Frequently Asked Questions
Everything you need to know about participating in Meta-Student. Can't find your answer? Get in touch.
General
What is Meta-Student?
Meta-Student is a platform that pools individual participant-level data from undergraduate and postgraduate research projects into living meta-analyses. Each contributing student earns co-authorship on the resulting peer-reviewed publication (if successfully published). The platform was developed by the Sports Science Replication Centre (SSRC), but is open to researchers and students from any scientific discipline.
Is Meta-Student only for sport and exercise science?
No. Although Meta-Student was developed by the Sports Science Replication Centre, the platform is designed to support collaborative IPD meta-analysis across any scientific discipline — psychology, health sciences, education, biology, nutrition, and beyond. If your study design fits one of the supported protocols (RCT, pre-post, crossover, cross-sectional, or RCT with pre-post measures), you are welcome to propose a study or register to contribute.
Who can participate?
Any student conducting a research project that matches one of the active study protocols can participate, regardless of discipline or institution. You need a supervisor who will approve your registration and verify your data. Both your account and your supervisor's email must be institutional addresses — see below.
Are personal email addresses (Gmail, Outlook, etc.) accepted?
No. A university or institutional email address is required for both student accounts and supervisor approvals. Personal email providers (including Gmail, Outlook, Hotmail, Yahoo, iCloud, etc) are not accepted at any stage. If you do not have an institutional email address, please contact your university IT services. This requirement exists to verify academic affiliation and maintain the integrity of the research record.
Does it cost anything?
No. Meta-Student is free for students, supervisors, and institutions. It is an academic research infrastructure project.
How do I earn co-authorship?
If your dataset passes validation and is included in the final meta-analysis, you are listed as a co-author on the resulting publication. Authorship follows the guidelines set by the project lead and the relevant journal policy. Users are reminded that the academic peer-review process does not guarantee that every study will be published, but we do guarantee that every study will be submitted for peer-review.
Registration & Supervisor Approval
Why is there a 4-week waiting period after registration?
Pre-registration before data collection is a core principle of open science. The 4-week minimum is there to allow time for ethics approval and data collection — it is a floor, not a deadline. You can submit any time after those 4 weeks have elapsed, as long as the study is still open (we will not close a study without contacting any registered students, no-one will be left behind). The gap prevents post-hoc submissions and strengthens the integrity of the meta-analysis. Planning, ethical approval and data collection take time.
What does my supervisor need to do?
Your supervisor receives an email to approve your registration. Upon final submission they also confirm that your project aligns with the study protocol, that you have ethical approval, that your methods are sound and deviations are reported, and they also approve your final data submission. You must provide a university or institutional email address for your supervisor — personal addresses (Gmail, Outlook, etc.) are rejected automatically.
Can I register for multiple studies?
Although we do not recomend this (research is time consuming and requires depth of reading and planning), Yes — you can register for as many studies as you have matching projects for. Each registration is independent and requires separate supervisor approval.
Can students working together on a project both receive authorship credit?
Yes. When registering, the lead student can add co-contributors — providing each person's name, email, and institution. All listed co-contributors will appear in the CONTACTS.csv included in the study report package, and will be acknowledged as co-authors on any resulting publication. Co-contributors can also see the registration on their own dashboard by logging in with the email address used when they were added. Only one student submits the data (the lead registrant), but the contribution is credited to the whole group.
How do I add a co-contributor to my registration?
On Step 2 of the registration wizard (Supervisor Details), scroll down to the "Co-Contributors" section. Enter each co-contributor's full name, email address, and institution, then click "+ Add". You can add as many as needed. Co-contributors do not need to have a Meta-Student account when you register, but if they create one using the same email address they will be able to see the registration on their dashboard.
What if students from the same project want to submit different datasets?
Each dataset submitted to a study must represent independent data collected by a distinct group. If two students collected the data together (same participants, same collection session), that is one dataset and one submission — use the co-contributor feature to share the credit. If students collected entirely separate datasets (different participants, different sessions), each student registers independently and submits their own data file.
Data & Privacy
What data format is required?
You upload a CSV file using the exact template provided at registration (attached to your confirmation email). Each row is one participant. Column names must match the template precisely — do not rename them. The platform analyses the raw individual participant data directly; you do not need to calculate any summary statistics.
What is the Data Sharing Agreement and do I need to sign it?
