Toward a Conversational Agent to Support the Self-Management of Adults and Young Adults With Sickle Cell Disease: Usability and Usefulness Study

Both Patients and Plastic Surgeons Prefer Artificial Intelligence-Generated Microsurgical Information

BACKGROUND

 With the growing relevance of artificial intelligence (AI)-based patient-facing information, microsurgical-specific online information provided by professional organizations was compared with that of ChatGPT (Chat Generative Pre-Trained Transformer) and assessed for accuracy, comprehensiveness, clarity, and readability.

METHODS

 Six plastic and reconstructive surgeons blindly assessed responses to 10 microsurgery-related medical questions written either by the American Society of Reconstructive Microsurgery (ASRM) or ChatGPT based on accuracy, comprehensiveness, and clarity. Surgeons were asked to choose which source provided the overall highest-quality microsurgical patient-facing information. Additionally, 30 individuals with no medical background (ages: 18-81, μ = 49.8) were asked to determine a preference when blindly comparing materials. Readability scores were calculated, and all numerical scores were analyzed using the following six reliability formulas: Flesch-Kincaid Grade Level, Flesch-Kincaid Readability Ease, Gunning Fog Index, Simple Measure of Gobbledygook Index, Coleman-Liau Index, Linsear Write Formula, and Automated Readability Index. Statistical analysis of microsurgical-specific online sources was conducted utilizing paired t-tests.

RESULTS

 Statistically significant differences in comprehensiveness and clarity were seen in favor of ChatGPT. Surgeons, 70.7% of the time, blindly choose ChatGPT as the source that overall provided the highest-quality microsurgical patient-facing information. Nonmedical individuals 55.9% of the time selected AI-generated microsurgical materials as well. Neither ChatGPT nor ASRM-generated materials were found to contain inaccuracies. Readability scores for both ChatGPT and ASRM materials were found to exceed recommended levels for patient proficiency across six readability formulas, with AI-based material scored as more complex.

CONCLUSION

 AI-generated patient-facing materials were preferred by surgeons in terms of comprehensiveness and clarity when blindly compared with online material provided by ASRM. Studied AI-generated material was not found to contain inaccuracies. Additionally, surgeons and nonmedical individuals consistently indicated an overall preference for AI-generated material. A readability analysis suggested that both materials sourced from ChatGPT and ASRM surpassed recommended reading levels across six readability scores.

GENEVIC: GENetic data Exploration and Visualization via Intelligent interactive Console

SUMMARY

The vast generation of genetic data poses a significant challenge in efficiently uncovering valuable knowledge. Introducing GENEVIC, an AI-driven chat framework that tackles this challenge by bridging the gap between genetic data generation and biomedical knowledge discovery. Leveraging generative AI, notably ChatGPT, it serves as a biologist's "copilot." It automates the analysis, retrieval, and visualization of customized domain-specific genetic information, and integrates functionalities to generate protein interaction networks, enrich gene sets, and search scientific literature from PubMed, Google Scholar, and arXiv, making it a comprehensive tool for biomedical research. In its pilot phase, GENEVIC is assessed using a curated database that ranks genetic variants associated with Alzheimer's disease, schizophrenia, and cognition, based on their effect weights from the Polygenic Score (PGS) Catalog, thus enabling researchers to prioritize genetic variants in complex diseases. GENEVIC's operation is user-friendly, accessible without any specialized training, secured by Azure OpenAI's HIPAA-compliant infrastructure, and evaluated for its efficacy through real-time query testing. As a prototype, GENEVIC is set to advance genetic research, enabling informed biomedical decisions.

AVAILABILITY AND IMPLEMENTATION

GENEVIC is publicly accessible at https://genevicanath2024.streamlit.app. The underlying code is open-source and available via GitHub at https://github.com/bsml320/GENEVIC.git (also at https://github.com/anath2110/GENEVIC.git).

