Stephen Beegle, Luis A Gomez, Jason T Blackard, Bingfang Yan, Jaime Robertson, Kevin T Fedders, Shaina Horner, Ramsey Miller, Chavez R Rodriguez, Abby Atreya, Jennifer L Brown
{"title":"四个人工智能平台的艾滋病防治信息专题分析","authors":"Stephen Beegle, Luis A Gomez, Jason T Blackard, Bingfang Yan, Jaime Robertson, Kevin T Fedders, Shaina Horner, Ramsey Miller, Chavez R Rodriguez, Abby Atreya, Jennifer L Brown","doi":"10.1007/s10461-025-04786-9","DOIUrl":null,"url":null,"abstract":"<p><p>Health information is highly accessible with the prominence of artificial intelligence (AI) platforms, such as Chat Generative Pre-Trained Transformer (ChatGPT). Within the context of human immunodeficiency virus (HIV), it is paramount to understand and evaluate the information being provided by AI platforms concerning the safety, side effects, and efficacy of medications to prevent and treat HIV. Prompts (n = 38) requesting information regarding HIV medication use for prevention and treatment were inputted into three AI-based Large Language Models (LLMs; ChatGPT 3.5, ChatGPT 4.0, Google Bard [now Gemini]) and one chatbot (HIV.gov Chatbot) on four consecutive weeks. Outputs (n = 608) were recorded verbatim, weekly by platform. Qualitative analyses using a conventional content analysis coding approach examined key themes in responses; response comprehensiveness was rated via the number of themes represented in a response. Core themes emerged across prompts. A recommendation to speak with a medical professional for further information was the most common theme across platforms. Organ/bone side effects were the most prevalent side effect. Responses pointed to medication efficacy to prevent and treat HIV. ChatGPT 4.0 provided the most comprehensive responses across platforms, while the HIV.gov Chatbot gave the least comprehensive information. Health information on HIV medication safety, side effects, and efficacy is widely available using AI platforms. Results indicate that AI responses typically included recommendations to consult a medical professional to personalize care. The efficacy of medications was never questioned across AI platforms. Future research directions for AI use within the context of HIV prevention and care are provided.</p>","PeriodicalId":7543,"journal":{"name":"AIDS and Behavior","volume":" ","pages":""},"PeriodicalIF":2.4000,"publicationDate":"2025-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"HIV Prevention and Treatment Information from Four Artificial Intelligence Platforms: A Thematic Analysis.\",\"authors\":\"Stephen Beegle, Luis A Gomez, Jason T Blackard, Bingfang Yan, Jaime Robertson, Kevin T Fedders, Shaina Horner, Ramsey Miller, Chavez R Rodriguez, Abby Atreya, Jennifer L Brown\",\"doi\":\"10.1007/s10461-025-04786-9\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Health information is highly accessible with the prominence of artificial intelligence (AI) platforms, such as Chat Generative Pre-Trained Transformer (ChatGPT). Within the context of human immunodeficiency virus (HIV), it is paramount to understand and evaluate the information being provided by AI platforms concerning the safety, side effects, and efficacy of medications to prevent and treat HIV. Prompts (n = 38) requesting information regarding HIV medication use for prevention and treatment were inputted into three AI-based Large Language Models (LLMs; ChatGPT 3.5, ChatGPT 4.0, Google Bard [now Gemini]) and one chatbot (HIV.gov Chatbot) on four consecutive weeks. Outputs (n = 608) were recorded verbatim, weekly by platform. Qualitative analyses using a conventional content analysis coding approach examined key themes in responses; response comprehensiveness was rated via the number of themes represented in a response. Core themes emerged across prompts. A recommendation to speak with a medical professional for further information was the most common theme across platforms. Organ/bone side effects were the most prevalent side effect. Responses pointed to medication efficacy to prevent and treat HIV. ChatGPT 4.0 provided the most comprehensive responses across platforms, while the HIV.gov Chatbot gave the least comprehensive information. Health information on HIV medication safety, side effects, and efficacy is widely available using AI platforms. Results indicate that AI responses typically included recommendations to consult a medical professional to personalize care. The efficacy of medications was never questioned across AI platforms. Future research directions for AI use within the context of HIV prevention and care are provided.</p>\",\"PeriodicalId\":7543,\"journal\":{\"name\":\"AIDS and Behavior\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":2.4000,\"publicationDate\":\"2025-06-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"AIDS and Behavior\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1007/s10461-025-04786-9\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"AIDS and Behavior","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1007/s10461-025-04786-9","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH","Score":null,"Total":0}
HIV Prevention and Treatment Information from Four Artificial Intelligence Platforms: A Thematic Analysis.
Health information is highly accessible with the prominence of artificial intelligence (AI) platforms, such as Chat Generative Pre-Trained Transformer (ChatGPT). Within the context of human immunodeficiency virus (HIV), it is paramount to understand and evaluate the information being provided by AI platforms concerning the safety, side effects, and efficacy of medications to prevent and treat HIV. Prompts (n = 38) requesting information regarding HIV medication use for prevention and treatment were inputted into three AI-based Large Language Models (LLMs; ChatGPT 3.5, ChatGPT 4.0, Google Bard [now Gemini]) and one chatbot (HIV.gov Chatbot) on four consecutive weeks. Outputs (n = 608) were recorded verbatim, weekly by platform. Qualitative analyses using a conventional content analysis coding approach examined key themes in responses; response comprehensiveness was rated via the number of themes represented in a response. Core themes emerged across prompts. A recommendation to speak with a medical professional for further information was the most common theme across platforms. Organ/bone side effects were the most prevalent side effect. Responses pointed to medication efficacy to prevent and treat HIV. ChatGPT 4.0 provided the most comprehensive responses across platforms, while the HIV.gov Chatbot gave the least comprehensive information. Health information on HIV medication safety, side effects, and efficacy is widely available using AI platforms. Results indicate that AI responses typically included recommendations to consult a medical professional to personalize care. The efficacy of medications was never questioned across AI platforms. Future research directions for AI use within the context of HIV prevention and care are provided.
期刊介绍:
AIDS and Behavior provides an international venue for the scientific exchange of research and scholarly work on the contributing factors, prevention, consequences, social impact, and response to HIV/AIDS. This bimonthly journal publishes original peer-reviewed papers that address all areas of AIDS behavioral research including: individual, contextual, social, economic and geographic factors that facilitate HIV transmission; interventions aimed to reduce HIV transmission risks at all levels and in all contexts; mental health aspects of HIV/AIDS; medical and behavioral consequences of HIV infection - including health-related quality of life, coping, treatment and treatment adherence; and the impact of HIV infection on adults children, families, communities and societies. The journal publishes original research articles, brief research reports, and critical literature reviews. provides an international venue for the scientific exchange of research and scholarly work on the contributing factors, prevention, consequences, social impact, and response to HIV/AIDS. This bimonthly journal publishes original peer-reviewed papers that address all areas of AIDS behavioral research including: individual, contextual, social, economic and geographic factors that facilitate HIV transmission; interventions aimed to reduce HIV transmission risks at all levels and in all contexts; mental health aspects of HIV/AIDS; medical and behavioral consequences of HIV infection - including health-related quality of life, coping, treatment and treatment adherence; and the impact of HIV infection on adults children, families, communities and societies. The journal publishes original research articles, brief research reports, and critical literature reviews.5 Year Impact Factor: 2.965 (2008) Section ''SOCIAL SCIENCES, BIOMEDICAL'': Rank 5 of 29 Section ''PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH'': Rank 9 of 76