Artificial Intelligence Chatbot Research Articles

The Educational Recommendation System with Artificial Intelligence Chatbot: A Case Study in Thailand

The educational recommendation system with an artificial intelligence (AI) chatbot is a system designed to operate on smartphones and is intended for use at the College of Industrial Technology in Thailand. Compatible with both iOS and Android operating systems, the educational recommendation system in this research is capable of providing educational recommendations and valuable information about the engineering degree program. It includes information about the Electronics Engineering Technology Department, relevant bodies of knowledge that can enhance awareness and public relations, and a proactive introduction to information. The main objectives of this study are to develop the capacity to analyze educational issues and provide useful and accurate information for educational recommendations, as well as to explore the possibilities for enhancing this system. The results of the study address the three research questions and demonstrate that the process and structure of the educational recommendation system with an AI chatbot can be utilized to create educational recommendation tools in higher education. These tools are accessible anywhere and at any time through small mobile devices. The system is also compatible with popular social media applications and is capable of analyzing user questions precisely and accurately to find the optimal answers that can meet the user’s needs. However, there are still gaps in the research that need to be investigated in the future. These studies should include exploring a broader range of applications among the general population and educational settings to assess the effectiveness of the educational recommendation system with an AI chatbot. Additionally, they should examine the skills that impact the utilization of educational technology in various contexts.

Utilization of Artificial Intelligence (AI) Chatbots in Improving Public Services: A Meta-Analysis Study

Utilization of Artificial Intelligence (AI) Chatbots in Improving Public Services: A Meta-Analysis Study

Comparative analysis of artificial intelligence chatbot recommendations for urolithiasis management: A study of EAU guideline compliance

ObjectivesArtificial intelligence (AI) applications are increasingly being utilized by both patients and physicians for accessing medical information. This study focused on the urolithiasis section (pertaining to kidney and ureteral stones) of the European Association of Urology (EAU) guideline, a key reference for urologists. Material and methodsWe directed inquiries to four distinct AI chatbots to assess their responses in relation to guideline adherence. A total of 115 recommendations were transformed into questions, and responses were evaluated by two urologists with a minimum of 5 years of experience using a 5-point Likert scale (1 – False, 2 – Inadequate, 3 – Sufficient, 4 – Correct, and 5 – Very correct). ResultsThe mean scores for Perplexity and ChatGPT 4.0 were 4.68 (SD: 0.80) and 4.80 (SD: 0.47), respectively, both significantly differed the scores of Bing and Bard (Bing vs. Perplexity, P<0.001; Bard vs. Perplexity, P<0.001; Bing vs. ChatGPT, P<0.001; Bard vs. ChatGPT, P<0.001). Bing had a mean score of 4.21 (SD: 0.96), while Bard scored 3.56 (SD: 1.14), with a significant difference (Bing vs. Bard, P<0.001). Bard exhibited the lowest score among all chatbots. Analysis of references revealed that Perplexity and Bing cited the guideline most frequently (47.3% and 30%, respectively). ConclusionOur findings demonstrate that ChatGPT 4.0 and, notably, Perplexity align well with EAU guideline recommendations. These continuously evolving applications may play a crucial role in delivering information to physicians in the future, especially for urolithiasis.

Reliability of artificial intelligence chatbot responses to frequently asked questions in breast surgical oncology.

Artificial intelligence (AI)-driven chatbots, capable of simulating human-like conversations, are becoming more prevalent in healthcare. While this technology offers potential benefits in patient engagement and information accessibility, it raises concerns about potential misuse, misinformation, inaccuracies, and ethical challenges. This study evaluated a publicly available AI chatbot, ChatGPT, in its responses to nine questions related to breast cancer surgery selected from the American Society of Breast Surgeons' frequently asked questions (FAQ) patient education website. Four breast surgical oncologists assessed the responses for accuracy and reliability using a five-point Likert scale and the Patient Education Materials Assessment (PEMAT) Tool. The average reliability score for ChatGPT in answering breast cancer surgery questions was 3.98 out of 5.00. Surgeons unanimously found the responses understandable and actionable per the PEMAT criteria. The consensus found ChatGPT's overall performance was appropriate, with minor or no inaccuracies. ChatGPT demonstrates good reliability in responding to breast cancer surgery queries, with minor, nonharmful inaccuracies. Its answers are accurate, clear, and easy to comprehend. Notably, ChatGPT acknowledged its informational role and did not attempt to replace medical advice or discourage users from seeking input from a healthcare professional.

