Effectiveness of Technology in the Implementation of Early Stroke Detection Applications: Integration into the Management of High-Risk Patient Care - Renny Triwijayanti; Annisa Rahmania; Romiko Romiko; Diah Indriastuti; Paray Theo Lonardo (Public Health of Indonesia, 2026)
Background: Early recognition of stroke symptoms is essential to reduce prehospital delay and improve patient outcomes. However, limited community awareness of stroke warning signs remains a challenge in many primary healthcare settings. Objective: This study aimed to evaluate the association between the D-Stroke mobile application and improvements in knowledge of early stroke detection among community health cadres in a primary healthcare setting. Methods: A quasi-experimental one-group pretest–posttest design was conducted at the Nagaswidak Public Health Center in Palembang. Twenty-eight community health cadres were recruited using a total sampling approach. Participants completed a 10-item knowledge questionnaire before and after one week of application use. Data were analyzed using the Wilcoxon signed-rank test due to non-normal distribution. Effect size (r) was calculated to determine the magnitude of change. Results: The median knowledge score increased from 15.00 (pretest) to 34.00 (posttest). The improvement was statistically significant (Z = −5.683, p = .001). The calculated effect size (r = .80) indicated a large magnitude of change. Conclusion: Use of the D-Stroke application was associated with significant improvement in knowledge of early stroke detection among community health cadres. Mobile-based educational tools may support stroke awareness and early referral capacity in primary healthcare settings; however, further controlled studies are needed to confirm behavioral and clinical impact.