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新冠病毒感染疫情背景下公众大流行疲劳情况及影响因素

刘艳妮 郝艳华 王子予 刘媛 潘天一 朱逸飞

刘艳妮, 郝艳华, 王子予, 刘媛, 潘天一, 朱逸飞. 新冠病毒感染疫情背景下公众大流行疲劳情况及影响因素[J]. 中国公共卫生. doi: 10.11847/zgggws1141011
引用本文: 刘艳妮, 郝艳华, 王子予, 刘媛, 潘天一, 朱逸飞. 新冠病毒感染疫情背景下公众大流行疲劳情况及影响因素[J]. 中国公共卫生. doi: 10.11847/zgggws1141011
LIU Yan-ni, HAO Yan-hua, WANG Zi-yu, . Prevalence and influencing factors of pandemic fatigue during normalized COVID-19 containment among the public in China: an online cross cross-sectional sectional survey[J]. Chinese Journal of Public Health. doi: 10.11847/zgggws1141011
Citation: LIU Yan-ni, HAO Yan-hua, WANG Zi-yu, . Prevalence and influencing factors of pandemic fatigue during normalized COVID-19 containment among the public in China: an online cross cross-sectional sectional survey[J]. Chinese Journal of Public Health. doi: 10.11847/zgggws1141011

新冠病毒感染疫情背景下公众大流行疲劳情况及影响因素

doi: 10.11847/zgggws1141011
基金项目: 国家自然科学基金新冠肺炎疫情专项(72042001);国家自然科学基金(71673072)
详细信息
    作者简介:

    刘艳妮(1997 – ),女,山东临沂人,硕士在读,研究方向:卫生应急管理

    通讯作者:

    郝艳华,E-mail:hyhyjw@126.com

  • 中图分类号: R 193.3

Prevalence and influencing factors of pandemic fatigue during normalized COVID-19 containment among the public in China: an online cross cross-sectional sectional survey

  • 摘要:   目的  了解新冠病毒感染疫情防控常态化期间公众大流行疲劳情况及其影响因素。  方法  于2021年2 — 3月对中国5省(直辖市)4325名 ≥ 18 周岁的人群进行网络问卷调查,调查内容包括个人基本信息、风险感知、防护行为、情绪状态、大流行疲劳情况,利用SPSS 22.0对调查对象基本信息和疲劳情况进行描述性分析,并采用χ2检验、logistic回归对大流行疲劳影响因素进行分析。  结果  1082人存在大流行疲劳情况,占调查人群的25.0 %,其中单存在心身疲劳情况1844人(42.6 %),单存在信息疲劳情况1050人(24.3 %)。健康状况差(OR = 1.838,P < 0.05,95 % CI = 1.575~2.144)、认为疫情易感性强(OR = 1.435,P < 0.05,95 % CI = 1.236~1.667)、可控性差(OR = 1.760,P < 0.05,95 % CI = 1.495~2.070)、消极情绪程度高(OR = 3.493,P < 0.05,95 % CI = 2.987~4.086)的公众更容易形成大流行疲劳。  结论  公众存在一定的大流行疲劳现象,健康状况、疫情可控性和易感性程度、消极情绪是造成公众大流行疲劳的主要因素。
  • 表  1  公众大流行疲劳情况

    疲劳维度主要条目$\bar x \pm s$存在疲劳
    人数 %
    心身疲劳 长期配合疫情防控使我感觉很疲倦 3.02 ± 1.31 1844 42.6
    有关新冠疫情的一切让我感到身心俱疲
    信息疲劳 我没有精力去了解目前繁多的疫情信息 2.46 ± 1.19 1050 24.3
    我已经不愿去获取疫情信息,甚至对信息感到厌倦
    大流行疲劳 10.97 ± 3.92 1082 25.00
    下载: 导出CSV

    表  2  不同人口及社会学特征公众大流行疲劳发生情况

    因素 人数 %不存在大流行疲劳存在大流行疲劳χ2P
    人数 % 人数 %
    性别 0.347 0.556
     男 2121 59.0 1582 74.6 539 25.4
     女 2204 51.0 1661 75.4 543 24.6
    年龄(岁) 6.128 0.047
     < 25 69 1.6 43 62.3 26 37.7
     25~45 674 15.6 503 74.6 171 25.4
     > 45 3582 82.8 2697 75.3 885 24.7
    居住地 0.770 0.380
     城市 2899 67.0 2162 74.6 737 25.4
     乡镇 1426 33.0 1081 75.8 345 24.2
    自评健康状况 a 119.882 0.000
     较差 1317 30.5 844 64.1 473 35.9
     较好 3008 69.5 2399 79.8 609 20.2
    文化程度 b 2.357 0.125
     低 947 21.9 692 73.1 255 26.9
     高 3378 78.1 2551 75.5 827 24.5
    就业状态 0.193 0.661
     在业 2790 64.5 2098 75.2 692 24.8
     其他 1535 35.5 1145 74.6 390 25.4
    过度防护行为
     戒备、抵触与陌生人接触 9.381 0.002
      低 1746 40.4 1352 77.4 394 22.6
      高 2579 59.6 1891 73.3 688 26.7
     反复洗手,擦洗东西 21.584 0.000
      低 2227 51.5 1736 78.0 491 22.0
      高 2098 48.5 1507 71.8 591 28.2
    风险感知
     严重性 21.975 0.000
      低 1753 40.5 1380 78.7 373 21.3
      高 2572 59.5 1863 72.4 709 27.6
     可控性 126.051 0.000
      低 2203 50.9 1492 67.7 711 32.3
      高 2122 49.1 1751 82.5 371 17.5
     易感性 82.761 0.000
      低 2552 59.0 2041 80.0 511 20.0
      高 1773 41.0 1202 67.8 571 32.2
    消极情绪 394.195 0.000
     低 2440 56.4 2110 86.5 330 13.5
     高 1885 43.6 1133 60.1 752 39.9
      注:a 自评健康状况分为“非常差”“较差”“一般”“较好”“非常好”5个维度,并分别赋值1~5分,本研究中进行二分类编码(1~3编为0 = 健康状况较差,4~5编为1 = 健康状况较好);b文化程度划分中将大专及以上学历界定为高文化程度。
    下载: 导出CSV

    表  3  公众大流行疲劳logistics回归分析结果

    项目变量参照组回归系数$S_{\bar x}$ Wald χ2POR95 % CI
    基本人口学特征 健康状况 较高 0.609 0.079 59.683 0.000 1.838 1.575~2.144
    风险感知 可控性 较高 0.565 0.083 46.341 0.000 1.760 1.495~2.070
    易感性 较差 0.361 0.076 22.373 0.000 1.435 1.236~1.667
    消极情绪 消极情绪 较低 1.251 0.080 244.597 0.000 3.493 2.987~4.086
    下载: 导出CSV
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  • 收稿日期:  2022-12-02
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