{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,24]],"date-time":"2026-09-24T21:20:51Z","timestamp":1790284851814,"version":"4.1.0"},"reference-count":38,"publisher":"SAGE Publications","license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"funder":[{"name":"Hong Kong Housing Society","award":["5-ZJJX"],"award-info":[{"award-number":["5-ZJJX"]}]}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["DIGITAL HEALTH"],"published-print":{"date-parts":[[2023,1]]},"abstract":"<jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>To examine the predictive attributes for accidental falls in community-dwelling older people in Hong Kong using decision tree analysis.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We recruited 1151 participants with an average age of 74.8 years by convenience sampling from a primary healthcare setting to carry out the cross-sectional study over 6 months. The whole dataset was divided into two sets, namely training set and test set, which respectively occupied 70% and 30% of the whole dataset. The training dataset was used first; decision tree analysis was used to identify possible stratifying variables that could help to generate separate decision models.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>The number of fallers was 230 with 20% 1-year prevalence. There were significant differences in gender, use of walking aids, presence of chronic diseases, and co-morbidities including osteoporosis, depression, and previous upper limb fractures, and performance in the Timed Up and Go test and the Functional Reach test among the baselines between the faller and non-faller groups. Three decision tree models for the dependent dichotomous variables (fallers, indoor fallers, and outdoor fallers) were generated, with overall accuracy rates of the models of 77.40%, 89.44% and 85.76%, respectively. Timed Up and Go, Functional Reach, body mass index, high blood pressure, osteoporosis, and number of drugs taken were identified as stratifying variables in the decision tree models for fall screening.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>The use of decision tree analysis for clinical algorithms for accidental falls in community-dwelling older people creates patterns for decision-making in fall screening, which also paves the way for utility-based decision-making using supervised machine learning in fall risk detection.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1177\/20552076231181202","type":"journal-article","created":{"date-parts":[[2023,6,8]],"date-time":"2023-06-08T01:40:13Z","timestamp":1686188413000},"update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":10,"title":["Factors associated with fall risk of community-dwelling older people: A decision tree analysis"],"prefix":"10.1177","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5909-4847","authenticated-orcid":false,"given":"Kenneth N K","family":"Fong","sequence":"first","affiliation":[{"name":"Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong SAR"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Raymond C K","family":"Chung","sequence":"additional","affiliation":[{"name":"Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong SAR"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Patrick P C","family":"Sze","sequence":"additional","affiliation":[{"name":"Elderly Resources Centre, Hong Kong Housing Society, Hong Kong SAR"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Carmen K M","family":"NG","sequence":"additional","affiliation":[{"name":"Elderly Resources Centre, Hong Kong Housing Society, Hong Kong SAR"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2023,6,7]]},"reference":[{"key":"bibr1-20552076231181202","unstructured":"HealthyHK \u2013 Public Health Information and Statistics of Hong Kong.\n                      Life expectancy\n                      . The Government of the Hong Kong SAR. Retrieved 10 January 2023 from https:\/\/www.healthyhk.gov.hk\/phisweb\/en\/chart_detail\/13\/"},{"key":"bibr2-20552076231181202","unstructured":"Dodwell D.\n                      Unlike in New York, Hong Kong\u2019s high-rise living has helped its communities thrive\n                      . South China Morning Post April 2022. Retrieved 10 January 2023 from https:\/\/www.scmp.com\/comment\/opinion\/article\/3177458\/unlike-new-york-hong-kongs-high-rise-living-has-helped-its"},{"key":"bibr3-20552076231181202","unstructured":"The Census and Statistics Department.