Well-Being and Cognitive Factors Influencing Health Care Workers' Adherence to Internet-Based Stress Management: Mixed Methods Analysis of a Nonrandomized Controlled Study.

Background: High stress levels are common among health care workers (HCWs), threatening their health and workforce stability. Internet-based mobile stress management (MSM) is a promising intervention for reducing work-related stress; however, poor adherence limits effectiveness. Exploring factors influencing HCWs' adherence may thus aid in developing optimal interventions. Objective: The research aimed to investigate (1) how HCWs' well-being and cognitive factors influenced MSM treatment adherence and (2) what HCWs' specific needs for MSM were. Methods: This study was a convergent mixed methods secondary analysis of a nonrandomized controlled trial. HCWs who were currently employed, had internet access, had no serious medical problems, and were willing to participate were recruited by convenience sampling through an MSM project in a large Chinese general hospital from August 11, 2021, to January 31, 2022. Those intending to leave the hospital or with insufficient medical condition for follow-up were excluded. Quantitative data were collected from 157 HCWs (n=135, 86% female participants; mean age of 33.7, SD 4.9 y) electronically via Research Electronic Data Capture (REDCap). Measures included sociodemographic characteristics, the Fatigue Assessment Scale, the 14-item Perceived Stress Scale, a user experience questionnaire, an attitudes scale (perceived usefulness, feasibility, and enjoyment), and self-reported practice frequency. Qualitative data were collected via an open-ended question answered by 96 participants. Quantitative data were analyzed using hierarchical regression and structural equation modeling. Qualitative data were analyzed using reflexive-thematic analysis in NVivo (QSR International). Results: In the quantitative study (n=157), hierarchical regression analyses showed that fatigue was a significant negative predictor of adherence (b=-0.050, 95% CI -0.086 to -0.015; t149=-2.859; 2-tailed P=.005), while user experience (b=0.074, 95% CI 0.042-0.106; t148=4.569; 2-tailed P<.001) and attitudes (b=0.238, 95% CI 0.140-0.336; t147=4.863; 2-tailed P<.001) were positive predictors. Results from the structural equation model demonstrated a significant indirect effect of user experience on adherence through attitudes (indirect effect=0.047, 95% CI 0.021-0.083; P<.001), but no significant direct effect. Separately, qualitative data of responses (n=96) identified four themes about the experience, namely, (1) individualized intervention, (2) effective feedback, (3) reward and constraint mechanisms, and (4) duration of intervention. Conclusions: This mixed methods study innovatively integrates quantitative and qualitative needs assessment to elucidate the adherence pathway in digital stress management for HCWs. It differentiates itself from prior research by moving beyond merely describing adherence barriers by quantifying the mediating role of attitudes between user experience and treatment adherence. The study indicates that despite fatigue barriers, improving user experience enhances positive attitudes toward MSM, which is vital for ensuring treatment adherence. This contributes to the field by elucidating a key psychological pathway for engagement. For real-world implications, to optimize user experience, future studies should consider focusing on individualized needs, providing effective feedback, developing reward and constraint mechanisms, and designing flexible intervention durations.