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For Publishers

ScienceOpen offers content hosting, context building and marketing services for publishers. See our tailored offerings

• For academic publishers  to promote journals and interdisciplinary collections
• For open access journals  to host journal content in an interactive environment
• For university library publishing  to develop new open access paradigms for their scholars
• For scholarly societies  to promote content with interactive features

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ScienceOpen offers state-of-the-art technology and a range of solutions and services

• For faculties and research groups  to promote and share your work
• For research institutes  to build up your own branding for OA publications
• For funders  to develop new open access publishing paradigms
• For university libraries to create an independent OA publishing environment

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Make an impact and build your research profile in the open with ScienceOpen

• Search and discover relevant research in over 93 million Open Access articles and article records
• Share your expertise and get credit by publicly reviewing any article
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ScienceOpen provides researchers with a wide range of tools to support their research – all for free. Here is a short checklist to make sure you are getting the most of the technological infrastructure and content that we have to offer. What can a researcher do on ScienceOpen? Continue reading “What can a Researcher do on ScienceOpen?”   

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A researcher’s complete guide to open access papers

Mathilde Darbier

Marketing Communications Manager

Open access is one of the most effective ways of ensuring your findings can be read and built upon by a broad audience. Sharing your papers and data without restrictions can help to build a better research culture, and lead to faster, more advanced outcomes for the global challenges we face today.

Open access isn’t an easy concept to grasp, however. In this blog, we provide you with a full overview of the various aspects of open access. We also cover the tools designed to help you discover freely-accessible papers and journals, including the Web of Science ™ and Journal Citation Reports ™.

• what open access is and how it developed
• the advantages of open access resources
• what to look out for when publishing open access papers
• the different types of open access available
• the costs involved in open access
• where you can find open access journals and papers

Looking for open access articles? Watch our video to quickly find and focus your search in the Web of Science.

What is open access and how did it develop?

Open access (OA) is the name for free, digital, full-text scientific and academic material made available online. As defined by Creative Commons, open access papers are “digital, online, free of charge, and free of most copyright and licensing restrictions.” 1 The 1990s saw the beginning of the open access movement brought on by the widespread availability of the World Wide Web, although researchers in physics and computer science had been self-archiving work on the internet long before this method of publication was officially named open access. Self-archiving articles into an online depository helped researchers share their papers more widely, optimizing access and maximizing its subsequent impact.

What are the advantages of making papers open access?

One of the greatest benefits of making your material open access is that you can disseminate your research more rapidly and to a broader audience. Your work will be available to a wider set of researchers, including to researchers and students from a diverse setting, helping them advance their work more quickly and enrich their learning without restriction 2 . This widespread distribution helps share new ideas, stimulate new studies, and greatly improves research and discovery in a vast number of academic disciplines. It may also increase your chances of more citations and impact. 2

Benefit from open access data in the Web of Science and Journal Citation Reports

The Web of Science is one of the most trusted solutions for researchers to discover open access publications. Our publisher-neutral approach means that you can quickly find papers that are not only free to read, but also from reputable sources worth your time and attention.

Using the Web of Science, you can access more than 14 million peer-reviewed open access papers. 32% of 2015 to 2019 Web of Science Core Collection™ records point to open access content.

Watch this video or read our blog to learn more about how to discover open access content on the Web of Science. This also extends to the Journal Citation Reports, where we included new open access publication data in early 2020 ( find out more ). This helps the research community better understand the contribution of gold open access content to the literature and its influence on scholarly discourse.

The different types of open access

There are no single, agreed-upon definitions of open access types. However, there are five relatively common types of open access worth knowing about, regardless of whether they’re “officially” accepted:

These different types of open access describe various ways to make academic work freely available online. We discuss these in more detail below (click any of the above links to skip to this section). First, here’s a short summary about Creative Commons Licences.

Creative Commons Licences

Open access papers sometimes have lenient copyright and licensing restrictions depending on the open access route they have been published through, allowing anyone on the internet to read, download, copy and distribute material within reasonable use.

Derivative work can also be produced using some open access papers, providing the original author is credited. Creative Commons licences help you share scholarly material legally online with standardized copyright licences. Below is a brief explanation of the different Creative Commons licences available.

With Creative Commons licences covered, what are the differences between open access types?

Green open access

Green open access makes the author responsible for making an article freely available and archiving it, whether it is archived by sharing it through an institution’s repository, a personal website or another public archive.

Some versions of Green OA papers may not have been copyedited, but may have been peer reviewed:

• Pre-publication Green refers to the version of your work before it has been submitted to a journal, and is sometimes called the pre-print version.
• Post-publication Green refers to the final draft of your work that has been accepted for publication by a journal, before it has been copyedited, typeset and proofread. It is also referred to as the post-print version.

The publisher will keep a copy of the full, peer reviewed version of your work, which is called the Version of Record (VOR) and readers can access these reviewed, full-text versions of the paper for a fee. This version is not Green open access, but alternative versions such as the pre-publication and post-publication version can be accessed under Green open access. The rights for reuse may be limited with Green open access, and access to Green OA papers may be limited by a publisher embargo period. An embargo period is when access to scholarly articles is not open to readers who have not paid for access. Different journals may have different embargo periods, so it is important to find out if the journal you have chosen to publish with will apply one to your work.

Bronze open access No open access fee is paid for Bronze open access, with the publisher choosing to make material freely available online. 5 Publishers are entitled to revoke open access rights to Bronze materials at any time, leading some to debate whether this is in line with true open access criteria.

Gold open access

Gold open access means the publisher is responsible for making the published academic material freely available online. Gold open access papers mean that the Version of Record is published and made freely available online. A Creative Commons licence will be applied to Gold open access papers in most cases. The Version of Record will be the final, peer reviewed paper.

Gold OA will not charge readers to access a paper, instead often charging an article processing charge (APC) to cover the publishing and distribution costs, for which the author isn’t always responsible. An institution or funder may pay the APC. A key benefit of Gold open access publishing is that as the author, you will retain copyright over your work under a Creative Commons licence. The full, unrestricted reuse of published work, providing the original author is cited, is allowed with Gold OA.

Platinum and Diamond open access In the Platinum and Diamond open access models, authors, institutions, and funders do not pay open access fees, and material is made free to read online. The publisher will pay any fees applied during the publication process. Platinum and Diamond open access models are popular with university presses that account for publishing costs in their budgets.

Hybrid open access

Hybrid open access is a mixed model where journals publish both Hybrid and subscription content. It allows authors to pay an article publication charge and publish specific work as Gold open access papers.

As an author, you can benefit from Hybrid open access because it allows you to publish with trusted journals. Authors often are more concerned about which journal is best to publish with than which business model (i.e. subscription or open access) journals use.

This can help a journal transition to operating on an open access business model as it will increase the amount of open access content its community is publishing.

Despite these advantages, Hybrid open access is not without its critics. Some take issue with the practice of so-called ‘double dipping’, where publishers charge institutions twice for the same content: authors who make their papers available as OA, and libraries who subscribe to the journal. With a number of charges applied to the publication process, it’s important to know what fees apply to making your work open access, and who is responsible for paying them.

What are the costs involved with open access?

There are a huge number of journals to submit academic work to, and it can be hard to know which journal is right for your work.

If you are the author of a paper, you may have to pay a fee to publish your work, or your research funder or institution may pay the fees in part or in full for you. A 2011 report showed that open access publication fees were only paid with personal funding in 12%  of cases, with funders paying in 59% of cases, and universities in 24% of cases. 6

APCs, also known as publication fees, are applied by many open access journals to account for peer reviewing and editorial costs, and to make material available in both open access journals or hybrid journals. There are still journals that do not apply article processing charges, but these charges are the most common way journals generate their income.

Luckily, as an author you may not always have to pay the full fees when publishing your work. For instance, some libraries offer deals to publishers, charging reduced rate fees if they publish your work in specific open access journals. This means you may be able to save money on article processing charges when submitting your papers to these peer reviewed journals.

