Daily prediction of inpatient suicide attempts using routinely collected theory-driven data.

IF 3.1 Q2 PSYCHIATRY Journal of psychopathology and clinical science Pub Date : 2024-02-01 Epub Date: 2023-12-14 DOI:10.1037/abn0000880
Michael J Kyron, Geoff R Hooke, Craig J Bryan, Glenn Kiekens, Wai Chen, Nikhila Udupa, Thomas Joiner, Andrew C Page
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Abstract

We lack knowledge about the short-term predictors of suicide attempts (SAs) among treatment-seeking individuals. The current study evaluated whether (a) interpersonal difficulties, hopelessness, and affective states are associated with an increased risk of SAs on the same and the next day; (b) these daily states are interconnected differently over time among inpatients who attempt suicide compared to those who do not. In total, 110 psychiatric inpatients who attempted suicide during their stay at a psychiatric hospital self-reported their suicidal ideation, negative affect, positive affect, wish to live, interpersonal needs, and hopelessness each day (3,018 daily reports). Multilevel structural equation modeling was used to examine same-day and next-day predictors of SAs. Multilevel temporal network models assessed interconnectedness between daily predictors and were compared to network models from a matched sample of 110 psychiatric inpatients who did not attempt suicide. In multivariate models, increases in perceived burdensomeness were significantly associated with same-day SAs, whereas increased hopelessness was associated with next-day SAs. Network models for patients who attempted suicide indicated that hopelessness and suicidal ideation were central to change, leading to next-day deteriorations in mental health. In subsequent models, feeling calm and relaxed, and feeling fresh and rested were centrally connected to other variables. The centrality of these metrics tended to be higher than in the network models for patients who did not attempt suicide, suggesting differences in the interplay between risk and protective factors. This study suggests routinely monitoring interpersonal factors and hopelessness may help identify increased short-term risk of SAs among psychiatric inpatients. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

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利用日常收集的理论数据,对住院病人企图自杀的情况进行日常预测。
我们对寻求治疗者自杀未遂(SAs)的短期预测因素缺乏了解。本研究评估了:(a) 人际交往困难、绝望和情感状态是否与当日和次日自杀未遂风险的增加有关;(b) 在企图自杀的住院患者中,这些日常状态随着时间的推移与未自杀者相比是否有不同的关联。共有 110 名在精神病院住院期间试图自杀的精神病住院患者自我报告了他们每天的自杀意念、消极情绪、积极情绪、求生愿望、人际需求和绝望感(3018 份每日报告)。多层次结构方程模型用于研究当日和次日自杀行为的预测因素。多层次时间网络模型评估了每日预测因素之间的相互关联性,并与 110 名未试图自杀的精神病住院患者的匹配样本网络模型进行了比较。在多变量模型中,感知到的负担感的增加与当天的自杀行为显著相关,而绝望感的增加与次日的自杀行为相关。针对自杀未遂患者的网络模型表明,绝望和自杀意念是导致第二天心理健康状况恶化的主要原因。在随后的模型中,平静和放松的感觉以及清爽和休息的感觉是与其他变量相关的核心因素。这些指标的中心性往往高于未试图自杀的患者的网络模型,这表明风险因素和保护因素之间的相互作用存在差异。这项研究表明,对人际关系因素和绝望情绪进行常规监测有助于识别精神病住院患者短期内增加的自杀风险。(PsycInfo Database Record (c) 2023 APA,保留所有权利)。
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