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Fall Prediction Model for Community-dwelling Elders based on Gender
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Eun Suk Yun
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J Korean Acad Nurs 2012;42(6):810-818. Published online December 31, 2012
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DOI: https://doi.org/10.4040/jkan.2012.42.6.810
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 Abstract
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Purpose
This study was done to explore factors relating to number of falls among community-dwelling elders, based on gender.
Methods
Participants were 403 older community dwellers (male=206, female=197) aged 60 or above. In this study, 8 variables were identified as predictive factors that can result in an elderly person falling and as such, supports previous studies. The 8 variables were categorized as, exogenous variables; perceived health status, somatization, depression, physical performance, and cognitive state, and endogenous variables; fear of falling, ADL & IADL and frequency of falls.
Results
For men, ability to perform ADL & IADL (β32=1.84, p<.001) accounted for 16% of the variance in the number of falls. For women, fear of falling (β31=0.14, p<.05) and ability to perform ADL & IADL (β32=1.01, p<.001) significantly contributed to the number of falls, accounting for 15% of the variance in the number of falls.
Conclusion
The findings from this study confirm the gender-based fall prediction model as comprehensive in relation to community-dwelling elders. The fall prediction model can effectively contribute to future studies in developing fall prediction and intervention programs.
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Citations
Citations to this article as recorded by  - Development of a fall prediction model for community-dwelling older adults in South Korea using machine learning: a secondary data analysis
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