Evaluating ChatGPT Responses on Atrial Fibrillation for Patient Education.

Background ChatGPT is a language model that has gained widespread popularity for its fine-tuned conversational abilities. However, a known drawback to the artificial intelligence (AI) chatbot is its tendency to confidently present users with inaccurate information. We evaluated the quality of ChatGPT responses to questions pertaining to atrial fibrillation for patient education. Our analysis included the accuracy and estimated grade level of answers and whether references were provided for the answers. Methodology ChatGPT was prompted four times and 16 frequently asked questions on atrial fibrillation from the American Heart Association were asked. Prompts included Form 1 (no prompt), Form 2 (patient-friendly prompt), Form 3 (physician-level prompt), and Form 4 (prompting for statistics/references). Responses were scored as incorrect, partially correct, or correct with references (perfect). Flesch-Kincaid grade-level unique words and response lengths were recorded for answers. Proportions of the responses at differing scores were compared using the chi-square analysis. The relationship between form and grade level was assessed using the analysis of variance. Results Across all forms, scoring frequencies were one (1.6%) incorrect, five (7.8%) partially correct, 55 (85.9%) correct, and three (4.7%) perfect. Proportions of responses that were at least correct did not differ by form (p = 0.350), but perfect responses did (p = 0.001). Form 2 answers had a lower mean grade level (12.80 ± 3.38) than Forms 1 (14.23 ± 2.34), 3 (16.73 ± 2.65), and 4 (14.85 ± 2.76) (p < 0.05). Across all forms, references were provided in only three (4.7%) answers. Notably, when additionally prompted for sources or references, ChatGPT still only provided sources on three responses out of 16 (18.8%). Conclusions ChatGPT holds significant potential for enhancing patient education through accurate, adaptive responses. Its ability to alter response complexity based on user input, combined with high accuracy rates, supports its use as an informational resource in healthcare settings. Future advancements and continuous monitoring of AI capabilities will be crucial in maximizing the benefits while mitigating the risks associated with AI-driven patient education.

Mental Wellness Self-Care in Singapore With mindline.sg: A Tutorial on the Development of a Digital Mental Health Platform for Behavior Change.

Singapore, like the rest of Asia, faces persistent challenges to mental health promotion, including stigma around unwellness and seeking treatment and a lack of trained mental health personnel. The COVID-19 pandemic, which created a surge in mental health care needs and simultaneously accelerated the adoption of digital health solutions, revealed a new opportunity to quickly scale innovative solutions in the region. In June 2020, the Singaporean government launched mindline.sg, an anonymous digital mental health resource website that has grown to include >500 curated local mental health resources, a clinically validated self-assessment tool for depression and anxiety, an artificial intelligence (AI) chatbot from Wysa designed to deliver digital therapeutic exercises, and a tailored version of the website for working adults called mindline at work. The goal of the platform is to empower Singapore residents to take charge of their own mental health and to be able to offer basic support to those around them through the ease and convenience of a barrier-free digital solution. Website use is measured through click-level data analytics captured via Google Analytics and custom application programming interfaces, which in turn drive a customized analytics infrastructure based on the open-source platforms Titanium Database and Metabase. Unique, nonbounced (users that do not immediately navigate away from the site), engaged, and return users are reported. In the 2 years following launch (July 1, 2020, through June 30, 2022), the website received >447,000 visitors (approximately 15% of the target population of 3 million), 62.02% (277,727/447,783) of whom explored the site or engaged with resources (referred to as nonbounced visitors); 10.54% (29,271/277,727) of those nonbounced visitors returned. The most popular features on the platform were the dialogue-based therapeutic exercises delivered by the chatbot and the self-assessment tool, which were used by 25.54% (67,626/264,758) and 11.69% (32,469/277,727) of nonbounced visitors. On mindline at work, the rates of nonbounced visitors who engaged extensively (ie, spent ≥40 seconds exploring resources) and who returned were 51.56% (22,474/43,588) and 13.43% (5,853/43,588) over a year, respectively, compared to 30.9% (42,829/138,626) and 9.97% (13,822/138,626), respectively, on the generic mindline.sg site in the same year. The site has achieved desired reach and has seen a strong growth rate in the number of visitors, which required substantial and sustained digital marketing campaigns and strategic outreach partnerships. The site was careful to preserve anonymity, limiting the detail of analytics. The good levels of overall adoption encourage us to believe that mild to moderate mental health conditions and the social factors that underly them are amenable to digital interventions. While mindline.sg was primarily used in Singapore, we believe that similar solutions with local customization are widely and globally applicable.

