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

Chaix, Benjamin; Bibault, Jean‐Emmanuel; Pienkowski, Arthur; Delamon, Guillaume; Guillemassé, Arthur; Nectoux, Pierre; Brouard, Benoît

doi:10.2196/preprints.12856

Cited by 3 publications

(1 citation statement)

References 21 publications

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“…For instance, a chatbot can answer questions at any time of the day, send reminders, avoid the feeling of discomfort for the patient when asking private questions. Additionally, it has been shown that chatbots can improve patients' compliance ( 17 ). Chatbots can also monitor patients and save time for healthcare teams for more complex tasks ( 18 ).…”

Section: Introductionmentioning

confidence: 99%

Using a Chatbot to Study Medication Overuse Among Patients Suffering From Headaches

Bézie¹,

Morisseau²,

Rolland³

et al. 2022

Front. Digit. Health

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According to the World Health Organization, half the adult population around the world suffers from headaches. Even though this condition remains in most cases innocuous, it can have a major impact on the patient's quality of life but also on public health expenditure. Moreover, most patients manage their headaches on their own, without consulting a doctor. Therefore, self-medication can eventually lead to drug overuse, and consequently the emergence of a secondary disease called medication-overuse headache (MOH). The detection and follow-up of these unconventional patients represent a major challenge. Some of the latest technology advancements seem to be tailored and fitting for this context. The goal of this study is to investigate medication overuse in French patients suffering from headaches using the chatbot Vik Migraine. Data collection and analysis were assembled from answers to a questionnaire of 28 questions divided into three parts: socio-demographic profile, drug consumption, and medical follow-up. The study showed that medication overuse was often linked to increased headache frequency. Prescription drugs like triptans and opioids, were the most overused drugs among the cohort. This suggests that healthcare professionals could play a critical role in targeting these drugs in prevention of overuse.

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Section: Introductionmentioning

confidence: 99%

Using a Chatbot to Study Medication Overuse Among Patients Suffering From Headaches

Bézie¹,

Morisseau²,

Rolland³

et al. 2022

Front. Digit. Health

Self Cite

View full text Add to dashboard Cite

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Cohort and Trajectory Analysis in Multi-Agent Support Systems for Cancer Survivors

et al. 2021

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In the past decades, the incidence rate of cancer has steadily risen. Although advances in early and accurate detection have increased cancer survival chances, these patients must cope with physical and psychological sequelae. The lack of personalized support and assistance after discharge may lead to a rapid diminution of their physical abilities, cognitive impairment, and reduced quality of life. This paper proposes a personalized support system for cancer survivors based on a cohort and trajectory analysis (CTA) module integrated within an agent-based personalized chatbot named EREBOTS. The CTA module relies on survival estimation models, machine learning, and deep learning techniques. It provides clinicians with supporting evidence for choosing a personalized treatment, while allowing patients to benefit from tailored suggestions adapted to their conditions and trajectories. The development of the CTA within the EREBOTS framework enables to effectively evaluate the significance of prognostic variables, detect patient’s high-risk markers, and support treatment decisions.

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Conversational Agents in Health Care: Scoping Review and Conceptual Analysis (Preprint)

Car¹,

Dhinagaran²,

Kyaw³

et al. 2019

Preprint

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BACKGROUND Conversational agents, also known as chatbots, are computer programs designed to simulate human text or verbal conversations. They are increasingly used in a range of fields, including health care. By enabling better accessibility, personalization, and efficiency, conversational agents have the potential to improve patient care. OBJECTIVE This study aimed to review the current applications, gaps, and challenges in the literature on conversational agents in health care and provide recommendations for their future research, design, and application. METHODS We performed a scoping review. A broad literature search was performed in MEDLINE (Medical Literature Analysis and Retrieval System Online; Ovid), EMBASE (Excerpta Medica database; Ovid), PubMed, Scopus, and Cochrane Central with the search terms “conversational agents,” “conversational AI,” “chatbots,” and associated synonyms. We also searched the gray literature using sources such as the OCLC (Online Computer Library Center) WorldCat database and ResearchGate in April 2019. Reference lists of relevant articles were checked for further articles. Screening and data extraction were performed in parallel by 2 reviewers. The included evidence was analyzed narratively by employing the principles of thematic analysis. RESULTS The literature search yielded 47 study reports (45 articles and 2 ongoing clinical trials) that matched the inclusion criteria. The identified conversational agents were largely delivered via smartphone apps (n=23) and used free text only as the main input (n=19) and output (n=30) modality. Case studies describing chatbot development (n=18) were the most prevalent, and only 11 randomized controlled trials were identified. The 3 most commonly reported conversational agent applications in the literature were treatment and monitoring, health care service support, and patient education. CONCLUSIONS The literature on conversational agents in health care is largely descriptive and aimed at treatment and monitoring and health service support. It mostly reports on text-based, artificial intelligence–driven, and smartphone app–delivered conversational agents. There is an urgent need for a robust evaluation of diverse health care conversational agents’ formats, focusing on their acceptability, safety, and effectiveness.

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

Cited by 3 publications

References 21 publications

Using a Chatbot to Study Medication Overuse Among Patients Suffering From Headaches

Using a Chatbot to Study Medication Overuse Among Patients Suffering From Headaches

Cohort and Trajectory Analysis in Multi-Agent Support Systems for Cancer Survivors

Conversational Agents in Health Care: Scoping Review and Conceptual Analysis (Preprint)

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