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This cross-sectional online survey examined factors influencing the acceptability of these technologies among 472 UK adults, considering demographics, digital literacy, healthcare access, familiarity with DHs and VAs, personality traits, and attitudes.<\/jats:p>\n                  <jats:p>VA acceptability was assessed using logistic regression, with willingness to use VAs as the outcome variable. Lower acceptance was found among women, ethnic minorities, those with lower education levels, and individuals who infrequently searched for health information online. Conversely, higher acceptance was associated with engagement in online health discussions, greater awareness and use of VAs, perceived usefulness, fewer perceived barriers, and openness. DH acceptability was analysed through multiple regression, with attitudes toward DHs as the outcome variable. More positive attitudes were linked to White\/Irish\/European ethnicity, a greater perceived need for in-person care, participation in online health discussions, higher conscientiousness, and lower neuroticism, explaining 27.8% of the variance. Although 85.8% had used VAs and 82.2% owned one, only 25.8% reported daily use. Awareness of DHs was reported by 70.3% of participants, with attitudes generally positive (median score: 2.17\/5, where lower scores indicate greater favourability). Institutional endorsement was a key factor, with 71.2% stating they would use VAs for healthcare if approved by the NHS. These findings support technology acceptance models, highlighting the roles of perceived usefulness, ease of use, and awareness. Culturally responsive design principles that address these factors may enhance adoption across diverse groups. Distinct personality traits influenced acceptance, with openness predicting VA acceptability, while conscientiousness and low neuroticism were associated with more positive attitudes toward DHs. While offering novel insights into human factors influencing AI adoption in healthcare, the study is limited by its reliance on proxy measures for acceptance.<\/jats:p>","DOI":"10.1007\/s00146-025-02332-8","type":"journal-article","created":{"date-parts":[[2025,4,19]],"date-time":"2025-04-19T13:33:54Z","timestamp":1745069634000},"page":"6783-6797","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Exploring acceptability of AI-enabled voice assistants and digital AI humans in healthcare: a cross-sectional survey"],"prefix":"10.1007","volume":"40","author":[{"given":"Oliver","family":"Miles","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sofia","family":"Pinckard","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Murat","family":"Gungor","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Damien","family":"Ridge","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tom","family":"Nadarzynski","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,4,19]]},"reference":[{"issue":"1","key":"2332_CR1","doi-asserted-by":"publisher","first-page":"15266","DOI":"10.1038\/s41598-022-19501-0","volume":"12","author":"E Abdi","year":"2022","unstructured":"Abdi E, Tojib D, Seong AK, Pamarthi Y, Millington-Palmer G (2022) A study on the influence of service robots\u2019 level of anthropomorphism on the willingness of users to follow their recommendations. 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