Accepted for/Published in: JMIR Cancer
Date Submitted: Nov 20, 2018
Open Peer Review Period: Dec 3, 2018 - Jan 28, 2019
Date Accepted: Mar 29, 2019
(closed for review but you can still tweet)
When chatbots meet patients: a one-year prospective study of conversations between patients with breast cancer and a chatbot.
ABSTRACT
Background:
Chatbots are softwares that interact with users by simulating a human conversation through text or voice via smartphones or computers. They could be a solution to follow-up with patients during their disease while saving time for healthcare providers.
Objective:
To evaluate 1 year of conversations between patients with breast cancer and a chatbot.
Methods:
Wefight Inc. designed a chatbot (Vik) to empower patients with breast cancer and their relatives. Vik answers the fears and concerns of patients with breast cancer using personalized insights through text messages. We conducted a prospective study by analyzing the users'/patients data, their usage duration, their interest in the various educational contents proposed and their level of interactivity. Patients were women with breast cancer or under remission.
Results:
4737 patients were included. Results show that an average of 132,970 messages exchanged per month was observed between patients and the chatbot Vik. Thus, we calculated the average medication adherence rate over 4 weeks by using a prescription reminder function and we showed that the more the patients use it, the more adherent they are. Patients regularly leave positive comments and recommend Vik to their friends. The overall satisfaction is 94%. When we ask them what Vik means to them and what Vik brings them, 88% say that Vik provides them with support and helps them to track their treatment effectively.
Conclusions:
We show that it is possible to obtain support through a chatbot. Thus, we showed that the chatbot Vik improves the medication adherence rate of patients with breast cancer.
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.