Factors influencing Australian podiatrists' behavioural intentions to adopt a smart insole into clinical practice: a mixed methods study
journal contributionposted on 03.08.2021, 00:18 by Emma MacdonaldEmma Macdonald, Byron PerrinByron Perrin, Michael KingsleyMichael Kingsley
Background: Diabetes is the leading cause of lower limb amputation in Australia, costing the Australian health care system an estimated A$1.6 billion annually. Podiatrists are the primary foot health care provider in Australia. Research suggests that health professional attitudes can impact patient utilisation of e-health technologies, such as wearable foot monitoring devices aimed at preventing foot ulceration. The aim of this study was to explore factors that impact the intentions of Australian podiatrists to adopt smart insole foot monitoring technology. Methods: A mixed methods explanatory sequential design was undertaken. One hundred and eleven Australian podiatrists completed an online version of the validated Unified Theory of Acceptance and Use of Technology (UTAUT) questionnaire. Multiple regression analysis was used to determine the strongest predictive model of podiatrists' behavioural intention to adopt technology. Additionally, two focus groups were conducted, and thematic analysis was performed to explore podiatrists' perceived barriers and enablers to smart insole adoption. Results: One hundred and eleven Australian podiatrists completed the online UTAUT questionnaire. The majority of respondents practiced in the private sector (58.6%) and were female (50.5%), with Victoria the most common practice location (39.6%). Significant positive correlations existed between behavioural intention and six psychosocial domains including performance expectancy (r = 0.64, p < 0.001), effort expectancy (r = 0.47, p < 0.001), attitude (r = 0.55, p < 0.001), social influence (r = 0.45, p < 0.001), facilitating conditions (r = 0.36, p < 0.001), and self-efficacy (r = 0.30, p < 0.002). Multiple regression analysis determined that performance expectancy alone was most predictive of behavioural intention to adopt a smart insole into clinical practice (adjusted R2 = 42%, p < 0.001). Qualitative analyses revealed that podiatrists believed that the insole would increase patient knowledge, engagement and self-efficacy. However, concerns were raised about cost, footwear issues and the device's utility with elderly and remote populations. Conclusions: Performance expectancy was the most important psychosocial factor predicting the intentions of Australian podiatrists to adopt smart insole foot monitoring technologies. While Australian podiatrists are open to adopting smart insoles into clinical practice, evidence of the device's efficacy is a precursor to adoption. Other perceived barriers to adoption including device cost, compatibility with off-loading, footwear issues and patient age also need to be addressed prior to implementation and clinical adoption.