Bridging the expectation–performance gap: how framing shapes older adults' intentions to engage with artificial intelligence health technologies.
Background and Objectives As China accelerates artificial intelligence (AI) integration in care of older adults to address population aging, understanding older adults' (65+) engagement with assistive technologies becomes imperative. However, their intention to engage with these innovations may be s...
| Publicado en: | Gerontologist Vol. 66; no. 7; pp. 1 - 12 |
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| Autores principales: | , , , |
| Formato: | Artículo |
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Oxford University Press / USA
Jul2026
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| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=195281398&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 195281398 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 00169013 GET jtl: Gerontologist issn: 00169013 maglogo: N pubinfo: dt: Jul2026 vid: 66 iid: 7 pid: 622 pub: Oxford University Press / USA artinfo: ui: 195281398 10.1093/geront/gnag025 ppf: 1 ppct: 11 formats: tig: atl: Bridging the expectation–performance gap: how framing shapes older adults' intentions to engage with artificial intelligence health technologies. aug: au: Zhu, Yanhan Zhou, Yaqi Xiong, Dan Chen, Zhuo affil: College of State Governance, Southwest University, Chongqing, China su: China Medical technology Artificial intelligence Decision making Emotions Psychology Social skills Analysis of variance Customer satisfaction Old age Statistical power analysis T-test (Statistics) Statistical sampling Attitudes toward computers Descriptive statistics Experimental design Intention Statistics Theory Medical care for older people Data analysis software sug: subj: Medical technology Artificial intelligence Decision making Emotions Psychology Social skills Analysis of variance Customer satisfaction Old age China Surgical and Medical Instrument Manufacturing Surgical Appliance and Supplies Manufacturing Medical, Dental, and Hospital Equipment and Supplies Merchant Wholesalers Marketing Research and Public Opinion Polling Statistical power analysis T-test (Statistics) Statistical sampling Attitudes toward computers Descriptive statistics Experimental design Intention Statistics Theory Medical care for older people Data analysis software keyword: aged aging AI adoption artificial intelligence Behavioral intention china copyrightHolder:The Gerontological Society of America copyrightYear:2026 Expectation confirmation https://dx.doi.org/10.1093/geront/gnag025 inLanguage:en Performance framing effects publisher:Oxford University Press sameAs:https://pubmed.ncbi.nlm.nih.gov/41849437/ self-help devices technology aged aging AI adoption artificial intelligence Behavioral intention china copyrightHolder:The Gerontological Society of America copyrightYear:2026 Expectation confirmation https://dx.doi.org/10.1093/geront/gnag025 inLanguage:en Performance framing effects publisher:Oxford University Press sameAs:https://pubmed.ncbi.nlm.nih.gov/41849437/ self-help devices technology ab: Background and Objectives As China accelerates artificial intelligence (AI) integration in care of older adults to address population aging, understanding older adults' (65+) engagement with assistive technologies becomes imperative. However, their intention to engage with these innovations may be significantly influenced by expectation confirmation, which refers to how individuals compare their initial expectations with their actual experience of use. This effect is shaped by framing—the way in which information is presented. This study extends Expectation-Confirmation theory by investigating (a) how expectation confirmation affects older adults' intention to use AI, and (b) whether the performance frame moderates this relationship. Research Design and Methods Through a 3 (expectation confirmation: positive or negative disconfirmation vs confirmation) × 3 (performance frame: positive or negative frame vs no frame) experiment (N = 291), we tested our hypotheses by manipulating experienced confirmation and descriptive frames of AI performance. Results Expectation confirmation significantly predicted the behavioral intention to use AI (F (2, 281) = 57.376, p < .001), and performance frame moderated this relationship (F (4, 275) = 2.830, p < .05). The positive frame mitigated the adverse effects of negative expectation disconfirmation and enhanced the effect of expectation confirmation. The absence of frame was most effective in stimulating the power of positive expectation disconfirmation. Discussion and Implications Our findings extend Expectation-Confirmation theory by identifying age-specific framing contingencies in AI adoption. Contrary to Technology Acceptance Model emphasizing perceived ease of use and usefulness, our results suggest expectation-frame also impacts older adults' AI adopting willingness. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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