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dc.contributor.authorLin, Chung‐Ying
dc.contributor.authorImani, Vida
dc.contributor.authorMajd, Nilofar Rajabi
dc.contributor.authorGhasemi, Zahra
dc.contributor.authorGriffiths, Mark D.
dc.contributor.authorHamilton, Kyra
dc.contributor.authorHagger, Martin S.
dc.contributor.authorPakpour, Amir H.
dc.date.accessioned2020-08-17T11:13:06Z
dc.date.available2020-08-17T11:13:06Z
dc.date.issued2020
dc.identifier.citationLin, C., Imani, V., Majd, N. R., Ghasemi, Z., Griffiths, M. D., Hamilton, K., Hagger, M. S., & Pakpour, A. H. (2020). Using an integrated social cognition model to predict COVID‐19 preventive behaviours. <i>British Journal of Health Psychology</i>, <i>25</i>(4), 981-1005. <a href="https://doi.org/10.1111/bjhp.12465" target="_blank">https://doi.org/10.1111/bjhp.12465</a>
dc.identifier.otherCONVID_41732397
dc.identifier.urihttps://jyx.jyu.fi/handle/123456789/71403
dc.description.abstractObjectives Rates of novel coronavirus disease 2019 (COVID‐19) infections have rapidly increased worldwide and reached pandemic proportions. A suite of preventive behaviours have been recommended to minimize risk of COVID‐19 infection in the general population. The present study utilized an integrated social cognition model to explain COVID‐19 preventive behaviours in a sample from the Iranian general population. Design The study adopted a three‐wave prospective correlational design. Methods Members of the general public (N = 1,718, M age = 33.34, SD = 15.77, male = 796, female = 922) agreed to participate in the study. Participants completed self‐report measures of demographic characteristics, intention, attitude, subjective norm, perceived behavioural control, and action self‐efficacy at an initial data collection occasion. One week later, participants completed self‐report measures of maintenance self‐efficacy, action planning and coping planning, and, a further week later, measures of COVID‐19 preventive behaviours. Hypothesized relationships among social cognition constructs and COVID‐19 preventive behaviours according to the proposed integrated model were estimated using structural equation modelling. Results The proposed model fitted the data well according to multiple goodness‐of‐fit criteria. All proposed relationships among model constructs were statistically significant. The social cognition constructs with the largest effects on COVID‐19 preventive behaviours were coping planning (β = .575, p < .001) and action planning (β = .267, p < .001). Conclusions Current findings may inform the development of behavioural interventions in health care contexts by identifying intervention targets. In particular, findings suggest targeting change in coping planning and action planning may be most effective in promoting participation in COVID‐19 preventive behaviours.en
dc.format.mimetypeapplication/pdf
dc.languageeng
dc.language.isoeng
dc.publisherJohn Wiley & Sons
dc.relation.ispartofseriesBritish Journal of Health Psychology
dc.rightsCC BY 4.0
dc.subject.otherattitude
dc.subject.otherbehaviour change
dc.subject.otherintention
dc.subject.otherplanning
dc.subject.otherpreventive behaviours
dc.titleUsing an integrated social cognition model to predict COVID‐19 preventive behaviours
dc.typearticle
dc.identifier.urnURN:NBN:fi:jyu-202008175539
dc.contributor.laitosLiikuntatieteellinen tiedekuntafi
dc.contributor.laitosFaculty of Sport and Health Sciencesen
dc.contributor.oppiaineLiikuntapsykologiafi
dc.contributor.oppiaineSport and Exercise Psychologyen
dc.type.urihttp://purl.org/eprint/type/JournalArticle
dc.description.reviewstatuspeerReviewed
dc.format.pagerange981-1005
dc.relation.issn1359-107X
dc.relation.numberinseries4
dc.relation.volume25
dc.type.versionpublishedVersion
dc.rights.copyright© 2020 the Authors
dc.rights.accesslevelopenAccessfi
dc.subject.ysoCOVID-19
dc.subject.ysopandemiat
dc.subject.ysointentio
dc.subject.ysoennaltaehkäisy
dc.subject.ysososiaalinen kognitio
dc.subject.ysoterveyskäyttäytyminen
dc.subject.ysoasenteet
dc.subject.ysotartuntataudit
dc.subject.ysosuunnittelu
dc.format.contentfulltext
jyx.subject.urihttp://www.yso.fi/onto/yso/p38829
jyx.subject.urihttp://www.yso.fi/onto/yso/p10121
jyx.subject.urihttp://www.yso.fi/onto/yso/p1001
jyx.subject.urihttp://www.yso.fi/onto/yso/p19552
jyx.subject.urihttp://www.yso.fi/onto/yso/p12416
jyx.subject.urihttp://www.yso.fi/onto/yso/p11100
jyx.subject.urihttp://www.yso.fi/onto/yso/p5619
jyx.subject.urihttp://www.yso.fi/onto/yso/p1804
jyx.subject.urihttp://www.yso.fi/onto/yso/p1377
dc.rights.urlhttps://creativecommons.org/licenses/by/4.0/
dc.relation.doi10.1111/bjhp.12465
jyx.fundinginformationThis study was supported by grants from the Qazvin University of Medical Sciences. The funders were not involved in the study design, data collection, data analysis, data interpretation, or writing of the report. Martin S. Hagger’s contribution was supported by a Finland Distinguished Professor (FiDiPro) award (#1801/31/2105) from Business Finland.


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