Empowering Indonesian Adolescents Through Digital Health Literacy: A Predictive Model for Breast Cancer Prevention Education Aligned with SDG 3

Indonesia faces unique challenges with breast cancer affecting younger populations, necessitating early health literacy interventions among adolescents to achieve SDG 3.4 targets. To develop a predictive model identifying determinants of breast cancer literacy among Indonesian adolescents. A cross-sectional study was conducted from March-June 2025 in West Sulawesi Province. The sample comprised 58 female adolescents (ages 14-17) from high schools (n=26, 44.8%) and vocational schools (n=32, 55.2%). Data collection utilized validated online surveys measuring ten breast cancer literacy indicators. Binary logistic regression with backward elimination was performed using SPSS 25.0. Overall, 56.9% (n=33) demonstrated inadequate literacy levels, with only 43.1% (n=25) achieving adequate levels. Critical knowledge deficits were found in prevention strategies (1.7% correct) and risk factor identification (37.3% correct), contrasting with high awareness of medical follow-up procedures (96.6% correct). The logistic regression model (Nagelkerke R²=0.618, Hosmer-Lemeshow p=0.512) identified four significant determinants: enrollment in high schools versus vocational schools (OR=4.3, 95% CI: 1.27-14.55, p=0.019), healthcare provider information sources (OR=7.3, 95% CI: 1.44-10.46, p=0.016), digital learning media utilization (OR=3.4, 95% CI: 1.13-10.46, p=0.031), and frequent health information-seeking behavior (OR=3.4, 95% CI: 1.01-11.66, p=0.048). This model enables targeted resource allocation for cancer prevention strategies supporting SDG 3.4, potentially reducing premature mortality through enhanced early detection behaviors among Indonesia's future generations.

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Publication Details

Journal
Journal of Scientific Insights
Published
2025-09-09
DOI
https://doi.org/10.69930/jsi.v2i5.508
Primary Topic
Public Health and Nutrition
Type
article
Field-Weighted Citation Impact
0.00

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article

Empowering Indonesian Adolescents Through Digital Health Literacy: A Predictive Model for Breast Cancer Prevention Education Aligned with SDG 3

Nurlina Subair, Irma Irma, Marlina Marlina, Andi Kamal M.Sallo
Journal of Scientific Insights
Public Health and Nutrition
article

Empowering Indonesian Adolescents Through Digital Health Literacy: A Predictive Model for Breast Cancer Prevention Education Aligned with SDG 3

Nurlina Subair, Irma Irma, Marlina Marlina, Andi Kamal M.Sallo
article en

Abstract

Indonesia faces unique challenges with breast cancer affecting younger populations, necessitating early health literacy interventions among adolescents to achieve SDG 3.4 targets. To develop a predictive model identifying determinants of breast cancer literacy among Indonesian adolescents. A cross-sectional study was conducted from March-June 2025 in West Sulawesi Province. The sample comprised 58 female adolescents (ages 14-17) from high schools (n=26, 44.8%) and vocational schools (n=32, 55.2%). Data collection utilized validated online surveys measuring ten breast cancer literacy indicators. Binary logistic regression with backward elimination was performed using SPSS 25.0. Overall, 56.9% (n=33) demonstrated inadequate literacy levels, with only 43.1% (n=25) achieving adequate levels. Critical knowledge deficits were found in prevention strategies (1.7% correct) and risk factor identification (37.3% correct), contrasting with high awareness of medical follow-up procedures (96.6% correct). The logistic regression model (Nagelkerke R²=0.618, Hosmer-Lemeshow p=0.512) identified four significant determinants: enrollment in high schools versus vocational schools (OR=4.3, 95% CI: 1.27-14.55, p=0.019), healthcare provider information sources (OR=7.3, 95% CI: 1.44-10.46, p=0.016), digital learning media utilization (OR=3.4, 95% CI: 1.13-10.46, p=0.031), and frequent health information-seeking behavior (OR=3.4, 95% CI: 1.01-11.66, p=0.048). This model enables targeted resource allocation for cancer prevention strategies supporting SDG 3.4, potentially reducing premature mortality through enhanced early detection behaviors among Indonesia's future generations.

Journal of Scientific InsightsVol. 2(5)
Muhammadiyah University of Makassar (ID), Universitas Persada Indonesia Yayasan Administrasi Indonesia (ID), Institut Teknologi dan Bisnis Kalbe (ID)
Ministrstvo za visoko šolstvo, znanost in tehnologijo, Direktorat Riset dan Pengabdian Masyarakat, Direcció General de Recerca, Generalitat de Catalunya
Openalex Percentile: Top 66%
Public Health and Nutrition
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