title: An adaptation of the theory of interpersonal behaviour to the study of telemedicine adoption by physicians.
abstract: Physicians' acceptance of telemedicine constitutes a prerequisite for its diffusion on a national scale. Based upon the Theory of Interpersonal Behavior, this study was aimed at assessing the predictors of physicians' intention to use telemedicine in their clinical practice. All of the physicians involved in the RQTE, the extended provincial telemedicine network of Quebec (Canada) were mailed a questionnaire to identify the psychosocial determinants of their intention to adopt telemedicine. Confirmatory factor analysis (CFA) was performed to assess the measurement model and structural equation modelling (SEM) was applied to test the theoretical model. The adapted theoretical model explained 81% (P<0.001) of variance in physicians' intention to use telehealth. The main predictors of intentions were a composite normative factor, comprising personal as well as social norms (beta=1.08; P<0.001) and self identity (beta=-0.33; P<0.001). Thus, physicians who perceived professional and social responsibilities regarding adoption of telehealth in their clinical practice had stronger intention to use this technology. However, it is likely that personal identity had a suppression effect in the regression equation, indicating that physicians' intention to use telemedicine was better predicted if their self-perception as telemedicine users was considered. These results have several implications at the theoretical and practical levels that are discussed in this paper.
mesh_terms: D000328:Adult; D001291:Attitude of Health Personnel; D001292:Attitude to Computers; D004059:Diffusion of Innovation; D005163:Factor Analysis, Statistical; D005260:Female; D006801:Humans; D033182:Intention; D008297:Male; D008875:Middle Aged; D008962:Models, Theoretical; D010820:Physicians / Q000523:psychology*; D011594:Psychometrics; D011792:Quebec; D012649:Self Concept; D011795:Surveys and Questionnaires; D017216:Telemedicine / Q000706:statistics & numerical data*