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

Early Results from COVID-19 Studies (342) Digital Mental Health Interventions, e-Mental Health and Cyberpsychology (1850) Depression and Mood Disorders; Suicide Prevention (1541) Mobile Health (mhealth) (3196) mHealth for Wellness, Behavior Change and Prevention (3131) Web-based and Mobile Health Interventions (3693)

Published on in Vol 7 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/48913, first published .
Designing High-Fidelity Mobile Health for Depression in Indonesian Adolescents Using Design Science Research: Mixed Method Approaches

Designing High-Fidelity Mobile Health for Depression in Indonesian Adolescents Using Design Science Research: Mixed Method Approaches

Designing High-Fidelity Mobile Health for Depression in Indonesian Adolescents Using Design Science Research: Mixed Method Approaches

Authors of this article:

Mila Shania1 Author Orcid Image ;   Putu Wuri Handayani1 Author Orcid Image ;   Sali Asih1 Author Orcid Image
Article Authors Cited by (3) Tweetations (3) Metrics

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  2. Ekireghwo P, Blamah N, Ajayi B, Anyachebelu T, Salihu A. An Implementation of Machine Learning-Based Framework for Tertiary Institutions Data Harmonization using Large Language Model. European Journal of Applied Science, Engineering and Technology 2025;3(3):285 View

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