Evidence map›Paper›PMID 41699048›Full record

ReviewNPJ digital medicine2026

Reimagining psychiatric care with agentic AI: promise, challenges, and a roadmap forward.

Divya Sharma, Shakila Meshkat, Argyrios Perivolaris, Mohammad Amin Kamaleddin, Bazen Gashaw Teferra, Alice Rueda, Reza Samavi, Rakesh Jetly, Vijay Mago, Yuqi Wu and 5 more

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in NPJ digital medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Review
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors.

Divya SharmaDepartment of Mathematics and Statistics, York University, Toronto, ON, Canada.
Shakila MeshkatInterventional Psychiatry Program, St. Michael's Hospital, Unity Health Toronto, Toronto, ON, Canada.
Argyrios PerivolarisInterventional Psychiatry Program, St. Michael's Hospital, Unity Health Toronto, Toronto, ON, Canada.
Mohammad Amin KamaleddinInterventional Psychiatry Program, St. Michael's Hospital, Unity Health Toronto, Toronto, ON, Canada.
Bazen Gashaw TeferraInterventional Psychiatry Program, St. Michael's Hospital, Unity Health Toronto, Toronto, ON, Canada.
Alice RuedaInterventional Psychiatry Program, St. Michael's Hospital, Unity Health Toronto, Toronto, ON, Canada.
Reza SamaviDepartment of Electrical, Computer, and Biomedical Engineering, Toronto Metropolitan University, Toronto, ON, Canada.
Rakesh JetlyInstitute of Mental Health Research, University of Ottawa, Ottawa, ON, Canada.
Vijay MagoSchool of Health Policy & Management, York University, Toronto, ON, Canada.
Yuqi WuElectrical and Computer Engineering, University of Alberta, Edmonton, AB, Canada.
Yanbo ZhangDepartment of Psychiatry, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, A, Canada.
Bo CaoDepartment of Psychiatry, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, A, Canada.
Andrew GreenshawDepartment of Psychiatry, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, A, Canada.
Sri KrishnanDepartment of Electrical, Computer, and Biomedical Engineering, Toronto Metropolitan University, Toronto, ON, Canada.
Venkat BhatInterventional Psychiatry Program, St. Michael's Hospital, Unity Health Toronto, Toronto, ON, Canada. venkat.bhat@utoronto.ca.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Agentic artificial intelligence (AI) represents a pivotal shift in clinical decision support, moving beyond static tools by reasoning, adapting, and acting alongside clinicians. Psychiatry, grounded in subjective experience, trust, and longitudinal care, offers both an opportunity and a high-stakes testbed. Agentic systems may enhance documentation, personalize care, support continuous monitoring, and extend access, while raising risks around bias, explainability, privacy, and therapeutic alliance. In this Perspective, we (i) define psychiatry-specific agentic AI distinct from decision-support and fully autonomous systems; (ii) synthesize current evidence across studies; (iii) propose assistive, collaborative, and semi-autonomous roles; and (iv) outline a roadmap for responsible implementation.

Identifiers

PMID41699048
PMCPMC13022085

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.