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The models answered a binary question about acceptance towards patient-prioritization or a 5-point Likert question on concern about amyloid-related imaging abnormalities (ARIA) under varied prompt settings. Aggregate similarity was measured with Jensen-Shannon Divergence (JSD) for binary and Earth Mover's Distance (EMD) for Likert scale; while individual agreement used Cohen's\u202f\u03ba and Spearman's\u202f\u03c1.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>While some LLM models achieved fair group-level agreement in both tasks (JSD\u2009\u2264\u20090.05, EMD\u2009&lt;\u20091.0), individual agreement was negligible across any LLM settings (\u03ba,\u202f\u03c1\u202f\u2248\u202f0). Adding detailed attributes like living condition, clinical status, or related personal opinions offered limited improvement. Performance was largely stable for most demographic levels, but deteriorated for minority subgroups, such as those with low education or requiring long-term care.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Our study demonstrates that current LLMs can approximate aggregate attitudes toward novel AD therapies but cannot predict individual opinions. They can amplify biases in some small subgroups. LLMs may be useful for pre-testing public survey in the field of AD\/dementia treatment but should not replace authentic human data.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1177\/13872877261464182","type":"journal-article","created":{"date-parts":[[2026,6,27]],"date-time":"2026-06-27T11:09:52Z","timestamp":1782558592000},"page":"1904-1919","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":1,"title":["Potential and biases of large language model simulation for public surveys on Alzheimer's disease therapies"],"prefix":"10.1177","volume":"112","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4351-9526","authenticated-orcid":false,"given":"Kenichiro","family":"Sato","sequence":"first","affiliation":[{"name":"The University of Tokyo Hospital"},{"name":"The University of Tokyo Hospital"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yoshiki","family":"Niimi","sequence":"additional","affiliation":[{"name":"The University of Tokyo Hospital"},{"name":"The University of Tokyo Hospital"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ryoko","family":"Ihara","sequence":"additional","affiliation":[{"name":"Tokyo Metropolitan Institute for Geriatrics and Gerontology"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kazushi","family":"Suzuki","sequence":"additional","affiliation":[{"name":"National Defense Medical College"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7308-5314","authenticated-orcid":false,"given":"Atsushi","family":"Iwata","sequence":"additional","affiliation":[{"name":"Tokyo Metropolitan Institute for Geriatrics and Gerontology"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Takeshi","family":"Iwatsubo","sequence":"additional","affiliation":[{"name":"The University of Tokyo Hospital"},{"name":"The University of Tokyo Hospital"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2026,6,27]]},"reference":[{"key":"e_1_3_3_2_2","doi-asserted-by":"publisher","DOI":"10.1017\/pan.2023.2"},{"key":"e_1_3_3_3_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.isci.2024.109713"},{"key":"e_1_3_3_4_2","doi-asserted-by":"publisher","DOI":"10.1287\/mksc.2025.0262"},{"key":"e_1_3_3_5_2","doi-asserted-by":"crossref","unstructured":"Li A Chen H Namkoong H et al. 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