Urinary and sexual dysfunctions are side effects of radical prostatectomy (RP) for prostate cancer (PC) that contribute to depression. Despite the effectiveness of support groups at reducing depression in cancer patients, men typically do not participate in them. The purpose of this pilot study was to test the effects of a dyadic intervention (one-to-one support) on social support (Modified Inventory of Socially Supportive Behaviors), self-efficacy (Stanford Inventory of Cancer Patient Adjustment), and depression (Geriatric Depression Scale). Subjects were randomized to group. Controls (N=15; Mage=59.7) received usual care. Experimentals were paired with long-term survivors (LTS) who had RP and who had treatment side effects in common. Experimentals (N=15; Mage=57.5) met with a LTS 8 times in 8 weeks to discuss concerns associated with survivorship. No significant differences were detected on social support, but after 4 weeks, significant differences were present on depression between controls and experimentals, however these differences were not seen at 8 weeks. After 8 weeks, there were also significant differences on self-efficacy between controls and experimentals. Weekly anecdotal data supported the feasibility and acceptance of the intervention that was a low cost strategy effective at reducing depression and increasing self-efficacy in men treated by RP. Future research directions and clinical application is presented.

The 15-item three-factor ASAS-R is a short, reliable and valid instrument to measure self-care agency among individuals from the general population, but further psychometric evaluation is needed among individuals with chronic diseases, especially those with diabetes mellitus.

Researchers are commonly faced with the problem of missing data. This article presents theoretical and empirical information for the selection and application of approaches for handling missing data on a single variable. An actual data set of 492 cases with no missing values was used to create a simulated yet realistic data set with missing at random (MAR) data. The authors compare and contrast five approaches (listwise deletion, mean substitution, simple regression, regression with an error term, and the expectation maximization [EM] algorithm) for dealing with missing data, and compare the effects of each method on descriptive statistics and correlation coefficients for the imputed data (n = 96) and the entire sample (n = 492) when imputed data are inculded. All methods had limitations, although our findings suggest that mean substitution was the least effective and that regression with an error term and the EM algorithm produced estimates closest to those of the original variables.

Costly complications of diabetes often arise from poor glycemic control. Appropriate diabetes self-care management may improve control. This study examined whether self-care management affects glycemic control and mediates relationships between self-efficacy and self-care agency with glycemic control. In a cross-sectional correlational design, data from a prior study of 141 insulin-requiring adults with type 1 or type 2 diabetes were examined using descriptive statistics, Pearson's correlation, and multiple hierarchical regression. Findings indicated that greater self-care agency and self-efficacy lead to greater self-care management, in turn leading to better glycemic control. Self-care management did not mediate between self-efficacy or self-care agency and glycemic control. Thus, beliefs or capabilities for self-care are insufficient to improve glycemic control; doing so requires self-care management.

This study used the resiliency model of family stress, adjustment, and adaptation as the framework to examine the main and moderating effects of social support and resourcefulness in the relationship between family life stresses and strain and depressive symptoms in grandmothers raising grandchildren, grandmothers in multigenerational homes, and noncaregivers to grandchildren. A sample of 486 Ohio grandmothers, recruited using random and supplemental convenience methods, completed mailed surveys. Analysis of variance was used to examine differences in family life stresses and strain, resourcefulness, support, and depressive symptoms across the three groups of grandmothers. Hierarchical multiple regression analyses were used to examine whether family stresses and strains affected the grandmother's depressive symptoms and whether social support and resourcefulness moderated the relationship between family stresses and strain and grandmothers' mental health. Grandmothers raising grandchildren reported more depressive symptoms, but in multiple regression analyses of the full sample that controlled for demo-graphics, primary caregiving status was not related to depressive symptoms. More strain and less subjective support and resourcefulness were associated with higher depressive symptoms for all grandmothers, with 33% to 54% explained variances of such symptoms for each caregiving group and the full sample. Subjective support moderated the effects of strain and instrumental support moderated the effects of family life stresses on depressive symptoms. Social support and resourcefulness may help protect grandmothers from the effects of family stresses and strain, and interventions to enhance these factors may assist grandmother caregivers to achieve better mental health.

Recommendations for research and for practice, especially during times of caregiving transition or for grandmothers raising grandchildren, are discussed.

No abstract

This cross-sectional study examined family functioning and normalization in 103 mothers of children ≤16 years of age dependent on medical technology (mechanical ventilation, intravenous nutrition/medication, respiratory/nutritional support) following initiation of home care. Differences in outcomes (mother’s depressive symptoms, normalization, family functioning), based on the type of technology used, were also examined. Participants were interviewed face-to-face using the Demographic Characteristics Questionnaire, the Functional Status II-Revised Scale, the Center for Epidemiological Studies-Depression Scale, a Normalization Scale subscale, and the Feetham Family Functioning Survey. Thirty-five percent of the variance in family functioning was explained primarily by the mothers’ level of depressive symptoms. Several variables were significant predictors of normalization. Analysis of variance revealed no significant difference in outcomes based upon the type of technology used. Mothers of technology-dependent children are at high risk for clinical depression that may affect family functioning. This article concludes with clinical practice and policy implications.