{
  "abstract": "Background: The diffusion of large-language-model (LLM) chatbots such as ChatGPT has introduced a new layer to the digital health information ecosystem, alongside search engines, social media, and national mobile-health (mHealth) platforms. The actual prevalence of AI chatbot-based self-diagnosis among Saudi university students, the ecosystem of tools they choose, and the factors that predict use are not well characterised.\n\nObjectives: To estimate AI chatbot use for self-diagnosis among Saudi university students, map the ecosystem of tools used, characterise attitudes and perceived superiority over traditional search, identify predictors through logistic regression, and surface qualitative themes.\n\nMethods: A cross-sectional online survey was administered to 511 Saudi university students between April and May 2024. Instruments included a binary item on prior self-diagnosis use, a multi-response item on AI tools used, an 8-item AI Chatbot Perceived Superiority scale, a 15-item AI Doctor Chatbot Attitudes and Trust scale, five multi-response items, and three open-ended items analysed thematically. Data were analysed using descriptive statistics, multivariable logistic regression, Mann–Whitney U/Kruskal-Wallis tests, tool co-use analysis, and latent class analysis. The study received IRB approval from Qassim University (No. 23-19-02).\n\nResults: ChatGPT was the dominant tool ( n = 355), followed by Google Gemini ( n = 197), Microsoft Copilot ( n = 166), and the Ministry of Health’s Sehhaty AI chatbot ( n = 154). Multivariable logistic regression identified three independent predictors: gender [female vs. male, adjusted OR = 0.32, 95% CI (0.20, 0.52), p < 0.001], age (per step OR = 1.24, p = 0.080), and specialty (Health vs. Education OR = 6.71, p < 0.001). AI was rated easier and faster than search engines ( M = 3.51) and more comprehensive (M = 3.43). Privacy concerns were prominent ( M = 3.69); 65.1% endorsed institutionally verified AI chatbots. Tool co-use analysis showed the seven AI tools were used largely independently (max phi = 0.12).\n\nConclusion: AI doctor chatbots have already become mainstream tools for self-diagnosis among Saudi university students, with ChatGPT dominating but the Sehhaty AI chatbot already in active use. Male students and those in Health, Management, Social Science, and Engineering are substantially more likely to use AI. The strong endorsement of institutionally verified chatbots provides a clear policy signal for embedding safe, MOH-aligned LLM tools within Sehhaty under Vision 2030.",
  "abstract_shown": true,
  "affiliations": [
    "Department of Health Informatics, College of Applied Medical Sciences, Qassim University",
    "Health Information Management and Technology Department, College of Applied Medical Sciences, King Faisal University"
  ],
  "article_type": "research article",
  "arxiv": null,
  "author_total": 2,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Haitham Alzghaibi"
    },
    {
      "affs": [
        1
      ],
      "name": "Manahil Alfuraydan"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/cg8dqjsb7xzfy.bib",
  "cited_by": 0,
  "doi": "10.3389/fpubh.2026.1899249",
  "fulltext_url": "https://europepmc.org/articles/PMC13692922",
  "id": "cg8dqjsb7xzfy",
  "issns": [
    "2296-2565"
  ],
  "landing_url": "https://www.frontiersin.org/articles/10.3389/fpubh.2026.1899249/full",
  "language": "eng",
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "openalex",
      "2718|Artificial Intelligence in Healthcare and Education"
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  "openalex": "W7221086269",
  "pdf_url": "https://europepmc.org/articles/PMC13692922?pdf=render",
  "pmcid": "PMC13692922",
  "pmid": "42921363",
  "published": "2026-10-08",
  "publisher": "Frontiers Media SA",
  "ris": "https://research.draconitic.com/paper/cg8dqjsb7xzfy.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:20:22Z",
      "native_id": "10.3389/fpubh.2026.1899249",
      "source": "crossref",
      "url": "https://www.frontiersin.org/articles/10.3389/fpubh.2026.1899249/full"
    },
    {
      "first_seen": "2026-10-30T12:20:36Z",
      "native_id": "MED:42921363",
      "source": "europepmc",
      "url": "https://europepmc.org/article/MED/42921363"
    }
  ],
  "subjects": [
    {
      "field": "medicine",
      "origin": "openalex:2718|Artificial Intelligence in Healthcare and Education",
      "subfield": "epidemiology-public-health"
    }
  ],
  "title": "AI chatbots for health information-seeking and self-diagnosis among Saudi university students: patterns of use, predictors, attitudes, and trust",
  "title_text": "AI chatbots for health information-seeking and self-diagnosis among Saudi university students: patterns of use, predictors, attitudes, and trust",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T12:20:36Z",
  "url": "https://research.draconitic.com/paper/cg8dqjsb7xzfy",
  "venue": "Frontiers in Public Health",
  "versions": []
}