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

Ecological Momentary Assessment (EMA) (424) mHealth for Wellness, Behavior Change and Prevention (3391) Usability of Apps and User Perceptions of mHealth (1219) Digital Mental Health Interventions, e-Mental Health and Cyberpsychology (2210) Focus Groups and Qualitative Research for Human Factors Research (1274)

Published on in Vol 13 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/65106, first published .
Health-Promoting Effects and Everyday Experiences With a Mental Health App Using Ecological Momentary Assessments and AI-Based Ecological Momentary Interventions Among Young People: Qualitative Interview and Focus Group Study

Health-Promoting Effects and Everyday Experiences With a Mental Health App Using Ecological Momentary Assessments and AI-Based Ecological Momentary Interventions Among Young People: Qualitative Interview and Focus Group Study

Health-Promoting Effects and Everyday Experiences With a Mental Health App Using Ecological Momentary Assessments and AI-Based Ecological Momentary Interventions Among Young People: Qualitative Interview and Focus Group Study

Authors of this article:

Selina Hiller1, 2 Author Orcid Image ;   Christian Götzl1, 3, 4 Author Orcid Image ;   Christian Rauschenberg5, 6 Author Orcid Image ;   Janik Fechtelpeter7, 8, 9, 10 Author Orcid Image ;   Georgia Koppe7, 8, 9 Author Orcid Image ;   Eva Wierzba5 Author Orcid Image ;   Julia Sauter1 Author Orcid Image ;   Sina Dietrich1 Author Orcid Image ;   Daniel Durstewitz7, 10, 11 Author Orcid Image ;   Ulrich Reininghaus5, 6, 12, 13 Author Orcid Image ;   Silvia Krumm1, 14 Author Orcid Image
Article Authors Cited by (4) Tweetations Metrics

Journals

  1. Engelskirchen L, Asbrand J, Tuschen-Caffier B. Feasibility and Potential Efficacy of an Ecological Momentary Intervention for Training Acceptance and Problem Solving in Young People. Cognitive Therapy and Research 2025 View
  2. Chen Y, Ho K, Zong X, Weng Y, Yuan C, Yorke J. The digital intelligent precise nursing framework: theory development in health recommender system. BMC Nursing 2025;24(1) View
  3. Fechtelpeter J, Rauschenberg C, Goetzl C, Hiller S, Wierzba E, Emonds N, Krumm S, Reininghaus U, Durstewitz D, Koppe G. Computational network models for forecasting and control of mental health trajectories in digital applications. npj Digital Medicine 2025;9(1) View

Conference Proceedings

  1. Noshin A, Boyapati Y, Beach M, Khan A. 2025 IEEE International Conference on Omni-layer Intelligent Systems (COINS). Cognitive Reserve Measurement: A Mobile Application and a Framework for Detecting, Monitoring and Enhancing Cognitive Resilience View