Evidence map›Paper›PMID 42458438›Full record

Trial reportBMC medical education2026

The effect of AI-enabled virtual patient simulation on training outcomes and insecurities in psychotherapy education.

Julia Cecil, Eesha Kokje, Anne-Kathrin Kleine, Insa Schaffernak, Lea Vogel, Selina Angerer, Eva Lermer, Susanne Gaube

Abstract readRandomized Controlled Trial
PubMed Full text at PMC Publisher
In one paragraph

Trial report in BMC medical education, 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

8 authors.

Julia CecilLMU Center for Leadership and People Management, Department of Psychology, LMU Munich, Munich, Germany. julia.cecil@psy.lmu.de.
Eesha KokjeLMU Center for Leadership and People Management, Department of Psychology, LMU Munich, Munich, Germany.
Anne-Kathrin KleineLMU Center for Leadership and People Management, Department of Psychology, LMU Munich, Munich, Germany.
Insa SchaffernakDepartment of Business Psychology, Technical University of Applied Sciences Augsburg, Augsburg, Germany.
Lea VogelDepartment of Psychology, LMU Munich, Munich, Germany.
Selina AngererDepartment of Business Psychology, Technical University of Applied Sciences Augsburg, Augsburg, Germany.
Eva LermerLMU Center for Leadership and People Management, Department of Psychology, LMU Munich, Munich, Germany.
Susanne GaubeUCL Global Business School for Health, University College London, London, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPreparing psychotherapy trainees for clinical complexity is a persistent educational challenge. Virtual patient (VP) simulations enabled by artificial intelligence (AI) may enhance training by offering practical, hands-on experience. This study examined their effectiveness in improving training outcomes and reducing insecurity in future psychotherapists.

methodsPsychology students and psychotherapy trainees (N = 87) were randomly assigned to four online 2D-VP sessions with automated feedback or pre-recorded role-play videos. Pre- and post-assessments measured perceived psychotherapeutic competence, self-efficacy, knowledge, and insecurity.

resultsVP training significantly improved competence and self-efficacy while reducing insecurity, but did not enhance knowledge, though effects did not surpass video training. Greater clinical experience predicted higher competence and lower insecurity, but not training-related gains. Insecurity decreased earlier with video than with VP training. Simulation-related factors did not affect training outcomes.

conclusionDesign recommendations emphasize pre-briefings and enhancing VP authenticity to use VP simulations as a scalable, engaging complementary method in psychotherapy training.

Indexed as

Artificial IntelligenceClinical CompetencePatient SimulationPsychotherapySimulation TrainingAdultFemaleHumansMalePsychologistsSelf EfficacyArtificial intelligenceClinical skillsPsychotherapy trainingVirtual patients

Identifiers

PMID42458438
PMCPMC13374200

What OpenQuestion holds

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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.