Search Results (13)

Background/Objectives: With advancements in Large Language Models (LLMs), counseling chatbots are becoming essential tools for delivering scalable and accessible mental health support. Traditional evaluation scales, however, fail to adequately capture the sophisticated capabilities of these systems, such as personalized interactions, empathetic responses, and memory retention. This study aims to design a robust and comprehensive evaluation scale, the Comprehensive Evaluation Scale for LLM-Powered Counseling Chatbots (CES-LCC), using the eDelphi method to address this gap. Methods: A panel of 16 experts in psychology, artificial intelligence, human-computer interaction, and digital therapeutics participated in two iterative eDelphi rounds. The process focused on refining dimensions and items based on qualitative and quantitative feedback. Initial validation, conducted after assembling the final version of the scale, involved 49 participants using the CES-LCC to evaluate an LLM-powered chatbot delivering Self-Help Plus (SH+), an Acceptance and Commitment Therapy-based intervention for stress management. Results: The final version of the CES-LCC features 27 items grouped into nine dimensions: Understanding Requests, Providing Helpful Information, Clarity and Relevance of Responses, Language Quality, Trust, Emotional Support, Guidance and Direction, Memory, and Overall Satisfaction. Initial real-world validation revealed high internal consistency (Cronbach’s alpha = 0.94), although minor adjustments are required for specific dimensions, such as Clarity and Relevance of Responses. Conclusions: The CES-LCC fills a critical gap in the evaluation of LLM-powered counseling chatbots, offering a standardized tool for assessing their multifaceted capabilities. While preliminary results are promising, further research is needed to validate the scale across diverse populations and settings. Full article

The integration of generative AI (GenAI) in school-based mental health services presents new opportunities and challenges. This study focuses on the challenges of using GenAI chatbots as therapeutic tools by exploring secondary school students’ perceptions of such applications. The data were collected from students who had both theoretical and practical experience with GenAI. Based on Grodniewicz and Hohol’s framework highlighting the “Problem of a Confused Therapist”, “Problem of a Non-human Therapist”, and “Problem of a Narrowly Intelligent Therapist”, qualitative data from student reflections were examined using thematic analysis. The findings revealed that while students acknowledged AI’s benefits, such as accessibility and non-judgemental feedback, they expressed significant concerns about a lack of empathy, trust, and adaptability. The implications underscore the need for AI chatbot use to be complemented by in-person counselling, emphasising the importance of human oversight in AI-augmented mental health care. This study contributes to a deeper understanding of how advanced AI can be ethically and effectively incorporated into school mental health frameworks, balancing technological potential with essential human interaction. Full article

Background: Pharmacists need up-to-date knowledge and decision-making support in HIV care. We aim to develop MARVIN-Pharma, an adapted artificial intelligence-based chatbot initially for people with HIV, to assist pharmacists in considering evidence-based needs. Methods: From December 2022 to December 2023, an online needs-assessment survey evaluated Québec pharmacists’ knowledge, attitudes, involvement, and barriers relative to HIV care, alongside perceptions relevant to the usability of MARVIN-Pharma. Recruitment involved convenience and snowball sampling, targeting National HIV and Hepatitis Mentoring Program affiliates. Results: Forty-one pharmacists (28 community, 13 hospital-based) across 15 Québec municipalities participated. Participants perceived their HIV knowledge as moderate (M = 3.74/6). They held largely favorable attitudes towards providing HIV care (M = 4.02/6). They reported a “little” involvement in the delivery of HIV care services (M = 2.08/5), most often ART adherence counseling, refilling, and monitoring. The most common barriers reported to HIV care delivery were a lack of time, staff resources, clinical tools, and HIV information/training, with pharmacists at least somewhat agreeing that they experienced each (M ≥ 4.00/6). On average, MARVIN-Pharma’s acceptability and compatibility were in the ‘undecided’ range (M = 4.34, M = 4.13/7, respectively), while pharmacists agreed to their self-efficacy to use online health services (M = 5.6/7). Conclusion: MARVIN-Pharma might help address pharmacists’ knowledge gaps and barriers to HIV treatment and care, but pharmacist engagement in the chatbot’s development seems vital for its future uptake and usability. Full article

