vision and machine learning, says this could make it easier for Apple’s engineers to experiment with different training methods and refinements before scaling up when they hit on something promising.

Saenko says the MM1 paper provides a surprising amount of detail on how the model was trained for a corporate publication. For instance, the engineers behind MM1 describe tricks for improving the performance of the model including increasing the resolution of images and mixing text and image data. Apple is famed for its secrecy, but it has previously shown unusual openness about AI research as it has sought to lure the talent needed to compete in the crucial technology.

Kate O'Flaherty

Saenko says it’s hard to draw too many conclusions about Apple’s plans from the research paper. Multimodal models have proven adaptable to many different use cases. But she suggests that MM1 could perhaps be a step toward building “some type of multimodal assistant that can describe photos, documents, or charts and answer questions about them.”

Apple’s flagship product, the iPhone, already has an AI assistant—Siri. The rise of ChatGPT and its rivals has quickly made the once revolutionary helper look increasingly limited and out-dated. Amazon and Google have said they are integrating LLM technology into their own assistants, Alexa and Google Assistant. Google allows users of Android phones to replace the Assistant with Gemini. Reports from The New York Times and Bloomberg that Apple may add Google’s Gemini to iPhones suggest Apple is considering expanding the strategy it has used for search on mobile devices to generative AI. Rather than develop web search technology in-house, the iPhone maker leans on Google, which reportedly pays more than $18 billion to make its search engine the iPhone default. Apple has also shown it can build its own alternatives to outside services, even when it starts from behind. Google Maps used to be the default on iPhones but in 2012 Apple replaced it with its own maps app .

Apple CEO Tim Cook has promised investors that the company will reveal more of its generative AI plans this year. The company faces pressure to keep up with rival smartphone makers, including Samsung and Google, that have introduced a raft of generative AI tools for their devices.

Apple could end up tapping both Google and its own, in-house AI, perhaps by introducing Gemini as a replacement for conventional Google Search while also building new generative AI tools on top of MM1 and other homegrown models. Last September, several of the researchers behind MM1 published details of MGIE , a tool that uses generative AI to manipulate images based on a text prompt.

Salakhutdinov believes his former employer may focus on developing LLMs that can be installed and run securely on Apple devices. That would fit with the company’s past emphasis on using “on-device” algorithms to safeguard sensitive data and avoid sharing it with other companies. A number of recent AI research papers from Apple concern machine-learning methods designed to preserve user privacy. “I think that's probably what Apple is going to do,” he says.

When it comes to tailoring generative AI to devices, Salakhutdinov says, Apple may yet turn out to have a distinct advantage because of its control over the entire software-hardware stack. The company has included a custom “neural engine” in the chips that power its mobile devices since 2017, with the debut of the iPhone X. “Apple is definitely working in that space, and I think at some point they will be in the front, because they have phones, the distribution.”

In a thread on X, Apple researcher Brandon McKinzie, lead author of the MM1 paper wrote : “This is just the beginning. The team is already hard at work on the next generation of models.”

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'Pretending to grow forests in the desert': New research questions integrity in safeguard mechanism scheme

A major Australian study has found some of the nation's biggest polluters are meeting their emissions obligations using carbon credits that have not actually resulted in emissions reductions.

Almost a third of projects under Australia's carbon credit scheme did little to nothing to reduce emissions despite costing taxpayers hundreds of millions of dollars, the researchers found.

Andrew Macintosh, one of the lead authors of the paper and an environment law and policy professor at the Australian National University first sounded the alarm two years ago, calling the carbon market "largely a sham".

His calls were rejected by a government-commissioned review, but Professor Macintosh said the new research shows further evidence that human-induced regeneration – a core part of the Australian Carbon Credit Unit (ACCU) scheme – hasn't worked.

"The data is telling us very clearly that the credits that are being issued are in no way shape or form being matched by the abatement that these projects are actually generating," He told the ABC.

Researchers monitored 182 Human Induced Regeneration (HIR) projects, which make up about 30 per cent of all ACCUs and have cost taxpayers nearly $300 million over their lifetime.

They found many of the projects to grow native forests were claiming to be regenerating them in uncleared desert and semi-desert areas.

According to the study, 80 per cent of those projects experienced either no change, or negative change to their tree cover between 2013 when first registered, and June 2022, despite receiving nearly 23 million credits.

Researchers say study calls into question emissions results of biggest emitters

In October 2023 the government banned the registration of new HIR projects, but existing projects are still operating and generating carbon credits.

The research group's claims would have significant implications for the government's safeguard mechanism, the emissions cap placed on heavy emitters that forces them to either lower their emissions or buy credits to abate them.

The safeguard mechanism applies to facilities that emit more than 100,000 tonnes of carbon dioxide emissions a year in the mining, oil and gas, manufacturing, transport and waste sectors.

Professor Macintosh said the ACCU scheme was "severely lacking in integrity" and jeopardised the integrity of the safeguard mechanism.

"Most of the [safeguard mechanism] entities that are covered by the [ACCU] scheme will meet their obligations by buying carbon credits and surrendering them, rather than reducing their own emissions," Professor Macintosh said.

"That would be fine if the carbon credits reflected real, additional and permanent abatement but what our results are saying is they're not."

HIR projects received 37 million credits to June 2023, nearing a third of the issuances under the scheme, and covering a total area of around 42 million hectares.

The researchers found an increase of just 1.8 per cent in tree cover across those projects, based on satellite data since the projects were registered.