In some cases, charges may be lifted due to financial hardship or due to the economic status of an author’s geographic location. If you do not have funding for APCs, ask the journal’s editorial team for their waiver policy. We also recommend checking whether the Directory of Open Access Journals (DOAJ) lists the journal you would like to be published in. Make sure you also read our blog to learn how products like Journal Citation Reports and the Master Journal List ™  help you find the right open access journal for your research in the fastest possible time. You can also watch our on demand webinar on the same topic.

Where can I find open access journals, papers and data?

There are a number of online tools that can help you source OA journals and papers, and below are just a few.

• The Web of Science allows you to discover world-class research literature from specially selected, high-quality journals, and users can easily access millions of peer-reviewed open access articles. You can also use Kopernio , a free browser plugin featured in the Web of Science to get one click access to your PDF faster using open access alternatives when the PDF you are looking for is not available via your existing institutional subscription. Watch our video to learn more .
• Master Journal List Manuscript Matcher is the ultimate place to begin your search for journals. It is a free tool that helps you narrow down your journal options based on your research topic and goals, with special filters for open access journals
• Journal Citation Reports is the most powerful product for journal intelligence. It uses transparent, publisher-neutral data and statistics to provide unique insights into a journal’s role, influence and the open access options available to you.
• Directory of Open Access Journals is a community-built directory that provides access to peer reviewed journals.
• PubMed Central is run by the National Institute of Health and is a full-text archive of biomedical and life sciences journals, which increases visibility of scholarly material.
• Check.Submit. is an international, cross-sector initiative offering tools and resources to help you identify trustworthy journals for your research.
• ROAD allows you to search for OA papers by name, subject or ISSN number.

If you’re looking for open access data , make sure you also check out the Web of Science Data Citation Index ™. It boasts 9.7 million datasets sourced from 380 repositories.

Open access is central to advancing discovery and improving education worldwide. It helps authors distribute their work more widely, and enables researchers like you to access quality, often peer reviewed work for free.

To ensure you can get the most out of open access publishing, don’t forget to check out our video about discovering open access content on the Web of Science. If you want to better understand the open access journals available when publishing your work, this blog (and on-demand webinar) will point you to the right tools to use.

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• Open access

Our open access publishing is key to delivering on our mission

Open access (OA) is a key part of how Oxford University Press (OUP) supports our mission to achieve the widest possible dissemination of high-quality research.  We publish rigorously peer-reviewed, world-leading, trusted open access research, upholding the highest standards of publication ethics and integrity.

We work closely with our publishing partners to ensure that we offer open access in a sustainable way, supporting publications for their communities and offering researchers publishing options for making their research available to all and compliant with funder mandates.

Our open access publishing in numbers

Our open access articles have the highest number of policy and patent document mentions, relative to volume of output, compared to other major academic publishers*

Our open access articles have the 2nd highest mean lifetime citation rate compared to other major academic publishers**

12 of our journals are diamond OA, meaning authors publish for free and readers access for free

We publish over 120 fully open access journals

More than 250 of the books we have published are open access

Over 400 of our journals have adopted a research data policy

Our Read & Publish agreements cover more than 900 institutions at which authors can use funds to publish their article open access in an OUP journal

More than 22,000 of the journal articles we published in 2022 are open access

Open access for Journals

OUP’s options for publishing open access in journals include:

Fully open access

Articles published in fully OA journals are available to all; no subscription is required. OUP’s fully OA journals use Creative Commons licenses and there is usually an Article Processing Charge (APC) for OA publication.

Hybrid open access

Hybrid journals include a mix of open access articles and articles available to those with a journal subscription.

Hybrid journals offer authors the option of gold open access publishing. With gold open access, authors usually pay an APC to make their research articles available immediately upon publication, under a Creative Commons licence with re-use rights for readers.

For articles published under a Creative Commons licence, readers can re-use the work under the terms of the applicable licence.

‘Read and Publish’ transformative agreements

OUP has agreements with many institutions to provide access to OUP journals for faculty and students and provide funding for open access publishing for affiliated researchers. Find out which institutions are participating, and how to take advantage of available funding for publishing in an OUP journal .

Green open access and self-archiving

OUP has self-archiving policies that permit authors to take advantage of green open access by depositing their accepted manuscript (i.e. the post-acceptance version, before copyediting) into a non-commercial repository. In non-commercial repositories, articles can become freely available after the proscribed embargo period. Find out more about OUP green OA for journals .

Inclusive publishing

OUP believes that the move to open access and open research needs to be equitable and inclusive for all. We want to ensure that authors can publish in their journal of choice. As part of our Developing Countries Initiative , corresponding authors based in qualifying countries publishing in any of OUP’s fully open access journals are eligible for a full waiver of their open access charge.

Open access for Books

OUP has supported OA for books since 2012 as part of our mission to publish high-quality academic and research publications and ensure they are accessible and discoverable.

Publishing your book on an OA basis makes your work freely available online, with no barriers to access. OUP applies the same peer review and editorial development processes to all books whether published open access or under a customer sales model.

If you are considering publishing a book on an OA basis with OUP, please discuss the idea with your Editor. In most instances, the open access fee for books is met by a research funder under their funding and open access policy. All prospective authors are encouraged to provide information on any funding which directly supports the research for a proposed book so that we can plan the publishing route accordingly. You can also consult our information on funders and funder policies.

When a book is published OA it is:

available to read on the Oxford Academic platform both in a browser and as a downloadable PDF

available on Google books as a full preview

indexed in, and available from, the OAPEN online library and the Directory of Open Access Books (DOAB) as a PDF

sold in print and as an eBook

Your editor will be able to provide a quote for open access based on your proposal. Our open access fee excludes any element for costs associated with print manufacture, stock, warehousing, and fulfilment. Our fee is based on the average costs associated with developing and producing a monograph adjusted in the case of longer works or works which involve additional features.

As well as publishing new books on an open access basis we are also able to convert backlist titles to OA and if you are the author of a published work and a funder has made funds available to help accelerate OA by converting existing published works, please contact your Editor.

Find out more about licences, charges and self-archiving for your open access book .

*Data source: Altmetric. Comparing number of policy and patent document mentions, relative to number of articles published, to Cambridge University Press, Elsevier, Frontiers, Hindawi, Institute of Physics Publishing, MDPI, PLOS, Sage, Springer Nature, Taylor & Francis, and Wiley.

**Data source: Dimensions. Comparing the mean lifetime citation rate of open access articles to those published by Cambridge University Press, Elsevier, Frontiers, Hindawi, Institute of Physics Publishing, MDPI, PLOS, Sage, Springer Nature, Taylor & Francis, and Wiley.

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

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Publishing open access offers a number of benefits

Explore open access journals and books

Open research is free to read, copy, reuse and distribute. Studies have shown that open access content attracts more attention than non-open access content.

Increased citation and usage

A number of research papers have shown that open access articles are viewed more often than articles that are only available to subscribers, and are cited more often.

Open access articles in hybrid journals attract more downloads, citations, and attention compared to those published behind a paywall. Our white paper, Assessing the open access effect for hybrid journals , examines the relationship between open access (OA) and impact, demonstrating the wider value hybrid journals bring to researchers, funders, institutions, and society more broadly.

A  study carried out by the Research Information Network  looking at articles published in Nature Communications found that the open access articles were viewed three times more often than non-open access content.

The Wellcome Trust also reported that open access articles they have funded were downloaded 89% more when compared with access-controlled content.

Greater public engagement

Open research means access to content is not limited to those with journal subscriptions. Many groups that miss out on subscription content - including researchers at institutions with limited access or funds, individual researchers not affiliated with an institution and the general public - find open access content not only available but valuable.

The impact of making research papers freely accessible from the moment of publication can be astonishing, particularly for research in which there is a strong public interest. For example, a  Scientific Reports paper exploring the biological impact of the Fukushima nuclear accident on the pale grass blue butterfly was accessed over a quarter of a million times during the first month after publication.