The IMPACT-FH study implemented strategies (packet, chatbot, direct contact) to promote family member cascade testing for familial hypercholesterolemia (FH). We evaluated the impact of genetic counseling (GC) on medical outcomes, strategy selection, and cascade testing. Probands (i.e., patients with FH) were recommended to complete GC and select sharing strategies. Comparisons were performed for both medical outcomes and strategy selection between probands with or without GC. GEE models for Poisson regression were used to examine the relationship between proband GC completion and first-degree relative (FDR) cascade testing. Overall, 46.3% (81/175) of probands completed GC. Probands with GC had a median LDL-C reduction of −13.0 mg/dL (−61.0, 4.0) versus −1.0 mg/dL (−16.0, 17.0) in probands without GC (p = 0.0054). Probands with and without GC selected sharing strategies for 65.3% and 40.3% of FDRs, respectively (p < 0.0001). Similarly, 27.1% of FDRs of probands with GC completed cascade testing, while 12.0% of FDRs of probands without GC completed testing (p = 0.0043). Direct contact was selected for 47 relatives in total and completed for 39, leading to the detection of 18 relatives with FH. Proband GC was associated with improved medical outcomes and increased FDR cascade testing. Direct contact effectively identified FH cases for the subset who participated. Full article

Background: Artificial intelligence (AI)-based chatbots have shown promise in providing counseling to patients with metabolic dysfunction-associated steatotic liver disease (MASLD). While ChatGPT3.5 has demonstrated the ability to comprehensively answer MASLD-related questions in English, its accuracy remains suboptimal. Whether language influences these results is unclear. This study aims to assess ChatGPT’s performance as a counseling tool for Italian MASLD patients. Methods: Thirteen Italian experts rated the accuracy, completeness and comprehensibility of ChatGPT3.5 in answering 15 MASLD-related questions in Italian using a six-point accuracy, three-point completeness and three-point comprehensibility Likert’s scale. Results: Mean scores for accuracy, completeness and comprehensibility were 4.57 ± 0.42, 2.14 ± 0.31 and 2.91 ± 0.07, respectively. The physical activity domain achieved the highest mean scores for accuracy and completeness, whereas the specialist referral domain achieved the lowest. Overall, Fleiss’s coefficient of concordance for accuracy, completeness and comprehensibility across all 15 questions was 0.016, 0.075 and −0.010, respectively. Age and academic role of the evaluators did not influence the scores. The results were not significantly different from our previous study focusing on English. Conclusion: Language does not appear to affect ChatGPT’s ability to provide comprehensible and complete counseling to MASLD patients, but accuracy remains suboptimal in certain domains. Full article

Artificial intelligence (AI) is rapidly transforming the field of medicine, announcing a new era of innovation and efficiency. Among AI programs designed for general use, ChatGPT holds a prominent position, using an innovative language model developed by OpenAI. Thanks to the use of deep learning techniques, ChatGPT stands out as an exceptionally viable tool, renowned for generating human-like responses to queries. Various medical specialties, including rheumatology, oncology, psychiatry, internal medicine, and ophthalmology, have been explored for ChatGPT integration, with pilot studies and trials revealing each field’s potential benefits and challenges. However, the field of genetics and genetic counseling, as well as that of rare disorders, represents an area suitable for exploration, with its complex datasets and the need for personalized patient care. In this review, we synthesize the wide range of potential applications for ChatGPT in the medical field, highlighting its benefits and limitations. We pay special attention to rare and genetic disorders, aiming to shed light on the future roles of AI-driven chatbots in healthcare. Our goal is to pave the way for a healthcare system that is more knowledgeable, efficient, and centered around patient needs. Full article

