Chou Shu-Ping, Hung Tsui-Mei
MSN, RN, Supervisor, Department of Nursing, Taipei City Hospital, Songde Branch, Taiwan, ROC.
MSN, RN, Chief Director, Department of Nursing, Taipei City Hospital, Songde Branch, Taiwan, ROC.
Hu Li Za Zhi. 2019 Jun;66(3):35-45. doi: 10.6224/JN.201906_66(3).06.
The incidence of falls is very high among psychiatric inpatients. However, the lack of an effective, validated psychiatric inpatient fall risk assessment tool inhibits the ability of medical staffs to make correct judgments.
The purposes of this study were to compare the sensitivity, specificity, and accuracy of the psychiatric inpatient fall risk assessment tool (PIFRAT) and the Wilson-Sims fall risk assessment tool (WSFRAT) and to predict the fall risk factors in PIFRAT and WSFRAT for psychiatric inpatients.
Study data were collected from 2016/10/01 to 2017/03/10. Fall assessment data were collected from new patients during their 1st through 7th days after admission to a psychiatry unit in northern Taiwan. Data were analyzed using descriptive analysis, logistic regression analysis, reliability and validity testing, tool effective testing, and receiver operating characteristic (ROC) curve analysis.
Both of the fall risk assessment tools exhibited low sensitivity (WSFRAT 57.1%, PIFRAT 50%), the specificity of WSFRAT (79.6%) was higher than that of PIFRAT (70.4%), and the accuracy of WSFRAT (76.9%) was higher than that of PIFRAT (67.9%). The ROC curve analysis revealed that the AUC of PIFRAT was .602 (95% CI [0.48, 0.73]). According to the Youden index, the best cutoff level is 7.5 points, in which the specificity is 88.8% and the sensitivity is 39.3%. To increase the sensitivity to 96.4%, the cutoff level must be set to 1.5 points. Moreover, the AUC of WSFRAT was .625 and the highest sensitivity was 82.1% when the cutoff point was set to 3.5 points. Further, multivariate logistic regression analysis revealed that fall risk was significantly higher among patients who had previously fallen than among those had not. Male gender (OR = 2.57, 95% CI [1.11, 5.94]), physical activity difficulties (OR = 3.43; 95% CI [1.40, 8.41]), and weakness (OR = 3.03; 95% CI [1.08, 8.49]) were each significantly associated with fall risk.
CONCLUSIONS / IMPLICATIONS FOR PRACTICE: This study identified four critical risk factors for falls. In the future, clinical healthcare professionals should be more aware of these factors and develop related fall-prevention interventions. The findings may serve as references for the future development of psychiatric fall assessment tools.
精神科住院患者跌倒发生率很高。然而，缺乏有效的、经过验证的精神科住院患者跌倒风险评估工具，这影响了医护人员做出正确判断的能力。
本研究旨在比较精神科住院患者跌倒风险评估工具（PIFRAT）和威尔逊 - 西姆斯跌倒风险评估工具（WSFRAT）的敏感性、特异性和准确性，并预测PIFRAT和WSFRAT中精神科住院患者的跌倒风险因素。
研究数据收集于2016年10月1日至2017年3月10日。跌倒评估数据收集自台湾北部一家精神科病房新入院患者入院后第1天至第7天。数据采用描述性分析、逻辑回归分析、信效度检验、工具有效性检验和受试者工作特征（ROC）曲线分析。
两种跌倒风险评估工具的敏感性均较低（WSFRAT为57.1%，PIFRAT为50%），WSFRAT的特异性（79.6%）高于PIFRAT（70.4%），WSFRAT的准确性（76.9%）高于PIFRAT（67.9%）。ROC曲线分析显示，PIFRAT的AUC为0.602（95%CI[0.48,0.73]）。根据约登指数，最佳截断水平为7.5分，此时特异性为88.8%，敏感性为39.3%。若将敏感性提高到96.4%，截断水平必须设定为1.5分。此外，WSFRAT的AUC为0.625，当截断点设定为3.5分时，最高敏感性为82.1%。进一步的多因素逻辑回归分析显示，既往有跌倒史的患者跌倒风险显著高于无跌倒史的患者。男性（OR = 2.57，95%CI[1.11,5.94]）、身体活动困难（OR = 3.43；95%CI[1.40,8.41]）和虚弱（OR = 3.03；95%CI[1.08,8.49]）均与跌倒风险显著相关。
结论/对实践的启示：本研究确定了四个跌倒的关键风险因素。未来，临床医护人员应更加关注这些因素，并制定相关的跌倒预防干预措施。这些发现可为精神科跌倒评估工具的未来发展提供参考。
