Instructions for Authors

Instructions for Authors

Instructions for Authors     

Instructions for Authors

Instructions for Authors

Instructions for Authors     

The role of familism in stress and coping processes among African American and White dementia caregivers: effects on mental and physical health.

OBJECTIVE: To explore how familism, burden, and coping styles mediate the relationships between ethnicity and the mental and physical health of caregivers. DESIGN: A probability sample of 65 White and 95 African Americans respondents caring for an older family member with dementia was used to test hypotheses from a sociocultural stress and coping model using path analysis. MAIN OUTCOME MEASURES: Measures of caregivers' health included subjective health, self-reported diseases, blood pressure, and heart rate. Mental health measures included self-reported depression and psychological symptoms. RESULTS: Contrary to the hypothesis, familism had an adverse effect on outcomes and was related to low education levels rather than to African American ethnicity. A buffering effect of active coping between being African American and diastolic blood pressure was found even after controlling for levels of education. CONCLUSIONS: Findings supported a core stress and coping model in which more behavior problems of care recipients were associated with poorer mental health of caregivers via greater burden and more use of avoidant coping. Results also demonstrate that this core model can be extended to physical health.     

The role of causal models in multiple judgments under uncertainty

Two studies examined a novel prediction of the causal Bayes net approach to judgments under uncertainty, namely that causal knowledge affects the interpretation of statistical evidence obtained over multiple observations. Participants estimated the conditional probability of an uncertain event (breast cancer) given information about the base rate, hit rate (probability of a positive mammogram given cancer) and false positive rate (probability of a positive mammogram in the absence of cancer). Conditional probability estimates were made after observing one or two positive mammograms. Participants exhibited a causal stability effect: there was a smaller increase in estimates of the probability of cancer over multiple positive mammograms when a causal explanation of false positives was provided. This was the case when the judgments were made by different participants (Experiment 1) or by the same participants (Experiment 2). These results show that identical patterns of observed events can lead to different estimates of event probability depending on beliefs about the generative causes of the observations.