This study validates and extends the latest unified theory of acceptance and use of technology (UTAUT2) with the privacy calculus model. To evaluate the adoption of healthcare and e-government applications, researchers have recommended—in previous literature—the application of technology adoption models with privacy, trust, and security-related constructs. However, the current UTAUT2 model lacks privacy, trust, and security-related constructs. Therefore, the proposed UTAUT2 with the privacy calculus model is incorporated into four constructs: privacy concern, perceived risk, trust in the smart national identity card (SNIC), and perceived credibility. Results from a survey data of 720 respondents show that habit, effort expectancy, performance expectancy, social influence, hedonic motivation, and price value are direct determinants that influence behavioral intentions to use. Results also revealed that behavioral intentions, facilitating conditions, habits, perceived risks, and privacy concerns are direct predictors of ‘use behavior’. The authors also analyzed the interrelationships among the research constructs. The extended model may lead toward establishing better innovative e-health services to cover the desires of the citizens through the use of health information applications embedded in an all-in-one card.

This paper presents a new capsule-shaped sensor to detect the glucose concentration in the human body. The model under study was formulated by relying on the index change in the refractive index (RI) because of the change in the sample that infiltrated the cavity. The index of refraction change is accompanied by modifying the resonant wavelength. The recommended model has considered the simple shape and ease of manufacture, along with other characteristics such as sensitivity and a low detection limit. The results report a high sensitivity of S = 546.72 nm/RI unit (RIU), a high quality factor of Q = 2066.24, a low detection limit of DL = 1.44 × 10⁻⁴ RIU, and a high value of transmission of 97%, which are considered to be sufficient and efficient in detecting measured material. This proposed model provides many opportunities and is promising for the manufacture of different types of sensing detection devices.