A PREDICTION-ORIENTED ACCEPTANCE SCORE FOR SUSTAINED mHEALTH USE: INTEGRATING HOT – FIT AND TAM IN COMMUNITY-BASED DENGUE SURVEILLANCE
Year: 2026
Type: article
Study design: Observational Study
Abstract: Sustaining the use of mobile health (mHealth) applications is an important challenge in community-based dengue surveillance. However, the combined roles of human capabilities, technology quality, and organizational support in shaping continued use require further examination in this setting. This study evaluated mHealth acceptance among dengue larvae monitoring cadres by integrating the Human-Organization-Technology Fit (HOT-Fit) framework and the Technology Acceptance Model (TAM), and explored a preliminary Acceptance Score (AS) for prediction-oriented decision support. A cross-sectional study involving 60 dengue larvae monitoring cadres used a questionnaire comprising 18 indicators across six constructs. We analyzed the hypothesized relationships using partial least squares structural equation modeling (PLS-SEM) in SmartPLS4. Predictive performance was assessed using PLSpredict. The Pearson correlation and regression analyses were used to examine the relationship between the proposed AS and continuance intention using SPSS 25. Human literacy (β = 0.32), technology quality (β = 0.35), and organizational support (β = 0.44) were positively associated with perceived usefulness. Perceived usefulness was positively associated with user satisfaction (β = 0.62) and continuance intention (β = 0.57); all reported paths were statistically significant (p < 0.001). The model explained 62% of the variance in perceived usefulness, 58% in user satisfaction, and 52% in continuance intention. The AS was positively correlated with continuance intention (r = 0.488, p < 0.001). Integrating HOT-Fit and TAM offers a framework for examining continued mHealth use in community-based dengue surveillance. The preliminary AS may inform future implementation support, but independent validation is required before operational use.
Language: English
Subfield: Information Systems and Management
Field: Decision Sciences
Domain: Social Sciences
Open Access status: diamond
OpenAlex ID: W7225296751