Evidence map›Paper›PMID 42034907›Full record

ArticleScientific reports2026

Intelligent virtual agents in psychotherapy: a safety evaluation across high-risk mental health scenarios.

Lara Rolvien, Lucie Kruse, Sebastian Rings, Christian Zimmer, Gesche Schauenburg, Friederike Thams, Anna Brähler, Catharina Rudschies, Ingrid Schneider, Steffen Moritz and 2 more

Abstract read
In one paragraph

Article in Scientific reports, 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
–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

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

12 authors.

Lara RolvienDepartment of Psychiatry and Psychotherapy, University Medical Center Hamburg-Eppendorf, Martinistrasse 52, 20246, Hamburg, Germany. l.rolvien@uke.de.
Lucie KruseDepartment of Informatics, University of Hamburg, Hamburg, Germany.
Sebastian RingsDepartment of Informatics, University of Hamburg, Hamburg, Germany.
Christian ZimmerFaculty of Media, University of Applied Sciences, Düsseldorf, Germany.
Gesche SchauenburgDepartment of Psychiatry and Psychotherapy, University Medical Center Hamburg-Eppendorf, Martinistrasse 52, 20246, Hamburg, Germany.
Friederike ThamsResearch and Development, Sympatient GmbH, Hamburg, Germany.
Anna BrählerDepartment of Psychiatry and Psychotherapy, University Medical Center Hamburg-Eppendorf, Martinistrasse 52, 20246, Hamburg, Germany.
Catharina RudschiesDepartment of Informatics, University of Hamburg, Hamburg, Germany.
Ingrid SchneiderDepartment of Informatics, University of Hamburg, Hamburg, Germany.
Steffen MoritzDepartment of Psychiatry and Psychotherapy, University Medical Center Hamburg-Eppendorf, Martinistrasse 52, 20246, Hamburg, Germany.
Frank Steinicke *Department of Informatics, University of Hamburg, Hamburg, Germany.
Jürgen Gallinat *Department of Psychiatry and Psychotherapy, University Medical Center Hamburg-Eppendorf, Martinistrasse 52, 20246, Hamburg, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The growing burden of mental illness and limited access to evidence-based psychotherapy have increased interest in artificial intelligence (AI)-driven conversational agents as potential supports for mental health care. In this exploratory pilot study, we examined the safety and feasibility of an intelligent virtual agent (IVA) designed to simulate psychotherapeutic interactions, with a focus on high-risk situations involving suicidality and substance use. Two licensed psychotherapists engaged in scripted interactions with the IVA across 12 predefined scenarios addressing suicidality and substance abuse. The IVA was powered by GPT-4omni and embedded in a Unity-based avatar. After each interaction, testers evaluated acceptance, usability, and human-robot interaction. Two independent psychotherapists rated the IVA's responses using a structured scale assessing guideline adherence, risk recognition, help provision, de-escalation, and empathy. No real patients were involved; all interactions were simulated for safety testing purposes. The IVA showed preliminary indications of good usability and generally empathic responses. However, problematic responses occurred in 29% of conversations, with 12.5% rated as highly critical. Responses rated as "critical" or "highly critical" referred to outputs that failed to provide adequate support, showed insufficient risk recognition, or included ethically problematic suggestions. Key concerns included inadequate recognition of risk, normalization of substance use, and insufficient referral to crisis resources, particularly in scenarios involving underage alcohol access and suicide-related inquiries. In this small, expert-based pilot safety evaluation, the findings suggest that although AI-based agents may improve access to mental health support, rigorous safety evaluation, clinical oversight, and robust safeguards are essential prior to clinical deployment. No clinical conclusions can be drawn from this simulated study.

Indexed as

Artificial IntelligenceMental DisordersMental HealthPsychotherapyAvatarFemaleHumansMalePilot ProjectsSubstance-Related DisordersArtificial intelligence (AI)Conversational agentsIntelligent virtual agentsPsychotherapySafety

Identifiers

PMID42034907
PMCPMC13110360

What OpenQuestion holds

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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 OpenQuestion graph.