JMIR Publications

ABSTRACT

Background:

Demographic changes and epidemiological trends require adjustments in health and long-term care sectors, including the integration of innovative digital technologies. The digital Remote Care Assist smartphone app enabled home health care workers to connect via video-streaming with care experts or supervisors. User acceptance is critical to realising the benefits of innovative technologies. While there is substantial research on user acceptance, there is hardly any research on how the interplay between own benefits and expected benefits for home care customers influences the care staff’s technology acceptance.

Objective:

This study aims to examine the predictors of user acceptance of the Remote Care Assist technology, with a particular focus on care staff’s perceptions of the technology’s expected benefits for home care service users.

Methods:

From September to October 2023, user acceptance data were collected from 139 care staff (45 care experts and 94 home care workers) in home care organisations in Austria and Luxembourg. The trial participants had access to the Remote Care Assist system for 5 months in Luxembourg to 6.5 months in Austria. Partial Least Squares Structural Equation Modelling was used to explore the latent constructs affecting their technology acceptance of Remote Care Assist.

Results:

The acceptance of the Remote Care Assist technology by home care staff was statistically significantly and positively associated with ‘Perceived Usefulness for Care Staff’ (β=0.314, CI [95%, 0.151, 0.460]), ‘Expected Benefit for Home Care Service Users’ (β=0.415, CI [95%, 0.276, 0.537]), and ‘Perceived Ease of Use’ (β=0.130, CI [95%, 0.038, 0.231]). Furthermore, ‘Expected Benefit for Home Care Service Users’ (β=0.130, CI [95%, 0.061, 0.194]) and ‘Perceived Ease of Use’ (β=0.053, CI [95%, 0.017, 0.101]) were mediated by ‘Perceived Usefulness for Care Staff’. Additionally, ‘Perceived Efficiency’ (β=0.396, CI [95%, 0.267, 0.531]) was statistically significantly and positively associated with the ‘Perceived Usefulness for Care Staff’, whereas ‘Reliable Functionality’ (β=-0.019, CI [95%, -0.098, 0.063]) was not.

Conclusions:

This study extends previous acceptance research, which has predominantly focused on human-technology interaction, by examining human-technology-human interactions within a long-term care service market context. By exploring the ‘Expected Benefit for Home Care Service Users’ from the intrinsic view of care staff, the findings suggest the ‘Expected Benefit for Home Care Service Users’ as a key predictor of care staff’s acceptance of telecare technologies. These findings may inform the development, implementation and roll-out of digital technologies to improve the adoption of telecare technologies in long-term care settings and, ideally, enhance quality of care. Clinical Trial: none