A quantitative and qualitative analysis of factors affecting acceptance of a computer-based disease self-monitoring system among patients with type 2 diabetes mellitus and/or hypertension

Abstract

Background: Consumer health information technologies (HITs) have become popular in facilitating chronically ill patients with their disease self-management as they are believed to help enhance patients’ independence with self-care, promote well-being and quality of life. However, patients may not always accept and maintain the use of the technologies over time. This is an important concern because patients’ nonacceptance of consumer HITs can reduce their benefits and eventually lead to a loss to the technology developers and investors. To this end, this thesis studied patients’ acceptance of a computer-based disease self-monitoring system over a 12-week period, whereby factors that may affect technology acceptance were examined. Methods: By capitalizing on a randomized controlled trial study, this research work was carried out in two parts. A quantitative study was conducted to test the key factors that predicted the acceptance of a consumer HIT, including perceived usefulness, perceived ease of use, attitude, subjective norm, perceived behavioral control, health consciousness, and application-specific self-efficacy. The acceptance of technology was measured by patients’ behavioral intentions and their actual usage behaviors. The technology-acceptance questionnaire developed in this study was administered to patients through home visits at baseline, and at four and eight weeks postimplementation. Valid observations collected at each measurement point in time were pooled (n = 119) and analyzed using partial least squares structural equation modeling. A qualitative analysis of acceptance was also conducted using semistructured interviews with patients (n = 38) after the 12 weeks’ intervention. Data were content analyzed to examine patients’ opinions on their perceived facilitators and barriers to acceptance. Results: The results of the quantitative analysis showed that patients’ behavioral intention was directly influenced by their attitudes, perceived behavioral control, and subjective norms. Perceived usefulness, perceived ease of use, health consciousness, and application-specific self-efficacy had an indirect influence on behavioral intention through one or more mediators. The overall amount of variance in behavioral intention explained by our research model was 73.8%. The impact of all these factors on patients’ actual technology usage was shown to be fully mediated by behavioral intention, which explained 16.7% of the variance in actual usage. The qualitative analysis yielded 239 interview statements that were associated with facilitators (n = 166) and barriers (n = 73) to acceptance and grouped into six themes: patient attributes; technology characteristics; interaction between patients and technology; home environment; influence, resource, and support; and health outcome expectancy. Conclusions: This study demonstrated that consumer HITs could be readily accepted by patients with chronic diseases. It is hoped that by proactively considering and applying the findings of this research and accordingly designing, developing, and implementing consumer HITs, patient technology acceptance could be increased.