Behavioral Intention to Use IoT Technology in Healthcare Settings

Rapid scaling of using the Internet of Things (IoT) technology has been seen recently in numerous applications in healthcare to deliver proper services. This was motivated by the declining size and cost of the employed IoT devices. Developing such technology has been well investigated in the literature; however, few studies have explored the factors influencing its adaptation in the healthcare setting. In this study, we investigate the core factors that influence the acceptance of using IoT for Healthcare Purposes in the Kingdom of Saudi Arabia (KSA). Accordingly, a theoretical framework, based on the Technology Acceptance Model (TAM), was developed and tested empirically. The modified model added variables that provide a better explanation of the acceptance of healthcare technology. To ground our conceptual idea, a survey was designed and performed on 407 patients (207 males, 200 females). The Partial Least Square Structural Equation Modeling (SEM) technique was applied to analyze the effect of eight hypothesized predicting constructs on the collected data. Results revealed that cost, privacy concerns, and perceived usefulness were the most significant predictors of behavioral intention to use. However, attitude and perceived connectedness were found to be irrelevant in predicting the intention to use IoT. Ultimately, results found that there is no correlation between gender and behavioral intention.