Professor Macintosh said those projects also didn't show a marked difference in regeneration from other nearby areas outside the credit scheme.

"We also compared the trends of tree cover inside the projects that have been credited to what's happening in comparison areas," he said.

"The primary driver is not the controlling of grazing areas but something else, and that something else is very likely to be rainfall."

Recommendations for ACCU monitor progressing

In 2022 after Professor Macintosh blew the whistle on the carbon credit scheme, the government ordered a review led by the former national chief scientist Ian Chubb.

That review, released in January last year, dismissed claims the scheme lacked integrity . 

It said it disagreed with Professor Macintosh's claims the level of emissions reduction was overstated, and that the carbon credits scheme was not effective.

But the review did make a suite of recommendations, including a new integrity committee to monitor the scheme, which the government has agreed to establish.

Professor Macintosh has always questioned the methodology of that review.

"The main problem with the Chubb review is that they didn't analyse the performance of a single project to inform their decision or their conclusion that there wasn't a problem with over-crediting," he said.

Professor Macintosh has declared he has a competing interest as a non-executive director of Paraway Pastoral Company, which has projects that use Australia's offset scheme but does not have any HIR projects.

Climate Change and Energy Minister Chris Bowen reiterated that while he understood Professor Macintosh's disagreement with Professor Chubb's findings, he emphasised that Professor Macintosh's own findings were not supported by Professor Chubb.

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Use of Abortion Pills Has Risen Significantly Post Roe, Research Shows

By Pam Belluck

Pam Belluck has been reporting about reproductive health for over a decade.

• Share full article

On the eve of oral arguments in a Supreme Court case that could affect future access to abortion pills, new research shows the fast-growing use of medication abortion nationally and the many ways women have obtained access to the method since Roe v. Wade was overturned in June 2022.

The Details

A study, published on Monday in the medical journal JAMA , found that the number of abortions using pills obtained outside the formal health system soared in the six months after the national right to abortion was overturned. Another report, published last week by the Guttmacher Institute , a research organization that supports abortion rights, found that medication abortions now account for nearly two-thirds of all abortions provided by the country’s formal health system, which includes clinics and telemedicine abortion services.

The JAMA study evaluated data from overseas telemedicine organizations, online vendors and networks of community volunteers that generally obtain pills from outside the United States. Before Roe was overturned, these avenues provided abortion pills to about 1,400 women per month, but in the six months afterward, the average jumped to 5,900 per month, the study reported.

Overall, the study found that while abortions in the formal health care system declined by about 32,000 from July through December 2022, much of that decline was offset by about 26,000 medication abortions from pills provided by sources outside the formal health system.

“We see what we see elsewhere in the world in the U.S. — that when anti-abortion laws go into effect, oftentimes outside of the formal health care setting is where people look, and the locus of care gets shifted,” said Dr. Abigail Aiken, who is an associate professor at the University of Texas at Austin and the lead author of the JAMA study.

The co-authors were a statistics professor at the university; the founder of Aid Access, a Europe-based organization that helped pioneer telemedicine abortion in the United States; and a leader of Plan C, an organization that provides consumers with information about medication abortion. Before publication, the study went through the rigorous peer review process required by a major medical journal.

The telemedicine organizations in the study evaluated prospective patients using written medical questionnaires, issued prescriptions from doctors who were typically in Europe and had pills shipped from pharmacies in India, generally charging about $100. Community networks typically asked for some information about the pregnancy and either delivered or mailed pills with detailed instructions, often for free.

Online vendors, which supplied a small percentage of the pills in the study and charged between $39 and $470, generally did not ask for women’s medical history and shipped the pills with the least detailed instructions. Vendors in the study were vetted by Plan C and found to be providing genuine abortion pills, Dr. Aiken said.

The Guttmacher report, focusing on the formal health care system, included data from clinics and telemedicine abortion services within the United States that provided abortion to patients who lived in or traveled to states with legal abortion between January and December 2023.

It found that pills accounted for 63 percent of those abortions, up from 53 percent in 2020. The total number of abortions in the report was over a million for the first time in more than a decade.

Why This Matters

Overall, the new reports suggest how rapidly the provision of abortion has adjusted amid post-Roe abortion bans in 14 states and tight restrictions in others.

The numbers may be an undercount and do not reflect the most recent shift: shield laws in six states allowing abortion providers to prescribe and mail pills to tens of thousands of women in states with bans without requiring them to travel. Since last summer, for example, Aid Access has stopped shipping medication from overseas and operating outside the formal health system; it is instead mailing pills to states with bans from within the United States with the protection of shield laws.

What’s Next

In the case that will be argued before the Supreme Court on Tuesday, the plaintiffs, who oppose abortion, are suing the Food and Drug Administration, seeking to block or drastically limit the availability of mifepristone, the first pill in the two-drug medication abortion regimen.

The JAMA study suggests that such a ruling could prompt more women to use avenues outside the formal American health care system, such as pills from other countries.

“There’s so many unknowns about what will happen with the decision,” Dr. Aiken said.

She added: “It’s possible that a decision by the Supreme Court in favor of the plaintiffs could have a knock-on effect where more people are looking to access outside the formal health care setting, either because they’re worried that access is going away or they’re having more trouble accessing the medications.”

Pam Belluck is a health and science reporter, covering a range of subjects, including reproductive health, long Covid, brain science, neurological disorders, mental health and genetics. More about Pam Belluck

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