\n                      Population and household statistics analysed by District Council District\n                      2021. The Government of the Hong Kong SAR Retrieved 10 January 2023 from http:\/\/www.censtat.gov.hk"},{"key":"bibr4-20552076231181202","doi-asserted-by":"publisher","DOI":"10.1016\/j.hkjot.2011.05.005"},{"key":"bibr5-20552076231181202","doi-asserted-by":"publisher","DOI":"10.15585\/mmwr.mm6537a2"},{"key":"bibr6-20552076231181202","doi-asserted-by":"publisher","DOI":"10.1056\/NEJMcp1903252"},{"key":"bibr7-20552076231181202","doi-asserted-by":"publisher","DOI":"10.1093\/ageing\/afac205"},{"key":"bibr8-20552076231181202","doi-asserted-by":"publisher","DOI":"10.1093\/ageing\/afl165"},{"key":"bibr9-20552076231181202","doi-asserted-by":"publisher","DOI":"10.1111\/j.1532-5415.2004.52416.x"},{"key":"bibr10-20552076231181202","doi-asserted-by":"publisher","DOI":"10.1111\/j.1532-5415.2007.01626.x"},{"key":"bibr11-20552076231181202","doi-asserted-by":"publisher","DOI":"10.1186\/s12889-022-14694-5"},{"key":"bibr12-20552076231181202","doi-asserted-by":"publisher","DOI":"10.1016\/j.jclinepi.2014.03.008"},{"key":"bibr13-20552076231181202","first-page":"25","volume":"4","author":"Chiu HFK","year":"1994","journal-title":"J Hong Kong College Psych"},{"key":"bibr14-20552076231181202","doi-asserted-by":"publisher","DOI":"10.1111\/j.1532-5415.2005.00509.x"},{"key":"bibr15-20552076231181202","volume-title":"Population and household statistics analysed by District Council District 2012","author":"Census and Statistics Department"},{"key":"bibr16-20552076231181202","volume-title":"WHO global report on falls prevention in older age","author":"World Health Organisation","year":"2007"},{"key":"bibr17-20552076231181202","doi-asserted-by":"publisher","DOI":"10.1111\/j.1532-5415.1991.tb01616.x"},{"key":"bibr18-20552076231181202","doi-asserted-by":"publisher","DOI":"10.1093\/geronj\/45.6.M192"},{"key":"bibr19-20552076231181202","doi-asserted-by":"publisher","DOI":"10.1007\/BF00422033"},{"key":"bibr20-20552076231181202","doi-asserted-by":"publisher","DOI":"10.1093\/gerona\/55.2.M70"},{"key":"bibr21-20552076231181202","doi-asserted-by":"publisher","DOI":"10.1093\/ptj\/80.9.896"},{"key":"bibr22-20552076231181202","doi-asserted-by":"publisher","DOI":"10.1002\/pri.150"},{"key":"bibr23-20552076231181202","unstructured":"Terry M, Elizabeth J, Mayo F.\n                      An introduction to recursive partitioning using the rpart routines\n                      . Accessed October 21, 2022 from https:\/\/cran.r-project.org\/web\/packages\/rpart\/vignettes\/longintro.pdf"},{"key":"bibr24-20552076231181202","first-page":"4832864","volume":"2021","author":"Nguyen QH","journal-title":"Math Probl Eng"},{"key":"bibr25-20552076231181202","doi-asserted-by":"publisher","DOI":"10.32614\/RJ-2014-008"},{"key":"bibr26-20552076231181202","doi-asserted-by":"publisher","DOI":"10.1191\/0269215506cr947oa"},{"key":"bibr27-20552076231181202","doi-asserted-by":"publisher","DOI":"10.1111\/j.1532-5415.2010.03234.x"},{"key":"bibr28-20552076231181202","unstructured":"Food and Health Bureau, Government Secretariat.\n                      Hong Kong reference framework for preventive care for older adults in primary care settings: module on falls in elderly\n                      2015. The Government of the Hong Kong Special Administrative Region; www.pco.gov.hk. (Accessed 15 Oct 2019)."},{"key":"bibr29-20552076231181202","doi-asserted-by":"publisher","DOI":"10.1093\/ageing\/afu157"},{"key":"bibr30-20552076231181202","doi-asserted-by":"publisher","DOI":"10.1093\/gerona\/gls190"},{"key":"bibr31-20552076231181202","doi-asserted-by":"publisher","DOI":"10.5812\/nms.10709"},{"key":"bibr32-20552076231181202","doi-asserted-by":"publisher","DOI":"10.1186\/1476-5918-7-4"},{"key":"bibr33-20552076231181202","doi-asserted-by":"publisher","DOI":"10.1016\/j.exger.2016.04.016"},{"key":"bibr34-20552076231181202","doi-asserted-by":"publisher","DOI":"10.1111\/1753-6405.12152"},{"key":"bibr35-20552076231181202","first-page":"127","author":"Gillain S","year":"2019","journal-title":"Exp Gerontol"},{"key":"bibr36-20552076231181202","first-page":"318","volume-title":"2011 Seventh international conference on intelligent environments","author":"Ojetola OE"},{"key":"bibr37-20552076231181202","unstructured":"Hoffmann J, Borgeaud S, Mensch A, et al.\n                      Training Compute-Optimal Large Language Models\n                      . arXiv, Mar. 29, 2022. 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