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突发公共卫生事件下社区居民风险感知的潜在剖面分析 被引量:2

Latent profile analysis of community residents’risk perception in public health emergencies
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摘要 目的:探索突发公共卫生事件下社区居民风险感知的潜在类别,分析潜在类别的影响因素。方法:采用横断面研究设计,于2022年3月至5月便利抽取全国30个省份7 844个居民为研究对象,采用一般资料问卷、新冠肺炎疫情风险感知量表、简易应对方式量表、突发性公共卫生事件心理问卷进行调查。采用潜在剖面分析识别社区居民风险感知类别;采用无序多分类Logistic回归分析各类别影响因素。结果:社区居民风险感知可分为低风险感知组(23.9%)、高风险感知组(29.3%)、低易感性-高感知组(46.8%)。无序多分类Logistic回归分析结果表明,与低风险感知组相比,年龄越大(OR=1.021,P<0.001),女性(OR=1.283,P=0.008)、居住地农村(OR=1.198,P=0.014)、曾被隔离(OR=1.277,P=0.031)、疫苗接种≤1次(OR=1.614,P=0.036)、消极应对(OR=1.420,P<0.001)、抑郁(OR=1.324,P=0.001)、恐惧(OR=2.579,P<0.001)、疑病(OR=1.421,P<0.001)得分越高的居民倾向于为高风险感知组,而中专或高中学历(OR=0.733,P=0.045)、积极应对(OR=0.662,P<0.001)、强迫-焦虑(OR=0.786,P=0.043)得分越高的居民更不可能是高风险感知组。与低风险感知组相比,女性(OR=1.382,P<0.001)、居住地农村(OR=1.297,P<0.001)、消极应对(OR=1.202,P<0.001)、神经衰弱(OR=1.189,P=0.023)、恐惧(OR=2.458,P<0.001)得分越高的居民倾向于为低易感性-高感知组,而已婚(OR=0.798,P=0.013)、曾参与抗击疫情相关活动(OR=0.862,P=0.015)、积极应对(OR=0.750,P<0.001)、强迫-焦虑(OR=0.653,P<0.001)得分越高的居民更不可能是低易感性-高感知组。结论:突发公共卫生事件下社区居民风险感知存在明显的分类特征,且居民风险感知与应对方式、心理健康状态有关,社区医务人员应注重不同人群风险感知特点,实施针对性干预措施。 Objective:To explore the potential categories of community residents’risk perception in public health emergencies and analyze the influencing factors of different categories.Methods:A cross-sectional study was designed to recruit 7844 residents from 30 provinces in China from March to May 2022 by convenient sampling.The general characteristics,COVID-19 Risk Perception Scale,Simplified Coping Style Questionnaire,and Psychological Questionnaires for Emergent Events of Public Health were collected.Latent profile analysis was used to explore the classification of the risk perception of community residents,and multinomial logistic regression analysis was used to compare the characteristics of each latent category and to investigate their influencing factors.Results:The risk perception of community residents could be divided into three categories:low risk-perception(23.9%),high risk-perception(29.3%),and high risk-perception with low-susceptibility in general(46.8%).The results of multinomial logistic regression showed that compared with the low risk-perception group,residents who were older(OR=1.021,P<0.001),female(OR=1.283,P=0.008),rural(OR=1.198,P=0.014),who had been isolated(OR=1.277,P=0.031),had≤1 vaccination(OR=1.614,P=0.036),and had higher scores of negative coping(OR=1.420,P<0.001),depression(OR=1.324,P=0.001),fear(OR=2.579,P<0.001),and suspicion of illness(OR=1.421,P<0.001)tended to be in the high risk-perception group,while residents with technical secondary or high school degrees(OR=0.733,P=0.045),who had higher scores of positive coping(OR=0.662,P<0.001),and obsessive-compulsive-anxiety(OR=0.786,P=0.043)were less likely to be in the high risk-perception group.Compared with the low risk-perception group,residents who were female(OR=1.382,P<0.001),living in the rural area(OR=1.297,P<0.001),who had higher scores of negative coping(OR=1.202,P<0.001),neurosis(OR=1.189,P=0.023),and fear(OR=2.458,P<0.001)tended to be in the group of lowsusceptibility high-perception,while residents who were married(OR=0.798,P=0.013),who had been engaged in epidemic-related activities(OR=0.862,P=0.015),had higher scores of positive coping(OR=0.750,P<0.001),and obsessive-compulsive-anxiety(OR=0.653,P<0.001)were less likely to be in the low-susceptibility highperception group.Conclusion:There is heterogeneity in the risk perception of community residents in public health emergencies,and the residents’risk perception is related to coping style and mental health status.Community medical staff should carry out targeted interventions according to the characteristics of different categories.
作者 章瑶 孙宏玉 陶静蕊 徐欢 董超群 ZHANG Yao;SUN Hongyu;TAO Jingrui;XU Huan;DONG Chaoqun(School of Nursing,Wenzhou Medical University,Wenzhou 325035,China;School of Nursing,Peking University,Beijing 100871,China)
出处 《温州医科大学学报》 CAS 2023年第7期595-602,F0003,共9页 Journal of Wenzhou Medical University
基金 北京市自然科学基金项目(9212008)。
关键词 风险感知 应对方式 心理健康 突发公共卫生事件 社区居民 潜在剖面分析 risk perception coping style mental health public health emergency community resident latent profile analysis
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