The case for case–control studies in the field of suicide prevention

背景(考古学) 自杀预防 医学 毒物控制 心理学 精神科 人口 伤害预防 人为因素与人体工程学 医疗急救 环境卫生 古生物学 生物
作者
Jane Pirkis,Angela Nicholas,David Gunnell
出处
期刊:Epidemiology and Psychiatric Sciences [Cambridge University Press]
卷期号:29 被引量:21
标识
DOI:10.1017/s2045796019000581
摘要

Abstract Much of our knowledge about the risk factors for suicide comes from case–control studies that either use a psychological autopsy approach or are nested within large register-based cohort studies. We would argue that case–control studies are appropriate in the context of a rare outcome like suicide, but there are issues with using this design. Some of these issues are common in psychological autopsy studies and relate to the selection of controls (e.g. selection bias caused by the use of controls who have died by other causes, rather than live controls) and the reliance on interviewing informants (e.g. recall bias caused by the loved ones of cases having thought about the events leading up to the suicide in considerable detail). Register-based studies can overcome some of these problems because they draw upon contain information that is routinely collected for administrative purposes and gathered in the same way for cases and controls. However, they face issues that mean that psychological autopsy studies will still sometimes be the study design of choice for investigating risk factors for suicide. Some countries, particularly low and middle income countries, don't have sophisticated population-based registers. Even where they do exist, there will be variable of interest that are not captured by them (e.g. acute stressful life events that may immediately precede a suicide death), or not captured in a comprehensive way (e.g. suicide attempts and mental illness that do not result in hospital admissions). Future studies of risk factors should be designed to progress knowledge in the field and overcome the problems with the existing studies, particularly those using a case–control design. The priority should be pinning down the risk factors that are amenable to modification or mitigation through interventions that can successfully be rolled out at scale.
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