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만성 뇌졸중 환자의 낙상 관련 자기 효능감을 이용한 낙상 위험 예측에 관한 연구

The Study on Predicting of Fall Incidence Using the Falls-related Efficacy Scale in People with Chronic Stroke

김우기|안승헌|박창식
특수교육재활과학연구소 (The Research Institute for Special Education & Rehabilitation Science)|2013.03|특수교육재활과학연구|제52권 제1호|pp. 241-258

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참고문헌

키워드

뇌졸중Stroke낙상Fall균형Fall down낙상관련 자기효능감Falls related self-efficacy
주제분류기타사회과학

초록

본 연구의 목적은 만성 뇌졸중 환자들의 낙상 관련 자기 효능감(Falls Efficacy Scale, FES)이 1회 또는 다발성 낙상군의 낙상을 예측하는데 변별력이 있는지 알아보고자 하였다. 뇌졸중 환자 63명을 대상으로 입원에서 퇴원까지 낙상 횟수를 기록하였고, 낙상 관련 자기효능감, 인지(Mini Mental State Examination-Korean version, MMSE-K), 우울증(Geriatric Depression Scale, GDS), 체간 조절(Trunk Impairment Scale, TIS), 하지 근력(Sit to Stand, STS), 마비측 상ㆍ하지 운동 기능(Fugl Meyer-Motor function of Upper/Lower Extremity), 동적 균형(Berg Balance Scale, BBS)과 이동성(Timed Up & Go test, TUG)을 평가하였다. 낙상에 따른 연구 대상자들의 일반의학적인 특성은 카이제곱 검정(χ²), 일원배치분산분석(one-way ANOVA)을 하였고, 수용자 작업특성곡선(Receiver operation characteristic curve, ROC curve)을 이용하여 낙상 예측에 관한 FES 최적의 선별 기준값(cutoff value)을 구하였고 낙상 예측 요인은 로지스틱 회귀분석(Logistic regression analysis; 전진 wald)을 실시하였다. 연구 결과 낙상 횟수가 많을수록 기능적 수행 능력에 제한이 있고, FES ≥14점은 1회 낙상, ≥34.5점은 다발성으로 낙상할 확률이 크다고 할 수 있다. 1회 낙상군은 FES, 다발성 낙상군은 FES와 GDS에 의해 영향을 받고 있으나 두 군 모두 FES에 영향을 받고 있으며, BBS, TUG, STS는 낙상을 예측하는 변수들로서 서로 밀접한 관련이 있었다. 따라서 만성 뇌졸중 환자들은 낙상의 재발을 방지하기 위해 낙상에 대한 두려움과 심리적 스트레스를 최소화 할 수 있는 치료 전략과 기능 훈련이 병행되어야 할 것이다.

Abstract

The purpose of this study was to investigate whether the use of falls efficacy scale for people with chronic stroke provided any discrimination of fall prediction to subjects who were having one (1) fall or multiple falls with chronic stroke. We recorded the number of falls that occurred during hospitalization for 69 subjects with chronic stroke studied, as well as the Falls Efficacy Scale(FES), Mini Mental State Examination-Korean version (MMSE-K), Geriatric Depression Scale(GDS), Trunk Impairment Scale(TIS), Sit to Stand(STS), Fugl Meyer- Motor function of Upper/Lower Extremity, Berg Balance Scale(BBS), and Timed Up & Go test(TUG) were estimated for the study. Chi-square statistics and one -way ANOVA were used to analyze demographic characteristics and measured value of the subjects. Receiver operation characteristic curve(ROC curve) was conducted to detect cutoff value of FES for fall prediction. To identify fall risk factor logistic regression analysis was used. The findings of this study were the following; first the subjects with the more numbers of falls had the more limited functional performance ability and we predicted that FES of ≥14 was associated with having 1 fall, FES of ≥34.5 was also associated with having multiple falls;second even though one (1) fall group was affected by FES, and multiple falls group was affected by FES and GDS, both groups were affected by FES and lastly all of BBS, TUG, and STS were significantly associated with each other as variables predicting fall incidence. Consequently, to prevent of falls we should provide chronic stroke patients with specific treatment strategy for minimizing fear and psychological stress of falling and functional training.

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