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


Journal

Neuroepidemiology
ISSN: 1423-0208
Titre abrégé: Neuroepidemiology
Pays: Switzerland
ID NLM: 8218700

Informations de publication

Date de publication:
2021
Historique:
received: 06 02 2021
accepted: 03 08 2021
pubmed: 19 9 2021
medline: 23 3 2022
entrez: 18 9 2021
Statut: ppublish

Résumé

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.

Sections du résumé

BACKGROUND
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.
OBJECTIVE
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.
METHODS
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.
CONCLUSION
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.
TRIAL REGISTRATION
ClinicalTrials.gov Identifier NCT04529681.

Identifiants

pubmed: 34535608
pii: 000518853
doi: 10.1159/000518853
doi:

Banques de données

ClinicalTrials.gov
['NCT04529681']

Types de publication

Clinical Trial Protocol Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

436-446

Informations de copyright

© 2021 S. Karger AG, Basel.

Auteurs

Zarudin Mat Said (Z)

Department of Community Medicine, School of Medical Sciences, Health Campus, Universiti Sains Malaysia, Health Campus, Kubang Kerian, Malaysia, zarudinmatsaid@yahoo.com.

Kamarul Imran Musa (KI)

Department of Community Medicine, School of Medical Sciences, Health Campus, Universiti Sains Malaysia, Health Campus, Kubang Kerian, Malaysia.

Tengku Alina Tengku Ismail (TA)

Department of Community Medicine, School of Medical Sciences, Health Campus, Universiti Sains Malaysia, Health Campus, Kubang Kerian, Malaysia.

Anees Abdul Hamid (A)

Primary Care Unit, Kelantan State Health Department, Kota Bharu, Malaysia.

Ramesh Sahathevan (R)

Department of Medicine and Neurology, Ballarat Health Services, Ballarat, Victoria, Australia.

Zariah Abdul Aziz (Z)

Department of Medicine, Hospital Sultanah Nur Zahirah, Kuala Terengganu, Malaysia.

Valery Feigin (V)

National Institute for Stroke and Applied Neurosciences, Auckland University of Technology (AUT), Auckland City, New Zealand.

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Classifications MeSH