{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,30]],"date-time":"2026-03-30T11:52:08Z","timestamp":1774871528900,"version":"3.50.1"},"reference-count":36,"publisher":"Wiley","issue":"2","license":[{"start":{"date-parts":[[2024,12,15]],"date-time":"2024-12-15T00:00:00Z","timestamp":1734220800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2024,12,15]],"date-time":"2024-12-15T00:00:00Z","timestamp":1734220800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Geriatrics Gerontology Int"],"published-print":{"date-parts":[[2025,2]]},"abstract":"<jats:sec>\n                    <jats:title>Aim<\/jats:title>\n                    <jats:p>Mobility restrictions cause older adults with musculoskeletal disorders to have lower levels of physical activity. However, the determinants of their physical activity during hospitalization are unclear. We aimed to compare two conceptual frameworks using structural equation modeling to identify factors influencing physical activity in older patients with musculoskeletal disorders.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>This cross\u2010sectional study included older patients with musculoskeletal disorders at a single convalescent rehabilitation hospital. Physical activity was objectively measured using a triaxial accelerometer. We utilized structural equation modeling to contrast two conceptual frameworks: (i) the sarcopenia\/nutrition\/activities of daily living model, and (ii) the age\u2010related deconditioning\/activities of daily living model. The models' goodness\u2010of\u2010fit was evaluated, including root mean square approximation error, goodness\u2010of\u2010fit index (GFI), adjusted GFI and Akaike information criterion.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>We enrolled 274 older patients (age 78.0\u2009years; 42 men, 232 women) with musculoskeletal disorders. Among them, 123 (44.9%) were diagnosed with sarcopenia and 69 (25.2%) with malnutrition. The goodness\u2010of\u2010fit of the (ii) model (root mean square approximation error\u2009=\u20090.068, GFI\u2009=\u20090.958, adjusted GFI\u2009=\u20090.909, Akaike information criterion\u2009=\u20095780.875) was superior to the (i) model (root mean square approximation error\u2009=\u20090.080, GFI\u2009=\u20090.953, adjusted GFI\u2009=\u20090.887, Akaike information criterion\u2009=\u20095791.429).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>\n                      We discovered that the age\u2010related deconditioning\/activities of daily living model effectively explained physical activity in hospitalized older patients with musculoskeletal disorders. A comprehensive approach considering age\u2010related changes, such as sarcopenia and malnutrition, might offer a simpler and more effective framework for understanding and promoting physical activity in this demographic.\n                      <jats:bold>Geriatr Gerontol Int 2025; 25: 160\u2013166<\/jats:bold>\n                      .\n                    <\/jats:p>\n                  <\/jats:sec>","DOI":"10.1111\/ggi.15022","type":"journal-article","created":{"date-parts":[[2024,12,16]],"date-time":"2024-12-16T02:22:07Z","timestamp":1734315727000},"page":"160-166","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Identifying determinants of physical activity in older patients with musculoskeletal disorders undergoing rehabilitation: Comparison of two distinct models using structural equation modeling"],"prefix":"10.1111","volume":"25","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0362-405X","authenticated-orcid":false,"given":"Masashi","family":"Kanai","sequence":"first","affiliation":[{"name":"Institute of Transdisciplinary Sciences for Innovation Kanazawa University  Kanazawa Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1701-6274","authenticated-orcid":false,"given":"Kazuki","family":"Yoshida","sequence":"additional","affiliation":[{"name":"Department of Rehabilitation Sciences, Faculty of Health Sciences Hokkaido University  Sapporo Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7844-9321","authenticated-orcid":false,"given":"Hiroki","family":"Okada","sequence":"additional","affiliation":[{"name":"Department of Rehabilitation Sciences, Faculty of Health Sciences Hokkaido University  Sapporo 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