From concerns to benefits: a comprehensive study of ChatGPT usage in education

Artificial Intelligence (AI) chatbots are increasingly becoming integral components of the digital learning ecosystem. As AI technologies continue to evolve, it is crucial to understand the factors influencing their adoption and use among students in higher education. This study is undertaken against this backdrop to explore the behavioral determinants associated with the use of the AI Chatbot, ChatGPT, among university students. The investigation delves into the role of ChatGPT’s self-learning capabilities and their influence on students’ knowledge acquisition and application, subsequently affecting the individual impact. It further elucidates the correlation of chatbot personalization with novelty value and benefits, underscoring their importance in shaping students’ behavioral intentions. Notably, individual impact is revealed to have a positive association with perceived benefits and behavioral intention. The study also brings to light potential barriers to AI chatbot adoption, identifying privacy concerns, technophobia, and guilt feelings as significant detractors from behavioral intention. However, despite these impediments, innovativeness emerges as a positive influencer, enhancing behavioral intention and actual behavior. This comprehensive exploration of the multifaceted influences on student behavior in the context of AI chatbot utilization provides a robust foundation for future research. It also offers invaluable insights for AI chatbot developers and educators, aiding them in crafting more effective strategies for AI integration in educational settings.

Artificial Intelligence Chatbot as a Mathematics Curriculum Developer: Discovering Preservice Teachers’ Overconfidence in ChatGPT

Artificial Intelligence Chatbot as a Mathematics Curriculum Developer: Discovering Preservice Teachers’ Overconfidence in ChatGPT

Unveiling the Potential of AI in Plastic Surgery Education: A Comparative Study of Leading AI Platforms' Performance on In-training Examinations.

Within the last few years, artificial intelligence (AI) chatbots have sparked fascination for their potential as an educational tool. Although it has been documented that one such chatbot, ChatGPT, is capable of performing at a moderate level on plastic surgery examinations and has the capacity to become a beneficial educational tool, the potential of other chatbots remains unexplored. To investigate the efficacy of AI chatbots in plastic surgery education, performance on the 2019-2023 Plastic Surgery In-service Training Examination (PSITE) was compared among seven popular AI platforms: ChatGPT-3.5, ChatGPT-4.0, Google Bard, Google PaLM, Microsoft Bing AI, Claude, and My AI by Snapchat. Answers were evaluated for accuracy and incorrect responses were characterized by question category and error type. ChatGPT-4.0 outperformed the other platforms, reaching accuracy rates up to 79%. On the 2023 PSITE, ChatGPT-4.0 ranked in the 95th percentile of first-year residents; however, relative performance worsened when compared with upper-level residents, with the platform ranking in the 12th percentile of sixth-year residents. The performance among other chatbots was comparable, with their average PSITE score (2019-2023) ranging from 48.6% to 57.0%. Results of our study indicate that ChatGPT-4.0 has potential as an educational tool in the field of plastic surgery; however, given their poor performance on the PSITE, the use of other chatbots should be cautioned against at this time. To our knowledge, this is the first article comparing the performance of multiple AI chatbots within the realm of plastic surgery education.

Utilising Artificial Intelligence Chatbots for Student Support at Comprehensive Open Distance E-learning Higher Learning Institutions in the Fifth Industrial Revolution

Abstract Artificial intelligence chatbot technology holds tremendous potential to be deployed as a student support service automation platform in comprehensive open distance e-learning institutions of higher learning in the Fifth Industrial Revolution. Inadequate support service provision to students at comprehensive open distance e-learning institutions of higher education has prompted this investigation into the use of artificial intelligence chatbot technology for the provision of student support services at comprehensive open distance e-learning higher education institutions in the Fifth Industrial Revolution. This qualitative study adopted content analysis as its research methodology, which is grounded in a literature review that incorporated insights from the researchers’ experiences with utilising artificial intelligence chatbots for student support in comprehensive open distance e-learning higher education institutions in the Fifth Industrial Revolution. The findings of the study indicate that artificial intelligence chatbot technology may be able to provide support services to students in a comprehensive open distance e-learning setting. Artificial intelligence chatbots can be utilised in the administration department to respond and make calls to students, as well as provide information about the application and registration processes, and assist students in this regard. Students could also use the artificial intelligence chatbots for learning and to conduct research. The study recommends a framework for the use of artificial intelligence chatbots for the provision of support services to students at comprehensive open distance e-learning higher education institutions in a new and emerging phase of industrialisation, namely the Fifth Industrial Revolution.

