[Prediction model on mental health status in middle-aged women of an urban area]

Abstract

Purpose: This study was designed to construct a structural model for explaining mental health status in middle-aged women.

Methods: The data was collected by self-reported questionnaires from 206 middle-aged women in Seoul. Data analysis was done with the SAS pc program for descriptive statistics and a PC-LISREL Program for finding the best fit model which assumes causal relationships among variables.

Results: The overall fit of the hypothetical model to the data was good, but paths and variables of the model were modified by considering theoretical implications and statistical significances of parameter estimates. Thus it was modified by excluding 3 paths. The modified model showed was good fit to the data(chi(2)=177.55, p=.00), GFI=0.908, AGFI=0.860, RMR=0.013, NFI=0.972, NNFI=0.982). Perceived stress, anger expression method, and self-esteem were found to have direct effects on mental health status in middle-aged women. These predictive variables of mental health status explained 66.6% of the model.

Conclusion: Programs to enhance mental health status in middle-aged women should include stress management skill, anger expression skill, and self-esteem enhancement skills to be effective.