Jae Soon Yoo, Chul Gyu Kim, Chul Gyu Kim, Mi Yang Jeon
언어
영어(ENG)
URL
https://www.earticle.net/Article/A351807
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4,000원
원문정보
초록
영어
This study aimed to provide evidence for the development of an algo-rithm to identify older adults with a high risk for repeated falls, along with strategies to prevent repeated falls, by analyzing the known physi-cal, psychological, and environmental factors related to falls in older adults. One hundred fifty-seven community-dwelling older adults aged 65 years or older who experienced a fall within the past year were en-rolled in this study. Participants’ physical, psychological, environmental, and fall prevention-related characteristics were surveyed using struc-tured questionnaires to identify the risk factors for repeated falls. The use of antidepressants, depression score, and compliance with fall pre-vention behaviors were found to differ significantly between the two groups, and the use of antidepressants and depression were found to be significant predictors of repeated falls. Depression should be con-sidered as a major variable when developing an algorithm to identify the risk of repeated falls among older adults living at home. Also, the practice of fall prevention behaviors was higher in the repeated-falls group, likely due to that group’s efforts to prevent additional falls.
목차
Abstract INTRODUCTION MATERIALS AND METHODS Research design Participants Method Measurement of physical activity Measurement of fear of falling Measurement of depression Measurement of home environment safety Measurement of knowledge of falls Data analysis RESULTS Comparison of the demographic characteristics of the single-fall group and repeated-falls group Comparison of the physical characteristics of both groups Comparison of the psychological characteristics of both groups Comparison of the environmental characteristics of both groups Comparison of the fall prevention-related characteristics of both groups Actors affecting falls in both groups DISCUSSION CONFLICT OF INTEREST ACKNOWLEDGMENTS REFERENCES