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

Digital Mental Health Interventions, e-Mental Health and Cyberpsychology (1515) Depression and Mood Disorders; Suicide Prevention (1363) Quality Evaluation and Descriptive Analysis/Reviews of Multiple Existing Mobile Apps (374) mHealth for Symptom and Disease Monitoring, Chronic Disease Management (1400) Mobile Health (mhealth) (2941) Information Quality in Digital Media (340) Quality/Credibility of eHealth Information and Trust Issues (531) Transdiagnostic Mental Health Interventions (160) Consumer Education and Learning for Mental Health (16) Reviews in Digital Mental Health (243)

Published on in Vol 24, No 3 (2022): March

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/28942, first published .
Education on Depression in Mental Health Apps: Systematic Assessment of Characteristics and Adherence to Evidence-Based Guidelines

Education on Depression in Mental Health Apps: Systematic Assessment of Characteristics and Adherence to Evidence-Based Guidelines

Education on Depression in Mental Health Apps: Systematic Assessment of Characteristics and Adherence to Evidence-Based Guidelines

Authors of this article:

Laura Martinengo1 Author Orcid Image ;   Anne-Claire Stona1 Author Orcid Image ;   Lorainne Tudor Car2, 3 Author Orcid Image ;   Jimmy Lee4, 5 Author Orcid Image ;   Konstadina Griva1 Author Orcid Image ;   Josip Car1, 3 Author Orcid Image
Article Authors Cited by (10) Tweetations (12) Metrics

Journals

  1. Martinengo L, Lum E, Car J. Evaluation of chatbot-delivered interventions for self-management of depression: Content analysis. Journal of Affective Disorders 2022;319:598 View
  2. Shan D, Li S, Xu R, Huang J, Wang Y, Zheng Y, Huang S, Song Y, Han J, Suto S, Dai Z. Low depression literacy exacerbates the development and progression of depressive mood in Chinese adult social media users during COVID-19: A 3-month observational online questionnaire-based study with multiple cross-sectional analyses. Frontiers in Public Health 2023;11 View
  3. Wang Q, Lee R, Hunter S, Chan S. Patients’ experiences of using a mobile application-based rehabilitation programme after total hip or knee arthroplasty: a qualitative descriptive study. BMC Nursing 2023;22(1) View
  4. Lin X, Martinengo L, Jabir A, Ho A, Car J, Atun R, Tudor Car L. Scope, Characteristics, Behavior Change Techniques, and Quality of Conversational Agents for Mental Health and Well-Being: Systematic Assessment of Apps. Journal of Medical Internet Research 2023;25:e45984 View
  5. Ribaut J, DeVito Dabbs A, Dobbels F, Teynor A, Mess E, Hoffmann T, De Geest S. Developing a Comprehensive List of Criteria to Evaluate the Characteristics and Quality of eHealth Smartphone Apps: Systematic Review. JMIR mHealth and uHealth 2024;12:e48625 View
  6. Kar N. Public education for mental health: Revisiting its intervention potential. Odisha Journal of Psychiatry 2023;19(2):31 View
  7. Rief W, Asmundson G, Bryant R, Clark D, Ehlers A, Holmes E, McNally R, Neufeld C, Wilhelm S, Jaroszewski A, Berg M, Haberkamp A, Hofmann S. The future of psychological treatments: The Marburg Declaration. Clinical Psychology Review 2024;110:102417 View
  8. Larsen R, Hole K, Selle M, Johannessen Landmark C, Krogstad T, Holm L. Access to a tailored mobile application enhances medication adherence among young users of antidepressants. Frontiers in Pharmacology 2024;15 View
  9. Wang X, Li C. Knowledge, attitude, and practice of depression among university students. Brain and Behavior 2024;14(9) View

Books/Policy Documents

  1. de Almeida R. Emerging Technologies for Health Literacy and Medical Practice. View