|Appears in Collections:||School of Health Sciences Journal Articles|
|Peer Review Status:||Refereed|
|Title:||Managing the risk of suicide in acute psychiatric inpatients: A clinical judgement analysis of staff predictions of imminent suicide risk|
clinical judgement analysis
|Publisher:||Taylor & Francis (Informa Healthcare)|
|Citation:||Paterson B, Dowding D, Harries C, Cassells C, Morrison R & Niven C (2008) Managing the risk of suicide in acute psychiatric inpatients: A clinical judgement analysis of staff predictions of imminent suicide risk, Journal of Mental Health, 17 (4), pp. 410-423.|
|Abstract:||Background: Predicting suicide risk in psychiatric in-patients in order to inform risk management decisions is compromised by the poor predictive validity of the available models. Aims: This study explored the factors influencing judgements regarding suicide risk in psychiatrists and nurses working in acute psychiatric in-patient units in Scotland. Method: Clinical judgement analysis. Information used by 12 psychiatrists and 52 nurses to make judgements about suicide risk were analysed over 130 hypothetical cases. Correlations and linear regression analysis were used to examine judgement consistency and information use. Results: There was agreement between clinicians on the relative but not absolute degree of risk of each patient case. Consistency of judgments was low, particularly amongst nurses. All clinicians rated those with more previous suicide attempts, men, those with shorter admission times, and those who were less compliant and not improving clinically as at greater risk of suicide. Conclusions: Clinicians use cues that have been associated with suicide in traditional predictive models based on epidemiological studies and short term factors that may be particularly relevant to acute psychiatric settings. The inconsistencies observed can be interpreted to cast doubt on the validity of predictions of risk for imminent suicide and the role of such predictions in the assessment process.|
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|Affiliation:||HS Research - Stirling|
University of York
University College London
University of Manchester
NHS Forth Valley
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