What factors predict user acceptance of ChatGPT for mental and physical healthcare: an extended technology acceptance model framework.
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| Title: | What factors predict user acceptance of ChatGPT for mental and physical healthcare: an extended technology acceptance model framework. |
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| Authors: | Kelly, Sage1, sage.kelly@hdr.qut.edu.au, Kaye, Sherrie-Anne1, White, Katherine M.1, Oviedo-Trespalacios, Oscar2 |
| Source: | AI & Society; Dec2025, Vol. 40 Issue 8, p6257-6275, 19p |
| Database: | Applied Science & Technology Source |
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| FullText | Links: – Type: pdflink Text: Availability: 1 |
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| Header | DbId: aci DbLabel: Applied Science & Technology Source An: 189358046 AccessLevel: 2 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1007/s00146-025-02334-6 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 19 StartPage: 6257 Titles: – TitleFull: What factors predict user acceptance of ChatGPT for mental and physical healthcare: an extended technology acceptance model framework. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Kelly, Sage – PersonEntity: Name: NameFull: Kaye, Sherrie-Anne – PersonEntity: Name: NameFull: White, Katherine M. – PersonEntity: Name: NameFull: Oviedo-Trespalacios, Oscar IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 12 Text: Dec2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 09515666 Numbering: – Type: volume Value: 40 – Type: issue Value: 8 Titles: – TitleFull: AI & Society Type: main |
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