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

Yiyang Sheng, Julie Doyle, RR Bond, Rajesh Jaiswal, Shane Gavin, John Dinsmore

Research output: Contribution to journalArticlepeer-review

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Abstract

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. 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. Specific objectives include examining user retention, frequency of monitoring, intervals in monitoring and patterns of daily engagement, with the overall goal of better understanding how to promote sustained engagement over time. 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, blood pressure etc.) was between three to 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. The findings indicate the patterns of engagement of older adults with complex chronic diseases with digital home-based self-management systems.
Original languageEnglish
Pages (from-to)1-15
Number of pages15
JournalDigital Health
Volume8
Early online date22 Sep 2022
DOIs
Publication statusPublished online - 22 Sep 2022

Keywords

  • Digital health
  • self management
  • data analysis
  • user log analysis

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