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Wearable Technologies and Health Behaviors: New Data and New Methods to Understand Population Health

Journal: American Economic Review

Date: 20170501

Author: Handel, Benjamin; Kolstad, Jonathan

Abstract:
We study a randomized control trial in a large employer population of access to "wearable" technologies and the associated planning and monitoring tools on improved health behaviors (sleep and exercise). Both ITT and IV estimates based on actual plan enrollment for the treatment group suggest statistically significant but economically small changes in behavior after three months. We then implement machine learning-based models to assess treatment effect heterogeneity. We find little evidence for heterogeneous treatment effects base on observables. We also present detailed data on sleep patterns underscoring the value of this new data source to researchers.

Link: Google Scholar

Key Findings

Small Impact on Physical Activity

Treatment group showed minimal increase in daily steps (51.85 steps/day) and cardiovascular exercise scores compared to control group

Minimal Effect on Sleep

Access to planning tools resulted in only 1.2 minutes additional sleep per night with no significant improvement in sleep quality

Limited Benefits for At-Risk Groups

Low activity/sleep participants showed mixed results, with some decline in exercise but improved sleep quality

Impact on Daily Physical Activity

  • Treatment group averaged 6,040.32 steps vs control group's 5,988.47 steps
  • Difference of only 51.85 steps represents approximately 1% improvement
  • IV estimate suggests actual plan enrollment led to 154.8 additional steps

Sleep Duration Changes

  • Treatment group averaged 6.30 hours vs control group's 6.28 hours of sleep
  • Minimal difference of 0.02 hours (1.2 minutes) between groups
  • Sleep quality scores showed negligible difference (43.02 vs 42.92)

Impact on Low Activity/Sleep Groups

  • Steps decreased for low activity group (33.03 fewer steps)
  • Sleep duration decreased slightly (-0.07 hours)
  • Sleep quality improved by 1.37 points (11% improvement)

Contribution and Implications

  • Wearable technology and planning tools alone may not be sufficient to drive meaningful behavior change
  • Simple access to data and planning capabilities produces statistically significant but economically small effects
  • Future interventions may need additional components beyond tracking and planning to achieve substantial impacts

Data Sources

  • Steps and sleep charts based on Table 1 Panel A "Base results" data
  • Low groups analysis visualized using Table 1 Panel C data
  • All treatment effects and statistical comparisons derived from the study's randomized control trial of 14,911 participants