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Effectiveness of Technology in the Implementation of Early Stroke Detection Applications: Integration into the Management of High-Risk Patient Care
Public Health of Indonesia · Vol. 12 No. 2 (2026) · hlm. 81–86
ISSN 2477-1570, 2528-1542
Terbit 2026-06-18
Penerbit YCAB Publisher
Bahasa eng
Abstrak
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.
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Sekolah Tinggi Ilmu Kesehatan Karya Kesehatan Hasanuddin University Universitas Muhammadiyah Semarang Afiliasi tidak diketahui
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Sumber metadata: OAI-PMH (metadata jurnal) http://stikbar.org/ycabpublisher/index.php/PHI/oai, pertama di-harvest 10 Nov 2026, terakhir terlihat 10 Nov 2026.
Metadata asli (oai_dc)
<oai_dc:dc xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
<dc:title xml:lang="en-US">Effectiveness of Technology in the Implementation of Early Stroke Detection Applications: Integration into the Management of High-Risk Patient Care</dc:title>
<dc:creator>Triwijayanti, Renny</dc:creator>
<dc:creator>Rahmania, Annisa</dc:creator>
<dc:creator>Romiko, Romiko</dc:creator>
<dc:creator> Indriastuti, Diah</dc:creator>
<dc:creator>Lonardo, Paray Theo </dc:creator>
<dc:subject xml:lang="en-US">Community Health Cadres</dc:subject>
<dc:subject xml:lang="en-US">Early Detection</dc:subject>
<dc:subject xml:lang="en-US">Mobile Health</dc:subject>
<dc:subject xml:lang="en-US">Prehospital Care</dc:subject>
<dc:description xml:lang="en-US">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.</dc:description>
<dc:publisher xml:lang="en-US">YCAB Publisher</dc:publisher>
<dc:date>2026-06-18</dc:date>
<dc:type>info:eu-repo/semantics/article</dc:type>
<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
<dc:type xml:lang="en-US">Peer-reviewed Article</dc:type>
<dc:format>application/pdf</dc:format>
<dc:identifier>https://stikbar.org/ycabpublisher/index.php/PHI/article/view/1621</dc:identifier>
<dc:identifier>10.36685/phi.v12i2.1621</dc:identifier>
<dc:source xml:lang="en-US">Public Health of Indonesia; Vol. 12 No. 2 (2026): April - June; 81 - 86</dc:source>
<dc:source>2477-1570</dc:source>
<dc:source>2528-1542</dc:source>
<dc:source>10.36685/phi.v12i2</dc:source>
<dc:language>eng</dc:language>
<dc:relation>https://stikbar.org/ycabpublisher/index.php/PHI/article/view/1621/794</dc:relation>
<dc:rights xml:lang="en-US">Copyright (c) 2026 Renny Triwijayanti, Annisa Rahmania, Diah Indriastuti</dc:rights>
<dc:rights xml:lang="en-US">https://creativecommons.org/licenses/by-nc/4.0</dc:rights>
</oai_dc:dc>
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APA 7
Triwijayanti, R., Rahmania, A., Romiko, R., Indriastuti, D., & Lonardo, P. T. (2026). Effectiveness of Technology in the Implementation of Early Stroke Detection Applications: Integration into the Management of High-Risk Patient Care. Public Health of Indonesia, 12(2), 81–86. https://doi.org/10.36685/phi.v12i2.1621
Salin
IEEE
R. Triwijayanti, A. Rahmania, R. Romiko, D. Indriastuti, and P. T. Lonardo, “Effectiveness of Technology in the Implementation of Early Stroke Detection Applications: Integration into the Management of High-Risk Patient Care,” Public Health of Indonesia, vol. 12, no. 2, pp. 81–86, 2026, doi: 10.36685/phi.v12i2.1621.
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