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

Non-randomized Protocols and Methods (ehealth) (673) mHealth for Data Collection and Research (1204) mHealth for Wellness, Behavior Change and Prevention (3332) Ecological Momentary Assessment (EMA) (411) Alcohol Abuse, Alcoholism Prevention and Recovery (341) mHealth for Symptom and Disease Monitoring, Chronic Disease Management (1741)

Published on in Vol 12 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/44275, first published .
Wearable Sensor and Mobile App–Based mHealth Approach for Investigating Substance Use and Related Factors in Daily Life: Protocol for an Ecological Momentary Assessment Study

Wearable Sensor and Mobile App–Based mHealth Approach for Investigating Substance Use and Related Factors in Daily Life: Protocol for an Ecological Momentary Assessment Study

Wearable Sensor and Mobile App–Based mHealth Approach for Investigating Substance Use and Related Factors in Daily Life: Protocol for an Ecological Momentary Assessment Study

Authors of this article:

Ayumi Takano1 Author Orcid Image ;   Koki Ono2 Author Orcid Image ;   Kyosuke Nozawa3 Author Orcid Image ;   Makito Sato4 Author Orcid Image ;   Masaki Onuki4 Author Orcid Image ;   Jun Sese4 Author Orcid Image ;   Yosuke Yumoto5 Author Orcid Image ;   Sachio Matsushita5 Author Orcid Image ;   Toshihiko Matsumoto6 Author Orcid Image
Article Authors Cited by (5) Tweetations (6) Metrics

Journals

  1. Cuesta-López I, Secades-Villa R, González-Roz A. Feasibility and Effects of Using Physical Activity Trackers With People Who Use Substances: A Systematic Review. Current Addiction Reports 2024;11(4):713 View
  2. Moon S, Schlenk E, Kraemer K, Lee H. A brief report: Lessons learned using wearable technology to collect data from adults receiving medications for opioid use disorder. Journal of Substance Use 2025;30(6):929 View
  3. Khan N, Deshpande N, Singh P, Kadam P. A review of AI-based health prediction using apple watch and fitbit data. Discover Applied Sciences 2025;7(10) View
  4. AbuHaweeleh M, Hamdan A, Al-Essa J, Aljaal S, Al Saad N, Georgakopoulos C, Botre F, Elrayess M. Integrating Advanced Metabolomics and Machine Learning for Anti-Doping in Human Athletes. Metabolites 2025;15(11):696 View

Conference Proceedings

  1. Kong H, Singh V. Adjunct Proceedings of the 2023 ACM International Joint Conference on Pervasive and Ubiquitous Computing & the 2023 ACM International Symposium on Wearable Computing. Toward Cognition-Aware Digital Phenotyping for Substance Use Disorder View