Care workers in residential care settings for older adults often experience job burnout, resulting in a high turnover rate. Previous studies offered contradictory findings on technology use in the workplace and its relationship with burnout. This study aimed to explore the moderator role technology acceptance plays in the relationship between burnout and intention to leave among care workers in residential care settings in Hong Kong. The study was based on a multicenter, cross-sectional questionnaire survey. The acceptance of general, and three specific, technologies (i.e., tablets, social robots and video gaming) was measured based on the scale of the Technology Acceptance Model. Two dimensions of burnout (exhaustion and disengagement) were measured using the Oldenburg Burnout Inventory scale. Intention to leave was measured using a self-reported item. Data collection took place from July to December 2018. We analysed data from 370 care workers from seven non-private residential care homes for older people in Hong Kong. A hierarchical multiple regression approach was used for moderator analysis. The results revealed that two measures of burnout (exhaustion and disengagement) were significantly and positively associated with intention to leave. The four measures of technology acceptance were negatively associated with intention to leave. The interaction of video-gaming acceptance and exhaustion was predictive of intention to leave (standardized beta = -0.20, p = .011). Acceptance of video gaming changed the strength of the relationship between exhaustion and intention to leave among participants. No significant moderating effects were observed in the relationship between disengagement and intention to leave. We highlight the importance of integrating technology variables, especially subjective appraisal of technology, in the issues of burnout and intention to leave. These findings shed new light on policies and practices that consider implement technology in routine care in residential care settings without unanticipated negative impacts for care staff.
Keywords: disengagement; exhaustion; health technologies; healthcare professional; long-term care setting; moderator analysis; questionnaire survey.
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