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Background: Reducing stroke risk behaviors is associated with reduced stroke incidence. The free Stroke Riskometer^TM mobile phone App (“App”) developed by AUT University (New Zealand) is a novel tool for primary stroke prevention. The App is being used in 78 countries and translated into 19 languages covering 70% of the world population (5.3 billion people).

Methods: The feasibility, acceptability and preliminary efficacy of the App for improving cardiovascular health (as measured by LS7 score) was tested in a pragmatic pilot, open-label, 2-arm prospective randomized controlled trial (RCT; n=50). Consented participants were randomly assigned to the intervention arm (App; n=26) or usual care (UC; n=24) using online minimization randomization. Usual care participants were not actively informed about the App.

Results: Recruitment was feasible with a recruitment rate of 70% (39% male; age range 20-81 years). Those randomized to the App group accessed the App up to 6 times over 6 months. In those who completed the 6-month follow-up, we observed an improvement of 0.36 points (95% CI -2.10 to 1.38) in the LS7 score for the App group since baseline vs. the UC. This positive trend in the LS7 score equates to about 4% stroke incidence reduction.

Conclusions: The Stroke Riskometer App is a feasible and proven motivational intervention for primary stroke prevention. Three large phase 3 RCTs (Australia, New Zealand, Brazil) are currently underway to determine effectiviness of the App in improving cardiovascular health and reducing stroke incidence.

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Stroke is one of the leading causes of death and disability worldwide. There is a decline in stroke incidence and death in high income countries (HICs) however in low to middle income countries there is an increase incidence of stroke. Ninety percent of the risk factors of stroke are preventable. Hypertension, diabetes, dyslipidemia, smoking, alcohol intake, atrial fibrillation, obesity are some of the imporatant risk factors for stroke. Prevention can be divided into primordial, primary and secondary. At the population level high risk individuals can be screened and interventions can be implemented. There is evidence in the use of mHealth, decision supporting system and task shifting to community health workers from LMICs in the prevention of stroke. Stroke riskometer and few other Mobile Apps can be used to identify people at risk of developing stroke. There is also evidence for the use of polypill and control of risk factors using health care workers in the villages to prevent cardiovascular diseases and stroke.