Development and early feasibility of chatbots for educating patients with lung cancer and their caregivers in Japan: A mixed-method study
ABSTRACT
Background:
Chatbots are artificial intelligence-driven programs that interact with people. The application of this technology is wide—including collecting and delivering information, creating and answering inquiries, collecting customer feedback, and even delivering personalized health and medical information to patients through mobile and web-based platforms. However, there are no chatbots for lung cancer patients and their caregivers.
Objective:
Our research objective was to develop and evaluate the early feasibility of a chatbot designed to improve symptom management knowledge of patients with lung cancer and their caregivers.
Methods:
We conducted a sequential mixed method approach that included conducting a web-based anonymized questionnaire survey of physicians and paramedics from June to July 2019. Two physicians conducted a content analysis of the questionnaire to organize it into frequently asked questions (FAQs). Based on the FAQs, we developed and integrated a chatbot into a social network service. The chatbot was then tested by the physicians and paramedics (alpha test), thereafter, by the patients or their caregivers (beta test).
Results:
We obtained 246 questions from 15 healthcare providers. After the test, we identified 91 FAQs and their corresponding answers. In the beta test, 11 patients and one caregiver participated. The participants were asked 60 questions. Eight questions (13%) did not match the appropriate categories. After the beta test, seven participants (64%) answered the post-experimental questionnaire. The mean satisfaction score was 2.7 points out of 5 (standard deviation: 0.5).
Conclusions:
Medical staff caring for lung cancer patients would be able to use the categories specified in this study to educate patients. Further research is warranted to improve chatbots in terms of interaction. Clinical Trial: Chatbot; lung cancer; symptom management education; mixed method approach
Citation
Request queued. Please wait while the file is being generated. It may take some time.
Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.