Self-management needs, strategies and support for individuals with sickle cell disease in developing countries: a scoping review

INTRODUCTION

Sickle cell disease (SCD) poses a significant global health burden, particularly affecting individuals in developing countries with constrained healthcare resources. While research on self-management in the context of SCD is emerging, it has predominantly focused on primary studies. The aim of the scoping review was to identify and map self-management needs of individuals living with SCD, the strategies they employed to meet those needs, and the support interventions available to them.

METHODS AND ANALYSIS

The review was conducted following the Askey and O'Malley's framework to examine the landscape of SCD self-management research. Searches were conducted in PubMed, Scopus, Embase and Dimensions AI, with additional searches in other databases from inception to June 2024 included. Evidence from 14 studies was synthesised to identify self-management needs, strategies and interventions for individuals with SCD.

RESULTS

The review identified diverse self-management needs among individuals with SCD, including knowledge deficits, emotional challenges, physical limitations and barriers to healthcare access. Various self-management strategies were reported, such as nutritional management, psychological coping techniques and proactive healthcare management. Self-management interventions, predominantly delivered by healthcare professionals, focused on providing education, skills training and support to individuals with SCD. The outcomes of self-management interventions consistently demonstrated significant improvements across various dimensions, including self-efficacy, knowledge enhancement, self-care practices and psychological well-being among individuals with SCD.

CONCLUSION

This scoping review underscores the importance of addressing the diverse self-management needs of individuals with SCD through tailored interventions and support systems to enhance overall well-being and disease management. Healthcare professionals should prioritise the implementation of multidisciplinary self-management interventions that encompass medical, emotional and social aspects of care to effectively support individuals with SCD in managing their condition. Future research should focus on longitudinal studies to assess the long-term effectiveness of self-management interventions in improving patient outcomes.

Exploring the characteristics of conversational agents in chronic disease management interventions: A scoping review

Objective

With the increasing global burden of chronic diseases, there is the potential for conversational agents (CAs) to assist people in actively managing their conditions. This paper reviews different types of CAs used for chronic condition management, delving into their characteristics and the chosen study designs. This paper also discusses the potential of these CAs to enhance the health and well-being of people with chronic conditions.

Methods

A search was performed in February 2023 on PubMed, ACM Digital Library, Scopus, and IEEE Xplore. Studies were included if they focused on chronic disease management or prevention and if systems were evaluated on target user groups.

Results

The 42 selected studies explored diverse types of CAs across 11 health conditions. Personalization varied, with 25 CAs not adapting message content, while others incorporated user characteristics and real-time context. Only 12 studies used medical records in conjunction with CAs for conditions like diabetes, mental health, cardiovascular issues, and cancer. Despite measurement method variations, the studies predominantly emphasized improved health outcomes and positive user attitudes toward CAs.

Conclusions

The results underscore the need for CAs to adapt to evolving patient needs, customize interventions, and incorporate human support and medical records for more effective care. It also highlights the potential of CAs to play a more active role in helping individuals manage their conditions and notes the value of linguistic data generated during user interactions. The analysis acknowledges its limitations and encourages further research into the use and potential of CAs in disease-specific contexts.

A chatbot for hypertension self-management support: user-centered design, development, and usability testing

Objectives

Health-related chatbots have demonstrated early promise for improving self-management behaviors but have seldomly been utilized for hypertension. This research focused on the design, development, and usability evaluation of a chatbot for hypertension self-management, called "Medicagent."

Materials and Methods

A user-centered design process was used to iteratively design and develop a text-based chatbot using Google Cloud's Dialogflow natural language understanding platform. Then, usability testing sessions were conducted among patients with hypertension. Each session was comprised of: (1) background questionnaires, (2) 10 representative tasks within Medicagent, (3) System Usability Scale (SUS) questionnaire, and (4) a brief semi-structured interview. Sessions were video and audio recorded using Zoom. Qualitative and quantitative analyses were used to assess effectiveness, efficiency, and satisfaction of the chatbot.