Accuracy of nine artificial intelligence chatbots in replying in accordance with the 2023 ESH guidelines for the management of arterial hypertension

Accuracy of nine artificial intelligence chatbots in replying in accordance with the 2023 ESH guidelines for the management of arterial hypertension

Enhancing Readability of Online Patient-Facing Content: The Role of AI Chatbots in Improving Cancer Information Accessibility.

Internet-based health education is increasingly vital in patient care. However, the readability of online information often exceeds the average reading level of the US population, limiting accessibility and comprehension. This study investigates the use of chatbot artificial intelligence to improve the readability of cancer-related patient-facing content. We used ChatGPT 4.0 to rewrite content about breast, colon, lung, prostate, and pancreas cancer across 34 websites associated with NCCN Member Institutions. Readability was analyzed using Fry Readability Score, Flesch-Kincaid Grade Level, Gunning Fog Index, and Simple Measure of Gobbledygook. The primary outcome was the mean readability score for the original and artificial intelligence (AI)-generated content. As secondary outcomes, we assessed the accuracy, similarity, and quality using F1 scores, cosine similarity scores, and section 2 of the DISCERN instrument, respectively. The mean readability level across the 34 websites was equivalent to a university freshman level (grade 13±1.5). However, after ChatGPT's intervention, the AI-generated outputs had a mean readability score equivalent to a high school freshman education level (grade 9±0.8). The overall F1 score for the rewritten content was 0.87, the precision score was 0.934, and the recall score was 0.814. Compared with their original counterparts, the AI-rewritten content had a cosine similarity score of 0.915 (95% CI, 0.908-0.922). The improved readability was attributed to simpler words and shorter sentences. The mean DISCERN score of the random sample of AI-generated content was equivalent to "good" (28.5±5), with no significant differences compared with their original counterparts. Our study demonstrates the potential of AI chatbots to improve the readability of patient-facing content while maintaining content quality. The decrease in requisite literacy after AI revision emphasizes the potential of this technology to reduce health care disparities caused by a mismatch between educational resources available to a patient and their health literacy.

Performance evaluation of ChatGPT in detecting diagnostic errors and their contributing factors: an analysis of 545 case reports of diagnostic errors

BackgroundManual chart review using validated assessment tools is a standardised methodology for detecting diagnostic errors. However, this requires considerable human resources and time. ChatGPT, a recently developed artificial intelligence chatbot...

End-of-life Care Patient Information Leaflets-A Comparative Evaluation of Artificial Intelligence-generated Content for Readability, Sentiment, Accuracy, Completeness, and Suitability: ChatGPT vs Google Gemini.

End-of-life care (EOLC) is a critical aspect of healthcare, yet accessing reliable information remains challenging, particularly in culturally diverse contexts like India. This study investigates the potential of artificial intelligence (AI) in addressing the informational gap by analyzing patient information leaflets (PILs) generated by AI chatbots on EOLC. Using a comparative research design, PILs generated by ChatGPT and Google Gemini were evaluated for readability, sentiment, accuracy, completeness, and suitability. Readability was assessed using established metrics, sentiment analysis determined emotional tone, accuracy, and completeness were rated by subject experts, and suitability was evaluated using the Patient Education Materials Assessment Tool (PEMAT). Google Gemini PILs exhibited superior readability and actionability compared to ChatGPT PILs. Both conveyed positive sentiments and high levels of accuracy and completeness, with Google Gemini PILs showing slightly lower accuracy scores. The findings highlight the promising role of AI in enhancing patient education in EOLC, with implications for improving care outcomes and promoting informed decision-making in diverse cultural settings. Ongoing refinement and innovation in AI-driven patient education strategies are needed to ensure compassionate and culturally sensitive EOLC. Gondode PG, Khanna P, Sharma P, Duggal S, Garg N. End-of-life Care Patient Information Leaflets-A Comparative Evaluation of Artificial Intelligence-generated Content for Readability, Sentiment, Accuracy, Completeness, and Suitability: ChatGPT vs Google Gemini. Indian J Crit Care Med 2024;28(6):561-568.

