Suicide warning signs of self-identification in patients with mood disorders: a qualitative analysis based on safety planning

情绪障碍患者自我识别的自杀预警信号:基于安全计划的定性分析

阅读:2

Abstract

INTRODUCTION: Warning signs serve as proximal indicators of suicide risk, making early recognition imperative for effective prevention strategies. This study aimed to explore self-identified suicide warning signs among Chinese patients with mood disorders based on safety planning framework. METHODS: Researchers collaborated with patients to develop a safety plan and compiled warning signs based on it. Word frequency and network analysis were conducted to identify key warning signs. Directed content analysis categorized these signs into cognitive, emotional, behavioral, or physiological themes according to the suicide mode theory. Additionally, we examined potential variations in reported warning signs among participants with different demographic characteristics, including age, gender, and history of suicide attempts. RESULTS: "Low mood" and "crying" emerged as prominent warning signs, with "social withdrawal" closely following. Patients commonly reported emotional themes during suicidal crises, often experiencing two to three themes simultaneously, primarily focusing on emotional, behavioral, and physiological themes. Males exhibited a higher proportion of concurrently reporting three sign themes compared to females (P < 0.05), while no difference was observed in warning signs among patients with other demographic traits. DISCUSSION: This study offers a nuanced understanding of warning signs among mood disorder patients in China. The findings underscore the necessity for comprehensive suicide risk management strategies, emphasizing interventions targeting emotional regulation and social support. These insights provide valuable information for enhancing suicide prevention and intervention efforts.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。