A pilot RCT does not ask whether the app works. It asks whether the full trial is feasible: can you recruit, randomize, retain and collect the outcome. Capture records those feasibility numbers next to the clinical data, from one free sandbox to a live study.
Free sandbox · No credit card · 21 CFR Part 11 aligned
Consented
38 / 40
Randomized
36
Week 8 outcome complete
27 / 36
Target 40 in 6 months
Progression threshold set at 80%
Percent of due tasks completed
What to know first
The purpose
Digital health teams often arrive at a pilot with a working prototype and a hope that the numbers will look promising. Funders and reviewers read a pilot differently. They want to see that you can find eligible people, that people agree to be randomized, that they stay in the study, that you can measure the outcome at the end, and that the intervention is acceptable enough to be used. If those things hold, a definitive trial is justified. If they do not, the pilot has done its job by saying so cheaply.
That reframes what the data system has to do. Effect estimates are secondary and should be reported with wide uncertainty. The primary numbers are counts and rates: screened, eligible, consented, randomized, started, completed, lost, and the proportion of outcome data that is usable. The reporting extension of the CONSORT statement for randomised pilot and feasibility trials is built around these ideas, including a flow diagram and a discussion of implications for progression.
Because those counts are the result, they need to be accurate and traceable. A participant who consented but was never randomized, or who was randomized and never opened the app, belongs in the flow diagram as such. Our CONSORT flow diagram generator and pilot study sample size calculator help with the two ends of that work.
Feasibility outcomes
Illustrative. Define your own thresholds in the protocol before the first participant is enrolled.
| Question | Number to report | Recorded as |
|---|---|---|
| Can we recruit? | Screened, eligible, consented per month | Screening and enrollment records, pre-screening form |
| Will people be randomized? | Proportion of eligible who agree | Consent and randomization events with dates |
| Do they start the intervention? | Proportion who activate it | Site or participant form: access date, first session |
| Do they keep using it? | Engagement over time | Usage data from the intervention, entered or exported by your team |
| Can we measure the outcome? | Proportion with usable outcome at follow-up | ePRO tasks and completion status |
| Do they stay in the study? | Retention at each time point | Visit status and withdrawal reasons |
| Is it acceptable and safe? | Short acceptability form; adverse events | Participant ePRO and the adverse event form |
Capture does not claim a tool to import usage logs from your app. Plan how engagement summaries reach the dataset, for example as a form entered by the study team.
Randomization
A pilot should rehearse the randomization procedure it will use in the definitive trial. Capture includes randomization in the same system as the forms, so allocation is recorded with the participant, the date and the user, and sits in the audit trail.
Study status Live
Site activated Yes
Randomization list 42 allocations left
Has the subject signed the current informed consent?
Randomize ten dummy participants, send a questionnaire to your own phone and look at the dashboard. The sandbox has every feature, no credit card and no time limit.
Follow-up
Your intervention is the thing you are testing; the outcome measurement should not need a second app. Capture runs ePRO questionnaires on the participant's phone and records completion, so you can report outcome completeness honestly.
Evening diary
Question 3 of 8
How would you rate your fatigue today?
0 = no fatigue, 10 = worst imaginable
Design choices
The same traps recur in feasibility trials of apps, online programmes and digital therapeutics. None needs special software, but each is easier to handle when the data system was configured for it.
Participants know whether they received the app, so self-reported outcomes carry expectation effects. Where possible add an assessor-rated or objective outcome collected by a blinded role, and record who collected each.
Waitlist or usual-care participants may find a similar tool. Add one short question about other digital tools used so the issue appears in the data rather than in the reviewer's comments.
Digital interventions get updated while the study runs. Record the version each participant used, and keep a change log. Within Capture, form changes follow a draft to approved lifecycle, so questionnaire changes are deliberate and traceable; see eCRF versioning mid-study.
Dropout from digital studies is often high. Record the reason for non-completion at each time point, not only the absence of data, and chase early using reminder schedules.
If the app is, or may become, a medical device or a digital therapeutic, the pilot is also early evidence generation. See DTx clinical validation software and EDC for digital health clinical trials. Whether your product is regulated as a device is a question for your regulatory adviser, not for this page.
Progression
A traffic-light approach is common: green means proceed, amber means proceed after changes, red means stop or rethink.
Minimum participants per site per month that makes a definitive trial plausible.
Proportion with outcome data at the primary time point that you will accept.
What counts as having received an adequate dose of the digital intervention.
Proportion of primary outcome questionnaires fully completed.
Which events trigger a pause, and who decides.
A named review point, with the dashboard counts as evidence.
A small randomised study whose purpose is to test whether a full trial of an app or online programme is feasible: recruitment, randomization, retention, outcome completion and acceptability. It is not designed to prove effectiveness.
It depends on your sponsor, funder and ethics requirements. Even where no formal regulation applies, an audit trail, role-based access and a clean export make the feasibility numbers trustworthy. Capture offers Part 11-aligned controls from the first sandbox study.
Yes. Randomization is part of the platform, with the allocation recorded in the audit trail and blinded roles never receiving treatment-arm values.
Yes. ePRO questionnaires run on the participant's phone, with completion tracked so you can report outcome completeness.
This page does not claim an import tool or API. Plan how engagement summaries reach the dataset, for example as a form entered by your study team, and test the process in the sandbox.
The CONSORT 2010 extension for randomised pilot and feasibility trials is the usual reference. Confirm the current checklist with your target journal.
You can build the definitive study in the same platform and reuse forms as a starting point. Capture is suitable for Phase 1, 2 and 3 studies.
Open the free sandbox, build the pilot, randomize dummy participants and look at the dashboard. It has every feature, no credit card and no time limit; you pay only when you go live.
Keep exploring
How to run a pilot study
The general pilot workflow.
EDC for pilot clinical trials
Data capture for small first studies.
Pilot study sample size calculator
Size the pilot on feasibility goals.
CONSORT flow diagram generator
Report the participant flow.
DTx clinical validation software
When the app may become a digital therapeutic.
EDC for digital health trials
Digital health research at scale.
Free sandbox with every feature. Build the pilot, randomize dummy participants and read your feasibility dashboard.