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Fitbit data in tracking exercise adherence in a clinical trial

  • Yue Hu
  • , Annan Deng
  • , Yannuo Jiang
  • , Hao Huang
  • , Tracey Thomas
  • , Karl R. Hansen
  • , Anne Z. Steiner
  • , Christos Coutifaris
  • , Marcelle I. Cedars
  • , Esther Eisenberg
  • , Nanette Santoro
  • , Michael P. Diamond
  • , Richard S. Legro
  • , Heping Zhang

Research output: Contribution to journalArticlepeer-review

Abstract

Adherence in behavioral modification studies is critical for ensuring reliable results, but it is often difficult to monitor or understand factors that may contribute to it. This study aims to investigate what factors may be associated with adherence and whether adherence is associated with the trial’s primary outcome, using the Fitbit actimetry data. We used “Improving Reproductive Fitness through Pretreatment with Lifestyle Modification in Obese Women with Unexplained Infertility (FIT-PLESE)” dataset (Clinicaltrials.gov: NCT02432209), including 358 women with a total of 57,496 observations. We defined an objective adherence score as the adherence to the increased exercise and performed correlation and regression analyses to examine the associations between adherence scores, baseline variables, and healthy live births (primary outcome). The overall adherence score was significantly associated with factors like baseline steps, education level, and history of prior conception. Notably, a higher adherence score was also associated with increased odds of a healthy live birth. These results showed that exercise adherence was associated with participants’ characteristics as well as the trial’s primary outcome. These findings also pointed to a broader focus beyond weight-loss treatment, suggesting that maintaining a high level of exercise adherence may be the key to healthy live births.

Original languageEnglish (US)
Pages (from-to)101-112
Number of pages12
JournalStatistics and its Interface
Volume19
Issue number1
DOIs
StatePublished - 2026

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Applied Mathematics

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