Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/116059
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dc.contributorSchool of Design-
dc.creatorZhao, Z-
dc.creatorLiu, K-
dc.creatorLyu, S-
dc.creatorWang, SJ-
dc.creatorChak, YH-
dc.creatorWang, H-
dc.date.accessioned2025-11-18T06:49:25Z-
dc.date.available2025-11-18T06:49:25Z-
dc.identifier.issn1460-4582-
dc.identifier.urihttp://hdl.handle.net/10397/116059-
dc.language.isoenen_US
dc.publisherSage Publications Ltd.en_US
dc.rights© The Author(s) 2025en_US
dc.rightsThis article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage).en_US
dc.rightsThe following publication Zhao Z, Liu K, Lyu S, Wang SJ, Chak YH, Wang H. Integrating embodied cognition with the UTAUT model to investigate factors influencing the adoption of home-based health monitoring systems. Health Informatics Journal. 2025;31(3) is available at https://doi.org/10.1177/14604582251363546.en_US
dc.subjectEmbodied cognitionen_US
dc.subjectEmbodied experienceen_US
dc.subjectHome-based health monitoring systemen_US
dc.subjectTechnology acceptanceen_US
dc.subjectUnified theory of acceptance and use of technology modelen_US
dc.titleIntegrating embodied cognition with the UTAUT model to investigate factors influencing the adoption of home-based health monitoring systemsen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume31-
dc.identifier.issue3-
dc.identifier.doi10.1177/14604582251363546-
dcterms.abstractObjective: Factors influencing users’ adoption of the home-based health monitoring system (HHMS) were examined by integrating embodied cognition with the unified theory of acceptance and use of technology (UTAUT) model.-
dcterms.abstractMethods: Data from 459 survey respondents were analyzed using partial least squares structural equation modeling (PLS-SEM).-
dcterms.abstractResults: The model explained 59.7% of the variance in behavioral intention to use the HHMS (typical range: 40%–60%). Perceived contextual adaptation, perceived sensorimotor feedback, and perceived body awareness significantly influenced behavioral intention. Perceived body awareness (i.e., an individual’s ability to perceive and interpret bodily signals) was identified as a crucial factor affecting performance expectancy, effort expectancy, facilitating conditions, and social influence.-
dcterms.abstractConclusions: The integration of embodied cognition with the UTAUT model contributes to theoretical advancements and demonstrates the importance of body awareness in users’ adoption of the HHMS, providing practical guidance for the effective design of HHMS.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationHealth informatics journal, July-Sept 2025, v. 31, no. 3, https://doi.org/10.1177/14604582251363546-
dcterms.isPartOfHealth informatics journal-
dcterms.issued2025-07-
dc.identifier.scopus2-s2.0-105012799356-
dc.identifier.pmid40742334-
dc.identifier.eissn1741-2811-
dc.description.validate202511 bcch-
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_Scopus/WOSen_US
dc.description.fundingSourceOthersen_US
dc.description.fundingTextThe author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was partially supported by the Health and Medical Research Fund, the Health Bureau, Hong Kong [no. 20211201], the Hong Kong Polytechnic University grants [no. P0049595, P0045769, and P0045577], and the National Natural Science Foundation of China [no. 72104176].en_US
dc.description.pubStatusPublisheden_US
dc.description.oaCategoryCCen_US
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