主管:中华人民共和国应急管理部
主办:应急管理部天津消防研究所
ISSN 1009-0029  CN 12-1311/TU

消防科学与技术 ›› 2021, Vol. 40 ›› Issue (1): 122-125.

• • 上一篇    下一篇

消防救援人员创伤后应激障碍影响因素研究

孔嘉文,江俊颖,刘志伟,罗贤刚   

  1. 上海市消防救援总队,上海200051
  • 出版日期:2021-01-15 发布日期:2021-01-15
  • 作者简介:孔嘉文(1967-),男,江苏泰兴人,上海市消防救援总队政治部主任,主要从事队伍管理和思想政治工作,上海市长宁区中山西路229 号,200051。
  • 基金资助:
    应急管理部消防救援局科研计划项目(2019XFLR59)

Study on the influencing factors of post-traumatic stress disorder in firefighters

KONG Jia-wen,JIANG Jun-ying, LIU Zhi-wei,LUO Xian-gang   

  1. Shanghai General Fire and Rescue Brigade,Shanghai 200051, China
  • Online:2021-01-15 Published:2021-01-15

摘要: 调查研究消防救援人员PTSD 的发生情况及影响因素,为早期发现心理问题及进行心理干预提供依据。研究采用PTSD 筛查表、社会心理学相关问卷和人口学资料对3 624 名上海市消防救援人员进行追踪测查。结果发现:被试人员在应急救援工作中PTSD 症状总发生率为2.90%;被试PCL-5 得分在岗位类别、年龄、工作年限、受教育程度和年出警次数上存在显著差异(p<0.001);分层回归分析显示,心理弹性、一般自我效能感、职业认同、朋友支持、集体自尊是保护性因素,神经质、开放性人格特质和消极应对方式是危险性因素(p<0.01)。消防救援人员个体易感性因素和社会心理因素会影响PTSD 症状的发生,日常训练中应当开展心理健康教育和心理训练。

关键词: 消防救援人员, PTSD, 影响因素, 分层回归分析

Abstract:

 To investigate the incidence and influencing factors of PTSD in firefighters and provide basis for early detection of psychological problems and psychological intervention, in this study, 3 624 firefighters in Shanghai were followed up with PCL-5, social psychology questionnaire and demographic data. The results showed that:the total incidence of PTSD symptoms was 2.90%;There were significant differences in PCL-5 scores of firefighters in job category, age, working hours, education level and annual number of rescues(p<0.001);Hierarchical regression analysis showed that, resilience, general self- efficacy, professional identity, friend support and collective self- esteem were protective factors, neuroticism and open personality and negative coping style were risk factors(p<0.01). The individual susceptibility factors and social psychological factors of firefighters can affect the occurrence of PTSD, mental health education and psychological training should be carried out in daily combat readiness training.   

Key words: fire fighters, PTSD, influencing factor, hierarchical regression analysis