This paper is in the following e-collection/theme issue:

Mobile Health (mhealth) (2941) Smoking Cessation (557) mHealth for Wellness, Behavior Change and Prevention (2872) Engagement with and Adherence to Digital Health Interventions, Law of Attrition (493) Web-based and Mobile Health Interventions (3299)

Published on in Vol 25 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/43629, first published .
Can a Single Variable Predict Early Dropout From Digital Health Interventions? Comparison of Predictive Models From Two Large Randomized Trials

Can a Single Variable Predict Early Dropout From Digital Health Interventions? Comparison of Predictive Models From Two Large Randomized Trials

Can a Single Variable Predict Early Dropout From Digital Health Interventions? Comparison of Predictive Models From Two Large Randomized Trials

Authors of this article:

Jonathan Bricker1, 2 Author Orcid Image ;   Zhen Miao3 Author Orcid Image ;   Kristin Mull1 Author Orcid Image ;   Margarita Santiago-Torres1 Author Orcid Image ;   David M Vock4 Author Orcid Image
Article Authors Cited by (8) Tweetations (9) Metrics

Jonathan Bricker   1, 2 , PhD ;   Zhen Miao   3 , PhD ;   Kristin Mull   1 , MSc ;   Margarita Santiago-Torres   1 , PhD ;   David M Vock   4 , PhD

1 Division of Public Health Sciences, Fred Hutch Cancer Center, Seattle, WA, United States

2 Department of Psychology, University of Washington, Seattle, WA, United States

3 Department of Statistics, University of Washington, Seattle, WA, United States

4 Division of Biostatistics, University of Minnesota, Minneapolis, MN, United States

Corresponding Author:

  • Jonathan Bricker, PhD
  • Division of Public Health Sciences
  • Fred Hutch Cancer Center
  • 1100 Fairview Avenue North
  • M3-B232
  • Seattle, WA, 98109
  • United States
  • Phone: 1 2066675000
  • Email: jbricker@fredhutch.org