| Consumer health information technologies (CHITs) are currently being considered as a possible solution to quality health care. These technologies benefit patients by providing them with better access to health information and resources, which in turn can lead to better patients' outcomes. However, many CHITs are still not always accepted by patients; patients who do not accept the technologies will not benefit from them. To this end, this study examined factors predicting CHIT acceptance among home care patients, in which CHIT acceptance refers to the strength of patient's intention to use the technology (i.e., behavioral intention).;A cross-sectional design, secondary analysis of data obtained from a larger project was used to examine acceptance. The technology acceptance questionnaire developed in this study was administered to 101 patients by mail and phone interview. Data were analyzed using the technique of latent variable modeling with item parceling.;The results showed that higher perceived usefulness was associated with increased behavioral intention and self-reported effective use. Health care knowledge also had a significant positive impact on self-reported effective use. Perceived ease of use and subjective norm indirectly influenced behavioral intention, through perceived usefulness. The results also indicated that the amount of variance in behavioral intention accounted for by perceived usefulness was 53.9%. The amount of variance in self-reported effective use accounted for by perceived usefulness, health care knowledge, and behavioral intention was 68.5%. Perceived ease of use and subjective norm explained 48% of the total variance in perceived usefulness.;By a priori identifying the relationships between the predictors and acceptance, a health care organization or system designer can proactively plan and develop an effective user interface, marketing strategies, technology evaluation and redesign tools, or other relevant interventions prior to the technology implementation. Proactively considering the predictors will help create acceptance for the technology and can increase the likelihood of implementation success. |
