Evidence map›Paper›PMID 42098952›Full record

ArticleAddiction (Abingdon, England)2026

Self-harm in individuals with substance use disorders: Predictive factors and risk model.

Rongqin Yu, Derek K Tracy, Julia Sinclair, Isabell Brikell, Paul Lichtenstein, Henrik Larsson, Seena Fazel

Abstract read
In one paragraph

Article in Addiction (Abingdon, England), 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. 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

7 authors.

Rongqin YuDepartment of Psychiatry, University of Oxford, Oxford, UK.ORCID https://orcid.org/0000-0001-7315-3348
Derek K TracySouth London and Maudsley NHS foundation Trust, London, UK.
Julia SinclairDepartment of Psychiatry, Faculty of Medicine, University of Southampton, Southampton, UK.ORCID https://orcid.org/0000-0002-1905-2025
Isabell BrikellDepartment of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden.
Paul LichtensteinDepartment of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden.
Henrik LarssonDepartment of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden.
Seena FazelDepartment of Psychiatry, University of Oxford, Oxford, UK.

Funding

John Fell Fund, University of Oxford 0013538Marcus and Amalia Wallenbergs foundation 2025-0063National Institute for Health and Care Research Oxford Health Biomedical Research CentreSwedish Research Council 2024-06592Swedish Research Council 2025-03176Wellcome TrustWellcome Trust 202836/Z/16/Z
6 · The paper itself

Abstract

BACKGROUND AND

aimsSubstance use disorders are associated with an elevated risk of self-harm. Currently, clinical and structured assessment of self-harm risk typically relies on evidence from the general population samples. The aim of this study was to develop a risk model for self-harm that incorporates predictors specific to individuals with substance use disorders.

methodsUsing national registers, we identified a population-based cohort of 449 720 individuals with substance use disorders in Sweden between 2006 and 2020. We tested independence and strength of a range of socio-demographic and clinical factors, obtained through linkage of population-based registers, with a Cox proportional hazards model, and estimated the risk of self-harm. For the risk model, 361 120 individuals were allocated to the development sample and 88 600 to external validation based on different geographical regions. We assessed self-harm risk over five predetermined follow-up periods-within 7 days, 1 month, 3 months, 6 months and 12 months-following a healthcare contact for substance use disorders.

resultsIn the development sample, self-harm rates ranged from 0.6% to 3.5%, and in the validation sample from 0.5% to 3.6%. Ten risk factors were retained in the final risk model. Strongest associations with subsequent self-harm were for clinical factors: previous self-harm [hazard ratio (HR) = 3.17, 95% confidence interval (CI) = 3.08-3.26] and comorbidity of mental disorders (HR = 2.63, 95% CI = 2.50-2.72). Recent psychotropic medication use, including antidepressant (HR = 1.29, 95% CI = 1.23-1.38) and antipsychotic treatments (HR = 1.34, 95% CI = 1.24-1.44), was associated with increased risk, even after adjusting for psychiatric comorbidity, likely reflecting greater clinical severity and complexity. Across follow-up periods, performance was good in terms of discrimination, with area under the curve (AUCs) ranging from 0.73 (95% CI = 0.71-0.76) to 0.79 (95% CI = 0.78-0.80). In relation to calibration, expected-to-observed risk ratios were 1.00 to 1.04 and Brier scores 0.01 to 0.04 across follow-up periods. We used the model to generate a simple web-based risk calculator [Oxford Self-hArM after substance use disorders (OxSAMS)].

conclusionsModifiable clinical factors appear to have the strongest associations with increased risk of self-harm in people with substance use disorders. Structured tools, taking account of the different strengths of those factors, could inform clinical decision-making and provide a baseline assessment for training and research.

Indexed as

Self-Injurious BehaviorSubstance-Related DisordersAdolescentAdultComorbidityFemaleHumansMaleMiddle AgedProportional Hazards ModelsRegistriesRisk AssessmentRisk FactorsSwedenYoung Adultcohort studiesnational registersrisk factorsrisk predictionself‐harmsubstance use disorders

Identifiers

PMID42098952
PMCPMC13486929

What OpenQuestion holds

Textmetadata
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.