The Effectiveness of Stroke Riskometer™ in Improving Stroke Risk Awareness in Malaysia: A Study Protocol of a Cluster-Randomized Controlled Trial

Abstract

<b><i>Background:</i></b> Stroke is considered the second leading cause of mortality and disability worldwide. The increasing burden of stroke is strong evidence that currently used primary prevention strategies are not sufficiently effective. The Stroke Riskometer^™ application (app) represents a new stroke prevention strategy distinctly different from the conventional high-cardiovascular disease risk approach. <b><i>Objective:</i></b> This proposed study aims to evaluate the effectiveness of the Stroke Riskometer^™ app in improving stroke awareness and stroke risk probability amongst the adult population in Malaysia. <b><i>Methods:</i></b> A non-blinded, parallel-group cluster-randomized controlled trial with a 1:1 allocation ratio will be implemented in Kelantan, Malaysia. Two groups with a sample size of 66 in each group will be recruited. The intervention group will be equipped with the Stroke Riskometer^™ app and informational leaflets, while the control group will be provided with standard management, including information leaflets only. The Stroke Riskometer^™ app was developed according to the self-management model of chronic diseases based on self-regulation and social cognitive theories. Data collection will be conducted at baseline and on the third week, sixth week, and sixth month follow-up via telephone interview or online questionnaire survey. The primary outcome measure is stroke risk awareness, including the domains of knowledge, perception, and intention to change. The secondary outcome measure is stroke risk probability within 5 and 10 years adjusted to each participant’s socio-demographic and/or socio-economic status. An intention-to-treat approach will be used to evaluate these measures. Pearson’s χ² or independent <i>t</i> test will be used to examine differences between the intervention and control groups. The generalized estimating equation and the linear mixed-effects model will be employed to test the overall effectiveness of the intervention. <b><i>Conclusion:</i></b> This study will evaluate the effect of Stroke Riskometer^™ app on stroke awareness and stroke probability and briefly evaluate participant engagement to a pre-specified trial protocol. The findings from this will inform physicians and public health professionals of the benefit of mobile technology intervention and encourage more active mobile phone-based disease prevention apps. <b><i>Trial Registration:</i></b> ClinicalTrials.gov Identifier NCT04529681.