Evidence map›Paper›PMID 42290984›Full record

ArticleFrontiers in psychiatry2026

Clinician and simulated patient perspectives on ambient AI scribes in psychiatric consultations: a qualitative study.

Syed Ali Bokhari, Faisal A Nawaz, Firdous M Usman, Zara Arshad, Meghana Sudhir, Ralf Krage, Syed Fahad Javaid, Rahul Kashyap

Abstract read
In one paragraph

Article in Frontiers in psychiatry, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

8 authors.

Syed Ali Bokhari *Al Amal Psychiatric Hospital, Emirates Health Services, Dubai, United Arab Emirates.
Faisal A Nawaz *Al Amal Psychiatric Hospital, Emirates Health Services, Dubai, United Arab Emirates.
Firdous M UsmanGlobal Remote Research Scholars' Program, Princeton Junction, NJ, United States.
Zara ArshadGlobal Remote Research Scholars' Program, Princeton Junction, NJ, United States.
Meghana SudhirInstitute of Learning, Mohammed Bin Rashid University of Medicine and Health Sciences, Dubai, United Arab Emirates.
Ralf KrageInstitute of Learning, Mohammed Bin Rashid University of Medicine and Health Sciences, Dubai, United Arab Emirates.
Syed Fahad JavaidDepartment of Psychiatry, College of Medicine and Health Sciences, United Arab Emirates University, Al Ain, United Arab Emirates.
Rahul KashyapGlobal Remote Research Scholars' Program, Princeton Junction, NJ, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Documentation burden contributes significantly to psychiatric clinician burnout, with psychiatrists spending an average of three hours per workday on administrative tasks rather than direct patient care. While quantitative studies demonstrate that ambient artificial intelligence (AI) scribes reduce workload and improve documentation quality, the experiential perspectives of clinicians and standardized patients (SPs) remain unexplored, particularly in psychiatry where the therapeutic relationship is central to practice. Our aims were to explore clinician and standardized simulated patient perspectives on ambient AI scribes in psychiatric consultations, examining experiences, concerns, and conditions for successful implementation. Methods: This study was part of a cross-sectional quantitative simulation study, where qualitative part was planned a-priori. We conducted focus groups with psychiatrists and SPs following a simulation-based crossover study comparing traditional versus AI-assisted documentation. Data were analyzed using Braun and Clarke's reflexive thematic analysis framework. Results: In this focus group session with eight psychiatrists and four SPs, total six themes were identified: (1) Clinical Presence, whereby reduced documentation barriers were perceived to allow more authentic human connection; (2) Liberation from documentation burden, with clinicians describing cognitive and emotional relief beneficial for their mental health; (3) Clinical Competence Amplified, in which clinicians perceived the AI scribe as enhancing practice through intelligent translation to psychiatric terminology and prompting for missed assessments; (4) Calibrating Trust, where participants navigated initial uncertainty while recognizing the importance of human oversight; (5) Privacy, stigma, and psychiatric exceptionalism, highlighting unique consent and confidentiality considerations for psychiatric populations; and (6) Perceptions of an enhanced standard of care, with both groups expressing strong preference for AI-assisted consultations with conditions for adoption. Conclusion: In this exploratory simulation-based qualitative study, AI scribes were perceived as having potential to support more present, patient-centered psychiatric consultations by reducing documentation burden. Implementation should be cautious and requires transparent consent processes, clinician training in behavioral adaptations, robust human oversight, specialty-specific templates, and real-world evaluation with patients receiving psychiatric care.

Indexed as

AI in psychiatryambient AIartificial intelligenceclinician burnoutdigital mental healthpatient experiencepsychiatric documentationqualitative research

Identifiers

PMID42290984
PMCPMC13254762

What Socratic holds

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LicenceCC BY
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Registered trials

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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 Socratic graph.