Using Behavioral Analytics to Increase Exercise: A Randomized N-of-1 Study

Published:February 08, 2018DOI:


      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.


      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.


      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.


      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).


      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.
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