Yes — signing and uploading the Data Sharing Agreement (DSA) is mandatory at the point of data submission. The DSA is a short formal document that records the terms under which your dataset is contributed to the Meta-Student project, including data storage, open-repository sharing, and co-authorship conditions. It must be signed by both you (the student) and your supervisor before submission. A copy of the DSA is attached to your registration confirmation email; you can also download it at any time from the submission page.
What participant consent is required?
Written, explicit informed consent is mandatory from every participant before any data is collected. Consent must cover two things: (1) that their de-identified data will be used as part of the student's university project, and (2) that their de-identified data will be contributed to the Meta-Student collaborative meta-analysis and may be included in a peer-reviewed publication. Both elements must be present in your consent form. Data collected without this dual consent cannot be submitted.
What ethics documentation is required at submission?
Proof of institutional ethics approval is mandatory and must be uploaded at the point of data submission. This must be the official signed ethics approval letter, on institutional headed paper, bearing the signatures of the approving ethics committee or officer. Reference numbers alone, emails, or unsigned documents are not accepted and will result in your submission being rejected.
Will my data be publicly available?
Yes. Meta-Student uses Individual Participant Data (IPD) meta-analysis, and in keeping with open science and FAIR data principles, the de-identified IPD dataset will be made publicly available — on Zenodo or a comparable open repository — upon completion of the project. This is standard practice for open-science research and is a condition of participation. It is why written informed consent from participants must explicitly cover contribution to Meta-Student and potential inclusion in a peer-reviewed publication. During the project, your raw CSV (data file) is accessible only to platform administrators and your supervisor.
What happens if my data has problems?
The platform runs automatic quality checks when you upload: it validates column types, checks for duplicate participant IDs, flags extreme values, and reports group imbalances. If errors are found, you will see a clear report and can fix and re-upload. Warnings (non-blocking) are shown for your information.
Can I update my data after submission?
If your submission is returned for revision (NEEDS_REVISION status), you can re-upload. Once a submission is validated and included in the analysis, it cannot be changed — this protects the integrity of the cumulative results.
How long is my data retained?
Meta-Student is operated by the Sports Science Replication Centre, and all data retention periods are aligned with our research records retention schedule. Research participant data that is submitted but not included in any analysis is retained for 7 years from the end of the project, or destroyed upon a valid participant withdrawal request, whichever is sooner. Research participant data that is included in a published meta-analysis and deposited in an open repository such as Zenodo is retained in accordance with the repository's own terms, which may be indefinite, consistent with the open-science model of the project and the informed consent obtained from participants. Ethics approval documents are retained for 7 years from the date of submission. Study protocols, data dictionaries, methods documentation, and signed Data Sharing Agreements are retained for 10 years from the end of the project. Analysis scripts and statistical output files are similarly retained for 10 years, or indefinitely where they form part of a published output.
Is participant data anonymised?
Yes — the platform accepts anonymous data only, and this is a requirement rather than a recommendation. Participants are represented by a meaningless sequential number, no names or contact details or other direct identifiers may appear anywhere in a submitted file, and the student must destroy the key linking those numbers to real people before uploading. The student confirms this explicitly at submission and their supervisor confirms it independently at approval. The destroyed key is what matters. Data where a code list still exists somewhere is pseudonymised, not anonymous, and remains personal data under GDPR because someone can still work back to a person. Once the key is gone, no one can — including us. That has a consequence worth being clear about: an individual participant's data cannot be withdrawn after submission, because nobody can tell which record belongs to whom. Participants must be told this before they consent. Guidance on how to anonymise a dataset properly is in the Terms and Conditions and is emailed to every student and supervisor at registration.
Can a research participant withdraw their data?
Yes, subject to practical limitations. Research participants wishing to withdraw their data should contact the student researcher who collected it in the first instance, as the student holds the direct relationship with their participants under their own institutional ethics approval. Where a withdrawal request is received before the participant's data has been included in the pooled meta-analysis, every effort will be made to remove that participant's record. Once data has been incorporated into the pooled dataset and deposited in an open repository, erasure from the published dataset may not be technically or practically feasible. This limitation is why written informed consent covering open repository sharing is a mandatory condition of participation and must be obtained before any data collection begins.
Analysis & Results
What statistical method is used?
Meta-Student uses Individual Participant Data (IPD) meta-analysis via linear mixed-effects models (lme4). This is considered the gold standard for meta-analysis because it uses the raw data rather than summary statistics, preserving within-study variation and enabling more robust estimates.
