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IoT-enabled solutions for paediatric diabetes: examining consumer readiness and adoption factors
Mohammad Al Nawayseh1,2, Ghazi Al-Naymat1, Dania Khraisat2
1Artificial Intelligence Research Center, College of Engineering and Information Technology, Ajman University, Ajman, United Arab Emirates.
Background:
Paediatric diabetes management can be improved using emergent technological solutions, such as the Internet of Things (IoT). IoT systems can collate instant data from sensors, whereby service users and Healthcare Professionals (HCPs) can undertake blood glucose tracking in real time, reacting promptly when needed. However, adoption facilitators in practice are poorly understood.
Research Objective:
To investigate healthcare adoption potential for paediatric diabetes care related to current IoT sensor technology.
Research Methods:
Based on the Technology Acceptance Model as the theoretical framework, this study uses mixed methods. A quantitative survey of 90 parents, concerning IoT is analysed with Fuzzy-Set Qualitative Comparative Analysis (fsQCA) and Partial Least Squares Structural Equation Modelling (PLS-SEM) is combined with qualitative thematic analysis of semi-structured contextualising interviews with 10 paediatric HCPs.
Results:
PLS-SEM analysis revealed that perceived ease of use and usefulness positively affect user predispositions and willingness to adopt IoT solutions in paediatric diabetes care, reaffirmed by fsQCA outcomes affirming that high positive attitudes and usefulness support use albeit perceived ease of use is low. These insights are reaffirmed by interview outcomes, which underscore the importance of usability, integration with existing systems, and concern about data access and privacy.
Implications:
The outcomes indicate that technological system design (i.e., designers and health policy and managerial stakeholders) must prioritise clinical utility and impacts and not myopically focus on ease of use per se, providing necessary training and consulting users in order to effectively integrate technologies into existing systems and ward contexts. Behavioural and configurational analyses can be used to apprize sophisticated interactions and behaviours of adoption in health contexts.
Conclusions:
The outcomes of this research provide quantitative and qualitative support for HCPs' attitudes and the perceived usefulness of IoT technologies being key drivers of their adoption in diabetes management.
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