社区老年人心理状态现状及其影响因素

Mental status and influencing factors of elderly people in community

目的回顾性研究社区老人心理状态现状及影响其焦虑抑郁情绪的相关因素。方法选取2022年12月~2023年12月某社区已建立居民健康档案的老人80例进行回顾性分析,依据档案资料中的Zung焦虑自评量表(Self-rating anxiety Scale,SAS)及Zung抑郁自评量表(Self-Rating Depression Scale,SDS)评估结果是否存在焦虑及抑郁情况进行分组,分为发生组和未发生组,收集对比两组社区老人的资料情况,存在差异的指标使用Logistic回归模型分析影响心理状态的相关因素,构建风险预测模型,利用受试者工作特征曲线(Receiver Operating Characteristic Curve,ROC)评价模型价值,构建校准曲线与决策曲线。结果两组婚姻状况,月收入,慢性疾病,独居,匹兹堡睡眠质量指数(Pittsburgh sleep quality index,PSQI)评分及自我效能感量表(General Self-Efficacy Scale,GSES)评分对比存在显著差异(P<0.05),且上述因素均是社区老人焦虑抑郁情绪的危险因素(OR值>1)。通过构建列线图,并绘制ROC曲线验证列预测模型准确性,发现AUC是0.769,95%CI为(0.666~0.871)。风险预测模型的校准曲线和参考曲线相近,证明社区老人焦虑抑郁情绪的预测风险和实际风险一致性较高;同时预测模型的净获益率较高,证明该预测模型的适用性较好。结论婚姻状况,月收入,慢性疾病,独居,睡眠情况及自我效能感均为社区老人焦虑抑郁情绪的影响因素,由此构建风险预测模型的预测效能高,适用性好,为采取干预措施提供指导。

Objective To study retrospectively the psychological status of elderly people in communities and the related factors affecting their anxiety and depression.Methods A retrospective analysis was conducted on 80 elderly patients with established resident health records in a community from December 2022 to December 2023,according to the Self-rating anxiety Scale(Zung)in the archives.The assessment results of SAS and Zung Self-Rating Depression Scale(SDS)were divided into two groups:occurrence group and non-occurrence group,and the data of the elderly in the two groups were collected and compared.Logistic regression model was used to analyze the relevant factors affecting the mental state,the risk prediction model was constructed,the value of the model was evaluated by Receiver Operating Characteristic Curve(ROC),and the calibration curve and decision curve were constructed.Results Marital status,monthly income,chronic disease,living alone,Pittsburgh sleep quality index(PSQI)score and General Self-Efficacy Scale,There were significant differences in GSES scores(P<0.05),and the above factors were all risk factors for anxiety and depression in the elderly in the community(OR value>1).By constructing a column graph and drawing a ROC curve to verify the accuracy of the column prediction model,it was found that the AUC was 0.769 and the 95%CI was(0.666~0.871).The calibration curve and reference curve of the risk prediction model are similar,which proves that the predicted risk and actual risk of anxiety and depression of the elderly in the community have high consistency.At the same time,the net benefit rate of the forecast model is high,which proves that the applicability of the forecast model is good.Conclusion Marital status,monthly income,chronic disease,living alone,sleep and self-efficacy are all influencing factors of anxiety and depression among elderly people in the community.Therefore,the risk prediction model built has high predictive efficacy and good applicability,and provides guidance for taking intervention measures.