To further public engagement, each article published by a  Nature Partner Journal  includes a plain English overview of the article’s key findings. Presented in a brief, digestible format, this allows researchers in other fields and the interested public to engage with research.

Patient outcomes

Patient involvement in research is now a well-accepted concept with a key emphasis in the community on how we can improve our methods and evidence base. Open access has enabled those outside of research to benefit from new findings. BMC journal  Research Involvement and Engagement recently co-published Guidance for Reporting Involvement of Patients and Public ( GRIPP2 ) as a key way for for researchers and patient to understand how they should report involvement and engagement in research papers.

In 2017, BMC announced the introduction of Registered Reports in  BMC Medicine . BMC Medicine  publishes research articles and reviews in all areas of research and practice in medicine and global health. By pre-registering the rationale and proposed methodology behind a research study, research becomes more transparent and reproducible, and can have a direct, positive impact on patients and communities.

Policy impact

Over 38,000 Springer Nature open access articles have been cited in global policy documents by institutes including the United Nations, WHO, the IMF and the World Bank.

Make new discoveries

Open research accelerates the pace of scientific enquiry.

Faster impact

By opening up research with permissive licences like CC BY, researchers are empowered to build on existing research quickly. A study of articles published in  PNAS: Proceedings of the National Academy of Sciences  between June 8, 2004, and December 20, 2004 supported the view that open access accelerates the process by which researchers built upon existing research, showing that open access articles are cited earlier and are, on average, cited more often than non-open access articles.

Wider collaboration

Open access publications and data enable researchers to carry out collaborative research on a global scale, with the Human Genome Project often cited as an example of the ability of open access to transform publications and data “into a much more powerful resource for research, education and innovation” ( OASPA ). This international, collaborative research project was enabled by the use of open data, with all the sequence data made openly available for other researchers to reuse.

Increased interdisciplinary conversation

Interdisciplinary publications foster greater dialogue across discipline boundaries, and often find novel approaches to traditional problems. Open access journals that cross multiple disciplines, such as the BMC-series journals  and  Scientific Reports ,  are helping researchers connect more easily by providing greater visibility of their research. Open research also means that researchers can discover relevant research and data outside their main field via search engines, repositories, social media and a variety of other channels. 

Comply with funder mandates

Many funders, institutions and governments around the world require open access.

Meet policy requirements

Increasingly, the funders of scholarly research (funding bodies or institutions) are requiring their grant holders to make publications related to their research available to the public, free and without restrictions on re-use. Our open access journals and books comply with major funding policies  internationally.

Share and link research data

Openly sharing your research data ensures a greater level of reproducibility in science – something that is vital to the integrity of the scientific record. But it also provides you with additional, individual benefits.

Greater opportunity for collaboration

When data is openly shared it enables greater collaboration between researchers and also creates new research opportunities, as exemplified in the case of the studyforrest project in which a single dataset has generated multiple studies from different labs and resulted in 19 different publications so far.

Increase in citations

Studies have shown that published papers which have their underlying data openly available and directly linked to them have a higher level of citation than those that don’t.

Find out more about the benefits of openly sharing data .

Discover true, personal stories from SN researchers about their experience of publishing open access

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Open Access to Research Papers

Making scholarly research outputs openly available is easy, legal, and has demonstrable benefits to authors, making it a good beginning step for a researcher just beginning to explore the open world. There is a set of knowledge required to navigate the Open Access landscape, involving copyright, article status, repositories, and economics. This module will introduce key concepts and tools that can help a researcher make their work openly available and maximize the benefits to themselves and others.

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• Region: Global
• Type of Resources: E-course or annotated syllabus, learning module
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Open access at the Nature Portfolio

Nature and the nature research journals – now with immediate gold open access options for all primary research.

What is open access (OA)?

Why publish oa in the nature portfolio, options for oa at the nature portfolio , transformative journals, guided oa pilot, funding for open access, dedicated support for authors from lower income countries.

Under the OA model, an article is made immediately available online when published, and is free to read for anyone in the world, rather than only to subscribing readers or institutions. The article is made available under a Creative Commons CC-BY license, which allows for anyone to reuse, share, or build upon the work.

In our fully OA journals (such as Nature Communications and Scientific Reports ), all articles are made OA on publication. In a hybrid or transformative Journal (including Nature and the Nature research journals), authors can choose between gold OA or subscription publication, based on their preferences, funder or institutional requirements for OA, and the availability of APC funding.

Payment for publication is typically made by the authors’ institutions or funding bodies, who pay an Article Processing Charge (APC) when the research is accepted. APCs vary from title to title, starting from €2,290 in Scientific Reports to €10,290 in Nature .

• OA is immediately accessible and highly discoverable: anyone, anywhere can read, reuse and build on your work.
• Previous research shows the OA advantage for researchers: OA articles are cited on average 1.6 times more than non-OA articles, downloaded 4 times more often and attract 2.5 times more attention, as measured by news and policy mentions. 1
• Editorial rigour, with even greater reach: our OA options build on the foundations of our strong in-house editorial expertise. OA articles follow the same stringent standards. 
• Funder compliance: many funders and institutions now require articles to be published OA as part of the conditions of funding. We are enabling OA options for all primary research to enable our authors to meet these requirements, this includes Plan S.

At Springer Nature, we have been innovating in open research for two decades. At the Nature Portfolio that includes:

• Launching Scientific Reports in 2011: home for all original research from across the natural and clinical sciences. Now the 7th most-cited journal in the world, it attracted more than 350,000 citations in 2019 and receives widespread attention in policy documents and the media.
• Through Nature Communications , creating the first Nature OA journal, publishing papers that significantly advance the natural sciences. Since becoming fully OA in 2014, it is the most cited multidisciplinary open science journal in the world.
• Ensuring deposition of data and code alongside the research article to maximise transparency and reuse. Our active encouragement of data deposition has boosted data availability associated with published papers from around 50% to over 80% in some disciplines.
• Encouraging authors to submit protocols to the Protocols Exchange  – an open sharing platform – providing valuable detailed reporting on the analytical and experimental design as well as statistical analyses.
• Offering transparent peer review, publishing peer reviewer comments alongside the paper should the authors wish to do so. 
• Developing new OA journals to support the growing need for rigorous OA journals, including the Nature Partner Journals in collaboration with preeminent scientists, and our Communications journal series .

Nature and the Nature research journals are the first highly selective journals to offer their authors an immediate OA publishing option in this way. With more than 280 professional in-house Editors, more than 50,000 submissions each year, and an acceptance rate of less than 10%, the exceptional research in these journals has a profound effect on the disciplines to which it relates and the wider world. Research published in Nature and the Nature research journals is cited on average around 12 times more and downloaded by institutional users around 34 times more than papers in a typical journal. Find out more about the Nature research journals  

The guided open access pilot is now closed for submissions, and we are evaluating the pilot. We will be providing further information in due course.

Many organisations offer funding to support the costs of OA publication, including Max Planck Digital Library, University of California, and Finnish and Swedish Universities. 

If your institution has an open access agreement with Springer Nature, you may be able to publish OA in the wider Nature portfolio with fees covered. Find out more

Visit our open access funding page to check whether your institution or research funder makes OA funding available.

A dedicated fund has been made available to enable authors from many lower income countries (currently those classified by the World Bank as low-income (LIC) or lower-middle-income economies (LMICs)) to publish their primary research OA in Nature and the Nature research journals. 

It is a specific provision to support a subset of authors and only applies to our highly selective Nature Portfolio hybrid or transformative journals as they transition to OA and will be reviewed at the end of 2024. 

