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Home-based digital health technologies for older adults to self-manage multiple chronic conditions: A data-informed analysis of user engagement from a longitudinal trial.
Sheng, Yiyang; Doyle, Julie; Bond, Raymond; Jaiswal, Rajesh; Gavin, Shane; Dinsmore, John.
Afiliação
  • Sheng Y; NetwellCASALA, Dundalk Institute of Technology, Dundalk, Co. Louth, Ireland.
  • Doyle J; NetwellCASALA, Dundalk Institute of Technology, Dundalk, Co. Louth, Ireland.
  • Bond R; School of Computing, Ulster University, Jordanstown, UK.
  • Jaiswal R; School of Computing, Dundalk Institute of Technology, Dundalk, Co. Louth, Ireland.
  • Gavin S; NetwellCASALA, Dundalk Institute of Technology, Dundalk, Co. Louth, Ireland.
  • Dinsmore J; Trinity Centre for Practice and Healthcare Innovation, School of Nursing and Midwifery, Trinity College Dublin, Dublin, Ireland.
Digit Health ; 8: 20552076221125957, 2022.
Article em En | MEDLINE | ID: mdl-36171962
ABSTRACT

Background:

Ageing populations are resulting in higher prevalence of people with multiple chronic conditions (multimorbidity). Digital health platforms have great potential to support self-management of multimorbidity, increasing a person's awareness of their health and well-being, supporting a better understanding of diseases and encouraging behaviour change. However, little research has explored the long-term engagement of older adults with such digital interventions.

Methods:

The aim of this study is to analyse how 60 older adults with multimorbidity engaged with digital symptom and well-being monitoring through a digital health platform over a period of approximately 12 months. Data analysis focused on user retention, frequency of monitoring, intervals in monitoring and patterns of daily engagement.

Results:

Our findings show that the overall engagement with the digital health platform was high, with more than 80% of participants using the technology devices for over 200 days. The submission frequency for symptom parameters (e.g. blood glucose (BG), blood pressure (BP), etc.) was between three and four times per week which was higher than that of self-report (2.24) and weight (2.84). Submissions of exercise (6.12) and sleep (5.67) were more frequent. The majority of interactions happened in the morning time. The most common time of submission for symptom parameters was 10 am, whereas 8 am was the most common time for weight measurements.

Conclusions:

The findings indicate the patterns of engagement of older adults with complex chronic diseases with digital home-based self-management systems.
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Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Risk_factors_studies Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Risk_factors_studies Idioma: En Ano de publicação: 2022 Tipo de documento: Article