Predictive Effects of Previous Fall History on Accuracy of Fall Risk Assessment Tool in Acute Care Settings

Park, Ihn Sook

doi:10.7739/jkafn.2012.19.4.444

Cited by 2 publications

(2 citation statements)

References 20 publications

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“…Fourth, fall history is a risk factor item used in the MFS and JHFRAT, patients with a history of falling having a 2.2 times higher fall-risk. This is consistent with studies by Park (2012);Ruchinskas (2003); and Vassallo et al (2005). Park (2012) pointed out that patients with a history of falling were 9 times more likely to fall again, emphasising that those with a fall history or an experience of falling in the hospital should be categorised in the high-risk group at the time of admission and be provided with nursing interventions accordingly.…”

Section: Discussionsupporting

confidence: 88%

“…This is consistent with studies by Park (2012);Ruchinskas (2003); and Vassallo et al (2005). Park (2012) pointed out that patients with a history of falling were 9 times more likely to fall again, emphasising that those with a fall history or an experience of falling in the hospital should be categorised in the high-risk group at the time of admission and be provided with nursing interventions accordingly. Thus, it is necessary to raise awareness of the significance of accurate fall history reporting in the patient or caregiver interview process and to review the history of fall-risk assessment in previous hospital admissions or check the history of unreported falls by physical examination.…”

Section: Discussionsupporting

confidence: 88%

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Comparison of the predictive validity of three fall risk assessment tools and analysis of fall‐risk factors at a tertiary teaching hospital

Cho

Woo

Han

et al. 2020

Journal of Clinical Nursing

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Aims and objectives The main purpose of this study was to identify the best fall‐risk assessment tool, among the Morse Fall Scale, the Johns Hopkins fall‐risk Assessment Tool and the Hendrich II fall‐risk Model, for a tertiary teaching hospital. The study also analysed fall‐risk factors in the hospital, focusing on the items of each fall assessment tool. Methods Data on falls were obtained from the patient safety reports and electronic nursing records of a tertiary teaching hospital. A retrospective study was conducted to compare the sensitivity, specificity, area under the curve, positive predictive value, negative predictive value, Youden index and accuracy of the Morse Fall Scale, the Johns Hopkins fall‐risk Assessment Tool and the Hendrich II fall‐risk Model. This study was conducted according to the Strengthening the Reporting of Observational Studies in Epidemiology guideline for reporting case–control studies. Results By analysing the association between falls and the items included in the three tools, we identified significant fall‐risk factors such as gait, dizziness or vertigo, changes in mental status, impulsivity, history of falling, elimination disorder, drugs affecting falls, and depression. Conclusions The Hendrich II fall‐risk Model had the best predictive performance for falls of the three tools, considering the highest in the area under the curve and the Youden index that comprehensively analysed sensitivity and specificity, while the Johns Hopkins fall‐risk Assessment Tool had the highest accuracy. The most significant fall‐risk predictors are gait, dizziness or vertigo, change in mental state, and history of falling. Relevance to clinical practice To improve the fall assessment performance of the Morse Fall Scale at the study hospital, we propose that it be supplemented with four most significant fall‐risk predictors identified in this study.

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Section: Discussionsupporting

confidence: 88%

Section: Discussionsupporting

confidence: 88%

Comparison of the predictive validity of three fall risk assessment tools and analysis of fall‐risk factors at a tertiary teaching hospital

Cho

Woo

Han

et al. 2020

Journal of Clinical Nursing

View full text Add to dashboard Cite

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Menstruation and the Variability of Food Intake in Female College Students

강수화¹,

이영미²

2013

Korean J Community Nutr

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This study aimed to elicit the variability of appetite and food intake patterns in female college students during different menstrual phases. The craving for certain foods and physiological and psychological symptoms of menstrual phase (pre-and post-menstrual) were investigated by self-administered questionnaire. Three hundred and sixty six students who were 20.9 years old and had 19.8 kg/m 2 of BMI volunteered to participate in this study. Most of the subjects (89.5%) experienced the premenstrual syndrome (PMS) such as irritation, bodily fatigue, nervosity. Symptoms such as tiredness, stomachache, changes in taste and increased appetite were pointed out to be experienced at the onset of the menstrual cycle. The variability of food intake in premenstrual phase, 11.0% of subjects had decreased food intake where as 68.8% had experienced increased intake. The postmenstrual phase, 20.1% had decreased food intake while 45.2% had experienced increased intake due to changes in the appetite. Before starting menstruation, most of the subjects craved for sweets. The group who had experienced abnormal appetite during menstrual phase was significantly high ratio in overweight and obese students (p < 0.05). We also observed an association between the PMS score and the variability of eating patterns during the menstrual phase. The students who experienced changing appetite and food intake had significantly high PMS score in the premenstrual phase (p < 0.01) and postmenstrual phase (p < 0.05). These results suggested a need for future study related to changes in the actual nutrient intake and activity level during the menstrual phase. (Korean J Community Nutr 18(6) : 577~587, 2013)

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Predictive Effects of Previous Fall History on Accuracy of Fall Risk Assessment Tool in Acute Care Settings

Cited by 2 publications

References 20 publications

Comparison of the predictive validity of three fall risk assessment tools and analysis of fall‐risk factors at a tertiary teaching hospital

Comparison of the predictive validity of three fall risk assessment tools and analysis of fall‐risk factors at a tertiary teaching hospital

Menstruation and the Variability of Food Intake in Female College Students

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