Evidence map›Paper›PMID 40538072›Full record

ArticleBJPsych open2025

Use of childhood adversity and mental health admission patterns to predict suicide in young people.

Anna Tarasenko, Dennis Ougrin

Abstract read
In one paragraph

Article in BJPsych open, 2025. 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

2 authors.

Anna TarasenkoMindly Ltd, London, UK.
Dennis OugrinYouth Resilience Unit, Wolfson Institute of Population Health, Queen Mary University of London, London, UK.ORCID https://orcid.org/0000-0003-1995-5408

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Dougall et al found that mental health admissions are a strong predictor of suicide risk in young people. The findings can improve machine learning models for predicting suicide risk. Limitations of machine learning models include recent changes in healthcare use patterns during the COVID-19 pandemic and poor long-term predictive value.

Indexed as

clinical decision support systemsmental health admission patternsrisk predictionYoung person suicide

Identifiers

PMID40538072
PMCPMC12188225

What OpenQuestion holds

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LicenceCC BY
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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.