{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,31]],"date-time":"2026-08-31T14:56:13Z","timestamp":1788188173902,"version":"build-2803163510"},"reference-count":33,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2026,5,11]],"date-time":"2026-05-11T00:00:00Z","timestamp":1778457600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2026,7,6]],"date-time":"2026-07-06T00:00:00Z","timestamp":1783296000000},"content-version":"vor","delay-in-days":56,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"name":"Orthogeriatric Research Fund"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["BMC Geriatr"],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Big data approaches are increasingly applied to hip fracture research, linking clinical, imaging, environmental and genomic data. Yet the views of older adults, whose data underpin these efforts, remain under-explored.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Focused, semi-structured interviews were conducted with older adults recruited from an orthopaedic ward at an inner city teaching hospital. Eligibility included age 60 years or older and a hip fracture within the previous three months. Fifteen participants took part. Interviews were audio recorded at the bedside, transcribed verbatim, anonymised and analysed using Braun and Clarke\u2019s reflexive thematic analysis.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Participants commonly reported limited familiarity with the term big data yet expressed broad support for its use in healthcare. Five themes described their perspectives: limited understanding alongside support for healthcare use; consent and trust as the moral foundation for sharing; altruism and social benefit; preference for treatment and recovery over prevention; and the importance of communication, comprehension and inclusion, including clear feedback and recognition of the digital divide. Hospitals and universities were the most trusted custodians. Governments and private companies elicited scepticism. Many viewed fractures as inevitable, which dampened enthusiasm for preventive analytics, while tangible improvements to treatment and coordination were strongly valued.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>There is clear acceptance of big data use amongst older adults with many perceived benefits. They prioritise trust, clear consent processes, visible public benefit and opportunities for feedback. Framing data initiatives around improving patient recovery and coordination of care, as well as communicating how fracture prevention supports independence, may strengthen social license. Ethical stewardship, transparency and co-design with older adults are essential to sustain confidence and ensure data-driven innovation delivers meaningful benefit.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1186\/s12877-026-07618-0","type":"journal-article","created":{"date-parts":[[2026,5,11]],"date-time":"2026-05-11T11:35:39Z","timestamp":1778499339000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Older adults\u2019 perspectives on big data use in hip fracture research: a qualitative study"],"prefix":"10.1186","volume":"26","author":[{"given":"Louis J.","family":"Koizia","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Su-Lee","family":"Xiao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8154-8953","authenticated-orcid":false,"given":"Benjamin H. L.","family":"Harris","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Michael B.","family":"Fertleman","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,5,11]]},"reference":[{"key":"7618_CR1","doi-asserted-by":"crossref","unstructured":"Roche JJ, Wenn RT, Sahota O, Moran CG. Effect of comorbidities and postoperative complications on mortality after hip fracture in elderly people: prospective observational cohort study. BMJ (Clinical Res ed.) 331, (2005).","DOI":"10.1136\/bmj.38643.663843.55"},{"key":"7618_CR2","doi-asserted-by":"crossref","unstructured":"Braithwaite RS, Col NF, Wong JB. Estimating hip fracture morbidity, mortality and costs. J Am Geriatr Soc 51, (2003).","DOI":"10.1046\/j.1532-5415.2003.51110.x"},{"key":"7618_CR3","doi-asserted-by":"crossref","unstructured":"Koizia LJ, Giovannantonio, Zhang P, Fertleman MB, Bh LH. 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