Models for the acceptance of tele-care solutions: Intention vs behaviour

Abstract

Purpose Tele-care is expected to replace regular home care when an integrated set of health monitoring devices and a communication network enables nursing staff to provide remotely appropriate care. While cost considerations and scarcity of nursing staff are strong motivators for tele-care, the actual effectiveness and acceptance of tele-care systems still falls short of expectations with an attrition rate often higher than 50%. As standard models of technology acceptance are poor predictors of actual adoption of tele-care systems we argue that the theoretical assumptions of models of technology acceptance are inadequate, and that the complexity of tele-care implementation has many facets that are not appropriately factored into those models. The identification of relevant factors will benefit and improve the development and acceptance process of tele-care systems. Method The study is based on a broad range of evaluation studies of tele-care systems, under development or installed in the Netherlands, in which many variables could be observed from the earliest stages of conception up to the full operation and (sometimes) demise of the systems. In addition the assumptions behind technology acceptance models (TAM) have been critically analyzed and serious methodological flaws were identified. Also the deployment of tele-care systems was systematically compared with the introduction of application software in industrial settings as described by TAM theories. Results & Discussion A main reason for poor acceptance level is that tele-care does not materialize as a stand-alone product with a specific and clear functionality, like a TV set or an espresso machine. Tele-care can have a surprising variety of instantiations and functions that easily obscure the functionality for the individual user. Another reason is that, even on somewhat longer trial periods, it is not evident to what extent it supersedes other and earlier functions and services that were available to the client. While many clients claim that their tele-care system is easy to use, its inherent complexity often seriously reduces its actual effectiveness. Currently there is more evidence on factors that reduce the adoption rate, than on those that increase it. We also show that part of the poor predictive value of the technology acceptance models can be explained by an inadequate interpretation of the attitude and intention concepts. There is, fortunately also more recent evidence that the use of assistive systems like tele-care can be promoted effectively by increasing self-efficacy of users. Both introductory individual guidance and errorless learning appear to affect user-system interaction in rehabilitation and tele-care to a considerable degree.