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

Quality Evaluation and Descriptive Analysis/Reviews of Multiple Existing Mobile Apps (418) mHealth for Wellness, Behavior Change and Prevention (3314) Mobile Health (mhealth) (3463) Mobile Health in Psychiatry (527)

Published on in Vol 10, No 10 (2022): October

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/41282, first published .
Mental Health Mobile Apps in the French App Store: Assessment Study of Functionality and Quality

Mental Health Mobile Apps in the French App Store: Assessment Study of Functionality and Quality

Mental Health Mobile Apps in the French App Store: Assessment Study of Functionality and Quality

Authors of this article:

Florence Carrouel1 Author Orcid Image ;   Benjamin du Sartz de Vigneulles1 Author Orcid Image ;   Denis Bourgeois1, 2 Author Orcid Image ;   Bernard Kabuth3, 4 Author Orcid Image ;   Nicolas Baltenneck5 Author Orcid Image ;   Fanny Nusbaum1 Author Orcid Image ;   Valérie Burge3, 4 Author Orcid Image ;   Sylvain Roy1 Author Orcid Image ;   Sophie Buchheit3, 4 Author Orcid Image ;   Marie-Line Carrion-Martinaud6 Author Orcid Image ;   Catherine Massoubre7 Author Orcid Image ;   Laurie Fraticelli1 Author Orcid Image ;   Claude Dussart1, 2 Author Orcid Image
Article Authors Cited by (19) Tweetations (4) Metrics

Journals

  1. Le Jeannic A, Turmaine K, Gandré C, Vinet M, Michel M, Chevreul K. Defining the Characteristics of an e-Health Tool for Suicide Primary Prevention in the General Population: The StopBlues Case in France. International Journal of Environmental Research and Public Health 2023;20(12):6096 View
  2. Geng L, Jiang G, Yu L, Xu Y, Huang W, Chen Z, Qi X, Zhang T, Zhao M. The Most Popular Commercial Weight Management Apps in the Chinese App Store: Analysis of Quality, Features, and Behavior Change Techniques. JMIR mHealth and uHealth 2023;11:e50226 View
  3. Toïgo M, Marc J, Hayot M, Moulis L, Carbonnel F. Quality Assessment of Smartphone Medication Management Apps in France: Systematic Search. JMIR mHealth and uHealth 2024;12:e54866 View
  4. Darko A, Antwi C, Adjei K, Zhang B, Ren J. Predicting determinants influencing user satisfaction with mental health app: An explainable machine learning approach based on unstructured data. Expert Systems with Applications 2024;249:123647 View
  5. Dominiak M, Gędek A, Antosik A, Mierzejewski P. Mobile health for mental health support: a survey of attitudes and concerns among mental health professionals in Poland over the period 2020-2023. Frontiers in Psychiatry 2024;15 View
  6. Ungerer M, Gumbinger C. A Comparative Survey on Daily Health Habits Among iPhone and Android Smartphone Users. American Journal of Lifestyle Medicine 2024 View
  7. Ki E, Jang J, Kang D. Evaluating mobile mental health apps using the mobile application rating scale (MARS) in the U.S.. Advances in Mental Health 2025;23(2):222 View
  8. González Pérez M. Diseño de actividades de aprendizaje, creación de contenido y uso de apps con base en técnicas didácticas en educación media superior y superior en línea. Revista Mexicana de Bachillerato a Distancia 2024;16(32) View
  9. González-Pérez A, Diaz-Sanahuja L, Matey-Sanz M, Osma J, Granell C, Bretón-López J, Casteleyn S. Towards a self-applied, mobile-based geolocated exposure therapy software for anxiety disorders: SyMptOMS-ET app. DIGITAL HEALTH 2024;10 View
  10. Jerjes W. The critical intersection of mental health and oral health in severe mental disorders. Clinical Oral Investigations 2024;28(11) View
  11. Poirier C, Gelin M. Boosting workplace well-being: Unveiling the impact of digital tools. Journal of Workplace Behavioral Health 2025;40(4):621 View
  12. Esmaeeli E, Khorashadizadeh M, Rahmani M. Mobile Applications for Hemodialysis: Evaluation Using the Mobile App Rating Scale (MARS). Seminars in Dialysis 2025;38(2):102 View
  13. Galibert O, Bessiere M, Toniolo J, Beloni P. L’utilisation des applications de téléphonie mobile dans la prévention et la prédiction du suicide : une revue narrative de littérature. Recherche en soins infirmiers 2025;N° 159(4):24 View
  14. Rapisarda F, Lanovaz M, Guay S, Geoffrion S. Machine learning models to predict posttraumatic stress injuries in a sample of firefighters: A proof of concept. International Journal of Mental Health 2025:1 View
  15. Ko S, Woo H. Users’ Needs for Mental Health Apps: Quality Evaluation Using the User Version of the Mobile Application Rating Scale. JMIR mHealth and uHealth 2025;13:e64622 View
  16. Lin X, Wu X, Zhu Z, Chen D, Li H, Lin R. Quality and Privacy Policy Compliance of Mental Health Care Apps in China: Cross-Sectional Evaluation Study. Journal of Medical Internet Research 2025;27:e66762 View
  17. Wu L, Pan J, Dou C, Gu A, Huang A, Tao H, Wang X, Zhang C, Wang L. Cognitive Training Mobile Apps for Older Adults With Cognitive Impairment: App Store Search and Quality Evaluation. JMIR mHealth and uHealth 2025;13:e69637 View
  18. Mehrotra S, Tripathi R, Sengupta P, Karishiddimath A, Francis A, Sharma P, Sudhir P, Srikanth T, Rao G, Sagar R. Evaluating Characteristics and Quality of Mental Health Apps Available in App Stores for Indian Users: Systematic App Search and Review. JMIR mHealth and uHealth 2025;13:e79238 View

Conference Proceedings

  1. Ramadhanti N, Karmagatri M. 2025 World Skills Conference on Universal Data Analytics and Sciences (WorldSUAS). A Sentimental Analysis Utilizing RapidMiner: Understanding the Insight of Strava's Users View