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dc.contributor.authorDinsmore, John
dc.date.accessioned2024-05-02T09:19:45Z
dc.date.available2024-05-02T09:19:45Z
dc.date.issued2024
dc.date.submitted2024en
dc.identifier.citationSheng Y., Doyle J., Bond R., Jaiswal R., Dinsmore J, Augmenting K-means Clustering with Qualitative Data to Discover Engagement Patterns of Older Adults with Multimorbidity when using Digital Health Technologies: Findings from a Proof-of-Concept Trial, Journal of Medical Internet Research, 2024, 1 - 23en
dc.identifier.otherY
dc.descriptionPUBLISHEDen
dc.description.abstractBackground: Multiple chronic conditions (multimorbidity) are becoming more prevalent among aging populations. Digital health technologies have the potential to assist in the self-management of multimorbidity, improving the awareness and monitoring of health and well-being, supporting a better understanding of the disease, and encouraging behavior change. Objective: The aim of this study was to analyze how 60 older adults (mean age 74, SD 6.4; range 65-92 years) with multimorbidity engaged with digital symptom and well-being monitoring when using a digital health platform over a period of approximately 12 months. Methods: Principal component analysis and clustering analysis were used to group participants based on their levels of engagement, and the data analysis focused on characteristics (eg, age, sex, and chronic health conditions), engagement outcomes, and symptom outcomes of the different clusters that were discovered. Results: Three clusters were identified: the typical user group, the least engaged user group, and the highly engaged user group. Our findings show that age, sex, and the types of chronic health conditions do not influence engagement. The 3 primary factors influencing engagement were whether the same device was used to submit different health and well-being parameters, the number of manual operations required to take a reading, and the daily routine of the participants. The findings also indicate that higher levels of engagement may improve the participants' outcomes (eg, reduce symptom exacerbation and increase physical activity). Conclusions: The findings indicate potential factors that influence older adult engagement with digital health technologies for home-based multimorbidity self-management. The least engaged user groups showed decreased health and well-being outcomes related to multimorbidity self-management. Addressing the factors highlighted in this study in the design and implementation of home-based digital health technologies may improve symptom management and physical activity outcomes for older adults self-managing multimorbidity.en
dc.format.extent1en
dc.format.extent23en
dc.language.isoenen
dc.relation.ispartofseriesJournal of Medical Internet Research;
dc.rightsYen
dc.subjectaging; chronic disease; digital health; engagement; k-means clustering; multimorbidityen
dc.titleAugmenting K-means Clustering with Qualitative Data to Discover Engagement Patterns of Older Adults with Multimorbidity when using Digital Health Technologies: Findings from a Proof-of-Concept Trialen
dc.typeJournal Articleen
dc.type.supercollectionscholarly_publicationsen
dc.type.supercollectionrefereed_publicationsen
dc.identifier.peoplefinderurlhttp://people.tcd.ie/dinsmorj
dc.identifier.rssinternalid262657
dc.identifier.doihttps://doi.org/10.2196/46287
dc.relation.ecprojectidinfo:eu-repo/grantAgreement/EC/FP7/689996
dc.relation.ecprojectidinfo:eu-repo/grantAgreement/EC/FP7/945449
dc.rights.ecaccessrightsopenAccess
dc.subject.TCDThemeAgeingen
dc.subject.TCDThemeDigital Engagementen
dc.subject.TCDThemeNext Generation Medical Devicesen
dc.subject.TCDTagAGEINGen
dc.subject.TCDTagChronic Illnessen
dc.subject.TCDTagChronic Illness self-managementen
dc.subject.TCDTagDigital Healthen
dc.subject.TCDTagHealth psychologyen
dc.subject.TCDTagmultimorbidityen
dc.identifier.orcid_id0000-0001-8387-3496
dc.subject.darat_impairmentChronic Health Conditionen
dc.subject.darat_thematicHealthen
dc.status.accessibleNen
dc.contributor.sponsorEuropean Commissionen
dc.contributor.sponsorGrantNumber945449en
dc.contributor.sponsorEuropean Commissionen
dc.contributor.sponsorGrantNumber689996en
dc.identifier.urihttp://hdl.handle.net/2262/108321


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