Uirassu Borges1, Thomas Kubiak1. 1. 1 Health Psychology, Johannes Gutenberg University Mainz, Mainz, Germany.
Abstract
BACKGROUND: Continuous glucose monitoring (CGM) patient systems have been shown to improve diabetes self-treatment when used consistently. The meaningful integration of this technology into everyday life, however, can vary greatly among CGM users and not all people with diabetes use CGM to its full potential. To address this issue, the study pursued 2 aims: first, to identify patient characteristics that underlie the acceptance of CGM in people with type 1 diabetes and, second, to examine the effects of different levels of experience with CGM use. METHODS: Guided by a model based on the technology acceptance model (TAM), structural equation modeling (SEM) was employed to model the patient characteristics as predictors of CGM acceptance. In all, 111 participants (60.4% female, mean = 37.6 years, SD = 11.2) participated in a web-based survey; 40 were current CGM users, 18 were former users and 53 had no experience with CGM systems. RESULTS: In general, participants evaluated CGM positively; however, the feeling of information overload represented a major barrier to the sustained use of CGM, while perceptions of usefulness and ease of use constituted incentives for using this technology. Moreover, patients without CGM experience imagined more information overload than current users reported. Current users showed more intention to use CGM than former users. CONCLUSION: This study highlights the importance of CGM user experience for the effective use of this technology.
BACKGROUND: Continuous glucose monitoring (CGM) patient systems have been shown to improve diabetes self-treatment when used consistently. The meaningful integration of this technology into everyday life, however, can vary greatly among CGM users and not all people with diabetes use CGM to its full potential. To address this issue, the study pursued 2 aims: first, to identify patient characteristics that underlie the acceptance of CGM in people with type 1 diabetes and, second, to examine the effects of different levels of experience with CGM use. METHODS: Guided by a model based on the technology acceptance model (TAM), structural equation modeling (SEM) was employed to model the patient characteristics as predictors of CGM acceptance. In all, 111 participants (60.4% female, mean = 37.6 years, SD = 11.2) participated in a web-based survey; 40 were current CGM users, 18 were former users and 53 had no experience with CGM systems. RESULTS: In general, participants evaluated CGM positively; however, the feeling of information overload represented a major barrier to the sustained use of CGM, while perceptions of usefulness and ease of use constituted incentives for using this technology. Moreover, patients without CGM experience imagined more information overload than current users reported. Current users showed more intention to use CGM than former users. CONCLUSION: This study highlights the importance of CGM user experience for the effective use of this technology.
Entities:
Keywords:
continuous glucose monitoring (CGM); human factors; structural equation modeling (SEM); technology acceptance model (TAM); type 1 diabetes
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