A student project has a fixed deadline, a busy supervisor and a spreadsheet that gets messier every month. Capture gives the team structured forms, validation, optional consent and a record of who changed what, so the dataset the student hands over is one the supervisor can defend.
Free sandbox · No credit card · 21 CFR Part 11 aligned
Patient and admission
Age at admission
AGESex
SEXLength of stay
LOSOutside expected range 0-120: please check
Outcome
Readmission within 30 days
READMWhat a student project needs from a data tool
The problem
Student projects fail quietly. The question is reasonable, the supervisor is supportive and the student collects data in a spreadsheet shared by email. By the time analysis starts, the same variable has three spellings, dates are in two formats, a column was deleted and nobody knows who changed which cell. The abstract deadline arrives and the student spends the final weeks cleaning data instead of writing. A purpose-built tool does not remove the work, but it moves most of the cleaning to the moment of entry.
Structured forms with units, ranges and required fields catch the typo while the chart is still in front of the student. Skip logic hides items that do not apply. Calculated fields compute BMI or eGFR so nobody does arithmetic by hand. A field-level audit trail records the old value, the new value, who changed it and why, which matters when a supervisor or reviewer asks how a number came to be. Compare the approach in how to design an eCRF and how to migrate from Excel spreadsheets.
Students often ask about REDCap, which many universities host. If your institution offers it, it is a legitimate choice; see the Capture vs REDCap comparison for where each fits, and thesis data collection if the project is a master's or PhD rather than a short clinical project.
Supervision
Give the student entry rights and the supervisor a review role. Source data verification can be set per field, so the supervisor ticks off key variables against the record. When the project passes to the next student, the build, data dictionary and audit trail are already there.
Study owner
Builds and configures the study
Principal investigator
Oversees the site, signs off the casebook
Sub-investigator
Enters and signs clinical data
Study coordinator
Screens subjects, enters visit data
Monitor (CRA)
Verifies data, raises queries
Data manager
Reviews, freezes and locks data
Participant
Completes their own questionnaires
Project types
| Project type | Typical data | Set-up in Capture |
|---|---|---|
| Retrospective case series | Chart review variables, outcomes | One form per record, edit checks on ranges, supervisor review role |
| Clinical audit or service evaluation | Standards met or not, timings | Short form, required fields; check whether approval is needed locally |
| Prospective questionnaire study | Participant-reported scores | ePRO via link or QR code, with optional eConsent |
| Small prospective cohort | Baseline, follow-up visits | Visit schedule, eCRFs, reminders |
| Teaching or pilot project | Practice data | Free sandbox only; see teaching clinical research courses |
Whether a project is audit, service evaluation or research, and what approval it needs, depends on your institution and country. Ask your supervisor and research office.
The sandbox is free with every feature and no time limit. Enter practice records, trigger a query on purpose and open the export before you touch real data.
Governance
Before any real participant data goes into a system, the project needs the right approval, and that route is set by your institution, not by the software. A retrospective chart review, a service evaluation and a prospective study with participants can sit in three different categories. Your supervisor and research office decide. A good habit is to write a one-page data management plan; the data management plan template is a starting point.
For prospective studies, consent is part of the build. eConsent lets participants sign on a phone, with email OTP confirmation and countersignature by authorized staff, and you can export the signed PDF. For data protection, code participants, keep identifiers out of the analysis file and ask your institution where student data may be stored. Capture data is hosted in the EU (Frankfurt) or the USA (N. Virginia), encrypted at rest and in transit. This is not legal advice, and you must follow your institution's rules.
Students planning a first publication often want reporting-guideline items captured up front. Add fields for the items the relevant checklist expects; the SPIRIT checklist generator helps if the project is a trial protocol.
The sandbox is free with every feature and no time limit. Paid plans apply when you go live with real participants. See pricing.
Role-based access lets you give the supervisor a reviewing role. Design the roles with your supervisor before real data goes in.
The build, data dictionary, audit trail and exports stay with the study, so the next student continues from a clean record.
That depends on the project type, your institution and your country. Ask your supervisor and research office before entering real data.
Yes, as a structured form with edit checks. Whether the review needs approval and where identifiable data may be held is set by your institution.
Typed fields, ranges, required items, a field-level audit trail and a codebook export. Errors are caught at entry rather than at analysis.
Keep exploring
Data collection tool for thesis research
Master's and PhD projects.
EDC for teaching clinical research courses
Course use.
How to migrate from Excel spreadsheets
Leave the shared sheet.
Capture vs REDCap
Head to head.
Data management plan template
One-page plan.
EDC for investigator-initiated trials
Next step up.
Free sandbox with every feature. No credit card, and you pay only when you go live with real participants.