Physicians' perceptions of how digital-intelligent medical technology reshapes job characteristics: a qualitative study.

backgroundDigital-intelligent medical technology, centered on big data and artificial intelligence (AI), is rapidly permeating the entire Chinese healthcare process. However, the dual impact mechanism of this technology on physicians’ job resources and job demands remains unclear. Based on the Job Demands–Resources (JD-R) model, this study examines how digital-intelligent medical technologies simultaneously influence physicians’ job characteristics as both job resources and job demands from the perspective of physicians’ psychological perceptions. It provides recommendations for leveraging these technologies to advance healthcare development.

methodsThis study employed a qualitative design. Between October 2024 and June 2025, we conducted semi-structured interviews with 32 clinicians recruited through purposive and snowball sampling in Guangdong Province, China. Participants included physicians with varying levels of clinical experience, including those currently working in medical-related positions at different-tier hospitals and academic institution. The interview guide was designed based on the JD-R model, and participants were asked about their perceived current state of digital-intelligent medical technology applications, the job resources and job demands it introduces to physicians, as well as future recommendations for its implementation. For physicians with prior experience in using such technologies, the interviews further explored the specific application scenarios and conditions of their usage. Data were analyzed using thematic analysis, proceeding through open, axial, and selective coding.

resultsParticipants were from neurosurgery, orthopedics, pediatrics, and other departments, with 19 males and 13 females. Their ages ranged from 24 to 54 years, and duration in profession spanned 2 to 28 years. A total of 25 individuals [78.1%] had used digital and intelligent medical technologies, which covered nearly the entire clinical diagnostic and treatment process, including AI-assisted medical record generation, intelligent decision support, intelligent treatment assistance, and AI-enabled follow-up. The study revealed the following findings: (1) Digital and intelligent medical technologies enhance physicians’ job resources through technological integration (efficiency resources, decision support systems, and knowledge expansion), improving diagnostic and therapeutic efficiency and decision accuracy. (2) Challenges such as technical dependency, operational complexity, and ethical responsibility arising from digital-intelligent medical technologies impose new job demands on physicians, exacerbating burnout and skill degradation risks. (3) Individual experience differences, types of disease treated, application scenarios of digital-intelligent medical technologies, and resource allocation influence physicians’ job characteristics. System optimization, technical training, and institutional safeguards can mitigate negative impacts by dynamically allocating technical resources and strengthening human-machine collaboration.

conclusionThis study proposes a triple mechanism of resources-demands-support, emphasizing that the impact of digital and intelligent medical technologies on physicians’ job characteristics depends on the interaction between technological attributes and organizational support. It is recommended that hospitals and policymakers advance scenario-specific system optimization, trust-based training, and liability insurance. Furthermore, to bridge the resource disparities, regional data sharing should be promoted to maximize technological empowerment while minimizing occupational risks.