Literature DB >> 28972271

Accuracy of Clinician Predictions of Future Self-Harm: A Systematic Review and Meta-Analysis of Predictive Studies.

Rachel Woodford1, Matthew J Spittal2, Allison Milner2, Katie McGill1,3, Navneet Kapur4, Jane Pirkis2, Alex Mitchell5, Gregory Carter3.   

Abstract

Assessment of a patient after hospital-treated self-harm or psychiatric hospitalization often includes a risk assessment, resulting in a classification of high risk versus low risk for a future episode of self-harm. Through systematic review and a series of meta-analyses looking at unassisted clinician risk classification (eight studies; N = 22,499), we found pooled estimates for sensitivity 0.31 (95% CI: 0.18-0.50), specificity 0.85 (0.75-0.92), positive predictive value 0.22 (0.21-0.23), and negative predictive value 0.89 (0.86-0.92). Clinician classification was too inaccurate to be clinically useful. After-care should therefore be allocated on the basis of a needs rather than risk assessment.
© 2017 The American Association of Suicidology.

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Mesh:

Year:  2017        PMID: 28972271     DOI: 10.1111/sltb.12395

Source DB:  PubMed          Journal:  Suicide Life Threat Behav        ISSN: 0363-0234


  11 in total

Review 1.  Suicide prediction models: a critical review of recent research with recommendations for the way forward.

Authors:  Ronald C Kessler; Robert M Bossarte; Alex Luedtke; Alan M Zaslavsky; Jose R Zubizarreta
Journal:  Mol Psychiatry       Date:  2019-09-30       Impact factor: 15.992

2.  Using Administrative Data to Predict Suicide After Psychiatric Hospitalization in the Veterans Health Administration System.

Authors:  Ronald C Kessler; Mark S Bauer; Todd M Bishop; Olga V Demler; Steven K Dobscha; Sarah M Gildea; Joseph L Goulet; Elizabeth Karras; Julie Kreyenbuhl; Sara J Landes; Howard Liu; Alex R Luedtke; Patrick Mair; William H B McAuliffe; Matthew Nock; Maria Petukhova; Wilfred R Pigeon; Nancy A Sampson; Jordan W Smoller; Lauren M Weinstock; Robert M Bossarte
Journal:  Front Psychiatry       Date:  2020-05-06       Impact factor: 4.157

3.  Predicting self-harm within six months after initial presentation to youth mental health services: A machine learning study.

Authors:  Frank Iorfino; Nicholas Ho; Joanne S Carpenter; Shane P Cross; Tracey A Davenport; Daniel F Hermens; Hannah Yee; Alissa Nichles; Natalia Zmicerevska; Adam Guastella; Elizabeth Scott; Ian B Hickie
Journal:  PLoS One       Date:  2020-12-31       Impact factor: 3.240

4.  Functional network alterations differently associated with suicidal ideas and acts in depressed patients: an indirect support to the transition model.

Authors:  Gerd Wagner; Meng Li; Matthew D Sacchet; Stéphane Richard-Devantoy; Gustavo Turecki; Karl-Jürgen Bär; Ian H Gotlib; Martin Walter; Fabrice Jollant
Journal:  Transl Psychiatry       Date:  2021-02-04       Impact factor: 6.222

5.  Identifying long-term and imminent suicide predictors in a general population and a clinical sample with machine learning.

Authors:  Lloyd D Balbuena; Marilyn Baetz; Joseph Andrew Sexton; Douglas Harder; Cindy Xin Feng; Kerstina Boctor; Candace LaPointe; Elizabeth Letwiniuk; Arash Shamloo; Hemant Ishwaran; Ann John; Anne Lise Brantsæter
Journal:  BMC Psychiatry       Date:  2022-02-15       Impact factor: 3.630

Review 6.  Mental Pain Surrounding Suicidal Behaviour: A Review of What Has Been Described and Clinical Recommendations for Help.

Authors:  Susana Morales; Jorge Barros
Journal:  Front Psychiatry       Date:  2022-01-27       Impact factor: 4.157

7.  Higher Suicide Intent in Patients Attempting Suicide With Violent Methods Versus Self-Poisoning.

Authors:  Per Sverre Persett; Øivind Ekeberg; Dag Jacobsen; Mari Asphjell Bjornaas; Hilde Myhren
Journal:  Crisis       Date:  2021-04-23

8.  Clinicians' Perspectives on Self-Harm in Pakistan: A Qualitative Study.

Authors:  Tayyeba Kiran; Nasim Chaudhry; Penny Bee; Sehrish Tofique; Sana Farooque; Afshan Qureshi; Anna K Taylor; Nusrat Husain; Carolyn A Chew-Graham
Journal:  Front Psychiatry       Date:  2021-05-20       Impact factor: 4.157

9.  Development and validation of the Durham Risk Score for estimating suicide attempt risk: A prospective cohort analysis.

Authors:  Nathan A Kimbrel; Jean C Beckham; Patrick S Calhoun; Bryann B DeBeer; Terence M Keane; Daniel J Lee; Brian P Marx; Eric C Meyer; Sandra B Morissette; Eric B Elbogen
Journal:  PLoS Med       Date:  2021-08-05       Impact factor: 11.613

10.  Implementing Machine Learning Models for Suicide Risk Prediction in Clinical Practice: Focus Group Study With Hospital Providers.

Authors:  Kate H Bentley; Kelly L Zuromski; Rebecca G Fortgang; Emily M Madsen; Daniel Kessler; Hyunjoon Lee; Matthew K Nock; Ben Y Reis; Victor M Castro; Jordan W Smoller
Journal:  JMIR Form Res       Date:  2022-03-11
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