The main purpose of this study was to find out variables relevant to self-care activities of physically disabled person. The subjects of this analysis were 1277 person which is between 15~64 years, the data came from the 1985 National Interview-Survey on Disabled Person in Korea. For this analysis, Breakdown, Oneway and Discriminant Analysis were used. The finding of the analysis can be summarized as follows: First, the mean of self-care activities-was 2.57 (SD: 0.69, range: 1-3). The relevance for the self-care activities by several variables is-as follows. 1. The relevance for the self-care activities by socio-economic status is significant at age, education level, occupation of household members variables. Especially, in the case of high age, low education level, the self- care activities are shown low score. 2. The relevance by impairment characteristics is shown high significance at all input variables. When disabled person have double impairment, paralysis, late occurance age, and is due to diseases, the self-care activities score is lowered. 3. The relevance by health care services variables-is not shown significant at all input variables. Second, the relevance for social activities by several variables was conducted by discriminant analysis. The relative importance of social activities discriminant function is 0.344 of eigenvalue. The canonical correlation between the social activities discriminant function and 9 dummy variables is 0.51, total variance of dummy variables for social activities is shown 26 persent. The self-care activities variable represents the highest contribution of its associated variable to the function (canonical coefficient: -.56). The occurance age, the occupation of household members, the education level, variables are shown comparatively high contribution to the function. To sum up, this analysis suggests that the selfcare activities variable is the highest contributed to the social activities. In relation to self-care concept, this finding will be useful in rehabilitation nursing care.

This study was conducted for the purpose of finding out the variance explaining the medical facilities utilization behavior, which is defined adaptation behavior process by focal, contextual, residual stimuli in Roy's Adaptation Model. What kinds of characteristics can explain adaptation behavior in Roy's Model? And which is the relative importance of input variables? For this analysis, stepwise multiple regression and path analysis was used. The data come from the 1981 Baseline Household Interview Survey in remote rural area. The findings of the analysis can be summarized as follow : First, Total variance of independent variables for adaptation behavior, that is medical facilities utilization including clinic, drug store, health center, herb medicine was shown 16.2 percent. The most important variable which explain the dependent variables was the occurrence of illness with the R2 of value 0.112. The illness symptom, living level, regular care source was shown important variables with relatively high the R2 value and significant beta coefficient. Second, in the path analysis of variables which is selected important variables, the occurrence of illness was shown variable which has the highest direct effect which 0.297 path coefficient. Also the education level of household was shown variable which has the highest indirect effect through living level and the occurrence of illness in causal model. Third, This analysis suggests that the occurrence of illness belonging focal stimuli are more influenced than others. To sum up, It is seem to the occurrence of illness, illness symptom belonging focal stimuli have high explanation ability through direct effect, education level of household among contextual stimuli have explanation ability through indirect effect.

Correlations among body weight and sociodemographic factors, including life-style were tested as social determinants of health in a sample of 5,201 adults in Korea. The aim of this study was to determine the extent to which sociodemographic variables and life-style associated health behaviors explain body weight distribution. A second aim was to explain the relation of body weight and health status to stress the importance of body weight as an early risk indicator of health status. The canonical correlation between the weight distribution(underweight and overweight) and the independent variables was 0.29, 17% of the total variance was explained. Perceived health level represented the highest contribution(canonical coefficient 0.82) to body weight. Sociodemographic factors such as sex, economic status, and life-style factors such as smoking, exercise, regular meals and sleep showed comparatively high contributions to body weight. The relevance of body weight for health status including the rate of chronic disease and the rate of medical utilization was significant. Especially, underweight was clarified as being more important than overweight to morbidity level and medical utilization. These findings suggest that perceived body weight is an important indicator status and is thus a valuable variable to be considered for nursing intervention and health education related to the promotion of health.

The purpose of this study was to analyze the level of the services provision of community health practitioners (CHP) and to find out the influence factors on the services provision of CHP. In this study the dependent variables were the level of community health services (CHS), maternal and child health services(MCH), family planning services(FPS), primary care services(PCS) and the ratios of preventive health services(PHS). And independent variables were predisposing, community demographic and task factors. For this analysis, atepwise regression was used. Data collected for the study on reorganization of health centers organization in 1985 was partly used. The findings of this study can be summarized as follows : First, total variance of independent variables for CHS, MCH, FPS, PCS and PHS are shown 62.5 percent, 58.3 percent, 41.8 percent, 17 percent and 61.9 percent respectively. Second, the most important variables which explain CHS, MCH, FPS. PCS and PHS was ratios of household contacted(R2=0.289), marital status(R2=0.177), marital status(R2=0.167), ratios of household contacted(R2=0. 119)and management of preventive health services(R2 =0.203) respectively. The independent varivbles used in this analysis presen -ted that the explnining for the provision of preventive health service are more influenced than primary care services. In summary this analysis suggests that the level of preventive health services provision of CHP is low and the provision of primary care services compared with preventive health services are occurred independentely. In the future, the strategies for active preventive services by CHP must to be strengthened.