/
Navigation
Chronicles
Browse all articles
Explore
Semantic exploration
Research
Entity momentum
Nexus
Correlations & relationships
Story Arc
Topic evolution
Drift Map
Semantic trajectory animation
Posts
Analysis & commentary
Pulse API
Tech news intelligence API
Browse
Entities
Companies, people, products, technologies
Domains
Browse by publication source
Handles
Browse by social media handle
Detection
Concept Search
Semantic similarity search
High Impact Stories
Top coverage by position
Sentiment Analysis
Positive/negative coverage
Anomaly Detection
Unusual coverage patterns
Analysis
Rivalry Report
Compare two entities head-to-head
Semantic Pivots
Narrative discontinuities
Crisis Response
Event recovery patterns
Connected
Search: /
Command: ⌘K
Embeddings: large
TEXXR

Chronicles

The story behind the story

days · browse · Enter similar · o open

Apple's HealthKit suite has the potential to aid medical research, but early studies have had low participation rates over time

if researchers figure out how to get people to actually use them. http://www.buzzfeed.com/... http://twitter.com/... John Torous / @johntorousmd : 50,000 people joined this app based #cardiology study. But how many stuck with it? @stephaniemlee explores in http://www.buzzfeed.com/...

BuzzFeed Stephanie M. Lee

Context & Ripple Effects

When Apple launched ResearchKit in March 2015, the pitch was friction removal — minimizing the obstacles that keep people out of medical studies — and the launch validated it on enrollment: Stanford's cardiovascular study signed up 11,000 people in under 24 hours, and the MyHeart Counts app soon carried the model to users in the UK and Hong Kong.

BuzzFeed's reporting with psychiatrist John Torous punctures the enrollment metric: some 50,000 people joined an app-based cardiology study, but participation decayed sharply over time. That gap between signing up and sticking around is precisely what Apple's later five-year Apple Health Study run with Brigham and Women's Hospital answers by design — one persistent Research app instead of many single-study downloads.

First-order effects

  • Researchers who cited headline enrollment figures must now confront retention curves: Torous's cardiology study's 50,000 joiners shrink to a much smaller active cohort, undercutting per-study apps whose success was measured at launch.
  • For Apple, the finding moves the HealthKit conversation from 'how many signed up' to whether its platform can hold participants long enough to produce clinically usable data.

Second-order effects

  • The retention problem pushes Apple away from standalone per-study apps toward a consolidated Research app and long-horizon hospital partnerships, the structure behind the Brigham and Women's collaboration.
  • Academic teams recruiting through smartphones have to budget for ongoing re-engagement rather than one-time acquisition, changing how app-based studies are staffed and costed.

Third-order effects

  • If the pattern holds, digital cohort research consolidates around platforms capable of sustaining multi-year engagement, with retention — not enrollment speed — becoming the metric funders and journals scrutinize before treating app-derived data as evidence.

The trend: App-based medical research is shifting from celebrating viral enrollment to engineering multi-year participant retention.