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

Mobile Health (mhealth) (1924) Smoking Cessation (438) mHealth for Wellness, Behavior Change and Prevention (2277) Engagement with and Adherence to Digital Health Interventions, Law of Attrition (368) Web-based and Mobile Health Interventions (2116)

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 Bricker 1, 2 Author Orcid Image ;   Zhen Miao 3 Author Orcid Image ;   Kristin Mull 1 Author Orcid Image ;   Margarita Santiago-Torres 1 Author Orcid Image ;   David M Vock 4 Author Orcid Image
Article Authors Cited by (1) Tweetations (8) 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 , US

2 Department of Psychology , University of Washington , Seattle , WA , US

3 Department of Statistics , University of Washington , Seattle , WA , US

4 Division of Biostatistics , University of Minnesota , Minneapolis , MN , US

Corresponding Author:

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