ArticleJournal of medical Internet research2023
Investigating the Impact of User Trust on the Adoption and Use of ChatGPT: Survey Analysis.
Article in Journal of medical Internet research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07631585 (Longitudinal Pre-Post Patient AI Trust Dynamics in Orthopedic Outpatients), which is not on this map. Cited by 91 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Longitudinal Pre-Post Patient AI Trust Dynamics in Orthopedic Outpatients: A Mixed-Methods Observational Study With Matched Physician-Patient Dyads
Who cites it
91 citing papers in PubMed, 1 synthesis or guideline pooled it.
- From interface to outcome: a 4I framework for AI-linked functionality in electronic health records.BMC medical informatics and decision making · 2026Pooled it
- Trust in Generative AI for Health Information Consumption and the Effect of Learned Dependency: Randomized Controlled Experimental Study.Journal of medical Internet research · 2026Trial
- Effects of a Safety User Interface Bundle on Verification Intentions in Generative AI Chat Use Among Older Chinese Adults: Randomized Vignette Survey.Journal of medical Internet research · 2026Trial
- Artificial Intelligence Can Direct Patients Toward a Complaint-specific Musculoskeletal Provider.Journal of the American Academy of Orthopaedic Surgeons. Global research & reviews · 2026Article
- Development and psychometric validation of the AI chatbots acceptance and perception scale for higher education students.Scientific reports · 2026Article
- Factors Shaping Trust and Satisfaction With AI Medical Chatbots: A Mixed Methods Vignette Survey of Caregivers Seeking Guidance on Pediatric Infectious Diseases.Journal of medical Internet research · 2026Article
- Evaluating the quality, reliability and readability of digital and artificial intelligence resources for adults with cancer who have significant caregiving responsibilities for children.PLOS digital health · 2026Article
- Cognitive offloading, critical thinking and attitudes towards artificial intelligence in the era of ChatGPT: a comparative study of artificial intelligence-assisted and manual task performance in young adults.Cognitive processing · 2026Article
- Trust-driven healthy engagement with conversational AI for mental health support in young adults: a mixed methods study.Scientific reports · 2026Article
- Emotional Responses to AI-Powered Personalised Advertising: The Role of Perceived Empathy and Social Cognition in Consumer Decision-Making.Journal of Intelligence · 2026Article
- The role of interpersonal trust in public acceptance of AI-driven recruitment.Scientific reports · 2026Article
- Unlocking AI Chatbot Potential in Healthcare: Trust-Enhanced DeLone & McLean IS Success Model.Healthcare (Basel, Switzerland) · 2026Article
- Factors influencing college student intention to use ChatGPT with an integrated TAM and IDT model.Scientific reports · 2026Article
- Eye-Tracked Visual Attention to Anthropomorphic Appearance and Empathic Responses in AI Medical Conversational Agents: Dissociating Trust Gains from Attentional Synergy.Journal of eye movement research · 2026Article
- An Assessment of GPT-3.5 and GPT-4.0 Responses to Scoliosis FAQs.Journal of personalized medicine · 2026Article
- Medicine digital transformation: evidence from Chinese physicians on generative artificial intelligence implementation and challenges.Journal of translational medicine · 2026Article
- Assessing the educational quality of YouTube videos on celiac plexus blocks: Expert review and AI-based evaluation.Interventional pain medicine · 2026Article
- Developing a Quality Evaluation Index System for Health Conversational Artificial Intelligence: Mixed Methods Study.Journal of medical Internet research · 2026Article
- Attitudes toward large language model-based Artificial Intelligence systems as an information source for shared decision-making in radiation oncology.The oncologist · 2026Article
- Metaphors of AI indicate that people increasingly perceive AI as warm and human-like.Communications psychology · 2026Article
31 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundChatGPT (Chat Generative Pre-trained Transformer) has gained popularity for its ability to generate human-like responses. It is essential to note that overreliance or blind trust in ChatGPT, especially in high-stakes decision-making contexts, can have severe consequences. Similarly, lacking trust in the technology can lead to underuse, resulting in missed opportunities.
objectiveThis study investigated the impact of users' trust in ChatGPT on their intent and actual use of the technology. Four hypotheses were tested: (1) users' intent to use ChatGPT increases with their trust in the technology; (2) the actual use of ChatGPT increases with users' intent to use the technology; (3) the actual use of ChatGPT increases with users' trust in the technology; and (4) users' intent to use ChatGPT can partially mediate the effect of trust in the technology on its actual use.
methodsThis study distributed a web-based survey to adults in the United States who actively use ChatGPT (version 3.5) at least once a month between February 2023 through March 2023. The survey responses were used to develop 2 latent constructs: Trust and Intent to Use, with Actual Use being the outcome variable. The study used partial least squares structural equation modeling to evaluate and test the structural model and hypotheses.
resultsIn the study, 607 respondents completed the survey. The primary uses of ChatGPT were for information gathering (n=219, 36.1%), entertainment (n=203, 33.4%), and problem-solving (n=135, 22.2%), with a smaller number using it for health-related queries (n=44, 7.2%) and other activities (n=6, 1%). Our model explained 50.5% and 9.8% of the variance in Intent to Use and Actual Use, respectively, with path coefficients of 0.711 and 0.221 for Trust on Intent to Use and Actual Use, respectively. The bootstrapped results failed to reject all 4 null hypotheses, with Trust having a significant direct effect on both Intent to Use (β=0.711, 95% CI 0.656-0.764) and Actual Use (β=0.302, 95% CI 0.229-0.374). The indirect effect of Trust on Actual Use, partially mediated by Intent to Use, was also significant (β=0.113, 95% CI 0.001-0.227).
conclusionsOur results suggest that trust is critical to users' adoption of ChatGPT. It remains crucial to highlight that ChatGPT was not initially designed for health care applications. Therefore, an overreliance on it for health-related advice could potentially lead to misinformation and subsequent health risks. Efforts must be focused on improving the ChatGPT's ability to distinguish between queries that it can safely handle and those that should be redirected to human experts (health care professionals). Although risks are associated with excessive trust in artificial intelligence-driven chatbots such as ChatGPT, the potential risks can be reduced by advocating for shared accountability and fostering collaboration between developers, subject matter experts, and human factors researchers.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.