Some participant in your database are not free to recruit yet. They might still be taking part in another study on the same area of the body, or their skin might be in a washout (rest period) right after one.
Availability does that check for you. For every participant, it shows the first date they are free again for the body zone your study needs, so you stop cross-checking between studies by hand.
How it works, in one picture
Think of each body zone as a room that only one study can book at a time:
A study books the zone for as long as the participant takes part.
The washout keeps it booked a little longer, so the skin can recover.
When you start a new study, Datacapt looks at who has that room free by the date you need it.
That single date, the availability date, is worked out from each participant's real study history.
What makes someone unavailable?
A recent study on the same zone → free again after it ends + its washout.
An ongoing or upcoming study on the same zone → counted until its expected end.
A study on a different zone → no effect. Different room.
No relevant history → free from the day they were added to your database.
Which participants count?
A participant holds a body zone (and gets a washout, applied automatically per study type) in these cases:
Completed → real completion date + washout.
Excluded → exclusion date + washout.
Disqualified → only if they completed the anchor visit → anchor date + study duration + washout.
Enrolled (ongoing or upcoming study):
study uses the scheduler (participant has an anchor visit) → anchor date + study duration + washout.
study does not use the scheduler (no anchor visit) → study end date + washout.
Prospect, contacted and qualified never occupy a zone.
How much setup do you really need?
The required baseline above is Level 1. The other levels are not decoration: each one fixes a specific inaccuracy. Level 2 will help you set-up washout duration by study type. If you use the scheduler and want precise dates, Level 3 is recommended for ongoing and recent studies.
🚀 Level 1: the required baseline
A body zone + study dates on each study, and one default washout in settings. Datacapt uses each participant's status (enrolled or completed) plus the washout. Enough to filter your database.
🚀 Level 2: sharper washout (optional)
Create your study types (e.g. Solar, Anti-aging, Skin tolerance) and give each one its own washout. The rest period now matches each protocol instead of a single default.
🚀 Level 3: real attendance (recommended for ongoing studies)
While a study is ongoing, Datacapt does not yet know when each participant personally finishes, so it falls back to the study's end date.
If the study's last slot is Friday but a participant actually finished on Monday (their D0 + duration), that person looks busy until Friday + washout instead of Monday + washout, so you would wrongly skip them. If you use the scheduler, mark an anchor visit (D0) so Datacapt uses their real end (anchor + duration).
💡 Two things to remember: with no excluded zone, everyone just shows their sign-up date (nothing is blocked). And a washout of 0 simply means "no rest period."
Already using Datacapt? Start with your existing studies
If you have been running studies in Datacapt for a while, you do not need to go back and reconfigure every past study. Availability is worked out from each participant's real study history, so the one thing worth doing is making sure your existing studies carry the two required fields: a body zone and study dates.
A study that is missing either field is skipped in the calculation. In practice, a participant who was actually busy on that zone could then wrongly show as available, so backfilling those two fields is what makes your dates trustworthy.
What to backfill, in order of usefulness:
Ongoing and upcoming studies: always. These are what make people unavailable right now.
Recently finished studies: the ones whose end date plus washout still falls in the near future. These still block people.
Old, long-finished studies: you can usually skip them. Once a study's end date plus washout is in the past, it no longer affects anyone's availability, so backfilling it changes nothing.
You do not need to add study types, per-type washout, or anchor visits to past studies. Those are precision layers for new studies. For studies that are already finished, Datacapt already uses the real completion date.
💡 Fastest way to start: set your default washout once in settings, backfill body zone + dates on your ongoing and recently-finished studies, then open Run availability dates. You will see a populated column in minutes, and you can tidy older studies later.
How to set it up
Your setup follows the three levels, and each level has its own Arcade walkthrough. Do Level 1 to get availability working; add Level 2 and Level 3 when you want more precise dates.
Level 1: the required baseline
Set the two required fields on each study, plus a default washout once. This is enough for availability to work.
🛠️ Step-by-step guide
How to set up Level 1
How to set up Level 1
On each study: go to Recruitment Studies, open the study, then Settings → General
Set the Study zone(s) and the study dates (start + end), then Save.
Once, globally: go to Settings → Recruitment → Washout and set a default washout (number + days / weeks / months).
💡 Study settings stay editable after participants are booked. A parent zone (e.g. Arms) automatically includes its sub-zones (Right + Left). A washout of 0 means "no rest period"; negative values become 0.
The optional study fields, such as expected duration, exclusion zone and study type, add precision and feed Levels 2 and 3.
Level 2: sharper washout
Give each study type its own washout, so the rest period matches your protocols instead of one default.
🛠️ Step-by-step guide
How to set up Level 2
How to set up Level 2
Go to Settings → Recruitment → Study types and add the types you run (names are unique).
Open Settings → Recruitment → Washout and give a type its own washout, which overrides the default for new studies.
💡 New types get the default value automatically. Deleting a type that is in use asks you to pick a replacement first. A per-type washout only applies to new studies.
Level 3: real attendance
Mark one visit as the anchor visit (D0) so Datacapt uses each participant's real end date instead of the study fallback.
🛠️ Step-by-step guide
How to set up Level 3
How to set up Level 3
Scheduler: open the visit and tick "Mark as anchor visit" (editable while the study is in draft).
Calendar: when creating or editing an event, tick "Mark as anchor visit" (link it to a study first).
Once ticked, an "Anchor visit" tag appears on the slot.
⚠️ Availability does not control self-scheduling. A participant in a pool can still book any open slot in the scheduler, even one before their availability date. Align the schedule window with the earliest acceptable date, or split pools by availability.
💡 Only one anchor visit per participant per study. Without one, dates fall back to study-level dates, and nothing breaks.
Use it
Compute the dates
From the subject database, on the Availability date column open the gear → Run availability dates. In the popover, either Preload from a recruitment study or fill excluded zones + washout yourself, then Set availability date.
⚠️ The dates are not saved. They are worked out fresh each run and clear when you refresh. Just run it again. Only your popover inputs are remembered when you save a view.
Filter & sort
Add the Availability date filter (operator "is on or before") and pick your target date. The column is sortable, combines with other filters, and can be saved in a view.
💡 Run the dates before filtering, and note that past dates are blocked in the picker.
Recruit from a study
+ Add Participants opens the same popover pre-filled from the study, then the participant picker with the filter already applied.
💡 It is a guide, not a wall. Remove the filter chip to add someone available a little later (for margin or a sponsor exception). A pool locks its date when created, so later changes will not empty your list.
Permission you need
To see the Availability date column: your workspace has the Recruitment Studies module and you have access to it. Without that access the column is hidden. (Recruitment → Recruitment studies → Access.)
To run the computation: access to both the subject database and Recruitment Studies.
To edit study settings (body zone, dates, washout): recruitment study settings edit rights. (Recruitment → Recruitment study settings → Edit.)
To manage global study types & washout: the recruitment studies settings permission, which grants read and write together (there is no read-only view). (Recruitment → Recruitment studies settings → Access + edit.)
To mark an anchor visit: your existing scheduler or calendar edit rights. No new permission.
Saved views: users with edit rights on the subject database can create, edit and delete them; read-only users can switch views only.
Good to know
Missing settings are skipped. A study with no body zone or no end date is left out of the calculation, so keep the studies you recruit against configured.
Body segmentation is provided by Datacapt. Fully custom segmentation is not supported yet.
Data & GDPR: availability dates are worked out on the fly and never stored. No new participant data is created, and people without recruitment access never see the column.