Determinants Influencing the Adoption of Internet Health Care Technology Among Chinese Health Care Professionals: Extension of the Value-Based Adoption Model With Burnout Theory

Abstract

Background The global COVID-19 pandemic has been widely regarded as a catalyst for adopting internet health care technology (IHT) in China. IHT consists of new health care technologies that are shaping health services and medical consultations. Health care professionals play a substantial role in the adoption of any IHT, but the consequences of doing so can often be challenging, particularly when employee burnout is prevalent. Few studies have explored whether employee burnout influences the adoption intention of IHT in health care professionals. Objective This study aims to explain the determinants influencing the adoption of IHT from the perspective of health care professionals. To do so, the study extends the value-based adoption model (VAM) with consideration for employee burnout as a determining factor. Methods A cross-sectional web-based survey using a sample of 12,031 health care professionals selected through multistage cluster sampling from 3 provinces in mainland China was conducted. The hypotheses of our research model were developed based on the VAM and employee burnout theory. Structural equation modeling was then used to test the research hypotheses. Results The results indicate that perceived usefulness, perceived enjoyment, and perceived complexity positively correlate with perceived value (β=.131, P=.01; β=.638, P<.001; β=.198, P<.001, respectively). Perceived value had a positive direct effect on adoption intention (β=.725, P<.001), perceived risk negatively correlated with perceived value (β=−.083, P<.001), and perceived value negatively correlated with employee burnout (β=−.308, P<.001). In addition, employee burnout was negatively related to adoption intention (β=−.170, P<.001) and mediated the relationship between perceived value and adoption intention (β=.052, P<.001). Conclusions Perceived value, perceived enjoyment, and employee burnout were the most important determinants of IHT adoption intention by health care professionals. In addition, while employee burnout was negatively related to adoption intention, perceived value inhibited employee burnout. Therefore, this study finds that it is necessary to develop strategies to improve the perceived value and reduce employee burnout, which will benefit the promotion of the adoption intention of IHT in health care professionals. This study supports the use of the VAM and employee burnout in explaining health care professionals’ adoption intention regarding IHT.

Translating a value-based framework for resilient e-learning impact in post COVID-19 times: Research-based Evidence from Higher Education in Kuwait

“…Developed by Kim, Chan, and Gupta [ 18 ], the VAM model was specifically designed to understand the value associated with adopting e-commerce. It aims to examine individuals' usage intentions towards technology and the factors influencing their decision to utilize mobile services [ 19 ]. With the VAM model, the assumption is that an individual is focusing on maximizing the value of usage.…”

Research on the Experience of Influencing Elements and the Strategy Model of Children’s Outpatient Medical Services under the Guidance of Design Thinking

“…In addition, there are some issues in the service quality of pediatric outpatient clinics in Shanghai [62][63][64], for example, doctor-patient communication problems [65][66][67][68]. At the same time, the medical equipment in some hospitals is outdated and inconvenient to operate, which also brings certain difficulties to doctors' diagnosis and treatment work [69][70][71].…”

“…In addition, there are some issues in the service quality of pediatric outpatient clinics in Shanghai [62][63][64], for example, doctor-patient communication problems [65][66][67][68]. At the same time, the medical equipment in some hospitals is outdated and inconvenient to operate, which also brings certain difficulties to doctors' diagnosis and treatment work [69][70][71]. Distribution of hospitals at all levels and types providing pediatric services in Shanghai in 2020 (according to reference [52]; this figure was created by the authors of the present study).…”