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Robot-Assisted Approach to Diabetes Care Consultations: Enhancing Patient Engagement and Identifying Therapeutic
Yuya Asada1, Tomomi Horiguchi1, Kunimasa Yagi2,3
1Faculty of Health Sciences, Institute of Medical, Pharmaceutical and Health Sciences, Kanazawa University, Kanazawa 920-1192, Japan.
Robot-assisted diabetes care is feasible for helping specialists manage patient needs. This technology effectively gathers patient feedback and identifies therapeutic issues, offering a scalable solution to the shortage of diabetes care experts.
Area of Science:
- Medical Technology
- Robotics in Healthcare
- Diabetes Management
Background:
- Diabetes presents a growing global health challenge, exacerbated by a shortage of specialized care professionals.
- Robot-assisted care offers a scalable and cost-effective alternative to traditional diabetes education and management methods.
Purpose of the Study:
- To assess the feasibility of using robots for diabetes care consultations.
- To evaluate robots' ability to gather patient feedback and identify therapeutic issues.
- To determine the potential of robots as substitutes for human diabetes care specialists.
Main Methods:
- Development of a robot-assisted consultation program, including robot selection, content design, and communication tailoring.
- Robot operation by experienced diabetes care nurses during patient consultations.
- Collection of patient feedback via a 17-item questionnaire and assessment of therapeutic reflection using a 5-item questionnaire.
Main Results:
- 32 participants (mean age 69.7 years, mean HbA1c 7.2%) completed the study with no reported discomfort.
- High patient satisfaction reported, with most feedback and therapeutic reflection items scoring above the median.
- Robot consultations successfully differentiated patients with treatment compliance issues from those managing their condition effectively, eliciting valuable patient narratives.
Conclusions:
- Robot-assisted diabetes care is a feasible approach to support human healthcare professionals.
- The program demonstrates potential for scalability and utility in various healthcare settings.
- Future research should investigate the application of this technology with healthcare professionals having limited diabetes care experience.
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