社区空巢老人心理弹性特征的潜在类别分析

Latent class analysis on resilience characteristics of empty-nest elderly in community

目的采用探索性潜在类别分析的方法对社区空巢老人心理弹性的特征进行分析，为不同特征群体实施针对性的干预措施提供依据。方法采用问卷调查法，使用自编空巢老人一般资料调查表、Connor和Davidson心理弹性量表（CD-RISC）中文版对203名社区空巢老人进行调查，利用统计软件Mplus7．0对心理弹性的特征进行探索性潜在类别分析。结果通过分析发现，社区空巢老人的心理弹性状况具有明显的分组特征，统计指标（AIC，BIC，Entropy等）支持了3个潜在类别的模型（P=0．006），根据每个类别在问卷各个条目上的条件概率，分别命名为高弹性组[54例（26．6％）]，低耐压弹性组[82例（40．4％）]，低弹性组[67例（33．0％）]。进一步的研究发现：高弹性组与低弹性组类别中空巢老人在年龄构成上差异有统计学意义（P〈0．05），低耐压弹性组与低弹性组类别中的空巢老人在性别构成比例上差异有统计学意义（P〈0．05）。结论社区空巢老人的心理弹性特征可分为3个类别，各类别的性别、年龄所占的比例不同。

Objective To analyze the characteristics of resilience among empty-nest elderly in community with exploratory latent class analysis method and provide a basis for making targeted intervention measures according to different characteristics.Methods This study enrolled 203 empty-nest elderly people as the study respondents. The general information, resilience of empty-nest elderly were investigated using the general information questionnaire, Connor-Davidson resilience scale in Chinese version. Latent class analyze （Mplus 7.0） was used to discuss the characteristics of resilience among empty-nest elderly. Results The results showed that the resilience of empty-nest elderly had obvious group characteristics and the statistical indicators（AIC, BIC, Entropy and so on） can support the three categories of potential model（P= 0.006）. Based on the conditional probability on the various items of the questionnaire in each category, they were respectively named ＂high resilience group＂（ 54 cases （26.6%）） and ＂low pressure resilience group＂（ 82 cases （40.4%）） and ＂low resilience group＂（67 cases （33.0%））.Further study showed that high resilience and low resilience group had a significant effect of age（P〈0.05 ） , low pressure resilience and low resilience group had a significant effect of gender（P〈0.05 ） .Conclusion The resilience of empty-nest elderly in communities can be divided into three categories according to its characteristics.Each category has different proportion of gender and age.