Results

Participants (n = 10) completed nearly all tasks (98%, 98/100) and spent an average of 18 min (SD = 10 min) interacting with Medicagent. Only 11 (8.6%) utterances were not successfully mapped to an intent. Medicagent achieved a mean SUS score of 78.8/100, which demonstrated acceptable usability. Several participants had difficulties navigating the conversational interface without menu and back buttons, felt additional information would be useful for redirection when utterances were not recognized, and desired a health professional persona within the chatbot.

Discussion

The text-based chatbot was viewed favorably for assisting with blood pressure and medication-related tasks and had good usability.

Conclusion

Flexibility of interaction styles, handling unrecognized utterances gracefully, and having a credible persona were highlighted as design components that may further enrich the user experience of chatbots for hypertension self-management.

Factors Influencing the Acceptability, Acceptance, and Adoption of Conversational Agents in Health Care: Integrative Review

BACKGROUND

Conversational agents (CAs), also known as chatbots, are digital dialog systems that enable people to have a text-based, speech-based, or nonverbal conversation with a computer or another machine based on natural language via an interface. The use of CAs offers new opportunities and various benefits for health care. However, they are not yet ubiquitous in daily practice. Nevertheless, research regarding the implementation of CAs in health care has grown tremendously in recent years.

OBJECTIVE

This review aims to present a synthesis of the factors that facilitate or hinder the implementation of CAs from the perspectives of patients and health care professionals. Specifically, it focuses on the early implementation outcomes of acceptability, acceptance, and adoption as cornerstones of later implementation success.

METHODS

We performed an integrative review. To identify relevant literature, a broad literature search was conducted in June 2021 with no date limits and using all fields in PubMed, Cochrane Library, Web of Science, LIVIVO, and PsycINFO. To keep the review current, another search was conducted in March 2022. To identify as many eligible primary sources as possible, we used a snowballing approach by searching reference lists and conducted a hand search. Factors influencing the acceptability, acceptance, and adoption of CAs in health care were coded through parallel deductive and inductive approaches, which were informed by current technology acceptance and adoption models. Finally, the factors were synthesized in a thematic map.

RESULTS

Overall, 76 studies were included in this review. We identified influencing factors related to 4 core Unified Theory of Acceptance and Use of Technology (UTAUT) and Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) factors (performance expectancy, effort expectancy, facilitating conditions, and hedonic motivation), with most studies underlining the relevance of performance and effort expectancy. To meet the particularities of the health care context, we redefined the UTAUT2 factors social influence, habit, and price value. We identified 6 other influencing factors: perceived risk, trust, anthropomorphism, health issue, working alliance, and user characteristics. Overall, we identified 10 factors influencing acceptability, acceptance, and adoption among health care professionals (performance expectancy, effort expectancy, facilitating conditions, social influence, price value, perceived risk, trust, anthropomorphism, working alliance, and user characteristics) and 13 factors influencing acceptability, acceptance, and adoption among patients (additionally hedonic motivation, habit, and health issue).

CONCLUSIONS

This review shows manifold factors influencing the acceptability, acceptance, and adoption of CAs in health care. Knowledge of these factors is fundamental for implementation planning. Therefore, the findings of this review can serve as a basis for future studies to develop appropriate implementation strategies. Furthermore, this review provides an empirical test of current technology acceptance and adoption models and identifies areas where additional research is necessary.

TRIAL REGISTRATION

PROSPERO CRD42022343690; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=343690.

Defining global strategies to improve outcomes in sickle cell disease: a Lancet Haematology Commission

All over the world, people with sickle cell disease (an inherited condition) have premature deaths and preventable severe chronic complications, which considerably affect their quality of life, career progression, and financial status. In addition, these people are often affected by stigmatisation or structural racism, which can contribute to stress and poor mental health. Inequalities affecting people with sickle cell disease are also reflected in the distribution of the disease—mainly in sub-Saharan Africa, India, and the Caribbean—whereas interventions, clinical trials, and funding are mostly available in North America, Europe, and the Middle East. Although some of these characteristics also affect people with other genetic diseases, the fate of people with sickle cell disease seems to be particularly unfair. Simple, effective interventions to reduce the mortality and morbidity associated with sickle cell disease are available. The main obstacle preventing better outcomes in this condition, which is a neglected disease, is associated with inequalities impacting the patient populations. The aim of this Commission is to highlight the problems associated with sickle cell disease and to identify achievable goals to improve outcomes both in the short and long term.