This applies to the following titles: Nature; Nature Aging; Nature Astronomy; Nature Biomedical Engineering; Nature Biotechnology; Nature Cancer; Nature Cardiovascular Research; Nature Catalysis; Nature Cell Biology; Nature Chemical Biology; Nature Chemistry; Nature Climate Change; Nature Computational Science; Nature Ecology & Evolution; Nature Electronics; Nature Energy; Nature Food; Nature Genetics; Nature Geoscience; Nature Human Behaviour; Nature Immunology; Nature Machine Intelligence; Nature Materials; Nature Medicine;  Nature Mental Health; Nature Metabolism; Nature Methods; Nature Microbiology; Nature Nanotechnology; Nature Neuroscience; Nature Photonics; Nature Physics; Nature Plants; Nature Structural & Molecular Biology; Nature Sustainability; Nature Synthesis and Nature Water; Nature Chemical Engineering and Nature Cities   . 

*It does not cover Nature Communications and Scientific Reports. 

Please see our journal pricing FAQs for more details. As part of this initiative, authors will not need to ask to benefit from the support. Corresponding authors  from qualifying countries whose primary research papers are accepted in principle (AIP) for publication in these titles will be informed as part of the publishing process that their paper will be published gold OA at no cost. Authors can opt out if they do not wish their papers to be published OA.

1 Within the first three years of publication.  Springer Nature hybrid journal OA impact analysis, 2018 .

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Open Access to Research Papers

Status : This module is currently in development

Making scholarly research outputs openly available is easy, legal, and has demonstrable benefits to authors, making it a good beginning step for a researcher just beginning to explore the open world. There is a set of knowledge required to navigate the Open Access landscape, involving copyright, article status, repositories, and economics. This module will introduce key concepts and tools that can help a researcher make their work openly available and maximize the benefits to themselves and others.

Learning outcomes

• The researcher will become familiar with the history of scholarly publishing, and development of the present Open Access landscape.
• The researcher will gain a multi-stakeholder insight into Open Access, and be able to convey a balanced overview of the perceived advantages and disadvantages associated with Open Access publishing.
• The researcher will be able to describe some of the complexities of the current the Open Access landscape, including allowances for self-archiving and embargoes, copyright transfer, and publishing contracts.
• Based on community-specific practices, the researcher will be able to use the different types of outlets (repositories) available for self-archiving, as well as the range of Open Access journal types available to them.
• Each researcher will able to make all of their own research papers Open Access through a combination of journals and development of a personal self-archiving protocol.
• Researchers will be able to describe the current ebb and flow in the debates around preprints, and be able to locate and use relevant disciplinary preprint platforms.
• Researchers will be able to use services like ImpactStory to track the proportion of their research that is Open Access.
• Think, Check, Submit and Cofactor journal selector tool
• SPARC Author Addendum and the Termination of Transfer tool , by Authors Alliance and Creative Commons
• Open Access Journal Whitelist , QUEST Center. Contains biomedical open access journals that are listed on the Directory of Open Access Journals (DOAJ) and Pubmed Central
• Unpaywall and the Open Access Button
• APCDOI , a program for determining how many DOIs are ‘gold’ or ‘hybrid’ Open Access and how much was spent on the article processing charges (APC) for these, Ryan Regier
• Open Science Framework preprints and PrePubMed
• SSRN (Social Sciences Research Network)
• ChemRxiv , Chemistry
• ESSOAr , Earth Sciences
• Cogprints , Psychology, Neuroscience and Linguistics
• CORE , an aggregator of 125 million Open Access articles
• Social Science Open Access Repository (SSOAR)
• LOADB , Listing of Open Access Databases
• REDALYC , network of scientific journals of Latin America and the Caribbean, Spain and Portugal
• LA Referencia
• SHERPA/RoMEO , Publisher Copyright Policies and Self-Archiving
• DULCINEA , for Spanish journals
• HAL , for French journals
• SHERPA Juliet ,Research Funders’ Open Access policies
• Wellcome Open Research and Gates Open Research
• Open Library of Humanities
• BioMed Central
• Open Knowledge Maps
• PASTEUR4OA , Open Access Policy Alignment Strategies for European Union Research
• The Publishing Trap , board game, to help researchers understand how money, intellectual property rights, and both open and closed publishing models affect the dissemination and impact of their work, UK Copyright Literacy
• Mathoverflow and PhysicsOverflow
• PubPub , collaborative community publishing
• JSTOR , a portal for open content
• Dimensions , for information on grants, publications, citations, clinical trials and patents
• Peer Community in
• Open Journals
• Discrete Analysis

Research Articles and Reports

• The Nine Flavours of Open Access Scholarly Publishing , Willinsky, 2003
• The Development of Open Access Journal Publishing from 1993 to 2009 , Laakso et al., 2011
• A Study of Open Access Journals Using Article Processing Charges , Solomon and Bjork, 2012
• Open Access (the book) , Suber, 2012
• Anatomy of Green Open Access , Bjork et al., 2013
• The case for open preprints in biology , Desjardins-Proulx et al., 2013
• arXiv e-prints and the journal of record: An analysis of roles and relationships , Lariviere et al., 2013
• Proportion of Open Access Papers Published in Peer-Reviewed Journals at the European and World Levels - 1996 - 2013 , European Commission, 2014
• Disrupting the subscription journals’ business model for the necessary large-scale transformation to open access , Schimmer et al., 2015
• Hybrid open access- A longitudinal study , Laakso and Bjork, 2016
• Point of View: How open science helps researchers succeed , McKiernan et al., 2016
• Converting scholarly journals to Open Access: A review of approaches and experiences , Solomon et al., 2016
• The academic, economic and societal impacts of Open Access: an evidence-based review , Tennant et al., 2016
• Open Access policies and Science Europe: State of play , Crowfoot, 2017
• Gold Open Access Publishing in Mega-Journals: Developing Countries Pay the Price of Western Premium Academic Output , Ellers et al., 2017
• Looking into Pandora’s Box: The Content of Sci-Hub and its Usage , Greshake, 2017
• On the origin of nonequivalent states: How we can talk about preprints , Neylon et al., 2017
• Open Access and OER in Latin America: A survey of the policy landscape in Chile, Colombia and Uruguay , Toledo, 2017
• Research: Sci-Hub provides access to nearly all scholarly literature , Himmelstein et al., 2018
• Converting the Literature of a Scientific Field to Open Access Through Global Collaboration: the Experience of SCOAP3 in Particle Physics , Kohls and Mele, 2018
• Open Access Initiatives and Networking in the Global South , Kuchma, 2018
• The State of OA: A large-scale analysis of the prevalence and impact of Open Access articles , Piwowar et al., 2018
• Authorial and institutional stratification in open access publishing: the case of global health research , Siler et al., 2018
• Good practices for university open-access policies , Harvard University
• Open Access Policy concerning UNESCO publications , UNESCO
• A genealogy of open access: negotiations between openness and access to research , Samuel Moore
• Open access and development: Research findings ,Elisa Liberatori Prati
• DOAJ APC information as of Jan 31, 2018 , Heather Morrison
• Open access policies and mandates around the globe , Jayashree Rajagopalan
• OpenDOAR , Directory of Open Access Repositories
• ROARMAP , Registry of Open Access Repository Mandates and Policies
• UK Scholarly Communications Licence and model policy , UKSCL
• Directory of Open Access Books , DOAB
• Knowledge Unlatched
• Compact on Open-Access Publishing Equity
• Quality Open Access Market
• Scientific Electronic Library Online , SciELO
• SCOAP3 , Sponsoring Consortium for Open Access Publishing in Particle Physics
• SPARC article and data sharing requirements by federal agency
• Open APC initiative , information on fees paid for OA journal articles by universities and research institutions under an Open Database License
• Free Journal Network ,
• Information Note: Towards a Horizon 2020 platform for Open Access , European Commission
• The Budapest Open Access Initiative
• HRCAK , Repository of the Croatian OA journals

Table of Content

The problem with making all academic research free

A new funding model for journals could deprive the world of valuable research in the humanities and social sciences..

There has been an earthquake in my corner of academia that will affect who teaches in prestigious universities and what ideas circulate among educated people around the world.

And it all happened because a concept rooted in good intentions — that academic research should be “open access,” free for everyone to read — has started to go too far.

