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

Evaluation and Research Methodology for mHealth (195) Mobile Health (mhealth) (2777) Engagement with and Adherence to Digital Health Interventions, Law of Attrition (461)

Published on in Vol 5, No 1 (2017): January

Analyzing mHealth Engagement: Joint Models for Intensively Collected User Engagement Data

Analyzing mHealth Engagement: Joint Models for Intensively Collected User Engagement Data

Analyzing mHealth Engagement: Joint Models for Intensively Collected User Engagement Data

Authors of this article:

Emily A Scherer1 Author Orcid Image ;   Dror Ben-Zeev1 Author Orcid Image ;   Zhigang Li1 Author Orcid Image ;   John M Kane2, 3 Author Orcid Image
Article Authors Cited by (48) Tweetations (30) Metrics

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  23. Gumley A, Bradstreet S, Ainsworth J, Allan S, Alvarez-Jimenez M, Birchwood M, Briggs A, Bucci S, Cotton S, Engel L, French P, Lederman R, Lewis S, Machin M, MacLennan G, McLeod H, McMeekin N, Mihalopoulos C, Morton E, Norrie J, Reilly F, Schwannauer M, Singh S, Sundram S, Thompson A, Williams C, Yung A, Aucott L, Farhall J, Gleeson J. Digital smartphone intervention to recognise and manage early warning signs in schizophrenia to prevent relapse: the EMPOWER feasibility cluster RCT. Health Technology Assessment 2022;26(27):1 View
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  26. Nuijten R, Van Gorp P, Khanshan A, Le Blanc P, Kemperman A, van den Berg P, Simons M. Health Promotion through Monetary Incentives: Evaluating the Impact of Different Reinforcement Schedules on Engagement Levels with a mHealth App. Electronics 2021;10(23):2935 View
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Books/Policy Documents

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