ArticleAI & society2022
Recommender systems for mental health apps: advantages and ethical challenges.
Article in AI & society, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
28 citing papers in PubMed, 1 synthesis or guideline pooled it, 80 citations in OpenAlex.
- Effectiveness of Digital Mental Health Interventions in the Workplace: Umbrella Review of Systematic Reviews.JMIR mental health · 2025Pooled it
- Effectiveness and uptake of ROOM to grow: Results of a Randomized Controlled Trial.Internet interventions · 2026Article
- Using Ultra-Abridged Individual Difference Scales for Personalization in Digital Mental Health to Improve Uptake, Engagement, and Experiences: Three-Tiered Decision Framework for Scale Shortening.Journal of medical Internet research · 2026Article
- What Youth Write About and Seek in an Anonymized Online Peer Support Forum: Insights from India.International journal of environmental research and public health · 2026Article
- Responsible data selection method for algorithmic personalization of health apps: a case study on promoting mental health.Frontiers in digital health · 2026Article
- ROOM to Grow, a Mobile Well-Being Intervention for University Students: Overview of the Design Process and Outcomes.JMIR formative research · 2025Article
- Effects of Choice Set Sizes and Moderations of Anxiety and State Emotions on Mental Health Self-Care Uptake, Engagement, and User Experience: Experimental Study.JMIR human factors · 2025Article
- Use of ai-based mental health tools and psychological well-being among Chinese university students: a parallel mediation model of emotional self-efficacy and perceived autonomy.Scientific reports · 2025Article
- What influences engagement with a bipolar disorder self-management app? A qualitative investigation of use of the PolarUs app.PLOS digital health · 2025Article
- Health promotion in the algorithmic age: recognizing the information environment as a determinant of health.Health promotion international · 2025Article
- Insights from fifteen years of real-world development, testing and implementation of youth digital mental health interventions.Internet interventions · 2025Review
- Causal AI Recommendation System for Digital Mental Health: Bayesian Decision-Theoretic Analysis.Journal of medical Internet research · 2025Article
- Advancing Mental Health Care: A Comprehensive Review of Digital Tools and Technologies for Enhancing Diagnosis, Treatment, and Wellness.Health care science · 2025Review
- A meta-analysis of persuasive design, engagement, and efficacy in 92 RCTs of mental health apps.NPJ digital medicine · 2025Article
- Generative AI-Enabled Therapy Support Tool for Improved Clinical Outcomes and Patient Engagement in Group Therapy: Real-World Observational Study.Journal of medical Internet research · 2025Observational
- Designing Health Recommender Systems to Promote Health Equity: A Socioecological Perspective.Journal of medical Internet research · 2025Article
- We don't need more apps, we need connection: recommender systems as under-explored chance to promote students' mental health at universities.Frontiers in psychology · 2025Article
- The Acceptability of AI-Driven Resource Signposting to Young People Using a Mental Health Peer Support App.Digital society : ethics, socio-legal and governance of digital technology · 2025Article
- A Personalized, Transdiagnostic Smartphone App (Mello) Targeting Repetitive Negative Thinking for Depression and Anxiety: Qualitative Analysis of Young People's Experience.Journal of medical Internet research · 2024Article
- Use of AI in Mental Health Care: Community and Mental Health Professionals Survey.JMIR mental health · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Recommender systems assist users in receiving preferred or relevant services and information. Using such technology could be instrumental in addressing the lack of relevance digital mental health apps have to the user, a leading cause of low engagement. However, the use of recommender systems for digital mental health apps, particularly those driven by personal data and artificial intelligence, presents a range of ethical considerations. This paper focuses on considerations particular to the juncture of recommender systems and digital mental health technologies. While separate bodies of work have focused on these two areas, to our knowledge, the intersection presented in this paper has not yet been examined. This paper identifies and discusses a set of advantages and ethical concerns related to incorporating recommender systems into the digital mental health (DMH) ecosystem. Advantages of incorporating recommender systems into DMH apps are identified as (1) a reduction in choice overload, (2) improvement to the digital therapeutic alliance, and (3) increased access to personal data & self-management. Ethical challenges identified are (1) lack of explainability, (2) complexities pertaining to the privacy/personalization trade-off and recommendation quality, and (3) the control of app usage history data. These novel considerations will provide a greater understanding of how DMH apps can effectively and ethically implement recommender systems.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.