GENERAL WELL-BEING AND USE OF SOCIAL SUPPORT

Research interest on well-being and social support has focused largely on social factors as related to attaining and maintaining well-being, self-perceptions of well-being and to a lesser extent the relationship of current level of self-perceived well-being to use of formal or informal sources of social support. This study analyzed responses to the General Well-Being Schedule of 6,913 subjects (25-74 years) interviewed during the National Health and Nutrition Examination Survey (1971-1975). The purpose of this analysis was to relate the level of GWBS scores to the use of social support, both informal (family and friends) and formal (community professionals).^ Study questions addressed were whether well-being level was related to selection of a specific social support resource and/or rate of use of resources and whether gender differences were apparent in level of well-being and social support use. Because age, sex, race, socioeconomic status (income and education) and marital status may confound the relation between level of GWB and type of social support chosen, the association between these variables with GWB and use of social support were considered. For analysis, test scores were grouped into four categories and for detailed analysis, two categories: low (0-70) and high (71-110). Cross tabulations and percentages were computed and the chi-square test of significance was used.^ Although 16 to 25 percent of the sample population reported low well-being, less than 10 percent used formal resources to discuss emotional, mental or behavior problems. Medical resources, mostly physicians, were the most used formal social supports. Informal social support was important for all well-being levels where 65-77% of each category reported using this resource.^ While well-being level does not appear to serve as a screener/selector of type of formal social support used, it is related to rates of use. Females reported slightly lower well-being than males, and except in the lowest well-being group, had higher rates of social support use. Findings support the conclusion that perceived well-being is related to use of social support such that the lower the well-being, the greater tendency to use formal and/or informal social support. ^

Application of the general linear model to assess the effect of missing data on bone marrow mononuclear cell therapy with infusion timing and follow-up MRI

With most clinical trials, missing data presents a statistical problem in evaluating a treatment's efficacy. There are many methods commonly used to assess missing data; however, these methods leave room for bias to enter the study. This thesis was a secondary analysis on data taken from TIME, a phase 2 randomized clinical trial conducted to evaluate the safety and effect of the administration timing of bone marrow mononuclear cells (BMMNC) for subjects with acute myocardial infarction (AMI).^ We evaluated the effect of missing data by comparing the variance inflation factor (VIF) of the effect of therapy between all subjects and only subjects with complete data. Through the general linear model, an unbiased solution was made for the VIF of the treatment's efficacy using the weighted least squares method to incorporate missing data. Two groups were identified from the TIME data: 1) all subjects and 2) subjects with complete data (baseline and follow-up measurements). After the general solution was found for the VIF, it was migrated Excel 2010 to evaluate data from TIME. The resulting numerical value from the two groups was compared to assess the effect of missing data.^ The VIF values from the TIME study were considerably less in the group with missing data. By design, we varied the correlation factor in order to evaluate the VIFs of both groups. As the correlation factor increased, the VIF values increased at a faster rate in the group with only complete data. Furthermore, while varying the correlation factor, the number of subjects with missing data was also varied to see how missing data affects the VIF. When subjects with only baseline data was increased, we saw a significant rate increase in VIF values in the group with only complete data while the group with missing data saw a steady and consistent increase in the VIF. The same was seen when we varied the group with follow-up only data. This essentially showed that the VIFs steadily increased when missing data is not ignored. When missing data is ignored as with our comparison group, the VIF values sharply increase as correlation increases.^