Perception-based influence factors of intention to adopt COVID-19 epidemic prevention in China
- PMID: 32739626
- PMCID: PMC7384406
- DOI: 10.1016/j.envres.2020.109995
Perception-based influence factors of intention to adopt COVID-19 epidemic prevention in China
Abstract
Background: The researches investigating the influence factors of epidemic prevention are not only scarce, but also provide a gap in the domain of perception-based influence factors of intention to adopt COVID-19 epidemic prevention.
Objective: This work has attempted to examine the perception-based influence factors of individuals' intention to adopt COVID-19 epidemic prevention in a modified behavioral framework.
Theoretical framework: A behavioral framework composed of the theory of reasoned action and the theory of planned behavior is developed to incorporate some additional perception-based influence factors.
Methods: A partial least square-based path analysis has been employed to estimate the path coefficients of those factors in terms of drivers, barriers, and neutral factors based on questionnaire data of 302 respondents from six universities and two hospitals in China.
Results: Among the perception-based influence factors, governments' guidelines on epidemic prevention is found to be the most important and influential factor, which was followed by risk perception. Finally, attitude towards epidemic prevention exhibited the least degree of impact on individuals' intention to adopt epidemic prevention. Moral norms did not show any contribution to individuals' intention to adopt epidemic prevention.
Conclusion: Concerning importance ranking, the governments' guidelines on epidemic prevention, risk perception, and epidemic knowledge are revealed as the top three drivers of individuals' intention to adopt epidemic prevention, while the perceived feasibility to adopt epidemic prevention is found to be a barrier. Moreover, moral norms is identified to have an insignificant influence on individuals' intention to adopt epidemic prevention. Given the empirical results, dissemination of Governments' guidelines on epidemic prevention, proper risk perception, and knowledge about epidemic would help prevent the COVID-19 pandemic outbreak within China and worldwide.
Keywords: Epidemic knowledge; Governments' guidelines on epidemic prevention; Modified behavioral framework; Risk aversion; Risk perception.
Copyright © 2020 Elsevier Inc. All rights reserved.
Conflict of interest statement
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Figures
Similar articles
-
Differences in Preventive Behaviors of COVID-19 between Urban and Rural Residents: Lessons Learned from A Cross-Sectional Study in China.Int J Environ Res Public Health. 2020 Jun 20;17(12):4437. doi: 10.3390/ijerph17124437. Int J Environ Res Public Health. 2020. PMID: 32575700 Free PMC article.
-
Impact of Online Information on Self-Isolation Intention During the COVID-19 Pandemic: Cross-Sectional Study.J Med Internet Res. 2020 May 6;22(5):e19128. doi: 10.2196/19128. J Med Internet Res. 2020. PMID: 32330115 Free PMC article.
-
Exploring How Media Influence Preventive Behavior and Excessive Preventive Intention during the COVID-19 Pandemic in China.Int J Environ Res Public Health. 2020 Oct 30;17(21):7990. doi: 10.3390/ijerph17217990. Int J Environ Res Public Health. 2020. PMID: 33143145 Free PMC article.
-
COVID-19 Pandemic: Experiences in China and Implications for its Prevention and Treatment Worldwide.Curr Cancer Drug Targets. 2020;20(6):410-416. doi: 10.2174/1568009620666200414151419. Curr Cancer Drug Targets. 2020. PMID: 32286947 Review.
-
[Guide for the prevention and treatment of coronavirus disease 2019].Zhonghua Jie He He Hu Xi Za Zhi. 2020 Jun 12;43(6):473-489. doi: 10.3760/cma.j.cn112147-112147-20200321-00392. Zhonghua Jie He He Hu Xi Za Zhi. 2020. PMID: 32486556 Review. Chinese.
Cited by
-
Evaluating COVID-19 infection prevention measures in Malaysia: A fuzzy DEMATEL approach.Digit Health. 2023 Dec 6;9:20552076231211670. doi: 10.1177/20552076231211670. eCollection 2023 Jan-Dec. Digit Health. 2023. PMID: 38074341 Free PMC article.
-
The effects of information framing on self-protective behavior: Evidence from the COVID-19 vaccine uptake.Digit Health. 2023 Oct 29;9:20552076231210655. doi: 10.1177/20552076231210655. eCollection 2023 Jan-Dec. Digit Health. 2023. PMID: 37915790 Free PMC article.
-
Antecedents predicting digital contact tracing acceptance: a systematic review and meta-analysis.BMC Med Inform Decis Mak. 2023 Oct 11;23(1):212. doi: 10.1186/s12911-023-02313-1. BMC Med Inform Decis Mak. 2023. PMID: 37821864 Free PMC article.
-
User Compliance With the Health Emergency and Disaster Management System: Systematic Literature Review.J Med Internet Res. 2023 May 5;25:e41168. doi: 10.2196/41168. J Med Internet Res. 2023. PMID: 37145840 Free PMC article. Review.
-
Application of behavioral change theory and models on COVID-19 preventive behaviors, worldwide: A systematic review.SAGE Open Med. 2023 Mar 31;11:20503121231159750. doi: 10.1177/20503121231159750. eCollection 2023. SAGE Open Med. 2023. PMID: 37026109 Free PMC article. Review.
References
-
- Ajzen I. Theory of planned behavior. Organ. Behav. Hum. Decis. Process. 1991;50:179–211.
-
- Ajzen I. Action-Control: from Cognitions to Behavior. 1985. From Intentions to Actions : A Theory of Planned Behavior; pp. 11–39.
-
- Ajzen I., Fishbein M. The prediction of behavior from attitudinal and normative variables. J. Exp. Soc. Psychol. 1970;6:466–487.
-
- Bagozzi R.P., Heatherton T.F. Structural Equation Modeling : a general approach to representing multifaceted personality constructs : application to state self ‐ esteem. Struct. Equ. Model. 1994;1:35–67. doi: 10.1080/10705519409539961. - DOI
MeSH terms
LinkOut - more resources
Full Text Sources
Miscellaneous