The ambition for the management of people with sickle cell disease is that curative treatments become available to every person with the condition. Although this would have seemed unrealistic a decade ago, developments in gene therapy make this potentially achievable, albeit in the distant future. Until these curative technologies are fully developed and become widely available, health-care professionals (with the support of policy makers, funders, etc) should make sure that a minimum standard of care (including screening, prophylaxis against infection, acute medical care, safe blood transfusion, and hydroxyurea) is available to all patients.

In considering what needs to be achieved to reduce the global burden of sickle cell disease and improve the quality of life of patients, this Commission focuses on five key areas: the epidemiology of sickle cell disease (Section 1 ); screening and prevention (Section 2 ); established and emerging treatments for the management of the disease (Section 3 ); cellular therapies with curative potential (Section 4 ); and training and education needs (Section 5 ). As clinicians, researchers, and patients, our objective to reduce the global burden of sickle cell disease aligns with wider public health aims to reduce inequalities, improve health for all, and develop personalised treatment options. We have observed in the past few years some long-awaited momentum following the development of innovative point-of-care testing devices, new approved drugs, and emerging curative options. Reducing the burden of sickle cell disease will require substantial financial and political commitment, but it will impact the lives of millions of patients and families worldwide and the lessons learned in achieving this goal would unarguably benefit society as a whole.

ChatGPT in medicine: an overview of its applications, advantages, limitations, future prospects, and ethical considerations

This paper presents an analysis of the advantages, limitations, ethical considerations, future prospects, and practical applications of ChatGPT and artificial intelligence (AI) in the healthcare and medical domains. ChatGPT is an advanced language model that uses deep learning techniques to produce human-like responses to natural language inputs. It is part of the family of generative pre-training transformer (GPT) models developed by OpenAI and is currently one of the largest publicly available language models. ChatGPT is capable of capturing the nuances and intricacies of human language, allowing it to generate appropriate and contextually relevant responses across a broad spectrum of prompts. The potential applications of ChatGPT in the medical field range from identifying potential research topics to assisting professionals in clinical and laboratory diagnosis. Additionally, it can be used to help medical students, doctors, nurses, and all members of the healthcare fraternity to know about updates and new developments in their respective fields. The development of virtual assistants to aid patients in managing their health is another important application of ChatGPT in medicine. Despite its potential applications, the use of ChatGPT and other AI tools in medical writing also poses ethical and legal concerns. These include possible infringement of copyright laws, medico-legal complications, and the need for transparency in AI-generated content. In conclusion, ChatGPT has several potential applications in the medical and healthcare fields. However, these applications come with several limitations and ethical considerations which are presented in detail along with future prospects in medicine and healthcare.

Usage of mobile health interventions among overweight/obese PCOS patients undergoing assisted reproductive technology treatment during the COVID-19 pandemic

Objective: In the context of the coronavirus disease 2019 (COVID-19) pandemic, telemedicine is a promising tool for providing clinical care for patients. Since the first-line treatment for infertile women with polycystic ovarian syndrome (PCOS) is lifestyle modification, a mobile-based service that provides lifestyle modification education would be helpful in the treatment of PCOS patients. In this observational study, the effect of a mobile Health (mHealth) application for lifestyle modification on PCOS patients undergoing assisted reproductive technology (ART) treatment was evaluated.Methods: A total of 79 overweight/obese patients (40 in the paper group and 39 in the WeChat application group) with PCOS from the First Affiliated Hospital of University of Science and Technology of China were enrolled in the study. The changes in the outcomes of BMI and ART treatment were analyzed between the two groups.Results: After three months of intervention, the BMIs in the control and mHealth groups were 24.5 ± 3.3 and 23.7 ± 3.1, respectively. The percentage of patients who lost weight was higher in the WeChat group than in the control group (87.2% vs. 67.5%). Furthermore, PCOS patients in the WeChat group were found to have a higher live birth rate than those in the control group (p = 0.005).Conclusion: Lifestyle modifications for PCOS patients undergoing ART treatment using the WeChat application improved weight loss and oocyte quality. Infertile patients with PCOS were more likely to make lifestyle modifications based on the usage of mobile applications during the COVID-19 pandemic.

