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      When Chatbots Meet Patients: One-Year Prospective Study of Conversations Between Patients With Breast Cancer and a Chatbot

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          Abstract

          Background

          A chatbot is a software that interacts with users by simulating a human conversation through text or voice via smartphones or computers. It could be a solution to follow up with patients during their disease while saving time for health care providers.

          Objective

          The aim of this study was to evaluate one 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 responds to the fears and concerns of patients with breast cancer using personalized insights through text messages. We conducted a prospective study by analyzing the users’ and 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

          A total of 4737 patients were included. Results showed 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 used the chatbot, the more adherent they were. Patients regularly left positive comments and recommended Vik to their friends. The overall satisfaction was 93.95% (900/958). When asked what Vik meant to them and what Vik brought them, 88.00% (943/958) said that Vik provided them with support and helped them track their treatment effectively.

          Conclusions

          We demonstrated that it is possible to obtain support through a chatbot since Vik improved the medication adherence rate of patients with breast cancer.

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          Most cited references11

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          It’s only a computer: Virtual humans increase willingness to disclose

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            A fully automated conversational agent for promoting mental well-being: A pilot RCT using mixed methods

            Fully automated self-help interventions can serve as highly cost-effective mental health promotion tools for massive amounts of people. However, these interventions are often characterised by poor adherence. One way to address this problem is to mimic therapy support by a conversational agent. The objectives of this study were to assess the effectiveness and adherence of a smartphone app, delivering strategies used in positive psychology and CBT interventions via an automated chatbot (Shim) for a non-clinical population — as well as to explore participants' views and experiences of interacting with this chatbot. A total of 28 participants were randomized to either receive the chatbot intervention (n = 14) or to a wait-list control group (n = 14). Findings revealed that participants who adhered to the intervention (n = 13) showed significant interaction effects of group and time on psychological well-being (FS) and perceived stress (PSS-10) compared to the wait-list control group, with small to large between effect sizes (Cohen's d range 0.14–1.06). Also, the participants showed high engagement during the 2-week long intervention, with an average open app ratio of 17.71 times for the whole period. This is higher compared to other studies on fully automated interventions claiming to be highly engaging, such as Woebot and the Panoply app. The qualitative data revealed sub-themes which, to our knowledge, have not been found previously, such as the moderating format of the chatbot. The results of this study, in particular the good adherence rate, validated the usefulness of replicating this study in the future with a larger sample size and an active control group. This is important, as the search for fully automated, yet highly engaging and effective digital self-help interventions for promoting mental health is crucial for the public health.
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              Association of a Smartphone Application With Medication Adherence and Blood Pressure Control

              Medication nonadherence accounts for up to half of uncontrolled hypertension. Smartphone applications (apps) that aim to improve adherence are widely available but have not been rigorously evaluated.
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                Author and article information

                Contributors
                Journal
                JMIR Cancer
                JMIR Cancer
                JC
                JMIR Cancer
                JMIR Publications (Toronto, Canada )
                2369-1999
                Jan-Jun 2019
                02 May 2019
                : 5
                : 1
                : e12856
                Affiliations
                [1 ] Department of Otolaryngology Head and Neck Surgery, University Hospital Gui de Chauliac Montpellier France
                [2 ] Université Montpellier I Montpellier France
                [3 ] Wefight, Brain & Spine Institute, Hospital Pitié-Salpêtrière Paris France
                [4 ] Department of Radiation Oncology, European Hospital Georges Pompidou, Assistance Publique-Hôpitaux de Paris Paris France
                Author notes
                Corresponding Author: Benjamin Chaix b-chaix@ 123456chu-montpellier.fr
                Author information
                http://orcid.org/0000-0001-5934-9774
                http://orcid.org/0000-0002-1728-6776
                http://orcid.org/0000-0003-2215-5452
                http://orcid.org/0000-0001-5629-5643
                http://orcid.org/0000-0003-1088-8907
                http://orcid.org/0000-0002-7983-9989
                http://orcid.org/0000-0003-1018-386X
                Article
                v5i1e12856
                10.2196/12856
                6521209
                31045505
                9f9eb20a-311c-4aa1-9f68-33a253b753f3
                ©Benjamin Chaix, Jean-Emmanuel Bibault, Arthur Pienkowski, Guillaume Delamon, Arthur Guillemassé, Pierre Nectoux, Benoît Brouard. Originally published in JMIR Cancer (http://cancer.jmir.org), 02.05.2019.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Cancer, is properly cited. The complete bibliographic information, a link to the original publication on http://cancer.jmir.org/.as well as this copyright and license information must be included.

                History
                : 20 November 2018
                : 4 February 2019
                : 8 March 2019
                : 29 March 2019
                Categories
                Original Paper
                Original Paper

                artificial intelligence,breast cancer,mobile phone,patient-reported outcomes,symptom management,chatbot,conversational agent

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