What happens if a study meets its stopping criteria while I am still collecting data?
If you have already registered for a study, you will always have the opportunity to submit your data — regardless of whether the study has met its stopping criteria or been marked as Closed. Stopping criteria signal that sufficient information has been accumulated for a statistical verdict, but they do not cut off registered contributors. A study marked "Closed" means new registrations are no longer accepted, but all existing registered students can still complete and submit their work. No registered student will ever be left behind.
What are the sequential stopping criteria?
Each study is monitored under a pre-specified sequential stopping framework with a burn-in (k ≥ 4 studies) and then five triggers. Two of them share a precision gate and are mirror images of each other: T1 Detection — the standard error of the standardised effect is below SESOI/2 and the pooled effect differs from zero; TOST Equivalence — the same precision is reached but the 90% confidence interval sits entirely inside ±SESOI, closing the study with a positive finding of no meaningful effect. If both fire at once the study closes as a trivial effect: real, but smaller than the smallest effect of interest. The remaining two are futility exits: T2 Conditional-power futility — the projected probability of ever reaching significance falls below the registered CP threshold; T3 Precision futility — the projected k needed to satisfy the precision target exceeds the registered k cap. A trigger only closes a study when the same trigger fires at two consecutive looks (strict 2-consecutive confirmation). The minimum k for any close is therefore 5.
What do the stopping badges mean on the studies page?
"Accumulating" means the study is still ongoing with no trigger confirmed yet. "Effect detected" means the T1 detection trigger fired on two consecutive looks; the pooled effect is precise and significant. "Futile close" means a futility trigger (T2 CP-futility or T3 precision-futility) fired on two consecutive looks; continued accumulation is unlikely to change the verdict given the registered SESOI. A futile close is not a positive null finding; it indicates the study has reached the point where extra data would not be expected to change the conclusion.
What study designs are supported?
Five designs: Randomised Controlled Trial (RCT), Paired Measures / Within-Subjects (PRE_POST), RCT with Pre-Post Measures, Crossover Trial, and Cross-Sectional / Correlational.
Publishing Your Own Paper
Can I write up my own individual paper for publication alongside contributing to the meta-synthesis?
Yes. Participating in a Meta-Student study does not prevent you from writing up your own dataset as a standalone empirical paper. Your individual dataset is your own research, conducted under your own ethics approval and with your own supervisor. You are entitled to submit it to a journal independently of the meta-synthesis. Bear in mind that individual papers based on small single-site samples face the same limitations that motivate the pooled approach — limited statistical power, wider confidence intervals, and reduced generalisability. The meta-synthesis is the primary scientific output of the project; individual write-ups are acceptable but should be understood in that context.
What guidelines should I follow when publishing my individual study?
Four things, and they matter because a single-site student study and a pooled meta-analysis answer different questions at different levels of certainty. (1) Cite and link to the Meta-Student project in your methods, including its pre-registration, so a reader can see your dataset also feeds a larger synthesis. (2) Justify your single-site study on its own terms — it needs its own rationale, hypotheses and analysis plan, not the pooled protocol’s. (3) Be honest about power. Either power your study adequately for the effect you are claiming, or label it explicitly as preliminary, exploratory or a feasibility study. Most single final-year projects are underpowered for the effects typical of this field, which is precisely why the pooled analysis exists. (4) Do not cite interim Meta-Student results in your interpretation. Accumulating results shown on the platform are provisional: data are still being validated, the pooled estimate moves as studies are added, and the sequential design means no verdict is final until a stopping rule has been met and confirmed. Treating an interim figure as a finding would misrepresent both your study and the project. Report your own data, and point readers to the pooled analysis for the collective answer.
Do I need to pre-register my individual paper separately?
Yes. If you intend to write up your individual dataset as a standalone publication, you should pre-register that study independently — for example on the Open Science Framework (OSF) or AsPredicted — before you begin data collection. Pre-registration of the individual study is separate from the pre-registration that Meta-Student performs for the pooled meta-analysis. Your individual pre-registration should describe your own analysis plan, hypotheses, and any analyses you intend to run on your single dataset that are beyond the scope of the shared Meta-Student protocol. This protects the integrity of both outputs.
Do I need to tell the Meta-Student team if I plan to publish individually?
