{
  "abstract": "Background/objectives\n\nGenerative artificial intelligence is increasingly used by health professions students and by patients seeking health information before consultation. This creates two related educational challenges: supporting critical AI use during learning and preparing future clinicians to respond appropriately to hypothetical AI-informed patients. This study evaluated a teacher-designed seven-step ChatGPT-assisted framework for autonomic pharmacology learning and explored whether principles embedded in the framework were reflected in students' attitudes toward AI-informed patients.Methods\n\nIn this matched-cohort educational study, 104 third-year dental students were included. Students who voluntarily participated in the seven-step ChatGPT-assisted framework (n = 52) were individually matched with nonusers (n = 52) by previous academic achievement and digital-tool familiarity. The primary outcome was performance on a three-item open-ended pharmacology quiz assessing mechanistic reasoning, scored independently by two blinded assessors. Framework participants also completed an eight-item learning-perception questionnaire and a ten-item questionnaire addressing hypothetical AI-informed patients. Exploratory Spearman correlations examined conceptually matched learning- and patient-facing statements.Results\n\nFramework participants achieved higher postlearning pharmacology scores than matched nonusers (1.77 ± 0.30 vs. 1.45 ± 0.47; p = 0.0003). The largest difference was observed for questions requiring integration of receptor mechanisms and downstream signaling (+28%; p < 0.001), whereas factual drug-name recall did not differ (p = 0.47). Students generally recognized both the potential usefulness and limitations of ChatGPT and endorsed professional, nondismissive responses to hypothetical AI-informed patients. The perceived usefulness of ChatGPT for learning and writing was associated with recognition of the risk of patient overreliance on AI-generated diagnoses (ρ = 0.32, p = 0.019), while intention to use ChatGPT for learning was associated with endorsement of a serious and professional approach to patients presenting with ChatGPT-generated diagnoses (ρ = 0.40, p = 0.004).Conclusions\n\nParticipation in the structured framework was associated with stronger postlearning mechanistic pharmacology performance. The novel cross-context analysis identified limited but potentially meaningful alignment between responsible AI use in learning and professional attitudes toward hypothetical AI-informed patients. These exploratory associations do not demonstrate transfer of clinical communication competence, but suggest that verification, contextualization, risk awareness, and human oversight may provide a shared educational foundation for addressing AI use by both learners and patients.",
  "abstract_shown": true,
  "affiliations": [
    "Department of Pharmacology in Dentistry School of Dental Medicine University of Belgrade Belgrade Serbia bg.ac.rs.",
    "Clinic for Vascular and Endovascular Surgery of the University Serbian Clinical Center Belgrade Serbia."
  ],
  "article_type": "research article",
  "arxiv": null,
  "author_total": 3,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Jelena Roganović",
      "orcid": "0000-0002-2950-4056"
    },
    {
      "affs": [
        1
      ],
      "name": "Igor Končar",
      "orcid": "0000-0002-4873-2775"
    },
    {
      "affs": [
        0
      ],
      "name": "Milena Barać",
      "orcid": "0000-0002-2996-5450"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/5dqf0374wckfc.bib",
  "cited_by": 0,
  "doi": "10.1155/sci5/3725461",
  "fulltext_url": "https://europepmc.org/articles/PMC13689541",
  "id": "5dqf0374wckfc",
  "issns": [
    "2090-908X"
  ],
  "landing_url": "https://europepmc.org/article/MED/42924135",
  "language": "eng",
  "licence": "CC-BY",
  "licence_label": "CC BY",
  "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"
    ]
  ],
  "openalex": "W7223178038",
  "pdf_url": "https://europepmc.org/articles/PMC13689541?pdf=render",
  "pmcid": "PMC13689541",
  "pmid": "42924135",
  "published": "2026-10-22",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/5dqf0374wckfc.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:20:33Z",
      "native_id": "MED:42924135",
      "source": "europepmc",
      "url": "https://europepmc.org/article/MED/42924135"
    }
  ],
  "subjects": [
    {
      "field": "medicine",
      "origin": "openalex:2718|Artificial Intelligence in Healthcare and Education",
      "subfield": "epidemiology-public-health"
    }
  ],
  "title": "A Seven-Step Framework for Structured ChatGPT-Assisted Pharmacology Learning: Educational Outcomes and Attitudes Toward Hypothetical AI-Informed Patients.",
  "title_text": "A Seven-Step Framework for Structured ChatGPT-Assisted Pharmacology Learning: Educational Outcomes and Attitudes Toward Hypothetical AI-Informed Patients.",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T12:20:33Z",
  "url": "https://research.draconitic.com/paper/5dqf0374wckfc",
  "venue": "Scientifica",
  "versions": []
}