Case study · Clinical research
Brighten
A mood research instrument for UCSF and the University of Washington.
- Clients
- UCSF, University of Washington
- Service
- Design and development
- Sector
- Clinical research
- Method
- Active and passive data collection
At a glance
How it collects
Built for UCSF and the University of Washington as a shared research instrument.
Mood assessment covering depression measures, activity level and overall functioning.
Participants can enable automatic collection so data arrives without a daily action.
Study burden is what erodes long studies. Reducing it is the design goal, not a side effect.
The brief
The enemy of a long study is the participant's Tuesday
Longitudinal mental health research needs data over months, from people whose willingness to supply it varies with exactly the thing being measured. A depression study asking for daily self-reporting is asking most for engagement on the days engagement is hardest.
That is why attrition, not instrument design, is usually what limits a study of this kind. Every additional daily action is a reason to drop out, and a dataset with a hole in it during participants' worst weeks is a dataset that misleads.
Every tap you remove from a daily protocol is retention you get back.
The build
Two data streams, one participant
Pairing self-report with device data does more than add a column. Self-report captures how someone experiences a day; activity data captures what the day contained. In mood research the gap between those two is frequently the finding.
The design decision that matters most is making passive collection something a participant enables rather than something that simply happens. It respects the consent model research requires, and once enabled it removes the daily action that would otherwise be the study's main source of attrition.
Wow Labz designed and developed the instrument for UCSF and the University of Washington.
How it works
Active and passive, together
Daily questionnaires
Structured assessment of mood, including depression measures, activity level and overall functioning — the active half, kept short because it has to survive a bad day.
Smartphone health and activity data
Health and activity signals collected directly from the device, pairing objective behavioural data with self-report rather than relying on either alone.
Passive collection, opted into
Participants can enable automatic collection so data arrives without them doing anything, which is the mechanism that minimises the burden eroding long study retention.
Stack
What it was built with
- Native mobile
- Health and activity APIs
- Passive data collection
- Research instrument design
Questions
Brighten, answered
What is Brighten?
A research instrument used to assess mood, including measures of depression, activity level and overall functioning. Wow Labz designed and developed it for UCSF and the University of Washington.
What data does it collect?
Daily questionnaire responses, paired with health and activity data collected directly from the participant's smartphone.
What is passive collection?
An option participants can enable so health and activity data arrives automatically rather than requiring a daily action. It is opt in, and it is the main mechanism for reducing the study burden that erodes retention in long studies.
Why does study burden matter so much?
Because attrition, not instrument quality, usually limits longitudinal mental health research. A protocol that demands effort on the participant's hardest days loses data precisely where the data matters most.
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