Department of Community Medicine, School of Medical Sciences, Health Campus, Universiti Sains Malaysia, Health Campus, Kubang Kerian, Malaysia,
Department of Community Medicine, School of Medical Sciences, Health Campus, Universiti Sains Malaysia, Health Campus, Kubang Kerian, Malaysia.
Neuroepidemiology. 2021;55(6):436-446. doi: 10.1159/000518853. Epub 2021 Sep 15.
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.
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.
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 t 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.
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.
ClinicalTrials.gov Identifier NCT04529681.
中风被认为是全球第二大致死和致残原因。中风负担不断增加，有力地证明了目前使用的初级预防策略效果不够显著。Stroke Riskometer™应用程序（app）代表了一种全新的中风预防策略，与传统的高心血管疾病风险方法明显不同。
本研究旨在评估 Stroke Riskometer™ app 提高马来西亚成年人群对中风的认识和中风风险概率的效果。
将在马来西亚吉兰丹州实施一项非盲、平行组、集群随机对照试验，采用 1:1 分配比。将招募两组，每组样本量为 66 人。干预组将配备 Stroke Riskometer™ app 和信息传单，而对照组将提供标准管理，包括仅信息传单。Stroke Riskometer™ app 根据慢性病自我管理模型开发，基于自我调节和社会认知理论。将在基线和第 3 周、第 6 周和第 6 个月的随访时通过电话访谈或在线问卷调查收集数据。主要结局测量指标是中风风险意识，包括知识、感知和改变意图领域。次要结局测量指标是调整每个参与者社会人口统计学和/或社会经济地位后的 5 年和 10 年内的中风风险概率。将采用意向治疗方法评估这些指标。将使用 Pearson's χ2 或独立 t 检验来检查干预组和对照组之间的差异。将使用广义估计方程和线性混合效应模型来测试干预的总体效果。
本研究将评估 Stroke Riskometer™ app 对中风意识和中风概率的影响，并简要评估参与者对预先指定的试验方案的参与度。这些结果将为医生和公共卫生专业人员提供移动技术干预的益处，并鼓励更多积极的基于手机的疾病预防应用。
ClinicalTrials.gov 标识符 NCT04529681。