The premise of open-access publishing is simple and attractive. It can cost libraries thousands of dollars a year to subscribe to academic journals, which sometimes means only academics affiliated with wealthy colleges and universities may access that research. But under open-access publishing, nearly anyone with an internet connection can find and read those articles for free. Authors win, because they find more readers. Academics around the world benefit, because they can access the latest scholarship. And the world wins, because scientific and intellectual progress is facilitated by the free exchange of ideas.

By now this model has taken hold in the natural sciences, especially in biology and biomedicine; during the pandemic many publishers removed paywalls from articles about vaccines and treatments. The Biden administration requires federally funded scholarly publications to be made freely available without any delay.

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However, there is no such thing as a free academic article. Even with digital distribution, the expenses of running a journal are considerable. These costs include hosting the websites where people submit, peer-review, and edit articles; copyediting; advertising; preserving journal archives; and maintaining continuity as editors come and go.

As a result, unless journals have a source of revenue other than subscription fees, any move toward open access raises the question of who will cover the costs of publication.

One answer is that the money will come from authors themselves or their academic institutions or other backers. This works well enough in the natural sciences, because those researchers are often funded by grants, and some of that money can be set aside to cover a journal’s fees for publishing scientific articles. The Bill and Melinda Gates Foundation demands that all research funded by the foundation, including the underlying data, be published open access.

According to a paper published in Quantitative Science Studies , however, only a small fraction of scholars in the humanities publish their articles on an open-access basis. Unlike biologists and biomedical engineers, humanities scholars such as philosophers and historians do not get grants that can cover the publishing costs.

This means that if open access is to take hold in those fields as well — as many publishers and academics are advocating — the costs will have to be covered by some foundation or other sponsor, by the scholars’ institutions, or even by the scholars themselves. And all these models have serious downsides.

I’m a political philosopher. The earthquake in my field that I mentioned earlier shook one of our most prominent journals: the Journal of Political Philosophy.

Publishing an article in this journal has long made the difference between whether a candidate gets hired, tenured, or promoted at an elite institution of higher education. The high quality has stemmed in large part from the rigorous approach of the founding editor, Robert Goodin.

At the end of 2023, the publisher, Wiley, terminated its contract with Goodin. The reasons were not immediately clear, and over 1,000 academics, including me, signed a petition stating that we would not serve on the editorial board or write or review for the journal until Wiley reinstates Goodin. I recently attended a panel at an American Philosophical Association conference where philosophers voiced their anger and puzzlement about the situation.

One source of the problem appears to be that Wiley now charges the authors of an article or their institutions $3,840 to get published open access in the journal.

The Journal of Political Philosophy is actually hybrid open access, which means it waives the article processing charges for authors who permit their work to appear behind a subscription-only paywall. Nonetheless, Goodin and Anna Stilz , a Princeton professor and Journal of Political Philosophy editorial board member, point out that publishers like Wiley now have a strong incentive to favor open-access articles.

In the old model, in which university libraries subscribed to journals, editors were mainly incentivized to publish first-rate material that would increase subscriptions. In the open-access model, however, now that authors or their universities must cover the costs of processing articles, publishers of humanities journals seem to be incentivized to boost revenue by accepting as many articles as possible. According to Goodin , open access has “been the death knell of quality academic publishing.” The reason that Goodin lost his job, Goodin and Stilz imply, is that Wiley pressured Goodin to accept more articles to increase Wiley’s profits, and he said no. (Wiley representatives say that lines of communication had collapsed with Goodin.)

Early this year, Goodin cofounded a new journal titled simply Political Philosophy . The journal will be published by the Open Library of Humanities, which is subsidized by libraries and institutions around the world. But this version of open-access publishing does not have the financial stability of the old subscription model. Scholars affiliated with the Open Library of Humanities have pointed out that the project has substantial overhead costs, and it relied on a grant from the Andrew W. Mellon Foundation that has already ended. The Open Library of Humanities is an experiment, and I hope that it works, but as of now it publishes only 30 journals , compared with the 1,600 journals that Wiley publishes.

The fact remains that no one has satisfactorily explained how open access could work in the humanities and social sciences.

In his 2023 book “ Athena Unbound : Why and How Scholarly Knowledge Should Be Free for All,” UCLA history professor Peter Baldwin attempts an answer. He points to Latin America, where some national governments cover all expenses of academic publishing. But this proposal ignores the fact that the governments of the United States and other nations probably do not want to pay for humanities and social sciences journals.

Baldwin also floats the idea of preprint depositories where academics could share documents on the cloud before they have undergone the (somewhat expensive) process of peer review. But this means that academics would lose the benefits that come from getting double-blind feedback from one’s peers. This idea would reduce the costs of publishing a journal article, but it would turn much academic writing into fancy blogging.

Ultimately, Baldwin’s solution is that authors might “have to participate directly, giving them skin in the game and helping contain costs.” This means academics might ask their employers to pay the article processing charges, ask a journal for the processing fees to be waived, or dig into their own pockets to pay to publish.

And it might mean less gets published overall. The journal Government and Opposition, published by Cambridge University Press, is entirely open access and charges $3,450 for an article to be published. I’d have to apply for a discount or a waiver to publish there. Or I could do what political philosophers in Japan and Bosnia and Herzegovina have told me they do: avoid submitting to open-access journals. Their universities will not cover their article processing charges except maybe in the top journals, and even the reduced fees can run into hundreds of dollars that these professors do not have.

In “Athena Unbound,” Baldwin notes that Harvard subscribes to 10 times as many periodicals as India’s Institute of Science. One can bemoan this fact, but one may also appreciate that Harvard’s largesse spreads enough subscription revenue around to reputable journals to enable academics to avoid paying to publish in them, no matter whether they teach at regional state schools, non-elite private schools, or institutions of higher education in poor countries. For all its flaws, the old model meant that when rich alumni donated to their alma maters, it increased library budgets and thereby made it possible for scholars of poetry and state politics to run and publish in academic journals.

Until we have more evidence that open-access journals in the humanities and social sciences can thrive in the long run, academics need to appreciate the advantages of the subscription model.

This article was updated on March 28 to correct the reference to the paper published in Quantitative Science Studies.

Nicholas Tampio is a professor of political science at Fordham University in New York City.

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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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Hazard ratio for obesity was modeled according to mean daily step counts and 25th, 50th, and 75th percentile PRS for body mass index. Shaded regions represent 95% CIs. Model is adjusted for age, sex, mean baseline step counts, cancer status, coronary artery disease status, systolic blood pressure, alcohol use, educational level, and a PRS × mean steps interaction term.

Mean daily steps and polygenic risk score (PRS) for higher body mass index are independently associated with hazard for obesity. Hazard ratios model the difference between the 75th and 25th percentiles for continuous variables. CAD indicate coronary artery disease; and SBP, systolic blood pressure.

Each point estimate is indexed to a hazard ratio for obesity of 1.00 (BMI [calculated as weight in kilograms divided by height in meters squared] ≥30). Error bars represent 95% CIs.

eTable. Cumulative Incidence Estimates of Obesity Based on Polygenic Risk Score for Body Mass Index and Mean Daily Steps at 1, 3, and 5 Years

eFigure 1. CONSORT Diagram

eFigure 2. Risk of Incident Obesity Modeled by Mean Daily Step Count and Polygenic Risk Scores Adjusted for Baseline Body Mass Index

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Brittain EL , Han L , Annis J, et al. Physical Activity and Incident Obesity Across the Spectrum of Genetic Risk for Obesity. JAMA Netw Open. 2024;7(3):e243821. doi:10.1001/jamanetworkopen.2024.3821

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Physical Activity and Incident Obesity Across the Spectrum of Genetic Risk for Obesity

• 1 Division of Cardiovascular Medicine, Vanderbilt University Medical Center, Nashville, Tennessee
• 2 Center for Digital Genomic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee
• 3 Division of Genetic Medicine, Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, Tennessee
• 4 Vanderbilt Institute of Clinical and Translational Research, Vanderbilt University Medical Center, Nashville, Tennessee
• 5 Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee
• 6 Department of Pharmacology, Vanderbilt University Medical Center, Nashville, Tennessee
• 7 Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee
• 8 Department of Biomedical Engineering, Vanderbilt University Medical Center, Nashville, Tennessee
• 9 Department of Biostatistics, Vanderbilt University Medical Center, Nashville, Tennessee
• 10 Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, Tennessee

Question   Does the degree of physical activity associated with incident obesity vary by genetic risk?

