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

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.

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(χ²=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.

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.

This study was to identify the relationship between perceived stress, anger expression, and level of depression in cancer patients.

A cross-sectional descriptive study design was used. Data was collected by questionnaires from 185 in- and out-patients who were diagnosed with cancer at 3 university hospitals and the National Cancer Center using Spielberger et al.'s Anger Expression Scale, Cohen, Kamarch & Mermelstein's Perceived Stress, and Derogatise's SCL-90. The data was analyzed using descriptive statistics, Pearson correlation coefficient, and stepwise multiple regression with SAS/PC.

The perceived stress in cancer patients indicated a significant positive correlation to anger-in(r=.288, p=.000), anger-out(r=.232, p=.001), and depression(r=.68, p=.000), but no significant correlation to anger-control. The anger-in of cancer patients showed a significant positive relationship to anger-out(r=.53, p=.000), and depression(r=.383, p=.000), but no significant correlation to anger-control. Anger-out showed a significantly negative correlation to anger-control(r=-.248, p=.001) and a positive correlation to depression(r=.240, p=.001). The most significant predictor which influenced depression in cancer patients was perceived stress, followed by anger-in and hobby, and these factors explained their depression with a variance of 54%.

These results suggested that cancer patients with a high degree of perceived stress are likely to be high in anger-out and anger-in. Perceived stress and anger-in are major factors which affect depression in cancer patients.

This study was to identify the relationship between stress, social support and depression in the elderly.

The subjects were 283 elderly adults over 60 in Seoul. Data was collected by questionnaire surveys using convenience sampling. The instruments used in this study are the ELSI developed by Aldwin(1990), the Interpersonal Support Evaluation List developed by Cohen & Hoberman (1983), and the Geriatric Depression Scale by Yesavage & Brink(1982). Data was analyzed by the SAS program, using descriptive statistics, Pearson Correlation Coefficient, t-test, ANOVA and progressed Multiple Regression.

The relationship between stress and depression had a positive correlation (r= 0.33), but the relationship between stress and social support had no significant correlations. The relationship between social support and depression had a negative correlation (r= -0.38). The most powerful predictor of depression was the economic status and then a combination of stress, and social support account for 39% of the variance in depression in the elderly.

These results suggested that stress and social support deficits can be potential risk factors in old age depression. Therefore, these findings give useful information for constructing an intervention program focused on depression in the elderly.

The purpose of this study was to identify the characteristics of anger expression in middle-aged Korean women by categorizing their patterns of expression while considering the complexity and multidimensionality of anger, and by investigating the characteristics relative to the patterns.

The research design was a descriptive design using Q methodology, which is a method of measuring subjectivity. A convenience sample of 42 participants aged 40–60 years and living in the community in Korea was recruited. The PC-QUANL software program (a factor analysis program for the Q technique) was used to analyze the Q-sort data.

Four factors were extracted that described different expressions of anger among middle-aged Korean women; these factors explained 50.1% of the total variance. The frames of reference of the four factors were a) direct diversion, b) silent masking with remaining anger, c) self digestion, and d) controlling anger with objectification.

In this study has identified patterns and characteristics of anger expression among middle-aged Korean women were identified, which will aid the development of effective anger-management programs for controlling anger in this population. In future studies, it would be helpful to investigate how the patterns of anger expression established herein are associated with specific health problems such as cardiovascular disorder and cancer.