Evidence map›Paper›PMID 40831472›Full record

ReviewIndian journal of psychological medicine2025

Artificial Intelligence for Psychotherapy: A Review of the Current State and Future Directions.

Mirza Jahanzeb Beg, Mohit Verma, Vishvak Chanthar K M M, Manish Kumar Verma

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Indian journal of psychological medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
38citing papers in PubMed, 5 pooled it
–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

38 citing papers in PubMed, 5 syntheses or guidelines pooled it.

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  5. Sustainability of AI-Assisted Mental Health Intervention: A Review of the Literature from 2020-2025.International journal of environmental research and public health · 2025
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  7. Digital doppelgangers in psychiatry.Discover mental health · 2026
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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

4 authors.

Mirza Jahanzeb BegDept. of Psychology, Lovely Professional University, Phagwara, Punjab, India.ORCID https://orcid.org/0000-0002-6308-2678
Mohit VermaDept. of Psychology, Lovely Professional University, Phagwara, Punjab, India.ORCID https://orcid.org/0009-0004-4032-2458
Vishvak Chanthar K M MDept. of Endocrine and Breast Surgery, Rajiv Gandhi Cancer Institute and Research Centre, New Delhi, India.
Manish Kumar VermaDept. of Psychology, Lovely Professional University, Phagwara, Punjab, India.ORCID https://orcid.org/0000-0002-4814-6987

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose of the Review: Psychotherapy is crucial for addressing mental health issues but is often limited by accessibility and quality. Artificial intelligence (AI) offers innovative solutions, such as automated systems for increased availability and personalized treatments to improve psychotherapy. Nonetheless, ethical concerns about AI integration in mental health care remain. This narrative review explores the literature on AI applications in psychotherapy, focusing on their mechanisms, effectiveness, and ethical implications, particularly for depressive and anxiety disorders. Collection and Analysis of Data: A review was conducted, spanning studies from January 2009 to December 2023, focusing on empirical evidence of AI's impact on psychotherapy. Following PRISMA guidelines, the authors independently screened and selected relevant articles. The analysis of 28 studies provided a comprehensive understanding of AI's role in the field. The results suggest that AI can enhance psychotherapy interventions for people with anxiety and depression, especially chatbots and internet-based cognitive-behavioral therapy. However, to achieve optimal outcomes, the ethical integration of AI necessitates resolving concerns about privacy, trust, and interaction between humans and AI. Conclusion: The study emphasizes the potential of AI-powered cognitive-behavioral therapy and conversational chatbots to address symptoms of anxiety and depression effectively. The article highlights the importance of cautiously integrating AI into mental health services, considering privacy, trust, and the relationship between humans and AI. This integration should prioritize patient well-being and assist mental health professionals while also considering ethical considerations and the prospective benefits of AI.

Indexed as

anxietyArtificial intelligencechatbotsdepressionpsychotherapy

Identifiers

PMID40831472
PMCPMC12359021

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.