Users' needs for a digital smoking cessation application and how to address them: A mixed-methods study

Background

Despite their increasing prevalence and potential, eHealth applications for behavior change suffer from a lack of adherence and from dropout. Advances in virtual coach technology provide new opportunities to improve this. However, these applications still do not always offer what people need. We, therefore, need a better understanding of people's needs and how to address these, based on both actual experiences of users and their reflections on envisioned scenarios.

Methods

We conducted a longitudinal study in which 671 smokers interacted with a virtual coach in five sessions. The virtual coach assigned them a new preparatory activity for quitting smoking or increasing physical activity in each session. Participants provided feedback on the activity in the next session. After the five sessions, participants were asked to describe barriers and motivators for doing their activities. In addition, they provided their views on videos of scenarios such as receiving motivational messages. To understand users' needs, we took a mixed-methods approach. This approach triangulated findings from qualitative data, quantitative data, and the literature.

Results

We identified 14 main themes that describe people's views of their current and future behaviors concerning an eHealth application. These themes relate to the behaviors themselves, the users, other parties involved in a behavior, and the environment. The most prevalent theme was the perceived usefulness of behaviors, especially whether they were informative, helpful, motivating, or encouraging. The timing and intensity of behaviors also mattered. With regards to the users, their perceived importance of and motivation to change, autonomy, and personal characteristics were major themes. Another important role was played by other parties that may be involved in a behavior, such as general practitioners or virtual coaches. Here, the themes of companionableness, accountability, and nature of the other party (i.e., human vs AI) were relevant. The last set of main themes was related to the environment in which a behavior is performed. Prevalent themes were the availability of sufficient time, the presence of prompts and triggers, support from one's social environment, and the diversity of other environmental factors. We provide recommendations for addressing each theme.

Conclusions

The integrated method of experience-based and envisioning-based needs acquisition with a triangulate analysis provided a comprehensive needs classification (empirically and theoretically grounded). We expect that our themes and recommendations for addressing them will be helpful for designing applications for health behavior change that meet people's needs. Designers should especially focus on the perceived usefulness of application components. To aid future work, we publish our dataset with user characteristics and 5,074 free-text responses from 671 people.

How Far Can Conversational Agents Contribute to IBD Patient Health Care—A Review of the Literature

Modern societies are facing health and healthcare challenges as never seen before. The digital world in which we are living today considers digital health interventions such as “internet-delivered” therapy (e-Therapy) or mobile apps as an integrated part of healthcare systems. Digital transformation in health care requires the active involvement of patients as the central part of healthcare interventions. In the case of chronic health conditions, such as inflammatory bowel disease (IBD), it is believed that the adoption of new digital tools helps to maintain and extend the health and care of patients, optimizing the course of the treatment of the disease. The study goal was to undertake a literature review associating the use of chatbot technology with IBD patients' health care. This study intends to support digital product developments, mainly chatbot for IBD or other chronic diseases. The work was carried out through two literature review phases. The first one was based on a systematic approach and the second was a scoping review focused only on Frontiers Journals. This review followed a planned protocol for search and selection strategy that was created by a research team discussion. Chatbot technology for chronic disease self-management can have high acceptance and usability levels. The more interaction with a chatbot, the more patients are able to increase their self-care practice, but there is a challenge. The chatbot ontology to personalize the communication still needed to have strong guidelines helping other researchers to define which Electronic Medical Records (EMRs) should be used in the chatbots to improve the user satisfaction, engagement, and dialog quality. The literature review showed us both evidence and success of these tools in other health disorders. Some of them revealed a huge potential for conversational agents as a part of digital health interventions.