Evidence map›Paper›PMID 41077965›Full record

ArticleBJPsych bulletin2025

A comparison of the quality of integrated case formulations produced by UK psychiatric trainees and an artificial intelligence-assisted application.

Mohammed J Abbas, Hannah Fosker, Harry Dudson, Simran Ramewal

Abstract read
In one paragraph

Article in BJPsych bulletin, 2025. 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. 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

4 authors.

Mohammed J AbbasLeicestershire Partnership NHS Trusthttps://ror.org/045wcpc71, Leicester, UK.ORCID https://orcid.org/0000-0002-5151-578X
Hannah FoskerLeicestershire Partnership NHS Trusthttps://ror.org/045wcpc71, Leicester, UK.
Harry DudsonLeicestershire Partnership NHS Trusthttps://ror.org/045wcpc71, Leicester, UK.
Simran RamewalLeicestershire Partnership NHS Trusthttps://ror.org/045wcpc71, Leicester, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

AIMS AND

methodThis study aimed to evaluate an artificial intelligence-assisted tool for psychiatric case formulation compared with human trainees. Twenty trainees and an artificial intelligence system produced formulations for three simulated psychiatric cases. Formulations were scored using the integrated case formulation scale (ICFS), assessing content, integration and total quality. Time taken was recorded, and assessor predictions of formulation origin were analysed.

resultsArtificial intelligence produced formulations significantly faster (<10 s) than trainees (mean 52.1 min). Trainees achieved higher ICFS total scores (mean difference 8.3, CLINICAL IMPLICATIONS: Artificial intelligence shows promise as a time-saving adjunct in psychiatric training and practice, but requires improvements in generating detailed content. Optimising teaching methods for trainees and refining artificial intelligence systems can enhance the integration of artificial intelligence into clinical workflows.

Indexed as

Artificial intelligencecase formulationmachine learning

Identifiers

PMID41077965
PMCPMC13386289

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.