Assessing the readability, reliability, and quality of artificial intelligence chatbot responses to the 100 most searched queries about cardiopulmonary resuscitation: An observational study.

This study aimed to evaluate the readability, reliability, and quality of responses by 4 selected artificial intelligence (AI)-based large language model (LLM) chatbots to questions related to cardiopulmonary resuscitation (CPR). This was a cross-sectional study. Responses to the 100 most frequently asked questions about CPR by 4 selected chatbots (ChatGPT-3.5 [Open AI], Google Bard [Google AI], Google Gemini [Google AI], and Perplexity [Perplexity AI]) were analyzed for readability, reliability, and quality. The chatbots were asked the following question: "What are the 100 most frequently asked questions about cardio pulmonary resuscitation?" in English. Each of the 100 queries derived from the responses was individually posed to the 4 chatbots. The 400 responses or patient education materials (PEM) from the chatbots were assessed for quality and reliability using the modified DISCERN Questionnaire, Journal of the American Medical Association and Global Quality Score. Readability assessment utilized 2 different calculators, which computed readability scores independently using metrics such as Flesch Reading Ease Score, Flesch-Kincaid Grade Level, Simple Measure of Gobbledygook, Gunning Fog Readability and Automated Readability Index. Analyzed 100 responses from each of the 4 chatbots. When the readability values of the median results obtained from Calculators 1 and 2 were compared with the 6th-grade reading level, there was a highly significant difference between the groups (P < .001). Compared to all formulas, the readability level of the responses was above 6th grade. It can be seen that the order of readability from easy to difficult is Bard, Perplexity, Gemini, and ChatGPT-3.5. The readability of the text content provided by all 4 chatbots was found to be above the 6th-grade level. We believe that enhancing the quality, reliability, and readability of PEMs will lead to easier understanding by readers and more accurate performance of CPR. So, patients who receive bystander CPR may experience an increased likelihood of survival.

Can Artificial Intelligence "Hold" a Dermoscope?-The Evaluation of an Artificial Intelligence Chatbot to Translate the Dermoscopic Language.

This survey represents the first endeavor to assess the clarity of the dermoscopic language by a chatbot, unveiling insights into the interplay between dermatologists and AI systems within the complexity of the dermoscopic language. Given the complex, descriptive, and metaphorical aspects of the dermoscopic language, subjective interpretations often emerge. The survey evaluated the completeness and diagnostic efficacy of chatbot-generated reports, focusing on their role in facilitating accurate diagnoses and educational opportunities for novice dermatologists. A total of 30 participants were presented with hypothetical dermoscopic descriptions of skin lesions, including dermoscopic descriptions of skin cancers such as BCC, SCC, and melanoma, skin cancer mimickers such as actinic and seborrheic keratosis, dermatofibroma, and atypical nevus, and inflammatory dermatosis such as psoriasis and alopecia areata. Each description was accompanied by specific clinical information, and the participants were tasked with assessing the differential diagnosis list generated by the AI chatbot in its initial response. In each scenario, the chatbot generated an extensive list of potential differential diagnoses, exhibiting lower performance in cases of SCC and inflammatory dermatoses, albeit without statistical significance, suggesting that the participants were equally satisfied with the responses provided. Scores decreased notably when practical descriptions of dermoscopic signs were provided. Answers to BCC scenario scores in the diagnosis category (2.9 ± 0.4) were higher than those with SCC (2.6 ± 0.66, p = 0.005) and inflammatory dermatoses (2.6 ± 0.67, p = 0). Similarly, in the teaching tool usefulness category, BCC-based chatbot differential diagnosis received higher scores (2.9 ± 0.4) compared to SCC (2.6 ± 0.67, p = 0.001) and inflammatory dermatoses (2.4 ± 0.81, p = 0). The abovementioned results underscore dermatologists' familiarity with BCC dermoscopic images while highlighting the challenges associated with interpreting rigorous dermoscopic images. Moreover, by incorporating patient characteristics such as age, phototype, or immune state, the differential diagnosis list in each case was customized to include lesion types appropriate for each category, illustrating the AI's flexibility in evaluating diagnoses and highlighting its value as a resource for dermatologists.

Use of artificial intelligence chatbots in clinical management of immune-related adverse events

BackgroundArtificial intelligence (AI) chatbots have become a major source of general and medical information, though their accuracy and completeness are still being assessed. Their utility to answer questions surrounding immune-related...

