55 resultados para suicide risk assessment
Resumo:
This paper describes the development and evaluation of a new instrument – the Clinician Suicide Risk Assessment Checklist (CSRAC). The instrument assesses the clinician’s competency in three areas: clinical interviewing, assessment of specific suicide risk factors, and formulating a management plan. A draft checklist was constructed by integrating information from 1) literature review 2) expert clinician focus group and 3) consultation with experts. It was utilised in a simulated clinical scenario with clinician trainees and a trained actor in order to test for inter-rater agreement. Agreement was calculated and the checklist was re-drafted with the aim of maximising agreement. A second phase of simulated clinical scenarios was then conducted and inter-rater agreement was calculated for the revised checklist. In the first phase of the study, 18 of 35 items had inadequate inter-rater agreement (60%>), while in the second phase, using the revised version, only 3 of 39 items failed to achieve adequate inter-rater agreement. Further evidence of reliability and validity are required. Continued development of the CSRAC will be necessary before it can be utilised to assess the effectiveness of risk assessment training programs.
Resumo:
Introduction: There is currently a need for research into indicators that could be used by non-clinical professionals working with young people, to inform the need for referral for further clinical assessment of those at risk of suicide. Method: Participants of this repeated measures longitudinal study, were 2603, 2485, and 2246 school students aged 13, 14, and 15, respectively, from 27 South Australian Schools. Results: Perceived academic performance, self-esteem and locus of control are significantly associated with suicidality. Further, logistic regression of longitudinal results suggests that perceived academic performance, over and above self-esteem and locus of control, in some instances, is a good long-term predictor of suicidality. (C) 2004 Published by Elsevier Ltd. on behalf of The Association for Professionals in Services for Adolescents.
Resumo:
How can empirical evidence of adverse effects from exposure to noxious agents, which is often incomplete and uncertain, be used most appropriately to protect human health? We examine several important questions on the best uses of empirical evidence in regulatory risk management decision-making raised by the US Environmental Protection Agency (EPA)'s science-policy concerning uncertainty and variability in human health risk assessment. In our view, the US EPA (and other agencies that have adopted similar views of risk management) can often improve decision-making by decreasing reliance on default values and assumptions, particularly when causation is uncertain. This can be achieved by more fully exploiting decision-theoretic methods and criteria that explicitly account for uncertain, possibly conflicting scientific beliefs and that can be fully studied by advocates and adversaries of a policy choice, in administrative decision-making involving risk assessment. The substitution of decision-theoretic frameworks for default assumption-driven policies also allows stakeholder attitudes toward risk to be incorporated into policy debates, so that the public and risk managers can more explicitly identify the roles of risk-aversion or other attitudes toward risk and uncertainty in policy recommendations. Decision theory provides a sound scientific way explicitly to account for new knowledge and its effects on eventual policy choices. Although these improvements can complicate regulatory analyses, simplifying default assumptions can create substantial costs to society and can prematurely cut off consideration of new scientific insights (e.g., possible beneficial health effects from exposure to sufficiently low 'hormetic' doses of some agents). In many cases, the administrative burden of applying decision-analytic methods is likely to be more than offset by improved effectiveness of regulations in achieving desired goals. Because many foreign jurisdictions adopt US EPA reasoning and methods of risk analysis, it may be especially valuable to incorporate decision-theoretic principles that transcend local differences among jurisdictions.
Resumo:
Background: Recent work has demonstrated that the lifetime suicide risk for patients with DSM IV Major Depression cannot mathematically approximate the accepted figure of 15%. Gender and age significantly affect both the prevalence of major depression and suicide risk, Methods: Gender and age stratified calculations were made on the entire population of the USA in 1994 using a mathematical algorithm. Sex specific corrections for under-reporting were incorporated into the design. Results: The lifetime suicide risks for men and women were 7% and 1%, respectively. The combined risk was 3.4%. The male:female ratio for suicide risk in major depression was 10:1 for youths under 25, and 5.6:1 for adults. Conclusions: Suicide in major depression is predominantly a male problem, although complacency towards female sufferers is to be avoided. Diagnosis of major depression is of limited help in predicting suicide risk compared to case specific factors. The male experience of depression that leads to suicide is often not identified as a legitimate medical complaint by either sufferers or professionals. Increasing help-accessing by males is a priority. Clinical implications: Patients with a history of hospitalisation; comorbidity, especially for substance abuse; and who are male, require greater vigilance for suicide risk. It may be that for males che threshold for diagnosing and treating major depression needs to be lowered. Limitations: This research is based on a mathematical algorithm to approximate a life-long longitudinal study that identifies community cases of depression. Our findings therefore rely on the validity of the statistics used. Extrapolation is limited to populations with an actual suicide rate of 17/100,000 or less and a lifetime prevalence of major depression of 17% or more. (C) 1999 Elsevier Science B.V. All rights reserved.