Predictors for E-Government Adoption of SANAD App Services Integrating UTAUT, TPB, TAM, Trust, and Perceived Risk

Area of Science:

• Public Health
• E-Government Technology
• Health Informatics

Background:

• The COVID-19 pandemic highlighted the need for innovative health protection tools.
• Mobile applications in e-government present a novel approach to public health.
• The SANAD App was developed as a health protection tool within this context.

Purpose of the Study:

• To examine factors influencing the adoption and use of the SANAD App for health protection.
• To identify antecedents of user attitude and behavioral intention towards the SANAD App.
• To test a model integrating established theories like UTAUT, TAM, and PBT.

Main Methods:

• Survey data collected from 442 SANAD App users in Jordan.
• Empirical validation using confirmatory factor analysis and structural equation modeling (SEM).
• Application of machine learning (ML) methods including Artificial Neural Networks (ANN), SMO, RepTree, and Random Forest.

Main Results:

• Performance expectancy, effort expectancy, social influence, facilitating conditions, trust, and perceived service quality significantly predicted attitude towards using the SANAD App.
• Demographic factors (age, gender, education) and internet experience moderated the relationship between antecedents and behavioral intention.
• Perceived risk was found not to significantly affect attitude towards the SANAD App.

Conclusions:

• The study provides empirical evidence on the determinants of SANAD App usage for public health.
• Findings contribute to understanding the role of e-government mobile applications in health protection.
• The integrated model offers insights for developing and promoting similar health-focused digital tools.