Published on in Vol 7 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/38831, first published .
Content Recommendation Systems in Web-Based Mental Health Care: Real-world Application and Formative Evaluation

Content Recommendation Systems in Web-Based Mental Health Care: Real-world Application and Formative Evaluation

Content Recommendation Systems in Web-Based Mental Health Care: Real-world Application and Formative Evaluation

Journals

  1. Shafiee S. Unveiling the Latest Trends and Advancements in Machine Learning Algorithms for Recommender Systems: A Literature Review. Procedia CIRP 2024;121:115 View
  2. Matthews P, Rhodes-Maquaire C. Personalisation and Recommendation for Mental Health Apps: A Scoping Review. Behaviour & Information Technology 2025;44(10):2389 View
  3. Wang X, Hu B. Machine Learning Algorithms for Improved Product Design User Experience. IEEE Access 2024;12:112810 View
  4. Barbaric A, Christofferson K, Benseler S, Lalloo C, Mariakakis A, Pham Q, Swart J, Yeung R, Cafazzo J. Health recommender systems to facilitate collaborative decision-making in chronic disease management: A scoping review. DIGITAL HEALTH 2025;11 View
  5. Varidel M, An V, Hickie I, Cripps S, Marchant R, Scott J, Crouse J, Poulsen A, O'Dea B, McKenna S, Iorfino F. Causal AI Recommendation System for Digital Mental Health: Bayesian Decision-Theoretic Analysis. Journal of Medical Internet Research 2025;27:e71305 View
  6. Kryvoshyya M, Andrunyk V. Modeling a mental health support recommendation system. Vìsnik Nacìonalʹnogo unìversitetu "Lʹvìvsʹka polìtehnìka". Serìâ Ìnformacìjnì sistemi ta merežì 2025;17:382 View

Books/Policy Documents

  1. Sneha , Raza S. Affective Computing for Social Good. View
  2. Chatterjee S, Dindarian A, Rengaraju U. Revolutionizing Youth Mental Health with Ethical AI. View

Conference Proceedings

  1. Hadi M, Shnawa A, Jebur M, Adnan M, Mohammed G, Hameed W. 2023 6th International Conference on Engineering Technology and its Applications (IICETA). Avoidance of Scalability Problem in Recommendation System Using Filtering Approch View