Understanding Adolescent Engagement With The E-Cohort Digital Application: A Technology-To-Performance Chain Perspective

Vollständiger Abstract

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Adolescent anemia remains a significant global health concern, highlighting the need for innovative approaches to improve adolescent health monitoring and service delivery. The Adolescent Health and Nutrition (E-Cohort) application was developed to support adolescent health services, but its utilization and effectiveness have not been comprehensively evaluated. This study aimed to assess the impact of the Adolescent Health and Nutrition (E-Cohort) application using the Technology-to-Performance Chain (TPC) framework. A quantitative cross-sectional survey was conducted among 450 adolescent users of the E-Cohort application attending Posyandu Remaja in Sidoarjo Regency, Indonesia. Data were collected using a structured questionnaire, and the hypothesized relationships among Task–Technology Fit (TTF), Attitude Toward the System (ATT), System Usability (SUS), and Utilization of the System (UTS) were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The study examined task–technology fit, precursor utilization, utilization, actual use, and performance outcomes. Structural Equation Modeling (SEM) was employed to analyze the relationships among these variables and to determine how the application contributes to improved adolescent health services and outcomes. The key constructs analyzed were Task–Technology Fit (TTF), System Usability Scale (SUS), Actual Utilization (UTS), and Performance Outcomes. Outer model analysis assessed indicator reliability and construct validity. Several indicators were removed due to low reliability, resulting in improved model fit and measurement accuracy. Most respondents were female (54.7%) and aged 15–19 years (61.8%). The structural model showed positive associations of ATT with UTS (β = 0.205, t = 4.661, p < 0.001) and SUS with UTS (β = 0.434, t = 9.889, p < 0.001), with SUS showing a stronger association. The model explained 31.1% of the variance in UTS (R² = 0.311). Improving system usability and incorporating additional explanatory factors may enhance technology utilization and strengthen the application’s contribution to adolescent health services.