Evidence map›Paper›PMID 42313226›Full record

ReviewCurrent psychiatry reports2026

The Digital Mirror: Clinical Potentials and Relational Risks of Generative AI in Mental Health Interventions.

Cesare Cavalera, Fabio Frisone, Chiara Rossi, Osmano Oasi, Francesco Pagnini, Giuseppe Riva, Lorenzo Antichi

Abstract readReview
In one paragraph

Review in Current psychiatry reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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

7 authors.

Cesare CavaleraDepartment of Psychology, Università Cattolica del Sacro Cuore, Via Nirone 15, Milan, 20123, Italy. cesarem.cavalera@unicatt.it.
Fabio FrisoneSophia University Institute, Firenze, Italy.
Chiara RossiDepartment of Human Science, Università degli Studi Guglielmo Marconi, Rome, Italy.
Osmano OasiDepartment of Psychology, Università Cattolica del Sacro Cuore, Via Nirone 15, Milan, 20123, Italy.
Francesco PagniniDepartment of Psychology, Università Cattolica del Sacro Cuore, Via Nirone 15, Milan, 20123, Italy.
Giuseppe RivaDepartment of Psychology, Università Cattolica del Sacro Cuore, Via Nirone 15, Milan, 20123, Italy.
Lorenzo AntichiDepartment of Psychology, Università Cattolica del Sacro Cuore, Via Nirone 15, Milan, 20123, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purpose of reviewThis review explores the rapidly evolving integration of Generative Artificial Intelligence (GenAI) in mental health care. It aims to evaluate current applications in assessment, treatment planning, and psychotherapeutic interventions, while critically examining the clinical risks, ethical dilemmas, and the future potential of GenAI as an adjunctive tool rather than a replacement for human-delivered therapy. RECENT

findingsRecent studies indicate that AI models can effectively assist in diagnostic reasoning, biomarker identification via EEG, and the prediction of symptom trajectories from session transcripts. Randomized controlled trials (RCTs) suggest that GenAI chatbots significantly reduce anxiety and depressive symptoms in the short term, particularly in settings with limited access to clinicians. However, human-led therapy remains superior in fostering deep emotional engagement and clinical impact. Significant risks identified include the potential for GenAI to foster dependency, reinforce maladaptive schemas or delusional ideation through "sycophantic" mirroring, and raise complex ethical-legal challenges regarding the reporting of criminal disclosures. AI represents a transformative adjunctive layer in mental health, offering scalable support for assessment, training, and between-session monitoring. While technological advances in personalization, multimodality, and immersive virtual reality enhance its clinical utility, GenAI lacks the authentic relational depth and"calibrated mismatches" essential for autonomy and transformative change. Future integration must prioritize a human-centered, blended approach, where GenAI is strictly supervised by clinicians within a robust ethical and regulatory framework to preserve the essential heart of the therapeutic connection. Research priorities, interim clinical safeguards, and recommendations for navigating the gap between current evidence and real-world adoption need to be defined and implemented.

Indexed as

Artificial IntelligenceGenerative Artificial IntelligenceMental DisordersPsychotherapyDigital HealthHumansChatbot-Delivered InterventionsDigital Mental HealthEthics in AIGenerative Artificial IntelligenceNatural Language ProcessingPsychotherapy Process

Identifiers

PMID42313226
PMCPMC13279657

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.