생성형 인공지능 챗봇을 활용한 질의응답에 대한 대학생의 인식 차이

To effectively conduct question-and-answer sessions using a generative artificial intelligence chatbot in the context of educational technology, it is necessary to first examine the learners' perceptions. In this study, we analyzed the perception differences among 110 university students regarding question-and-answer interactions with instructors and ChatGPT. The research results revealed the following: First, the utility and trustworthiness of question-and-answer interactions were perceived higher for instructors, while ChatGPT demonstrated higher usability. Second, regardless of whether the questions were directed to ChatGPT or instructors, trustworthiness was consistently higher for instructors. Responses indicating a preference for asking instructors for language-related information were more prevalent than those favoring ChatGPT. This trend persisted even among the group that did not frequently ask questions to instructors. Third, only in the group that did not frequently ask questions to instructors scored higher in utility. This suggests that the perceived utility of instructors is more prominent in the group that refrains from posing questions to instructors. This study shows significance in providing foundational data on how to utilize ChatGPT as an effective question-and-answer instructional tool, particularly in the realm of educational technology.

Exploring the competence of artificial intelligence programs in the field of oculofacial plastic and orbital surgery

Aims: It aims to evaluate the knowledge level of ChatGPT, Bing, and Bard artificial intelligence chatbots developed based on Large Language Models (LLM) about oculofacial plastic surgery and to investigate the presence of superiority over each other. Methods: Twenty-nine questions that tested knowledge about oculofacial plastic and orbital surgery were taken from the study questions section of the American Academy and Ophthalmology 2022-2023 Basic and Clinical Science Course Oculofacial Plastic and Orbital Surgery. The questions were asked to ChatGPT, Bing, and Bard programs, which are current artificial intelligence chatbots. The questions were classified as either correct or incorrect. Results: ChatGPT gave 44.8% correct answers, Bing 48.3% correct answers, and Bard 58.6% correct answers to 29 questions about artificial intelligence chatbots. No statistical difference was observed between the rates of correct and incorrect answers given by 3 the intelligence programs (p=0.609, Pearson’s chi-squared test). Conclusion: The use of artificial intelligence to access information regarding oculofacial plastic and orbital surgery may provide limited benefits. Care should be taken in terms of accuracy and timeliness when evaluating the results of artificial intelligence programs.

The Impact of Performance Expectancy, Workload, Risk, and Satisfaction on Trust in ChatGPT: Cross-Sectional Survey Analysis.

ChatGPT (OpenAI) is a powerful tool for a wide range of tasks, from entertainment and creativity to health care queries. There are potential risks and benefits associated with this technology. In the discourse concerning the deployment of ChatGPT and similar large language models, it is sensible to recommend their use primarily for tasks a human user can execute accurately. As we transition into the subsequent phase of ChatGPT deployment, establishing realistic performance expectations and understanding users' perceptions of risk associated with its use are crucial in determining the successful integration of this artificial intelligence (AI) technology. The aim of the study is to explore how perceived workload, satisfaction, performance expectancy, and risk-benefit perception influence users' trust in ChatGPT. A semistructured, web-based survey was conducted with 607 adults in the United States who actively use ChatGPT. The survey questions were adapted from constructs used in various models and theories such as the technology acceptance model, the theory of planned behavior, the unified theory of acceptance and use of technology, and research on trust and security in digital environments. To test our hypotheses and structural model, we used the partial least squares structural equation modeling method, a widely used approach for multivariate analysis. A total of 607 people responded to our survey. A significant portion of the participants held at least a high school diploma (n=204, 33.6%), and the majority had a bachelor's degree (n=262, 43.1%). The primary motivations for participants to use ChatGPT were for acquiring information (n=219, 36.1%), amusement (n=203, 33.4%), and addressing problems (n=135, 22.2%). Some participants used it for health-related inquiries (n=44, 7.2%), while a few others (n=6, 1%) used it for miscellaneous activities such as brainstorming, grammar verification, and blog content creation. Our model explained 64.6% of the variance in trust. Our analysis indicated a significant relationship between (1) workload and satisfaction, (2) trust and satisfaction, (3) performance expectations and trust, and (4) risk-benefit perception and trust. The findings underscore the importance of ensuring user-friendly design and functionality in AI-based applications to reduce workload and enhance user satisfaction, thereby increasing user trust. Future research should further explore the relationship between risk-benefit perception and trust in the context of AI chatbots.