Evaluation of a Clinical Protocol-Guided Chatbot to Support Telecarers in Diabetes Management: Embedded Mixed Methods Study.

@article{ong2026evaluation,
  title = {{Evaluation of a Clinical Protocol-Guided Chatbot to Support Telecarers in Diabetes Management: Embedded Mixed Methods Study.}},
  author = {Rebecca Hui Shan Ong and Hong Choon Oh and Bryan Peide Choo and Linette Zhi Ai Tan and Melissa Hui Wen Gunn and Jin Wee Ng and Anne Ching Ching Teng and Sharon Yu Bing Ong and Angela Hwee Koon Ng and Winnie Yi Ling Soo and Yian Chin Lee and Halimah Binte Sarim and Geok Choo Lee and Junaidah Binte Ibrahim and Kryslyn Mei Ying Kae and Jinyang Wu and Zhengyuan Liu and Mojisola Erdt and Siti Umairah Md Salleh and Siti Maryam Binte Ahmad Subaidi and Sakinah Binte Yusof and Nabilah Binte Md Johan and Kavineshaan Ramdas and Jia Shern Ang and Qi Yuan Tay and Yong Mong Bee and Nancy F Chen and Pavitra Krishnaswamy and Joan Joo Ching Khoo},
  journal = {Journal of medical Internet research},
  year = {2026},
  month = oct,
  doi = {10.2196/91058},
  url = {https://europepmc.org/article/MED/42913398},
  note = {CC BY},
}

TY  - JOUR
TI  - Evaluation of a Clinical Protocol-Guided Chatbot to Support Telecarers in Diabetes Management: Embedded Mixed Methods Study.
AU  - Rebecca Hui Shan Ong
AU  - Hong Choon Oh
AU  - Bryan Peide Choo
AU  - Linette Zhi Ai Tan
AU  - Melissa Hui Wen Gunn
AU  - Jin Wee Ng
AU  - Anne Ching Ching Teng
AU  - Sharon Yu Bing Ong
AU  - Angela Hwee Koon Ng
AU  - Winnie Yi Ling Soo
AU  - Yian Chin Lee
AU  - Halimah Binte Sarim
AU  - Geok Choo Lee
AU  - Junaidah Binte Ibrahim
AU  - Kryslyn Mei Ying Kae
AU  - Jinyang Wu
AU  - Zhengyuan Liu
AU  - Mojisola Erdt
AU  - Siti Umairah Md Salleh
AU  - Siti Maryam Binte Ahmad Subaidi
AU  - Sakinah Binte Yusof
AU  - Nabilah Binte Md Johan
AU  - Kavineshaan Ramdas
AU  - Jia Shern Ang
AU  - Qi Yuan Tay
AU  - Yong Mong Bee
AU  - Nancy F Chen
AU  - Pavitra Krishnaswamy
AU  - Joan Joo Ching Khoo
PY  - 2026
DA  - 2026/10/23
JO  - Journal of medical Internet research
DO  - 10.2196/91058
UR  - https://europepmc.org/article/MED/42913398
AB  - Background  Type 2 diabetes mellitus (T2DM) is a chronic condition that requires ongoing self-management. While chatbots offer scalable monitoring and management, evidence on their integration into structured hospital tele-support workflows, where patient engagement and digital readiness may differ from those in standalone digital interventions, remains limited.Objective  This study aimed to describe the design of a clinical protocol-guided chatbot, Sharing Information with Users on Diabetes Actions and Interventions (Siu Dai), and evaluate its feasibility, usability, and acceptability among patients and telecarers within a hospital tele-support program.Methods  We used an embedded mixed methods design (QUAL [quan]) guided by the World Health Organization (WHO) monitoring and evaluating digital health interventions and the theoretical framework of acceptability. Through a co-design process involving clinicians, researchers, telecarers, and developers, the chatbot was aligned with established clinical protocols. It featured 7 precall sessions designed to collect patient data, generate summary reports for staff, and deliver targeted educational content. Patients (≥21-year-old individuals with T2DM) and telecarer nurses (with experience ≥6 mo) were recruited from an existing tele-support program. Data sources included interviews, online surveys (5-point Likert scale), and chatbot usage logs. Qualitative data were analyzed thematically; quantitative data were summarized descriptively to supplement and contextualize the qualitative findings.Results  Fourteen participants (7 patients and 7 telecarers) completed both interviews and surveys and were included in the analysis. Patients (mean age 45.3, SD 15.4 y) had a median diabetes duration of 10 (IQR 3-25; range 1-30) years, and all were digitally literate. Telecarers had a median of 5 (IQR 4-9) years of telehealth experience. Quantitatively, patients showed high engagement, completing 79% of started sessions with a median completion time of 2 minutes and 58 seconds. Patient satisfaction was high, with 86% (6/7) willing to recommend the tool; however, telecarer endorsement for universal rollout to patients in other clinical programs or outpatient clinics was more cautious (3/7, 43%). Qualitative findings revealed 5 themes: (1) perceptions of chatbot usability, (2) alignment and integration into telecarers' processes, (3) factors influencing acceptability of the chatbot, (4) perceived efficacy of the chatbot for T2DM self-management and care delivery, and (5) suggested improvements and enhancements. Integrated findings revealed that the chatbot was usable and functioned as a precall support tool that optimized the personalization of tele-support sessions. However, its perceived efficacy in self-management behavior was limited by this cohort's extensive experience with T2DM management. Key barriers to adoption included administrative burden for telecarers due to a lack of electronic medical record integration and content redundancy for patients. Suggested enhancements included multilingual support and adaptive content catering to different levels of disease-specific literacy.Conclusions  A clinical protocol-guided chatbot is feasible for hospital tele-support, complementing rather than replacing human care. It automates routine assessments and reinforces education, but future iterations must prioritize workflow integration and adaptive content to sustain engagement.
SN  - 1439-4456
SN  - 1438-8871
ER  -