Research on the Influencing Factors of Inpatients’ Behavioral Intention to “Internet + Nursing Service” based on Unified Theory of Acceptance and Use of Technology (Preprint)

BACKGROUND With the increase of China’s aging population and the popularization of internet communication technology, extended nursing services show great potential. However, “Internet + Nursing services” is a relatively new technology in China, and the adoption rate of “Internet + Nursing services” applications by patients is low, and the factors influencing patients’ willingness to use them are unclear. Therefore, it’s necessary to understand patients’ behavioral intentions so as to support the development and widespread use of the “Internet + Nursing services” application. OBJECTIVE To identify key factors in inpatient behavioral willingness to use “Internet + Nursing services” based on the Unified Theory of Acceptance and Use of Technology (UTAUT) model. METHODS We established a hypothetical model based on UTAUT, constructed a structured questionnaire, and adopted convenience sampling method to conduct a cross-sectional study of inpatients in public hospitals in Yichang City from May 2023 to June 2023. We used SPSSS 24 and SPSS Amos 24.0 software for data analysis and model test, and Structural Equation Model (SEM) to estimate the significance of path coefficients to understand the influencing factors better. RESULTS A total of 1348 inpatients were investigated in this study, and 944 valid questionnaires were collected. The fitness indices suggested that the collected data fit well with the research model. The Cronbachα value and KMO value of the questionnaire were 0.944 and 0.953, indicating good reliability and validity of the questionnaire. The model explained 66.8% of the variance in performance expectancy and 59.3% of the variance in behavioral intention. Performance expectancy(β =0.160, P=0.003),social influence(β =0.692, P＜0.001),effort expectation(β =0.152, P＜0.001) have a direct effect on behavioral intention.Facilitating conditions and perceived risk have no direct effect on behavioral intention. Besides, social influence, effort expectation and facilitating conditions mediated by performance expectancy have indirect influence on behavioral intention. CONCLUSIONS This study identified the factors affecting the behavioral intention of inpatients to use “Internet + Nursing services”. Social influence is the most important determinant factor of the use of “Internet + Nursing services”, and facilitating conditions is the most important determinant of performance expectancy. Guidance and publicity should be strengthened at the national or social level, while the practicability and convenience of the application should be improved to help patients to accept and promote the application of “Internet + Nursing services”.