Abstract:

Objective To analyze the influencing factors of disaster resilience in medical rescue workers，to construct a prediction model for the low-level risk of disaster resilience in medical rescue workers，and to verify the predictive effect of the model. Methods Using the convenience sampling method and the snowball method，1 037 medical rescue workers who participated in disaster rescue in 18 provinces（autonomous regions and municipalities） were selected as the participants from May to July 2022. Online questionnaire surveys were conducted using general information questionnaires，disaster resilience measuring tools for healthcare rescuers，the Mindful Attention Awareness Scale，the Simple Coping Style Questionnaire and the Depression-Anxiety-Stress Scale. Univariate and multivariate logistic regression analyses were used to determine the independent influencing factors for the low level of disaster resilience of medical rescue workers. A risk prediction model was constructed，and a nomogram chart was drawn. The model’s effectiveness was evaluated using the receiver operating characteristic curve（ROC） and calibration curve. The Bootstrap method was applied for internal validation. Results The logistic regression analysis showed that per capita monthly income of households，whether to participate in on-site disaster rescue，positive coping，mindfulness level，and adequacy of rescue supplies were independent influencing factors for the disaster resilience of medical rescue workers（P<0.05）. The predictive formula for the low-level risk of disaster resilience in medical rescue workers was established as follows：Logit（P）=8.741-0.381 × per capita monthly income of households -0.891 × whether to participate in on-site disaster rescue -2.544 × positive coping -0.020 × mindfulness level -0.222 × adequacy of rescue supplies. The area under the ROC curve was 0.823，and the optimal critical value was 0.353. The sensitivity and specificity were 79.12% and 71.43%，respectively. The Hosmer-Lemeshow test showed that χ²=12.250（P=0.140），and the predicted curve fitted well with the ideal curve. The external validation showed that the sensitivity and specificity of the model were 75.00% and 66.39%，respectively，and the overall accuracy was 69.95%. Conclusion The prediction model in this study has sound predictive effects and can provide references and guidance for managers to select，recruit，and train medical rescue workers.

Key words: Medical Rescue Workers, Disaster Resilience, Prediction Model, Nomogram, Disaster Nursing

摘要：

目的 分析医护救援人员灾害韧性的影响因素，构建其灾害韧性低水平风险的预测模型，并验证模型的预测效果。 方法 通过便利抽样法及滚雪球法，于2022年5月—7月选取全国18个省（区、市）参与过灾害救援的1 037名医护人员作为调查对象，采用一般资料调查问卷、医疗救援人员灾害韧性测量工具、正念注意觉知量表、简易应对方式问卷及抑郁-焦虑-压力量表精简版进行问卷调查，通过单因素分析及多因素Logistic回归分析确定医护救援人员灾害韧性低水平的影响因素，建立风险预测模型并绘制列线图。采用受试者操作特征曲线（receiver operating characteristic curve，ROC）、校准曲线等对模型效能进行评价，采用Bootstrap法进行内部验证。 结果 Logistic回归分析结果显示，家庭人均月收入、是否参与灾害现场救援、积极应对、正念水平、救援物资充足程度为医护救援人员灾害韧性水平的影响因素（P<0.05）。医护救援人员灾害韧性低水平风险的预测公式为：Logit（P）=8.741-0.381 × 家庭人均月收入-0.891 × 是否参与灾害现场救援-2.544 × 积极应对-0.020 × 正念水平-0.222 × 救援物资充足程度。ROC曲线下面积为0.823，最佳临界值为0.353，灵敏度和特异度分别为79.12%、71.43%。Hosmer-Lemeshow检验结果为χ²=12.250（P=0.140），预测曲线与理想曲线拟合较好。外部验证结果显示，该模型的灵敏度和特异度分别为75.00%、66.39%，总体正确率为69.95%。 结论 该研究构建的预测模型预测效果较好，可为管理者甄选、招募和培训医护救援人员提供参考和指导。

关键词: 医护救援人员, 灾害韧性, 预测模型, 列线图, 灾害护理