Implementation of Chatbot Technology in Health Care: Protocol for a Bibliometric Analysis.

BACKGROUND: Chatbots have the potential to increase people's access to quality health care. However, the implementation of chatbot technology in the health care system is unclear due to the scarce analysis of publications on the adoption of chatbot in health and medical settings. OBJECTIVE: This paper presents a protocol of a bibliometric analysis aimed at offering the public insights into the current state and emerging trends in research related to the use of chatbot technology for promoting health. METHODS: In this bibliometric analysis, we will select published papers from the databases of CINAHL, IEEE Xplore, PubMed, Scopus, and Web of Science that pertain to chatbot technology and its applications in health care. Our search strategy includes keywords such as "chatbot," "virtual agent," "virtual assistant," "conversational agent," "conversational AI," "interactive agent," "health," and "healthcare." Five researchers who are AI engineers and clinicians will independently review the titles and abstracts of selected papers to determine their eligibility for a full-text review. The corresponding author (ZN) will serve as a mediator to address any discrepancies and disputes among the 5 reviewers. Our analysis will encompass various publication patterns of chatbot research, including the number of annual publications, their geographic or institutional distribution, and the number of annual grants supporting chatbot research, and further summarize the methodologies used in the development of health-related chatbots, along with their features and applications in health care settings. Software tool VOSViewer (version 1.6.19; Leiden University) will be used to construct and visualize bibliometric networks. RESULTS: The preparation for the bibliometric analysis began on December 3, 2021, when the research team started the process of familiarizing themselves with the software tools that may be used in this analysis, VOSViewer and CiteSpace, during which they consulted 3 librarians at the Yale University regarding search terms and tentative results. Tentative searches on the aforementioned databases yielded a total of 2340 papers. The official search phase started on July 27, 2023. Our goal is to complete the screening of papers and the analysis by February 15, 2024. CONCLUSIONS: Artificial intelligence chatbots, such as ChatGPT (OpenAI Inc), have sparked numerous discussions within the health care industry regarding their impact on human health. Chatbot technology holds substantial promise for advancing health care systems worldwide. However, developing a sophisticated chatbot capable of precise interaction with health care consumers, delivering personalized care, and providing accurate health-related information and knowledge remain considerable challenges. This bibliometric analysis seeks to fill the knowledge gap in the existing literature on health-related chatbots, entailing their applications, the software used in their development, and their preferred functionalities among users. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/54349.

Formative Evaluation of the Acceptance of HIV Prevention Artificial Intelligence Chatbots By Men Who Have Sex With Men in Malaysia: Focus Group Study.

BACKGROUND: Mobile technologies are being increasingly developed to support the practice of medicine, nursing, and public health, including HIV testing and prevention. Chatbots using artificial intelligence (AI) are novel mobile health strategies that can promote HIV testing and prevention among men who have sex with men (MSM) in Malaysia, a hard-to-reach population at elevated risk of HIV, yet little is known about the features that are important to this key population. OBJECTIVE: The aim of this study was to identify the barriers to and facilitators of Malaysian MSM's acceptance of an AI chatbot designed to assist in HIV testing and prevention in relation to its perceived benefits, limitations, and preferred features among potential users. METHODS: We conducted 5 structured web-based focus group interviews with 31 MSM in Malaysia between July 2021 and September 2021. The interviews were first recorded, transcribed, coded, and thematically analyzed using NVivo (version 9; QSR International). Subsequently, the unified theory of acceptance and use of technology was used to guide data analysis to map emerging themes related to the barriers to and facilitators of chatbot acceptance onto its 4 domains: performance expectancy, effort expectancy, facilitating conditions, and social influence. RESULTS: Multiple barriers and facilitators influencing MSM's acceptance of an AI chatbot were identified for each domain. Performance expectancy (ie, the perceived usefulness of the AI chatbot) was influenced by MSM's concerns about the AI chatbot's ability to deliver accurate information, its effectiveness in information dissemination and problem-solving, and its ability to provide emotional support and raise health awareness. Convenience, cost, and technical errors influenced the AI chatbot's effort expectancy (ie, the perceived ease of use). Efficient linkage to health care professionals and HIV self-testing was reported as a facilitating condition of MSM's receptiveness to using an AI chatbot to access HIV testing. Participants stated that social influence (ie, sociopolitical climate) factors influencing the acceptance of mobile technology that addressed HIV in Malaysia included privacy concerns, pervasive stigma against homosexuality, and the criminalization of same-sex sexual behaviors. Key design strategies that could enhance MSM's acceptance of an HIV prevention AI chatbot included an anonymous user setting; embedding the chatbot in MSM-friendly web-based platforms; and providing user-guiding questions and options related to HIV testing, prevention, and treatment. CONCLUSIONS: This study provides important insights into key features and potential implementation strategies central to designing an AI chatbot as a culturally sensitive digital health tool to prevent stigmatized health conditions in vulnerable and systematically marginalized populations. Such features not only are crucial to designing effective user-centered and culturally situated mobile health interventions for MSM in Malaysia but also illuminate the importance of incorporating social stigma considerations into health technology implementation strategies.

Venous Thromboembolic Events in African American Lupus Patients in Association With Antiphospholipid Antibodies Compared to White Patients.

OBJECTIVE: The risk of thrombotic events is elevated in patients with systemic lupus erythematosus (SLE) compared to the general population and has been attributed to both systemic inflammation and to the presence of antiphospholipid antibodies (aPLs). Our objective was to examine differences in aPL prevalence in White and African American patients with SLE and venous thromboembolic (VTE) events, and to compare inflammatory markers at the time of a VTE event. METHODS: Records of White and African American patients with SLE and VTE events were retrieved from a rheumatology practice based at an academic hospital. A clinically significant aPL profile was defined as anti-cardiolipin IgG/IgM and/or anti-ß2 -glycoprotein I IgG/IgM ≥40 units, and/or positive lupus anticoagulant ≥1.3. Logistic regression was used to determine predictors of a clinically significant aPL profile. RESULTS: Ninety-seven patients fulfilled American College of Rheumatology and/or 2012 Systemic Lupus Erythematosus International Collaborating Clinics classification criteria for SLE, had a history of VTE events, and had available aPL tests (59 White and 38 African American patients). African American patients were 66% less likely (95% confidence interval 0.12-0.96; P = 0.04) to have a clinically significant aPL profile compared to White patients in multivariable regression. Triple positivity was most frequent among White patients, while 7 of 8 African American patients had a positive lupus anticoagulant test. At the time of a VTE event, African American patients had significantly higher levels of anti-double-stranded DNA (P = 0.02), lower hemoglobin (P = 0.01), and higher erythrocyte sedimentation rate (P = 0.008). CONCLUSION: Among patients with SLE and VTE events, African American patients were less likely to have a clinically significant aPL profile compared to White patients, indicating that a negative aPL profile in African American patients does not decrease VTE risk.