IEOR - Designing a More Efficient World

Evaluating Machine Learning–Based Automated Personalized Daily Step Goals Delivered Through a Mobile Phone App: Randomized Controlled Trial

Publication Date: January 1, 2018

M. Zhou, Y. Fukuoka, Y. Mintz, K. Goldberg, P. Kaminsky, E. Flowers, and A. Aswani (2018), Evaluating machine learning-based automated personalized daily step goals delivered through a mobile phone app: Randomized controlled trial, JMIR Mhealth & Uhealth, vol. 6, no. 1: e28.


Abstract:

Background: Growing evidence shows that fixed, nonpersonalized daily step goals can discourage individuals, resulting in unchanged or even reduced physical activity.

Objective: The aim of this randomized controlled trial (RCT) was to evaluate the efficacy of an automated mobile phone–based personalized and adaptive goal-setting intervention using machine learning as compared with an active control with steady daily step goals of 10,000.