Year: 2025
Type: article
Study design: Observational Study
Abstract: BACKGROUND: Mobile devices enable doctors to make informed decisions that provide quality healthcare outcomes. With Bring Your Own Device (BYOD), privacy and security are considered primary concerns to doctors since they handle sensitive and highly confidential data. OBJECTIVE: The study aims to identify the determinant factors that affect the adoption of BYOD among Pakistani doctors. METHODS: A theoretical study was conducted to identify the determinant factors, and then a hybrid model based on the identified factors was proposed. The hybrid model was developed by integrating the UTAUT model and PMT. Performance expectancy, effort expectancy, social influence and facilitating conditions from the UTAUT model were incorporated with perceived vulnerability, perceived severity, response cost and self-efficacy factors from PMT. Data collection was performed based on snowball sampling and was realised through an online survey instrument on Facebook. A total of 245 licensed doctors from Pakistan participated in the survey. RESULTS: The survey data were analysed using Structural Equation Modelling (SEM). The findings indicate that the hybrid model is an acceptable fit model as it explains 87 percent of the variance in behavioural intention. The results show that the UTAUT's performance expectancy, effort expectancy, facilitating conditions, and PMT's self-efficacy positively affected doctors' BYOD adoption, while PMT's perceived vulnerability and perceived severity had a negative impact. CONCLUSIONS: Theoretically, this study contributes to enhance the BYOD adoption model for the medical domain. The findings of this study also serve as a basis for hospital management to formulate and implement policies regarding data protection and security measures.
Source: BMC Health Services Research
Authors: Saima Nisar, Wan Rozaini Bt Sheik Osman, Alawiyah Bt Abd Wahab, Muhammad Shahzad Aslam
Institutions: Xiamen University Malaysia, Universiti Utara Malaysia
Language: English
Subfield: Information Systems and Management
Field: Decision Sciences
Domain: Social Sciences
Open Access status: gold
Estimated APC paid: $3,290
OpenAlex ID: W4415137016