A longitudinal examination of tablet self-management technology acceptance by patients with chronic diseases:...

Health information technologies (HITs) are increasingly being used to support the self-management of chronic diseases. However, patients' initial or continued acceptance of such technologies is not always achieved.

The aim of this study was to develop a theory-driven HIT acceptance model to examine factors affecting acceptance of HIT (measured by behavioral intention; BI) for disease self-management among patients with chronic diseases, in which we also focused on three additional, previously unexplored factors related to perceived hand function (PHF), perceived visual function (PVF), and perceived space adequacy (PSA) and a longitudinal scrutinization of changes in the effects of these factors on acceptance over time.

The theoretical basis of our acceptance model was drawn from the technology acceptance model and the theory of planned behavior. The model was further extended by including patients' PHF, PVF (related to patients with chronic diseases who are mostly elderly), and PSA (related to the patients' home environment). The model was tested in the context of type 2 diabetes and hypertension self-management via a touchscreen tablet-based system over a 24-week period. A questionnaire was administered at four time points (baseline and 8, 16, and 24 weeks after implementation) to collect data from 151 patients with coexisting type 2 diabetes and hypertension. We tested the model at each time point using partial least squares structural equation modeling.

Perceived usefulness of the self-management system influenced BI directly at 8 and 24 weeks and indirectly at 8, 16, and 24 weeks. Perceived ease of use indirectly affected BI at 8, 16, and 24 weeks. Attitude directly affected BI at 8, 16, and 24 weeks. Perceived behavioral control directly influenced BI at baseline and 8 and 16 weeks. Subjective norms indirectly influenced BI at 8, 16, and 24 weeks. PHF and PVF indirectly influenced BI over the entire study period. PSA influenced BI directly at 16 weeks and indirectly at 8, 16, and 24 weeks.

The effects of the proposed factors in our model on patient-focused HIT acceptance changed over a longer time period, emphasizing the importance of further investigation of the longitudinal mechanisms influencing technology acceptance behavior. It is recommended that healthcare practitioners consider such changes when implementing comparable technologies. Moreover, beyond technology attributes, the characteristics, needs, and limitations of older adults and elderly patient users and their home environments should also be considered in the design and implementation of patient-focused HIT systems for chronic disease self-management at home.