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

Non-randomized Protocols and Methods (ehealth) (572) mHealth for Wellness, Behavior Change and Prevention (2922) Fitness Trackers and Smart Pedometers/Accelerometers (571) Wearable Devices and Sensors (903) Behavior Change (723) mHealth for Treatment Adherence (404) Decision Support for Health Professionals (1211)

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

Marie McCarthy   1 , MSc, MBA ;   Lili Zhang   1 , MSc ;   Greta Monacelli   1 , MSc ;   Tomas Ward   1 , BEng, MEngSc, PhD

1 Insight Centre For Data Analytics, Dublin City University, Dublin, Ireland

Corresponding Author: