Evidence map›Paper›PMID 41651560›Full record

ArticleBMJ mental health2026

Clinical guidelines on self-harm and suicide prevention: taking uncertainty into account in the evidence base.

Aida Seyedsalehi, Seena Fazel

Abstract read
In one paragraph

Article in BMJ mental health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

2 authors.

Aida SeyedsalehiDepartment of Psychiatry, University of Oxford, Oxford, UK.ORCID http://orcid.org/0000-0002-3949-2386
Seena FazelDepartment of Psychiatry, University of Oxford, Oxford, UK seena.fazel@psych.ox.ac.uk.ORCID http://orcid.org/0000-0002-5383-5365

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The National Institute for Health and Care Excellence (NICE) guideline for self-harm advises against the use of risk assessment tools to predict future occurrence of repeat self-harm or suicide in individuals who have self-harmed, or to inform decisions regarding their treatment and discharge. In this perspective article, we discuss shortcomings in the process of developing this guideline, including: (1) limitations in the NICE evidence review underpinning these recommendations, which resulted in very minimal evidence being included; (2) developing definitive recommendations and drawing strong conclusions regarding the limited predictive ability and potential harms of tools, which were almost entirely based on the committee's expertise and experience and (3) not acknowledging the uncertainty and gaps in the evidence base, particularly around model impact, acceptability and feasibility. We highlight new evidence since this 2022 guideline, including examples of international work assessing model implementation and cost-effectiveness. We propose that there is an urgent need for more rigorous primary research assessing model impact, feasibility and acceptability, as well as empirical work addressing concerns about potential harms and misuse of tools, notably the denial of care. While prediction models should not be prematurely implemented in clinical practice without adequate validation and impact assessment, well-developed and validated tools in this area have the potential to improve clinical care for individuals who self-harm. Future updates to the guideline should be informed by emerging higher quality evidence in the field.

Indexed as

Practice Guidelines as TopicSelf-Injurious BehaviorSuicide PreventionEvidence-Based MedicineHumansRisk AssessmentUncertaintypsychiatry

Identifiers

PMID41651560
PMCPMC12887452

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.