THE EFFECT OF MOTIVATION AND ABILITY ON ATTITUDES TOWARDS VIRTUAL COMMUNITIES OF PRACTICE: AN ELABORATION LIKELIHOOD APPROACH

Abstract

Sharing of information between health care workers improves evidence dissemination and quality of care. One way to share information is through a community of practice (CoP), whereby members interact regularly towards a common goal. Advances in technology allow CoPs to exist virtually, removing the traditional barriers to information sharing. Virtual CoPs have been shown to be effective, but little is known about why health care workers choose to use them — warranting further investigation. This exploratory research consisted of 86 participants and took place in partnership with Health Quality Ontario. At the time of data collection, the organization was developing a virtual CoP for those in health care to learn from one another about quality improvement. The research utilized the elaboration likelihood model (ELM) — a theoretical model of persuasion that posits that one’s motivation and ability determines how information is processed — to guide the study of attitude formation. ELM distinguishes between Central Route information processing, whereby one is highly motivated and able and pays attention to argument quality, and Peripheral Route processing, whereby lower motivation and ability cause one to be persuaded by peripheral messaging cues. The sustainability of resulting attitudes is influenced by the route through which information is processed. Higher motivation to use a virtual CoP was found to be more strongly correlated to the central route than peripheral route, as expected. Post-hoc analysis found that argument quality had the greatest overall influence on attitudes towards virtual CoPs, regardless of the user’s experience level with them. Users with more experience were also influenced by peripheral cues. The chosen theoretical framework provided insight into the determinants of attitude formation, allowing for a better understanding of how to design and position a virtual CoP for those working in health care — a population yet to be studied through ELM.