COVID-19风险感知措施:行为意图和政策支持的因素分析和预测

IF 2.4 4区 管理学 Q1 SOCIAL SCIENCES, INTERDISCIPLINARY Journal of Risk Research Pub Date : 2023-10-11 DOI:10.1080/13669877.2023.2264301
Branden B. Johnson, Byungdoo Kim
{"title":"COVID-19风险感知措施:行为意图和政策支持的因素分析和预测","authors":"Branden B. Johnson, Byungdoo Kim","doi":"10.1080/13669877.2023.2264301","DOIUrl":null,"url":null,"abstract":"AbstractAlthough early concepts of risk perception measures distinguished cognitive from affective items, until recently multi-dimensional taxonomies were absent from risk perception studies, and even more from tests of their association with behavior or policy support. Six longitudinal panel surveys on U.S. COVID-19 views (n = 2004 February 2020, ending April 2021) allowed testing of these relationships among ≤ 10 risk perception items measured in each wave. Confirmatory factor analyses revealed consistent distinctions between personal (conditioning perceived risk on taking further or no further protective action), collective (U.S., global), affective (concern, dread), and severity (estimates of eventual total U.S. infections and deaths) measures, while affect (good-bad feelings) and duration (how long people expect the outbreak to last) did not fit with their assumed affective and severity (respectively) parallels. Collective and affective/affect risk perceptions most strongly predicted both behavioral intentions and policy support for mask wearing, avoidance of large public gatherings, and vaccination, controlling for personal risk perception (which might be partly reflected in the affective/affect effects) and other measures. These findings underline the importance of multi-dimensionality (e.g. not just asking about personal risk perceptions) in designing risk perception research, even when trying to explain personal protective actions.Keywords: behavioral intentionsCOVID-19policy supportRisk perceptiontaxonomy Disclosure statementNo potential conflict of interest was reported by the authors.Notes1 A corollary might be that the global risk perception measure also belongs in this cluster, particularly for duration, which does impose a geographical limit on the area where the pandemic “ends.” A separate analysis (unreported here) showed results similar to those for this fifth model.2 Backup exploratory factor analyses for Waves 2-6 identified six factors out of the 10 items: collective, severity (infection, deaths), personal, affect, duration, and dread. Concern loaded on both collective and personal factors (> .49 and > .41, respectively). The personal connection might be prompted by the measure’s reference to “where you live”; its association with collective measures is unclear. Models clustering personal, collective, and concern measures, including affect and duration as single-item factors, had poor fit (e.g. Wave 2: chi-square/df = 26.849; RMSEA = .127 [.118, .135]; CFI = .928; AIC = 42,991.443).Additional informationFundingThe work contributing to this article was funded by the United States National Science Foundation under Grant No. 2022216.","PeriodicalId":16975,"journal":{"name":"Journal of Risk Research","volume":null,"pages":null},"PeriodicalIF":2.4000,"publicationDate":"2023-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"COVID-19 risk perception measures: factoring and prediction of behavioral intentions and policy support\",\"authors\":\"Branden B. Johnson, Byungdoo Kim\",\"doi\":\"10.1080/13669877.2023.2264301\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"AbstractAlthough early concepts of risk perception measures distinguished cognitive from affective items, until recently multi-dimensional taxonomies were absent from risk perception studies, and even more from tests of their association with behavior or policy support. Six longitudinal panel surveys on U.S. COVID-19 views (n = 2004 February 2020, ending April 2021) allowed testing of these relationships among ≤ 10 risk perception items measured in each wave. Confirmatory factor analyses revealed consistent distinctions between personal (conditioning perceived risk on taking further or no further protective action), collective (U.S., global), affective (concern, dread), and severity (estimates of eventual total U.S. infections and deaths) measures, while affect (good-bad feelings) and duration (how long people expect the outbreak to last) did not fit with their assumed affective and severity (respectively) parallels. Collective and affective/affect risk perceptions most strongly predicted both behavioral intentions and policy support for mask wearing, avoidance of large public gatherings, and vaccination, controlling for personal risk perception (which might be partly reflected in the affective/affect effects) and other measures. These findings underline the importance of multi-dimensionality (e.g. not just asking about personal risk perceptions) in designing risk perception research, even when trying to explain personal protective actions.Keywords: behavioral intentionsCOVID-19policy supportRisk perceptiontaxonomy Disclosure statementNo potential conflict of interest was reported by the authors.Notes1 A corollary might be that the global risk perception measure also belongs in this cluster, particularly for duration, which does impose a geographical limit on the area where the pandemic “ends.” A separate analysis (unreported here) showed results similar to those for this fifth model.2 Backup exploratory factor analyses for Waves 2-6 identified six factors out of the 10 items: collective, severity (infection, deaths), personal, affect, duration, and dread. Concern loaded on both collective and personal factors (> .49 and > .41, respectively). The personal connection might be prompted by the measure’s reference to “where you live”; its association with collective measures is unclear. Models clustering personal, collective, and concern measures, including affect and duration as single-item factors, had poor fit (e.g. Wave 2: chi-square/df = 26.849; RMSEA = .127 [.118, .135]; CFI = .928; AIC = 42,991.443).Additional informationFundingThe work contributing to this article was funded by the United States National Science Foundation under Grant No. 2022216.\",\"PeriodicalId\":16975,\"journal\":{\"name\":\"Journal of Risk Research\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.4000,\"publicationDate\":\"2023-10-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Risk Research\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1080/13669877.2023.2264301\",\"RegionNum\":4,\"RegionCategory\":\"管理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"SOCIAL SCIENCES, INTERDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Risk Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/13669877.2023.2264301","RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"SOCIAL SCIENCES, INTERDISCIPLINARY","Score":null,"Total":0}
引用次数: 1

