Using Behavioral Analytics to Increase Exercise: A Randomized N-of-1 Study.
Academic Article
Overview
abstract
INTRODUCTION: This intervention study used mobile technologies to investigate whether those randomized to receive a personalized "activity fingerprint" (i.e., a one-time tailored message about personal predictors of exercise developed from 6 months of observational data) increased their physical activity levels relative to those not receiving the fingerprint. STUDY DESIGN: A 12-month randomized intervention study. SETTING/PARTICIPANTS: From 2014 to 2015, 79 intermittent exercisers had their daily physical activity assessed by accelerometry (Fitbit Flex) and daily stress experience, a potential predictor of exercise behavior, was assessed by smartphone. INTERVENTION: Data collected during the first 6 months of observation were used to develop a person-specific "activity fingerprint" (i.e., N-of-1) that was subsequently sent via email on a single occasion to randomized participants. MAIN OUTCOME MEASURES: Pre-post changes in the percentage of days exercised were analyzed within and between control and intervention groups. RESULTS: The control group significantly decreased their proportion of days exercised (10.5% decrease, p<0.0001) following randomization. By contrast, the intervention group showed a nonsignificant decrease in the proportion of days exercised (4.0% decrease, p=0.14). Relative to the decrease observed in the control group, receipt of the activity fingerprint significantly increased the likelihood of exercising in the intervention group (6.5%, p=0.04). CONCLUSIONS: This N-of-1 intervention study demonstrates that a one-time brief message conveying personalized exercise predictors had a beneficial effect on exercise behavior among urban adults.