Glaucoma, the leading cause of irreversible blindness worldwide, comprises a group of progressive optic neuropathies requiring early detection and lifelong treatment to preserve vision. Artificial intelligence (AI) technologies are now demonstrating transformative potential across the spectrum of clinical glaucoma care. This review summarizes current capabilities, future outlooks, and practical translation considerations. For enhanced screening, algorithms analyzing retinal photographs and machine learning models synthesizing risk factors can identify high-risk patients needing diagnostic workup and close follow-up. To augment definitive diagnosis, deep learning techniques detect characteristic glaucomatous patterns by interpreting results from optical coherence tomography, visual field testing, fundus photography, and other ocular imaging. AI-powered platforms also enable continuous monitoring, with algorithms that analyze longitudinal data alerting physicians about rapid disease progression. By integrating predictive analytics with patient-specific parameters, AI can also guide precision medicine for individualized glaucoma treatment selections. Advances in robotic surgery and computer-based guidance demonstrate AI’s potential to improve surgical outcomes and surgical training. Beyond the clinic, AI chatbots and reminder systems could provide patient education and counseling to promote medication adherence. However, thoughtful approaches to clinical integration, usability, diversity, and ethical implications remain critical to successfully implementing these emerging technologies. This review highlights AI’s vast capabilities to transform glaucoma care while summarizing key achievements, future prospects, and practical considerations to progress from bench to bedside. Full article

Religion-based AI chatbots serve religious practitioners by bringing them godly wisdom through technology. These bots reply to spiritual and worldly questions by drawing insights or citing verses from the Quran, the Bible, the Bhagavad Gita, the Torah, or other holy books. They answer religious and theological queries by claiming to offer historical contexts and providing guidance and counseling to their users. A criticism of these bots is that they may give inaccurate answers and proliferate bias by propagating homogenized versions of the religions they represent. These “embodied spiritual machines” may likewise bear bias against women, their gender, and their societal roles. This paper crafts a concept intended to address this GPT issue by reimagining, modifying, and implementing a feminist approach to these chatbots. It examines the concepts and designs of these bots and how they address women-related questions. Along with the challenge of bringing gender and diversity-sensitive religious wisdom closer to the people through technology, the paper proposes a re-engineered model of a fair religion-based AI chatbot. Full article

Depression disorder is a disease that causes a deterioration of daily function and can induce thoughts of suicide. The Diagnostic and Statistical Manual of Mental Disorders Fifth Edition (DSM-5), which is the official reference of the American Psychiatry Association and is also used in Korea to identify depressive disorders, sets nine criteria for diagnosing depressive disorders. The lack of counseling personnel, including psychiatrists, and negative social perceptions of depressive disorders prevent counselors from being treated for depressive disorders. Natural language processing-based artificial intelligence (AI) services such as chatbots can help fill this need, but labeled datasets are needed to train AI services. In this study we collected data from AI Hub wellness consultations and crawls of the Reddit website to augment and build word dictionaries and analyze morphemes using the Kind Korean Morpheme Analyzer and Word2Vec. The collected datasets were labeled based on word dictionaries built according to nine DSM-5 depressive disorder diagnostic criteria. Full article

Nutritional status is one of the most relevant prognostic factors in Amyotrophic Lateral Sclerosis (ALS), and close monitoring can help avoid severe weight loss over the disease course. We describe the impact of a Chatbot webapp on improving the communications between physicians, patients, and/or caregivers for dietary monitoring. We developed a chatbot that provides patients with a tool to register their meals through an intuitive and carefully designed conversational interface. Patients recorded their dietary intake twice weekly and received an adequate nutritional recommendation monthly. We monitored their functional and nutritional parameters. The data were compared with a control group followed up by standard counseling. We enrolled 26 patients. Regarding feasibility, 96% of participants completed the three-month follow-up, and 77% ended the six months. Regarding the change in weight in the Chatbot group, we observed a weight stabilization (F = 1.874, p-value: 0.310 for changes) over the telehealth compared to the control group (F = 1.710, p-value: 0.024 for changes). A telehealth approach for nutritional support is feasible and reproducible in an ALS setting: frequent monitoring turned out to help prevent further weight loss, allowing an early nutritional strategy adjustment. Full article

