Evidence map›Paper›PMID 40421579›Full record

ArticleAustralasian psychiatry : bulletin of Royal Australian and New Zealand College of Psychiatrists2025

Artificial intelligence (AI) in psychotherapy: A challenging frontier.

Daniel Jesudason, Stephen Bacchi, Tarun Bastiampillai

Abstract readEditorial
In one paragraph

Article in Australasian psychiatry : bulletin of Royal Australian and New Zealand College of Psychiatrists, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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.

Daniel JesudasonFaculty of Health & Medical Sciences, The University of Adelaide, Adelaide, SA, Australia.ORCID 0009-0001-7604-0119
Stephen BacchiFaculty of Health & Medical Sciences, The University of Adelaide, Adelaide, SA, Australia.ORCID 0000-0001-5130-8628
Tarun BastiampillaiCollege of Medicine & Public Health, Flinders University, Bedford Park, SA, Australia.ORCID 0000-0002-6931-2913

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

ObjectiveArtificial intelligence (AI) chatbots have emerged as a potential tool to revolutionise mental health care, offering innovative solutions for the diagnosis and management of psychiatric conditions. AI psychotherapy is being trialled as a possible replacement or adjunct to traditional human-led therapy, showing promise in enhancing the accessibility and personalisation of mental health care. This paper seeks to explore the potential risks of AI for psychotherapy.ConclusionsAI psychotherapy represents relatively unchartered territory. There are concerns surrounding the trainability of AI chatbots, as well as the ultimate ability for an AI to effectively deliver human-like care. We must also consider other consequences, such as the potential for technological misuse. Thus, as AI continues to evolve, we must approach its integration with caution, and ensure the necessary regulatory mechanisms are in place for its effective and equitable implementation.

Indexed as

Artificial IntelligenceMental DisordersPsychotherapyHumansartificial intelligencemachine learningneurologypsychiatrypsychotherapy

Identifiers

PMID40421579
PMCPMC12314210

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.