Findings   In this cohort study of 3124 adults, individuals at high genetic risk of obesity needed higher daily step counts to reduce the risk of obesity than those at moderate or low genetic risk.

Meaning   These findings suggest that individualized physical activity recommendations that incorporate genetic background may reduce obesity risk.

Importance   Despite consistent public health recommendations, obesity rates in the US continue to increase. Physical activity recommendations do not account for individual genetic variability, increasing risk of obesity.

Objective   To use activity, clinical, and genetic data from the All of Us Research Program (AoURP) to explore the association of genetic risk of higher body mass index (BMI) with the level of physical activity needed to reduce incident obesity.

Design, Setting, and Participants   In this US population–based retrospective cohort study, participants were enrolled in the AoURP between May 1, 2018, and July 1, 2022. Enrollees in the AoURP who were of European ancestry, owned a personal activity tracking device, and did not have obesity up to 6 months into activity tracking were included in the analysis.

Exposure   Physical activity expressed as daily step counts and a polygenic risk score (PRS) for BMI, calculated as weight in kilograms divided by height in meters squared.

Main Outcome and Measures   Incident obesity (BMI ≥30).

Results   A total of 3124 participants met inclusion criteria. Among 3051 participants with available data, 2216 (73%) were women, and the median age was 52.7 (IQR, 36.4-62.8) years. The total cohort of 3124 participants walked a median of 8326 (IQR, 6499-10 389) steps/d over a median of 5.4 (IQR, 3.4-7.0) years of personal activity tracking. The incidence of obesity over the study period increased from 13% (101 of 781) to 43% (335 of 781) in the lowest and highest PRS quartiles, respectively ( P  = 1.0 × 10 −20 ). The BMI PRS demonstrated an 81% increase in obesity risk ( P  = 3.57 × 10 −20 ) while mean step count demonstrated a 43% reduction ( P  = 5.30 × 10 −12 ) when comparing the 75th and 25th percentiles, respectively. Individuals with a PRS in the 75th percentile would need to walk a mean of 2280 (95% CI, 1680-3310) more steps per day (11 020 total) than those at the 50th percentile to have a comparable risk of obesity. To have a comparable risk of obesity to individuals at the 25th percentile of PRS, those at the 75th percentile with a baseline BMI of 22 would need to walk an additional 3460 steps/d; with a baseline BMI of 24, an additional 4430 steps/d; with a baseline BMI of 26, an additional 5380 steps/d; and with a baseline BMI of 28, an additional 6350 steps/d.

Conclusions and Relevance   In this cohort study, the association between daily step count and obesity risk across genetic background and baseline BMI were quantified. Population-based recommendations may underestimate physical activity needed to prevent obesity among those at high genetic risk.

In 2000, the World Health Organization declared obesity the greatest threat to the health of Westernized nations. 1 In the US, obesity accounts for over 400 000 deaths per year and affects nearly 40% of the adult population. Despite the modifiable nature of obesity through diet, exercise, and pharmacotherapy, rates have continued to increase.

Physical activity recommendations are a crucial component of public health guidelines for maintaining a healthy weight, with increased physical activity being associated with a reduced risk of obesity. 2 - 4 Fitness trackers and wearable devices have provided an objective means to capture physical activity, and their use may be associated with weight loss. 5 Prior work leveraging these devices has suggested that taking around 8000 steps/d substantially mitigates risk of obesity. 3 , 4 However, current recommendations around physical activity do not take into account other contributors such as caloric intake, energy expenditure, or genetic background, likely leading to less effective prevention of obesity for many people. 6

Obesity has a substantial genetic contribution, with heritability estimates ranging from 40% to 70%. 7 , 8 Prior studies 9 - 11 have shown an inverse association between genetic risk and physical activity with obesity, whereby increasing physical activity can help mitigate higher genetic risk for obesity. These results have implications for physical activity recommendations on an individual level. Most of the prior work 9 - 11 focused on a narrow set of obesity-associated variants or genes and relied on self-reported physical activity, and more recent work using wearable devices has been limited to 7 days of physical activity measurements. 12 Longer-term capture in large populations will be required to accurately estimate differences in physical activity needed to prevent incident obesity.

We used longitudinal activity monitoring and genome sequencing data from the All of Us Research Program (AoURP) to quantify the combined association of genetic risk for body mass index (BMI; calculated as weight in kilograms divided by height in meters squared) and physical activity with the risk of incident obesity. Activity monitoring was quantified as daily step counts obtained from fitness tracking devices. Genetic risk was quantified by using a polygenic risk score (PRS) from a large-scale genomewide association study (GWAS) of BMI. 13 We quantified the mean daily step count needed to overcome genetic risk for increased BMI. These findings represent an initial step toward personalized exercise recommendations that integrate genetic information.

Details on the design and execution of the AoURP have been published previously. 14 The present study used AoURP Controlled Tier dataset, version 7 (C2022Q4R9), with data from participants enrolled between May 1, 2018, and July 1, 2022. Participants who provided informed consent could share data from their own activity tracking devices from the time their accounts were first created, which may precede the enrollment date in AoURP. We followed the Strengthening the Reporting of Observational Studies in Epidemiology ( STROBE ) reporting guideline. In this study, only the authorized authors who completed All of Us Responsible Conduct of Research training accessed the deidentified data from the Researcher Workbench (a secured cloud-based platform). Since the authors were not directly involved with the participants, institutional review board review was exempted in compliance with AoURP policy.

Activity tracking data for this study came from the Bring Your Own Device program that allowed individuals who already owned a tracking device (Fitbit, Inc) to consent to link their activity data with other data in the AoURP. By registering their personal device on the AoURP patient portal, patients could share all activity data collected since the creation of their personal device account. For many participants, this allowed us to examine fitness activity data collected prior to enrollment in the AoURP. Activity data in AoURP are reported as daily step counts. We excluded days with fewer than 10 hours of wear time to enrich our cohort for individuals with consistently high wear time. The initial personal activity device cohort consisted of 12 766 individuals. Consistent with our prior data curation approach, days with less than 10 hours of wear time, less than 100 steps, or greater than 45 000 steps or for which the participant was younger than 18 years were removed. For time-varying analyses, mean daily steps were calculated on a monthly basis for each participant. Months with fewer than 15 valid days of monitoring were removed.

The analytic cohort included only individuals with a BMI of less than 30 at the time activity monitoring began. The primary outcome was incident obesity, defined as a BMI of 30 or greater documented in the medical record at least 6 months after initiation of activity monitoring. The latter stipulation reduced the likelihood that having obesity predated the beginning of monitoring but had not yet been clinically documented. We extracted BMI values and clinical characteristics from longitudinal electronic health records (EHRs) for the consenting participants who were associated with a health care provider organization funded by the AoURP. The EHR data have been standardized using the Observational Medical Outcomes Partnership Common Data Model. 15 In the AoURP, upon consent, participants are asked to complete the Basics survey, in which they may self-report demographic characteristics such as race, ethnicity, and sex at birth.

