Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/109103
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dc.contributorSchool of Nursing-
dc.creatorZhang, H-
dc.creatorChen, D-
dc.creatorZou, P-
dc.creatorShao, J-
dc.creatorWu, J-
dc.creatorCui, N-
dc.creatorLin, S-
dc.creatorTang, L-
dc.creatorZheng, Q-
dc.creatorWang, X-
dc.creatorYe, Z-
dc.date.accessioned2024-09-19T03:13:14Z-
dc.date.available2024-09-19T03:13:14Z-
dc.identifier.urihttp://hdl.handle.net/10397/109103-
dc.language.isoenen_US
dc.publisherBioMed Central Ltd.en_US
dc.rights© The Author(s) 2023.en_US
dc.rightsThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.en_US
dc.rightsThe following publication Zhang, H., Chen, D., Zou, P. et al. The integrated common-sense model of illness self-regulation: predicting healthy eating, exercise behaviors, and health among individuals at risk of metabolic syndrome. BMC Public Health 23, 1486 (2023) is available at https://doi.org/10.1186/s12889-023-16403-2.en_US
dc.subjectHealth behaviorsen_US
dc.subjectIllness perceptionen_US
dc.subjectMetabolic syndromeen_US
dc.subjectThe common-sense modelen_US
dc.titleThe integrated common-sense model of illness self-regulation : predicting healthy eating, exercise behaviors, and health among individuals at risk of metabolic syndromeen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume23-
dc.identifier.doi10.1186/s12889-023-16403-2-
dcterms.abstractBackground: Little is known about the potential mechanisms of healthy eating and exercise change, and design interventions which aim to promote healthy eating and exercise change among individuals at risk of metabolic syndrome. This study aimed to identify key determinants of healthy eating, exercise behaviors, and health among individuals at risk of metabolic syndrome using the integrated common-sense model of illness self-regulation.-
dcterms.abstractMethod: A cross-sectional study with a multi-wave data collection strategy. A total of 275 participants at risk of metabolic syndrome based on the clinical prediction model were included in the final analysis. Path analysis was employed to explore the pattern of relationships between key variables using AMOS.-
dcterms.abstractResults: The mediation analysis suggested that personal and treatment control, and coherence can positively affect self-reported health via intentions and health behaviors (exercise and healthy eating). Additionally, relationships between self-efficacy (exercise and healthy eating) and health outcomes can be mediated by health behaviors, and both intentions and health behaviors.-
dcterms.abstractConclusions: This current research used the integrated common-sense model of illness self-regulation to predict healthy eating, exercise behaviors, and self-reported health among individuals at risk of metabolic syndrome. The results suggested that self-efficacy, intention, consequences, personal control, treatment control, and coherence were the key determinants of behavior and health, which can help design interventions to encourage healthy eating and exercise changes among individuals with a high risk of MetS.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationBMC public health, 2023, v. 23, 1486-
dcterms.isPartOfBMC public health-
dcterms.issued2023-
dc.identifier.scopus2-s2.0-85166597489-
dc.identifier.pmid37542247-
dc.identifier.eissn1471-2458-
dc.identifier.artn1486-
dc.description.validate202409 bcch-
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_Scopus/WOSen_US
dc.description.fundingSourceOthersen_US
dc.description.fundingTextGuizhou Provincial People’s Hospital Yuan Ren Cai Xiang Mu; National Natural Science Foundation of China; Science Technology Platform and Talent Team Plan Projects in Guizhou Province; Zhejiang province medical technology projecten_US
dc.description.pubStatusPublisheden_US
dc.description.oaCategoryCCen_US
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