摘要

尽管早期的风险感知测量概念区分了认知和情感项目,但直到最近,多维分类在风险感知研究中都是缺失的,甚至在风险感知与行为或政策支持的关联测试中更是缺失的。关于美国COVID-19观点的六项纵向小组调查(n = 2004年2月至2021年4月)允许在每波测量的≤10个风险感知项目之间测试这些关系。验证性因素分析揭示了个人(对采取进一步或不采取进一步保护行动的感知风险)、集体(美国、全球)、情感(担忧、恐惧)和严重程度(对美国最终感染和死亡总数的估计)措施之间的一致区别,而影响(好坏的感觉)和持续时间(人们预计疫情持续多久)与假设的情感和严重程度(分别)不相符。集体和情感/影响风险感知最能预测佩戴口罩、避免大型公共集会、接种疫苗、控制个人风险感知(可能部分反映在情感/影响效应中)和其他措施的行为意图和政策支持。这些发现强调了多维度(例如,不只是询问个人风险感知)在设计风险感知研究中的重要性,甚至在试图解释个人保护行动时也是如此。关键词:行为意向政策支持风险感知分类披露声明作者未报告潜在利益冲突。注1一个推论可能是,全球风险感知措施也属于这一类,特别是就持续时间而言,这确实对大流行“结束”的地区施加了地理限制。另一项单独的分析(此处未报道)显示了与第五种模型相似的结果波浪2-6的备份探索性因素分析从10个项目中确定了6个因素:集体、严重程度(感染、死亡)、个人、影响、持续时间和恐惧。对集体和个人因素的关注(分别> .49和> .41)。个人联系可能是由测量中提到的“你住在哪里”引起的;它与集体措施的关系尚不清楚。将个人、集体和关注措施聚类的模型,包括影响和持续时间作为单项因素,拟合度较差(例如,波2:卡方/df = 26.849;Rmsea = .127[。]118年,.135];Cfi = .928;Aic = 42,991.443)。本文的工作由美国国家科学基金会资助,资助号为2022216。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
COVID-19 risk perception measures: factoring and prediction of behavioral intentions and policy support
AbstractAlthough early concepts of risk perception measures distinguished cognitive from affective items, until recently multi-dimensional taxonomies were absent from risk perception studies, and even more from tests of their association with behavior or policy support. Six longitudinal panel surveys on U.S. COVID-19 views (n = 2004 February 2020, ending April 2021) allowed testing of these relationships among ≤ 10 risk perception items measured in each wave. Confirmatory factor analyses revealed consistent distinctions between personal (conditioning perceived risk on taking further or no further protective action), collective (U.S., global), affective (concern, dread), and severity (estimates of eventual total U.S. infections and deaths) measures, while affect (good-bad feelings) and duration (how long people expect the outbreak to last) did not fit with their assumed affective and severity (respectively) parallels. Collective and affective/affect risk perceptions most strongly predicted both behavioral intentions and policy support for mask wearing, avoidance of large public gatherings, and vaccination, controlling for personal risk perception (which might be partly reflected in the affective/affect effects) and other measures. These findings underline the importance of multi-dimensionality (e.g. not just asking about personal risk perceptions) in designing risk perception research, even when trying to explain personal protective actions.Keywords: behavioral intentionsCOVID-19policy supportRisk perceptiontaxonomy Disclosure statementNo potential conflict of interest was reported by the authors.Notes1 A corollary might be that the global risk perception measure also belongs in this cluster, particularly for duration, which does impose a geographical limit on the area where the pandemic “ends.” A separate analysis (unreported here) showed results similar to those for this fifth model.2 Backup exploratory factor analyses for Waves 2-6 identified six factors out of the 10 items: collective, severity (infection, deaths), personal, affect, duration, and dread. Concern loaded on both collective and personal factors (> .49 and > .41, respectively). The personal connection might be prompted by the measure’s reference to “where you live”; its association with collective measures is unclear. Models clustering personal, collective, and concern measures, including affect and duration as single-item factors, had poor fit (e.g. Wave 2: chi-square/df = 26.849; RMSEA = .127 [.118, .135]; CFI = .928; AIC = 42,991.443).Additional informationFundingThe work contributing to this article was funded by the United States National Science Foundation under Grant No. 2022216.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Journal of Risk Research
Journal of Risk Research SOCIAL SCIENCES, INTERDISCIPLINARY-
CiteScore
12.20
自引率
5.90%
发文量
44
期刊介绍: The Journal of Risk Research is an international journal that publishes peer-reviewed theoretical and empirical research articles within the risk field from the areas of social, physical and health sciences and engineering, as well as articles related to decision making, regulation and policy issues in all disciplines. Articles will be published in English. The main aims of the Journal of Risk Research are to stimulate intellectual debate, to promote better risk management practices and to contribute to the development of risk management methodologies. Journal of Risk Research is the official journal of the Society for Risk Analysis Europe and the Society for Risk Analysis Japan.
期刊最新文献
Beyond the singular and linear risk approach Investigating the psychological impact of communicating epistemic uncertainty in personalized and generic risk estimates: an experimental study Securing public spaces: public willingness to sacrifice convenience and privacy for security at three U.S. public venues Seismic hazard and risk analysis in The Netherlands for deep subsurface activities in practice The role of knowledge and trust in developing risk perceptions of autonomous vehicles: a moderated mediation model
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1