We filtered the data to include only biallelic, autosomal single-nucleotide variants (SNVs) that had passed AoURP initial quality control. 16 We then removed duplicate-position SNVs and kept only individual genotypes with a genotype quality greater than 20. We further filtered the SNVs based on their Hardy-Weinberg equilibrium P value (>1.0 × 10 −15 ) and missing rate (<5%) across all samples. Next, we divided the samples into 6 groups (Admixed American, African, East Asian, European, Middle Eastern, and South Asian) based on their estimated ancestral populations 16 , 17 and further filtered the SNVs within each population based on minor allele frequency (MAF) (>0.01), missing rate (<0.02), and Hardy-Weinberg equilibrium P value (>1.0 × 10 −6 ). The SNVs were mapped from Genome Reference Consortium Human Build 38 with coordinates to Build 37. Because the existing PRS models have limited transferability across ancestry groups and to ensure appropriate power of the subsequent PRS analysis, we limited our analysis to the populations who had a sample size of greater than 500, resulting in 5964 participants of European ancestry with 5 515 802 common SNVs for analysis.

To generate principal components, we excluded the regions with high linkage disequilibrium, including chr5:44-51.5 megabase (Mb), chr6:25-33.5 Mb, chr8:8-12 Mb, and chr11:45-57 Mb. We then pruned the remaining SNVs using PLINK, version 1.9 (Harvard University), pairwise independence function with 1-kilobase window shifted by 50 base pairs and requiring r 2 < 0.05 between any pair, resulting in 100 983 SNPs for further analysis. 18 Principal component analysis was run using PLINK, version 1.9. The European ancestry linkage disequilibrium reference panel from the 1000 Genomes Project phase 3 was downloaded, and nonambiguous SNPs with MAF greater than 0.01 were kept in the largest European ancestry GWAS summary statistics of BMI. 13 We manually harmonized the strand-flipping SNPs among the SNP information file, GWAS summary statistics files, and the European ancestry PLINK extended map files (.bim).

We used PRS–continuous shrinkage to infer posterior SNP effect sizes under continuous shrinkage priors with a scaling parameter set to 0.01, reflecting the polygenic architecture of BMI. GWAS summary statistics of BMI measured in 681 275 individuals of European ancestry was used to estimate the SNP weights. 19 The scoring command in PLINK, version 1.9, was used to produce the genomewide scores of the AoURP European individuals with their quality-controlled SNP genotype data and these derived SNP weights. 20 Finally, by using the genomewide scores as the dependent variable and the 10 principal components as the independent variable, we performed linear regression, and the obtained residuals were kept for the subsequent analysis. To check the performance of the PRS estimate, we first fit a generalized regression model with obesity status as the dependent variable and the PRS as the independent variable with age, sex, and the top 10 principal components of genetic ancestry as covariates. We then built a subset logistic regression model, which only uses the same set of covariates. By comparing the full model with the subset model, we measured the incremental Nagelkerke R 2 value to quantify how much variance in obesity status was explained by the PRS.

Differences in clinical characteristics across PRS quartiles were assessed using the Wilcoxon rank sum or Kruskal-Wallis test for continuous variables and the Pearson χ 2 test for categorical variables. Cox proportional hazards regression models were used to examine the association among daily step count (considered as a time-varying variable), PRS, and the time to event for obesity, adjusting for age, sex, mean baseline step counts, cancer status, coronary artery disease status, systolic blood pressure, alcohol use, educational level, and interaction term of PRS × mean steps. We presented these results stratified by baseline BMI and provided a model including baseline BMI in eFigure 2 in Supplement 1 as a secondary analysis due to collinearity between BMI and PRS.

Cox proportional hazards regression models were fit on a multiply imputed dataset. Multiple imputation was performed for baseline BMI, alcohol use, educational status, systolic blood pressure, and smoking status using bootstrap and predictive mean matching with the aregImpute function in the Hmisc package of R, version 4.2.2 (R Project for Statistical Computing). Continuous variables were modeled as restricted cubic splines with 3 knots, unless the nonlinear term was not significant, in which case it was modeled as a linear term. Fits and predictions of the Cox proportional hazards regression models were obtained using the rms package in R, version 4.2.2. The Cox proportional hazards regression assumptions were checked using the cox.zph function from the survival package in R, version 4.2.2.

To identify the combinations of PRS and mean daily step counts associated with a hazard ratio (HR) of 1.00, we used a 100-knot spline function to fit the Cox proportional hazards regression ratio model estimations across a range of mean daily step counts for each PRS percentile. We then computed the inverse of the fitted spline function to determine the mean daily step count where the HR equals 1.00 for each PRS percentile. We repeated this process for multiple PRS percentiles to generate a plot of mean daily step counts as a function of PRS percentiles where the HR was 1.00. To estimate the uncertainty around these estimations, we applied a similar spline function to the upper and lower estimated 95% CIs of the Cox proportional hazards regression model to find the 95% CIs for the estimated mean daily step counts at each PRS percentile. Two-sided P < .05 indicated statistical significance.

We identified 3124 participants of European ancestry without obesity at baseline who agreed to link their personal activity data and EHR data and had available genome sequencing. Among those with available data, 2216 of 3051 (73%) were women and 835 of 3051 (27%) were men, and the median age was 52.7 (IQR, 36.4-62.8) years. In terms of race and ethnicity, 2958 participants (95%) were White compared with 141 participants (5%) who were of other race or ethnicity (which may include Asian, Black or African American, Middle Eastern or North African, Native Hawaiian or Other Pacific Islander, multiple races or ethnicities, and unknown race or ethnicity) ( Table ). The analytic sample was restricted to individuals assigned European ancestry based on the All of Us Genomic Research Data Quality Report. 16 A study flowchart detailing the creation of the analytic dataset is provided in eFigure 1 in Supplement 1 . The BMI-based PRS explained 8.3% of the phenotypic variation in obesity (β = 1.76; P  = 2 × 10 −16 ). The median follow-up time was 5.4 (IQR, 3.4-7.0) years and participants walked a median of 8326 (IQR, 6499-10 389) steps/d. The incidence of obesity over the study period was 13% (101 of 781 participants) in the lowest PRS quartile and 43% (335 of 781 participants) in the highest PRS quartile ( P  = 1.0 × 10 −20 ). We observed a decrease in median daily steps when moving from lowest (8599 [IQR, 6751-10 768]) to highest (8115 [IQR, 6340-10 187]) PRS quartile ( P  = .01).

We next modeled obesity risk stratified by PRS percentile with the 50th percentile indexed to an HR for obesity of 1.00 ( Figure 1 ). The association between PRS and incident obesity was direct ( P  = .001) and linear (chunk test for nonlinearity was nonsignificant [ P  = .07]). The PRS and mean daily step count were both independently associated with obesity risk ( Figure 2 ). The 75th percentile BMI PRS demonstrated an 81% increase in obesity risk (HR, 1.81 [95% CI, 1.59-2.05]; P  = 3.57 × 10 −20 ) when compared with the 25th percentile BMI PRS, whereas the 75th percentile median step count demonstrated a 43% reduction in obesity risk (HR, 0.57 [95% CI, 0.49-0.67]; P  = 5.30 × 10 −12 ) when compared with the 25th percentile step count. The PRS × mean steps interaction term was not significant (χ 2 = 1.98; P  = .37).

Individuals with a PRS at the 75th percentile would need to walk a mean of 2280 (95% CI, 1680-3310) more steps per day (11 020 total) than those at the 50th percentile to reduce the HR for obesity to 1.00 ( Figure 1 ). Conversely, those in the 25th percentile PRS could reach an HR of 1.00 by walking a mean of 3660 (95% CI, 2180-8740) fewer steps than those at the 50th percentile PRS. When assuming a median daily step count of 8740 (cohort median), those in the 75th percentile PRS had an HR for obesity of 1.33 (95% CI, 1.25-1.41), whereas those at the 25th percentile PRS had an obesity HR of 0.74 (95% CI, 0.69-0.79).

