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

Non-randomized Protocols and Methods (ehealth) (568) mHealth for Wellness, Behavior Change and Prevention (2872) Fitness Trackers and Smart Pedometers/Accelerometers (561) Wearable Devices and Sensors (889) Behavior Change (712) mHealth for Treatment Adherence (398) Decision Support for Health Professionals (1185)

Published on in Vol 10, No 11 (2021): November

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/29758, first published .
Using Methods From Computational Decision-making to Predict Nonadherence to Fitness Goals: Protocol for an Observational Study

Using Methods From Computational Decision-making to Predict Nonadherence to Fitness Goals: Protocol for an Observational Study

Using Methods From Computational Decision-making to Predict Nonadherence to Fitness Goals: Protocol for an Observational Study

Authors of this article:

Marie McCarthy1 Author Orcid Image ;   Lili Zhang1 Author Orcid Image ;   Greta Monacelli1 Author Orcid Image ;   Tomas Ward1 Author Orcid Image
Article Authors Cited by (1) Tweetations (2) Metrics

Journals

  1. Zhang L, Monacelli G, Vashisht H, Schlee W, Langguth B, Ward T. The Effects of Tinnitus in Probabilistic Learning Tasks: Protocol for an Ecological Momentary Assessment Study. JMIR Research Protocols 2022;11(11):e36583 View