Yes — please let us know at the time of project registration (or as soon as possible if you decide later). You can note your intention to publish individually in the notes field when registering, or contact us directly. This is important for two reasons: first, so we can flag any potential overlap between your individual paper and the meta-synthesis (e.g., if the meta-synthesis is nearing completion); second, so that the Data Sharing Agreement conditions and authorship arrangements are clear from the start. We will not block or discourage individual publication — we just need to know so we can coordinate appropriately.
Does the Data Sharing Agreement affect my right to publish individually?
No. The DSA governs how your de-identified participant-level data is contributed to and shared through the Meta-Student project. It does not restrict your right to write up and publish your own findings based on your own dataset. Your individual paper reports your study; the DSA covers the contribution of the underlying data to the pooled open repository. If you have any concerns about how the DSA interacts with a specific journal's data-sharing policies, contact us before submission.
What is the typical timeline, and will my individual paper come out before the meta-synthesis?
It is quite possible — and perfectly normal — for an individual paper to be submitted and published before the meta-synthesis is complete. Meta-Student studies accumulate data over one or more academic years, so the pooled publication may come significantly later than individual contributions. If your individual paper is published first, we recommend citing the pre-registration of the Meta-Student study in your methods section and noting that your data will also be contributed to a collaborative pooled analysis. This is transparent, good practice, and signals the contribution to the wider scientific community.
For Supervisors & Institutions
How can my institution get involved?
Supervisors can propose new meta-analysis studies via the Propose a Study page, although this prcoess will require substantial buy-in from the proposer to assist in the development and planning of a study beyond simply sharing an idea. Alternatively, they can direct students to register for existing active studies. No institutional agreement is required — individual supervisors can participate directly.
Can I propose a new meta-analysis topic?
Yes. Visit the "Propose a Study" page to submit a proposal. The platform administrators will review it and, if approved, they will be in touch to engagie with you in creating a new active study that students can register for. This process is not undertaken lighlty, and we require careful planning as well as domain expertise for each study.
Will I be named as an author on the pooled meta-analysis?
Not by default — supervisors are named in the Acknowledgements rather than the author list, and the reason is a published standard rather than a house rule. The ICMJE recommendations, the most widely adopted authorship standard across health and life sciences including sport and exercise science, require an author to meet ALL FOUR of the following: (1) substantial contributions to the conception or design of the work, or the acquisition, analysis or interpretation of data; (2) drafting the work or revising it critically for important intellectual content; (3) final approval of the version to be published; and (4) agreement to be accountable for all aspects of the work. The decisive point for Meta-Student is what ICMJE says next. It names explicitly the contributions that do not, on their own, justify authorship: acquisition of funding, general supervision of a research group, and general administrative support. A supervisor’s default role — overseeing the module, mentoring the student, signing off on ethics, keeping the project on the rails — maps precisely onto “general supervision”. That work is real and genuinely valuable, and the students could not contribute without it. ICMJE has simply already ruled that it is not authorship. Applying that consistently is also what protects the value of the students’ authorship: a paper listing every supervisor of every contributing project would dilute the credit this platform exists to give them, and would not survive scrutiny at most journals.
So how is my contribution recognised?
Every supervisor who approved a contributing registration is named in the Acknowledgements section of the manuscript, generated automatically from the registration records rather than depending on anyone remembering. The completion archive produces the statement “The authors thank the following supervisors for their oversight of the contributing research teams”, followed by the names. The manuscript also carries a CRediT (Contributor Roles Taxonomy) statement setting out what each named author actually did, so the division of labour is explicit and auditable rather than implied by author order.
Is there any route for a supervisor to be named as an author?
Yes — the ICMJE criteria are a threshold, not a bar, and they are met by contribution rather than by job title. A supervisor who proposes a study and helps design the protocol has made a substantial contribution to the conception of the work. One who then takes part in interpreting the pooled results, drafts or critically revises the manuscript, approves the final version and accepts accountability for it has met all four. Several members of the project team are supervisors who became authors in exactly that way. If you want that involvement, the route is to propose or co-lead a study rather than to supervise a single contributing project — see “Can I propose a new meta-analysis topic?” above. What does not qualify is supervision alone, however diligent.
What if I have concerns about a student's data?
You approve or reject each submission via an email link. If you have concerns, reject the submission with notes — the student will see your feedback and can revise. Administrators also run outlier detection and can flag or exclude problematic datasets.