The mean daily step count required to achieve an HR for obesity of 1.00 across the full PRS spectrum and stratified by baseline BMI is shown in Figure 3 . To reach an HR of 1.00 for obesity, when stratified by baseline BMI of 22, individuals at the 50th percentile PRS would need to achieve a mean daily step count of 3290 (additional 3460 steps/d); for a baseline BMI of 24, a mean daily step count of 7590 (additional 4430 steps/d); for a baseline BMI of 26, a mean daily step count of 11 890 (additional 5380 steps/d); and for a baseline BMI of 28, a mean daily step count of 16 190 (additional 6350 steps/d).

When adding baseline BMI to the full Cox proportional hazards regression model, daily step count and BMI PRS both remain associated with obesity risk. When comparing individuals at the 75th percentile with those at the 25th percentile, the BMI PRS is associated with a 61% increased risk of obesity (HR, 1.61 [95% CI, 1.45-1.78]). Similarly, when comparing the 75th with the 25th percentiles, daily step count was associated with a 38% lower risk of obesity (HR, 0.62 [95% CI, 0.53-0.72]) (eFigure 2 in Supplement 1 ).

The cumulative incidence of obesity increases over time and with fewer daily steps and higher PRS. The cumulative incidence of obesity would be 2.9% at the 25th percentile, 3.9% at the 50th percentile, and 5.2% at the 75th percentile for PRS in year 1; 10.5% at the 25th percentile, 14.0% at the 50th percentile, and 18.2% at the 75th percentile for PRS in year 3; and 18.5% at the 25th percentile, 24.3% at the 50th percentile, and 30.9% at the 75th percentile for PRS in year 5 ( Figure 4 ). The eTable in Supplement 1 models the expected cumulative incidence of obesity at 1, 3, and 5 years based on PRS and assumed mean daily steps of 7500, 10 000, and 12 500.

We examined the combined association of daily step counts and genetic risk for increased BMI with the incidence of obesity in a large national sample with genome sequencing and long-term activity monitoring data. Lower daily step counts and higher BMI PRS were both independently associated with increased risk of obesity. As the PRS increased, the number of daily steps associated with lower risk of obesity also increased. By combining these data sources, we derived an estimate of the daily step count needed to reduce the risk of obesity based on an individual’s genetic background. Importantly, our findings suggest that genetic risk for obesity is not deterministic but can be overcome by increasing physical activity.

Our findings align with those of prior literature 9 indicating that engaging in physical activity can mitigate genetic obesity risk and highlight the importance of genetic background for individual health and wellness. Using the data from a large population-based sample, Li et al 9 characterized obesity risk by genotyping 12 susceptibility loci and found that higher self-reported physical activity was associated with a 40% reduction in genetic predisposition to obesity. Our study extends these results in 2 important ways. First, we leveraged objectively measured longitudinal activity data from commercial devices to focus on physical activity prior to and leading up to a diagnosis of obesity. Second, we used a more comprehensive genomewide risk assessment in the form of a PRS. Our results indicate that daily step count recommendations to reduce obesity risk may be personalized based on an individual’s genetic background. For instance, individuals with higher genetic risk (ie, 75th percentile PRS) would need to walk a mean of 2280 more steps per day than those at the 50th percentile of genetic risk to have a comparable risk of obesity.

These results suggest that population-based recommendations that do not account for genetic background may not accurately represent the amount of physical activity needed to reduce the risk of obesity. Population-based exercise recommendations may overestimate or underestimate physical activity needs, depending on one’s genetic background. Underestimation of physical activity required to reduce obesity risk has the potential to be particularly detrimental to public health efforts to reduce weight-related morbidity. As such, integration of activity and genetic data could facilitate personalized activity recommendations that account for an individual’s genetic profile. The widespread use of wearable devices and the increasing demand for genetic information from both clinical and direct-to-consumer sources may soon permit testing the value of personalized activity recommendations. Efforts to integrate wearable devices and genomic data into the EHR further support the potential future clinical utility of merging these data sources to personalize lifestyle recommendations. Thus, our findings support the need for a prospective trial investigating the impact of tailoring step counts by genetic risk on chronic disease outcomes.

The most important limitation of this work is the lack of diversity and inclusion only of individuals with European ancestry. These findings will need validation in a more diverse population. Our cohort only included individuals who already owned a fitness tracking device and agreed to link their activity data to the AoURP dataset, which may not be generalizable to other populations. We cannot account for unmeasured confounding, and the potential for reverse causation still exists. We attempted to diminish the latter concern by excluding prevalent obesity and incident cases within the first 6 months of monitoring. Genetic risk was simplified to be specific to increased BMI; however, genetic risk for other cardiometabolic conditions could also inform obesity risk. Nongenetic factors that contribute to obesity risk such as dietary patterns were not available, reducing the explanatory power of the model. It is unlikely that the widespread use of drug classes targeting weight loss affects the generalizability of our results, because such drugs are rarely prescribed for obesity prevention, and our study focused on individuals who were not obese at baseline. Indeed, less than 0.5% of our cohort was exposed to a medication class targeting weight loss (phentermine, orlistat, or glucagonlike peptide-1 receptor agonists) prior to incident obesity or censoring. Finally, some fitness activity tracking devices may not capture nonambulatory activity as well as triaxial accelerometers.

This cohort study used longitudinal activity data from commercial wearable devices, genome sequencing, and clinical data to support the notion that higher daily step counts can mitigate genetic risk for obesity. These results have important clinical and public health implications and may offer a novel strategy for addressing the obesity epidemic by informing activity recommendations that incorporate genetic information.

Accepted for Publication: January 30, 2024.

Published: March 27, 2024. doi:10.1001/jamanetworkopen.2024.3821

Open Access: This is an open access article distributed under the terms of the CC-BY License . © 2024 Brittain EL et al. JAMA Network Open .

Corresponding Author: Evan L. Brittain, MD, MSc ( [email protected] ) and Douglas M. Ruderfer, PhD ( [email protected] ), Vanderbilt University Medical Center, 2525 West End Ave, Suite 300A, Nashville, TN 37203.

Author Contributions: Drs Brittain and Ruderfer had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Brittain, Annis, Master, Roden, Ruderfer.

Acquisition, analysis, or interpretation of data: Brittain, Han, Annis, Master, Hughes, Harris, Ruderfer.

Drafting of the manuscript: Brittain, Han, Annis, Master, Ruderfer.

Critical review of the manuscript for important intellectual content: All authors.

Statistical analysis: Brittain, Han, Annis, Master.

Obtained funding: Brittain, Harris.

Administrative, technical, or material support: Brittain, Annis, Master, Roden.

Supervision: Brittain, Ruderfer.

Conflict of Interest Disclosures: Dr Brittain reported receiving a gift from Google LLC during the conduct of the study. Dr Ruderfer reported serving on the advisory board of Illumina Inc and Alkermes PLC and receiving grant funding from PTC Therapeutics outside the submitted work. No other disclosures were reported.

Funding/Support: The All of Us Research Program is supported by grants 1 OT2 OD026549, 1 OT2 OD026554, 1 OT2 OD026557, 1 OT2 OD026556, 1 OT2 OD026550, 1 OT2 OD 026552, 1 OT2 OD026553, 1 OT2 OD026548, 1 OT2 OD026551, 1 OT2 OD026555, IAA AOD21037, AOD22003, AOD16037, and AOD21041 (regional medical centers); grant HHSN 263201600085U (federally qualified health centers); grant U2C OD023196 (data and research center); 1 U24 OD023121 (Biobank); U24 OD023176 (participant center); U24 OD023163 (participant technology systems center); grants 3 OT2 OD023205 and 3 OT2 OD023206 (communications and engagement); and grants 1 OT2 OD025277, 3 OT2 OD025315, 1 OT2 OD025337, and 1 OT2 OD025276 (community partners) from the National Institutes of Health (NIH). This study is also supported by grants R01 HL146588 (Dr Brittain), R61 HL158941 (Dr Brittain), and R21 HL172038 (Drs Brittain and Ruderfer) from the NIH.

Role of the Funder/Sponsor: The NIH had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Data Sharing Statement: See Supplement 2 .

Additional Contributions: The All of Us Research Program would not be possible without the partnership of its participants.

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