ArticleJMIR mental health2018
Psychiatrists' Attitudes Toward Disruptive New Technologies: Mixed-Methods Study.
Article in JMIR mental health, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers, 3 of them syntheses that pooled it.
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Who cites it
36 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Stakeholder Perspectives of Clinical Artificial Intelligence Implementation: Systematic Review of Qualitative Evidence.Journal of medical Internet research · 2023Pooled it
- Inclusion of Clinicians in the Development and Evaluation of Clinical Artificial Intelligence Tools: A Systematic Literature Review.Frontiers in psychology · 2022Pooled it
- Virtual Reality (VR) in Assessment and Treatment of Addictive Disorders: A Systematic Review.Frontiers in neuroscience · 2019Pooled it
- Navigating the complexity of AI adoption in psychotherapy by identifying key facilitators and barriers.Npj mental health research · 2026Article
- Ethical Knowledge, Challenges, and Institutional Strategies Among Medical AI Developers and Researchers: Focus Group Study.Journal of medical Internet research · 2026Article
- Acceptability of Health Information Technology by Health Care Professionals: Where We Are Now and How We Can Fill the Gap.Journal of medical Internet research · 2025Review
- Exploring nurse perspectives on AI-based shift scheduling for fairness, transparency, and work-life balance.BMC nursing · 2025Article
- Physician Perspectives on the Potential Benefits and Risks of Applying Artificial Intelligence in Psychiatric Medicine: Qualitative Study.JMIR mental health · 2025Article
- Prospective Acceptability of Digital Therapy for Major Depressive Disorder in France: Multicentric Real-Life Study.JMIR formative research · 2024Article
- Mapping the ethical landscape of digital biomarkers: A scoping review.PLOS digital health · 2024Article
- Insights into medical students' perceptions of work culture during the COVID-19 pandemic: a mixed method study.BMC medical education · 2024Article
- Lessons learned from a multimodal sensor-based eHealth approach for treating pediatric obsessive-compulsive disorder.Frontiers in digital health · 2024Article
- Digital Phenotyping: Data-Driven Psychiatry to Redefine Mental Health.Journal of medical Internet research · 2023Article
- Mental Health Professionals' Attitudes Toward Digital Mental Health Apps and Implications for Adoption in Portugal: Mixed Methods Study.JMIR human factors · 2023Article
- Digital mental health: challenges and next steps.BMJ mental health · 2023Review
- Health professionals' sentiments towards implemented information technologies in psychiatric hospitals: a text-mining analysis.BMC health services research · 2022Article
- Expectations for Artificial Intelligence (AI) in Psychiatry.Current psychiatry reports · 2022Review
- Psychiatric diagnosis and treatment in the 21st century: paradigm shifts versus incremental integration.World psychiatry : official journal of the World Psychiatric Association (WPA) · 2022Article
- Clinical Targets and Attitudes Toward Implementing Digital Health Tools for Remote Measurement in Treatment for Depression: Focus Groups With Patients and Clinicians.JMIR mental health · 2022Article
- Self-directed Technology-Based Therapeutic Methods for Adult Patients Receiving Mental Health Services: Systematic Review.JMIR mental health · 2021Review
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundRecent discoveries in the fields of machine learning (ML), Ecological Momentary Assessment (EMA), computerized adaptive testing (CAT), digital phenotype, imaging, and biomarkers have brought about a new paradigm shift in medicine.
objectiveThe aim of this study was to explore psychiatrists' perspectives on this paradigm through the prism of new clinical decision support systems (CDSSs). Our primary objective was to assess the acceptability of these new technologies. Our secondary objective was to characterize the factors affecting their acceptability.
methodsA sample of psychiatrists was recruited through a mailing list. Respondents completed a Web-based survey. A quantitative study with an original form of assessment involving the screenplay method was implemented involving 3 scenarios, each featuring 1 of the 3 support systems, namely, EMA and CAT, biosensors comprising a connected wristband-based digital phenotype, and an ML-based blood test or magnetic resonance imaging (MRI). We investigated 4 acceptability domains based on International Organization for Standardization and Nielsen models (usefulness, usability, reliability, and risk).
resultsWe recorded 515 observations. Regarding our primary objective, overall acceptability was moderate. MRI coupled with ML was considered to be the most useful system, and the connected wristband was considered the least. All the systems were described as risky (410/515, 79.6%). Regarding our secondary objective, acceptability was strongly influenced by socioepidemiological variables (professional culture), such as gender, age, and theoretical approach.
conclusionsThis is the first study to assess psychiatrists' views on new CDSSs. Data revealed moderate acceptability, but our analysis shows that this is more the result of the lack of knowledge about these new technologies rather than a strong rejection. Furthermore, we found strong correspondences between acceptability profiles and professional culture profiles. Many medical, forensics, and ethical issues were raised, including therapeutic relationship, data security, data storage, and privacy risk. It is essential for psychiatrists to receive training and become involved in the development of new technologies.
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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.