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Stroke Riskometer™ Mobile Phone Application Improves Stroke Knowledge in a Randomised Controlled Trial

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Authors

Wake, Addisu Dabi

Krishnamurthi, Rita

Fraser, Brooklyn J

Chappell, Katherine

Feigin, Valery L

Thrift, Amanda G

Kleinig, Timothy

Cadilhac, Dominique

Bennett, Derrick

Nelson, Mark R

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SAGE Publications

Abstract

BACKGROUND: Increasing knowledge about stroke may reduce its burden. We examined the effect of the Stroke Riskometer™ mobile phone application (the App) on stroke knowledge in a randomised controlled trial (RCT). METHODS: This was pre-specified secondary outcome analysis in a phase III, prospective, participant and outcome assessor-blinded, 2-arm RCT in Australia and New Zealand. Participants were recruited between 2021 and 2023, aged 35-75 years, with ≥2 stroke risk factors and no cardiovascular disease history. Participants were randomised after assessment of stroke risk factors and knowledge to the intervention group (IG- received risk factor assessment by e-mail and links to the App), and the usual care group (UCG - received risk factor assessment with links to generic information by e-mail). Stroke knowledge was measured at baseline, 3, 6, and 12 months using six validated questions (total score 0 [low knowledge] to 19 [high knowledge]). We used linear and logistic mixed effects modelling to assess differences in the level of overall stroke knowledge and domains (description, warning signs, risk factors, management) between IG and UCG at each time point. Effect modification of the intervention with age, sex, level of education, ethnicity, socioeconomic status (SES), and country was assessed. RESULTS: There were 862 participants (mean age 58.1 years [SD 10.8], 63.0% female, 61.6% tertiary educated, 73.3% European, and 14.7% most disadvantaged area-level SES) randomised to IG (n=429) and UCG (n=433). Dropouts (IG/UCG) were: 7.9%/4.8% at 3 months, 3.0%/1.8% at 6 months, and 13.5%/9.0% at 12 months. The time-IG interaction showed a statistically significantly increased overall stroke knowledge (β 0.50 95% CI 0.02, 0.97) compared to UCG at 6 months only. The intervention effect was stronger in tertiary educated, non-European and non-Indigenous ethnic groups, and least disadvantaged SES group. For domains, IG were more likely to correctly identify stroke risk factors (OR 1.92, 95% CI 1.09, 3.39) at 3 months, compared to UCG. CONCLUSIONS: The Stroke Riskometer™ App modestly improved stroke knowledge compared to UCG at 6 months but lacks evidence for retaining knowledge at 12 months. As knowledge can drive behaviour change, the App may be a tool to enhance primary stroke prevention.

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Clinical trial, Epidemiology, Intervention, Prevention, Risk factors, Stroke, Health knowledge, Stroke RiskometerTM app, mobile applications, primary prevention, 4202 Epidemiology, 4203 Health Services and Systems, 4206 Public Health, 42 Health Sciences, Aging, Prevention, Brain Disorders, Cerebrovascular, Clinical Trials and Supportive Activities, Clinical Research, 1103 Clinical Sciences, 1109 Neurosciences, Neurology & Neurosurgery, 3202 Clinical sciences, 3209 Neurosciences, 4201 Allied health and rehabilitation science

Source

International Journal of Stroke, ISSN: 1747-4930 (Print); 1747-4949 (Online), SAGE Publications, 17474930261449736-. doi: 10.1177/17474930261449736

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Creative Commons Attribution-NonCommercial 4.0
© 2026 World Stroke Organization.

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Except where otherwise noted, this item's license is described as Creative Commons Attribution-NonCommercial 4.0