Data collection
Collecting wearable data in a study without participant accounts
How to collect Apple Health and Health Connect data in a study without participant accounts: activation cards, consent scope and data you can trust.
You can collect wearable data in a study without asking participants for an account: the research team hands each participant a personal activation card, the participant activates a phone app with it, grants the operating system permissions for the metrics the study needs, and the app sends data from Apple Health or Health Connect to the organization's environment. No email address, no password and no identity provider account are involved. This article explains why that matters, what a study team has to decide up front and which checks keep the data usable.
Status: In EnaResearch, the ingestion pipeline and the metric catalog are live. The iOS and Android participant apps are built and are awaiting App Store and Google Play release, so device data collection is marked "in development" on this site. The rest of the workflow described here (participant codes, activation cards, the participant area) is available today.
Why accounts get in the way
Asking a research participant to sign up for yet another service has a cost:
- Drop-out before day one. Every extra step between consent and the first data point loses participants, especially older ones and people who are unwell.
- More personal data than the study needs. An email address and a password reset flow are personal data you now hold and must protect, without any benefit to the research question.
- Support load. Forgotten passwords become the study team's problem.
A card-based approach replaces all of this with something the team already does well: handing a participant a piece of paper at enrolment.
How card-based activation works
In EnaResearch the flow has three parts.
1. A participant code. Each person gets one active 6-character code at a time. Codes are generated from a secure random source, are not sequential and are unique across the organization. Look-alike characters are corrected on input (the letter O is read as zero, I and L as one). The code works like a user name: it never signs anyone in on its own.
2. A single-use activation card. The researcher prints the card from the admin panel. It carries a QR code, the organization code, the participant code and the activation key, and no identity details such as name, date of birth or the person identifier. The activation key (also contained in the QR code) is single-use and valid for 14 days; issuing a new key invalidates the old one. In the activation link, the key travels in the part of the address after the #, which is never sent to the server or written to its logs.
3. A device-bound session. Activating the app turns the key into a session bound to that phone. On the web, participants sign in to the organization's participant area with their code and a 6-digit PIN they set during activation. Repeated wrong attempts lock sign-in, and every attempt is written to the audit trail.
If a card is lost, the researcher rotates or revokes the code; both actions end all of the participant's sessions and pending keys. Read more on the participant access page.
Decide the scope before the first participant
Consent and data scope belong in the protocol, not in the app. Before enrolment, the team should settle three things.
Which metrics. Researchers pick metrics from a versioned catalog of about 197 device metrics (activity, heart, sleep, body measurements, vitals, mobility, nutrition and more). The permitted sources follow automatically from that choice. Metrics the study does not select are never collected, and the app asks the phone for permission only for the selected ones.
Sensitive metrics. Reproductive health and sexual activity metrics are flagged as sensitive and are collected only if a study explicitly selects them; selecting them shows a reminder about ethics approval and participant information. For mental health scales such as GAD-7 and PHQ-9, only the total score and severity band are collected.
How far back. Data is collected from the start of participation. If the study needs a baseline, it can ask for up to 30 days of history before participation; after that only new data is read.
Write the same scope into your participant information sheet, so that what participants read matches the permission screen they see on the phone. The participant can withdraw operating system permissions at any time in the phone's settings.
Make the data trustworthy
Phone health data has quirks that a study should handle on purpose, not discover at analysis time.
- Double counting. A phone and a watch can both record the same steps. Cumulative metrics such as steps and active energy are collected as 5-minute buckets through the platform's de-duplicating aggregate query, so overlapping samples are not counted twice.
- Source. Every measurement is stored with its source type, device or app identifier, time at the source, time of arrival and transformation version. When the same metric arrives from several sources, the sources are kept apart rather than merged.
- Gaps. Phones go offline and operating systems limit background work. The app keeps data locally and deletes its copy only after the server confirms the batch was stored durably; resends do not create duplicates.
- Quality flags. Invalid values are rejected at ingestion. Suspicious values (out of range, sudden jump, source conflict, low wear time) are flagged but never changed.
On Android, the source is Health Connect: Samsung Health data arrives only if it is written to Health Connect, and Huawei Health is out of scope. On iOS, data written to Apple Health by Apple Watch and other sources is read through HealthKit.
Keep an eye on participation
Participants do not receive automatic notifications, so the study team needs its own view of who is sending data. Active participants show a "Not connected" warning when no data source is connected and a "No data" warning when nothing has arrived for more than 7 days. The data quality page shows completeness per participant and metric, which is the earliest place to spot a participant who changed phones or switched off a permission.
Participants can see their own status too: the participant area shows their studies, connected sources, last sync time and a daily summary of the last 7 days, without individual measurements or identity details.
A short checklist
- Choose the metrics and, if needed, the baseline period in the protocol.
- Align the participant information sheet with the selected metrics.
- Print activation cards at enrolment and hand them over in person.
- Check the warnings and the data quality page weekly.
- Rotate or revoke a code as soon as a card is reported lost.
EnaResearch is a research data platform, not a medical device or a patient monitoring system. It raises no alarms, and whether device data is fit for a study is for the research team to assess under its protocol. See the participant app page for the current store status.