College students encounter various types of stresses in school due to schoolwork, personal relationships, health issues, and future career concerns. Some students are susceptible to the strikes of failures and are inexperienced with or fearful of dealing with setbacks. When these negative emotions gradually accumulate without resolution, they can cause long-term negative effects on students’ physical and mental health. Some potential health problems include depression, anxiety, and disorders such as eating disorders. Universities commonly offer counseling services; however, the demand often exceeds the counseling capacities due to limited numbers of counsellors/psychologists. Thus, students may not receive immediate counseling or treatments. If students are not treated, some repercussions may lead to severe abnormal behavior and even suicide. In this study, combining immersive virtual reality (VR) technique with psychological knowledge base, we developed a VR empathy-centric counseling chatbot (VRECC) that can complementarily support troubled students when counsellors cannot provide immediate support. Through multi-turn (verbal or text) conversations with the chatbot, the system can demonstrate empathy and give therapist-like responses to the users. During the study, more than 120 students were required to complete a questionnaire and 34 subjects with an above-median stress level were randomly drawn for the VRECC experiment. We observed decreasing average stress level and psychological sensitivity scores among subjects after the experiment. Although the system did not yield improvement in life-impact scores (e.g., behavioral and physical impacts), the significant outcomes of lowering stress level and psychological sensitivity have given us a very positive outlook for continuing to integrate VR, AI sentimental natural language process, and counseling chatbot for advanced VRECC research in helping students improve their psychological well-being and life quality at schools. Full article

Extended and immersive gamified pharmacy simulation has been demonstrated to provide transformative learning in pharmacy education, preparing graduates for real-world practice. An international consortium of universities has implemented local adaptations of the Pharmacy Game into their curricula. From early 2020, pharmacy academics modified the delivery of gamified simulation in response to the COVID-19 pandemic, while still aiming to deliver the important learning outcomes of enhanced communication, collaboration, confidence and competence. Australian universities went into full lockdown from March 2020, and the critical gamified simulation at Griffith University was delivered entirely virtually in 2020. An array of synchronous and asynchronous approaches and software platforms was employed, including Microsoft Teams, Forms and Stream plus the online interview platform Big Interview. These allowed for the simulation activities, including dispensing, counselling and clinical cases, to be conducted by students online. In 2021, Griffith University conducted hybrid delivery of its Pharmacy Game, balancing student participation both in person and online. Microsoft Power Apps was added to the hosting platform to enhance the simulation interface, and Power Virtual Agent artificial intelligence chatbots, with natural language processing, were used to enable asynchronous clinical interaction. The combination of learning technologies provided the means to deliver successful gamified simulation in the virtual and hybrid environments while still achieving outstanding learning outcomes from the capstone activity. This paper details the technologies used to virtualize the Australian Pharmacy Game and the analytics available to educators to assess student participation, engagement and performance. Full article

Student life causes many sources of stress due to the requirements of managing schoolwork, family, friends, health and wellbeing, and future career planning. Some students are overwhelmed and lack resilience to overcome stress, especially if they are inexperienced in managing setbacks, fail to achieve expectations, or lack skills to independently manage social skills, recreation, and study time. The long-term accumulation of stress has a negative impact on students’ physical and mental health, and may lead to a range of symptoms such as depression, anxiety, headache, insomnia, and eating disorders. Although most universities provide psychological counseling services, there is often a shortage of professional psychologists, which leads to students suffering from stress for longer than necessary without immediate assistance. The build-up of stress can lead to tragic consequences including abnormal reasoning, anti-social behavior, and suicide. There should never be a need for a student to wait more than a month to make an appointment for counseling services and every request for help should be immediately addressed and assessed. In this research, we designed a unique test platform for an immersive virtual reality group chatbot counseling system so students can receive psychological help and stress management counseling anytime and anywhere. First, the research used questionnaires to measure the stress levels and identifies how stress affects their lives. An immersive virtual reality chatbot was developed using professional psychological counseling knowledge that can provide answers during individual or group counseling sessions. Students can log in to the platform as avatars and ask the chatbot questions or interact with other students on the platform. This research provides college students with a new technology-based counseling environment designed to help relieve stress and learn new ways to improve student life quality from others. The platform provides a test base for future clinical trials to evaluate and improve the automated virtual reality chatbot counseling system. Full article