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作 者:张楠 王爱媛[2] 高春霞[1] 吴医学 ZHANG Nan;WANG Aiyuan;GAO Chunxia;WU Yixue(Nursing Department,Qingdao Eighth People's Hospital,Qingdao 266100,China;Human Resources Department,Qingdao Eighth People's Hospital,Qingdao 266100,China)
机构地区:[1]青岛市第八人民医院护理部,266100 [2]青岛市第八人民医院人力资源部,266100
出 处:《护理管理杂志》2023年第5期408-412,共5页Journal of Nursing Administration
基 金:青岛市2021年度医药卫生科研计划项目(2021-WJZD114)。
摘 要:目的调查社区老年人失能现状和风险因素,并构建风险预测模型。方法采用一般资料调查表、卡茨量表、老年抑郁量表和社会支持评定量表对青岛市580名社区老年人入户访谈式调查,分析老年人失能风险因素,建立风险预测模型,采用ROC曲线下面积评价所构建的风险模型。结果580名社区老年人中,失能老人67人,失能率为11.55%。多因素分析结果显示,高龄、经济来源为政府最低生活保障、子女补贴、缺乏兴趣爱好、不锻炼身体、抑郁是老年人失能的危险因素(P<0.01或P<0.05)。基于以上危险因素构建的风险预测模型ROC曲线下面积为0.965,灵敏度为0.940,特异度为0.904,Youden指数为0.844。结论社区老年人失能情况不容忽视,应加强高龄老人的健康管理,关注经济困难老年人,鼓励老年人积极锻炼,加强心理护理。构建的失能风险预测模型具有较高的预测能力和判断能力,可作为社区老年人失能的风险筛查工具。Objective To investigate the status and risk factors of the disabled elderly in the community,and develop a risk prediction model.Methods A total of 580 community elderly people in Qingdao were investigated by general information questionnaire,Katz scale,Ger-iatric Depression Scale and Social Support Rating Scale.The Logistic regression was used to analyze risk factors,and the area under ROC curve was used to evaluated the constructed risk model.Results Among 580 elderly people in the community,67 were disabled,and the disa-bility rate was 11.55%.Multifactor analysis results showed that the risk factors of disabled elderly were old age,low income from the govern-ment,children's subsidies,lack of interests,lack of exercise,and depression(P<0.01 or P<0.05).Risk prediction model based on the above risk factors was 0.965,the sensitivity was 0.940,the specificity was 0.904,and the Youden index was 0.844.Conclusion The disabled elder-ly in community can not be ignored.We should strengthen the health management for elderly,pay attention to their financial difficulties,and encourage the elderly to take active exercise,and strengthen psychological nursing.The risk prediction model for disabled elderly has good clinic practice and is helpful to effectively distinguish groups at high risk of disabled elderly.
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