Psychometric validation of the Chinese version of the Johns Hopkins Fall Risk Assessment Tool for older Chinese inpatients

Abstract

To culturally adapt and evaluate the reliability and validity of the Chinese version of the Johns Hopkins Fall Risk Assessment Tool among older inpatients in the mainland of China. Patient falls are an important safety consideration within hospitals among older inpatients. Nurses need specific risk assessment tools for older inpatients to reliably identify at-risk populations and guide interventions that highlight fixable risk factors for falls and consequent injuries. In China, a few tools have been developed to measure fall risk. However, they lack the solid psychometric development necessary to establish their validity and reliability, and they are not widely used for elderly inpatients. A cross-sectional study. A convenient sampling was used to recruit 201 older inpatients from two tertiary-level hospitals in Beijing and Xiamen, China. The Johns Hopkins Fall Risk Assessment Tool was translated using forward and backward translation procedures and was administered to these 201 older inpatients. Reliability of the tool was calculated by inter-rater reliability and Cronbach's alpha. Validity was analysed through content validity index and construct validity. The Inter-rater reliability of Chinese version of Johns Hopkins Fall Risk Assessment Tool was 97·14% agreement with Cohen's Kappa of 0·903. Cronbach's α was 0·703. Content of Validity Index was 0·833. Two factors represented intrinsic and extrinsic risk factors were explored that together explained 58·89% of the variance. This study provided evidence that Johns Hopkins Fall Risk Assessment Tool is an acceptable, valid and reliable tool to identify older inpatients at risk of falls and falls with injury. Further psychometric testing on criterion validity and evaluation of its advanced utility in geriatric clinical settings are warranted. The Chinese version of Johns Hopkins Fall Risk Assessment Tool may be useful for health care personnel to identify older Chinese inpatients at risk of falls and falls with injury.