This is an Open Access article distributed under the terms of the Creative Commons Attribution NoDerivs License. (http://creativecommons.org/licenses/by-nd/4.0)If the original work is properly cited and retained without any modification or reproduction, it can be used and re-distributed in any format and medium. Purpose: The aim of this study was to explore characteristics of and risk factors for accidental inpatient falls. Methods: Participants were classified as fallers or non-fallers based on the fall history of inpatients in a tertiary hospital in Seoul between June 2014 and May 2015. Data on falls were obtained from the fall report forms and data on risk factors were obtained from the electronic nursing records. Characteristics of fallers and non-fallers were analyzed using descriptive statistics. Risk factors for falls were identified using univariate analyses and logistic regression analysis. Results: Average length of stay prior to the fall was 21.52 days and average age of fallers was 61.37 years. Most falls occurred during the night shifts and in the bedroom and were due to sudden leg weakness during ambulation. It was found that gender, BMI, physical problems such elimination, gait, vision and hearing and medications such as sleeping pills, antiarrhythmics, vasodilators, and muscle relaxant were statistically significant factors affecting falls. Conclusion: The findings show that there are significant risk factors such as BMI and history of surgery which are not part of fall assessment tools. There are also items on fall assessment tools which are not found to be significant such as mental status, emotional unstability, dizziness, and impairment of urination. Therefore, these various risk factors should be examined in the fall risk assessments and these risk factors should be considered in the development of fall assessment tools.
The purpose of this study was to translate and test reliability and validity of The Korean version of The Cornell Scale for Depression in Dementia (K-CSDD) used for assessing depression among impaired cognitive older adults. Methods: Original CSDD was translated into Korean and Linguistic contents were verified through back-translation procedures. The participants were 97 older adults reside in long-term care facilities. The participants were assessed using the Korean version of Mini-mental Status Examination (MMSE-K), The Korean version of the Hamilton Depression Rating Scale (K-HDRS), The short form of the Geriatric Depression Scale-Korean (SGDS-K), and K-CSDD. Results: In the reliability test, Cronbach's ⍺ coefficient and test-retest reliabilities were .78 and .48, respectively. In concurrent validity of the K-CSDD, there were significant correlations between the K-CSDD and K-HDRS (r=.78, p<.01). Factor analysis resulted in six factors accounting for 68.8% of the common variance. ROC curve analysis identified a cutoff score of 5 for the K-CSDD, where the sensitivity was 80.4% and the specificity was 89.0%. Conclusion: This study shows that K-CSDD is the reliable and valid scale for healthcare professionals to assess depression in cognitive impaired older adults in Korea.
This study was done objected to the chronic stroke patients in order to evaluate change in brain wave activity and cognitive performance when Neurofeedback training. The subjects were over 6 months ago in chronic stroke patients screened-test through the 20 patients, 10 persons in each group were randomly placed. This was carried out in 4 weeks in total, with control group(n=10) on general physical therapy and experimental group(n=10) on general physical therapy along with Neurofeedback training. The general physical therapy was applied 5 times a week, 30 minutes at once, Neurofeedback training was applied as equally as the general physical therapy, which makes 20 times in total. To learn about the effect before the training, after training, and 2 weeks after the training in electric physiological measurement method of the brain, electroencephalogram(EEG) to examine challenges by calculating the absolute spectrum power for standard EEG change(%), followed by evaluation with clinical assessment tool MMSE-K, Stroop Test, Digit Span Test. As a result of comparing the change in brain wave through EEG, after training and 2 weeks after training showed that absolute α-power and absolute β-SMR power of experimental group have increased and absolute θ-power decreased significantly compared to experimental group I. Moreover, the MMSE-K score in trial appraisal has increased significantly, and the error in Stroop Test and Digit Span Test has decreased significantly. such results, with the chronic stroke patient's brain wave control, Neurofeedback training was determined to improve the cognitive performance. this study suggests a new training possibility of stroke patients by identifying the training effects of Neurofeedback training that trains the brain directly with brain wave control.
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