Evidence map›Paper›PMID 42423992›Full record

ArticleDer Nervenarzt2026

[When AI is involved in making decisions. Ethical considerations on shared decision-making in psychotherapeutic-psychiatric treatment].

Eva Kuhn, Laura Fässler, Florian Funer

Abstract readEnglish Abstract
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In one paragraph

Article in Der Nervenarzt, 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

3 authors.

Eva KuhnKlinik für Psychiatrie und Psychotherapie, Campus Charité Mitte (CCM), Charité - Universitätsmedizin Berlin, Bonhoefferweg 3, 10117, Berlin, Deutschland. Eva.Kuhn@charite.de.
Laura FässlerKlinik für Psychiatrie und Psychotherapie, Campus Charité Mitte (CCM), Charité - Universitätsmedizin Berlin, Bonhoefferweg 3, 10117, Berlin, Deutschland.
Florian FunerInstitut für Ethik und Geschichte der Medizin, Eberhard Karls Universität Tübingen, Tübingen, Deutschland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundArtificial intelligence (AI) is on the rise in the treatment of persons with psychiatric disorders. It can integrate diverse data points, analyze patterns and thereby generate clinically relevant insights that can influence the shared decision-making (SDM) process between patient and practitioner.

objectiveThis article aims to examine how AI can influence the SDM process in psychiatric and psychotherapeutic care. Furthermore, ethical and clinical considerations relevant to an appropriate and justified implementation are addressed.

methodsThe potential effects on SDM are analyzed with an adapted process model which is expanded by the dimensions of relational autonomy and epistemic justice, using three exemplary clinical applications.

resultsThe use of AI has the potential to support patients in reflecting on and validating their own experiences by providing additional information; however, the use of such tools can influence the patient-practitioner relationship. This is particularly important if algorithmic assessments undermine the patients' self-reports or shift responsibilities in the decision-making process. DISCUSSION: Whether AI supports or hinders SDM seems to depend on its embedment in the treatment context. When results are transparently communicated, interpreted within the participant-practitioner alliance and considered as a part of the participatory decision-making process, AI can be implemented in a clinically and ethically responsible and beneficial manner.

Indexed as

Artificial intelligenceClinical ethicsPerson-centered psychotherapyProfessional-patient relationsShared decision making

Identifiers

PMID42423992

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.