Background: Our novel, multicomponent care assistant and support program (CAPS) for stroke or TIA was co-designed with consumers, clinicians, and scientists to improve secondary stroke prevention. The CAPS program is delivered entirely virtually over 12 weeks. It comprises of clinician-facilitated goal setting, health behaviours/risk factor monitoring through a mobile application (app) and a wearable device, and SMS messages to support the achievement of goals.
Aim: To determine the reach, adoption, and usability of CAPS as a secondary prevention program for people with stroke or TIA.
Methods: An open-label, non-randomised feasibility study which applied a single group, pretest-posttest mixed methods design. We sought to recruit ~40 participants via the Australian Stroke Clinical Registry from Victoria, Queensland, South Australia, and Tasmania. Eligibility: stroke or TIA 6 months to 3 years ago, ≥18 years, access to a mobile phone with internet, and living in a private residence. At baseline, participants set 1-2 secondary prevention goals, provided a wearable device to monitor risk factors, and trained to use the app. Feasibility outcomes included study recruitment, retention, and technology usage.
Results: Following mailed invitations, 58/600 (10%) agreed to participate, 22 were ineligible. Of the 36 eligible participants, 2 withdrew following baseline assessment. Subsequently, 34/36 (94%) participants commenced the program (median age 70 years, 27% female, 64% stroke). As of May 5th, 32 had completed the study, 1 withdrew. Preferred secondary prevention goals included increasing exercise (40%) and losing weight (23%). Wearable devices were provided to 26 participants (20 Fitbit, 6 Apple Watch); 11 requested to keep these. In the app, participants entered 4,775 health measurements (average of 132 per participant), recorded 874 text notes, and set 72 medication reminders.
Conclusions: The CAPS digital secondary prevention program was feasible, demonstrating good retention and engagement from participants. Findings will inform the design of an effectiveness trial.