ArticleAddiction (Abingdon, England)2024
ChatGPT-4: Alcohol use disorder responses.
Article in Addiction (Abingdon, England), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed.
- Receptiveness to Formal and Informal Alcohol Intervention Approaches Among Emerging Adults Without Bachelor's Degrees.Substance use & misuse · 2026Article
- ChatGPT-4's Consistency, Specificity, and Inclusion of Behavior Change Techniques in Delivering Smoking Cessation Advice in Traditional Chinese: A Content Analysis.Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco · 2026Article
- Engaging Artificial Intelligence (AI)-based chatbots in digital health: A systematic review.PLOS digital health · 2026Article
- Initial testing of the College Parent Guide: an artificial intelligence chatbot to support parents in preventing college student drinking and reducing related risks.Journal of psychology and AI · 2026Article
- ChatGPT Clinical Use in Mental Health Care: Scoping Review of Empirical Evidence.JMIR mental health · 2025Article
- Article
- Can Large Language Models Address Problem Gambling? Expert Insights from Gambling Treatment Professionals.Journal of gambling studies · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
BACKGROUND AND
aimsAlcohol use disorder (AUD) is characterized by low levels of engagement with effective treatments. Enhancing awareness of AUD treatments and how to navigate the treatment system is crucial. Many individuals use online sources (e.g. search engines) for answers to health-related questions; web-based results include a mix of high- and low-quality information. Artificial intelligence may improve access to quality health information by providing concise, high-quality responses to complex health-related questions. This study evaluated the quality of ChatGPT-4 responses to AUD-related queries.
methodA comprehensive list of 64 AUD-related questions was developed through a combination of Google Trends analysis and expert consultation. ChatGPT-4 was prompted with each question, followed by a request to provide 3-5 peer-reviewed scientific citations supporting each response. Responses were evaluated for whether they were evidence-based, provided a referral and provided supporting documentation.
resultsChatGPT-4 responded to all AUD-related queries, with 92.2% (59/64) of responses being fully evidence-based. Although only 12.5% (8/64) of responses included referrals to external resources, all responses (100%; 5/5) to location-specific ('near me') queries directed individuals to appropriate resources like the NIAAA Treatment Navigator. Most (85.9%; 55/64) responses to the follow-up question provided supporting documentation.
conclusionsChatGPT-4 responds to alcohol use disorder-related questions with evidence-based information and supporting documentation. ChatGPT-4 could be promoted as a reasonable resource for those looking online for alcohol use disorder-related information.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.