Correlations among Coping Skills and Life Satisfaction in Ethnic Older Caregivers

The purpose of the present study is to extend our current understanding of the effects of caregiver burden on life satisfaction by examining whether or not there are ethnic differences in coping strategies used to manage caregiving. Several specific hypotheses were tested in order to determine the linkages among age, gender, ethnicity (i.e., familism, filial piety), caregiver burden, coping with caregiving, and life satisfaction. A total of 103 Hispanic and Non-Hispanic White participants ages 60 and older were included in this study (mean age was 67.42; 16.5% male; 83.5 % female; 52.4% Hispanic; 47.6% Non-Hispanic White). The results suggest that demographics and certain coping skills can influence levels of life satisfaction and burden experienced by caregivers. The findings from this study shed light on how to structure effective psychoeducational interventions, facilitate adaptive coping, reduce burden, and improve life satisfaction for older adult caregivers.

Coping with a diagnosis of Alzheimer's disease: A client and caregiver perspective

The purpose of this study was to examine how individuals and their caregivers cope with a diagnosis of Alzheimer's disease. The sample size consisted of six patients with Alzheimer's disease and seven caregivers. The caregivers included spouses and adult children. The study was conducted at an academic medical center in the South Florida area. Using a phenomenological approach, data were collected by audiotaped interviews. Data were analyzed following the seven steps of Colaizzi (1978).^ The results of the study indicated that clients experienced fear, social withdrawal, decreased self-esteem and a need for love and support. Caregivers experienced psychological strain, burden, lifestyle adjustments and sacrifice. Both clients and caregivers identified numerous strategies for coping with Alzheimer's disease. The findings reflect the need for a holistic approach to promoting the quality of life for patients and caregivers. ^

Improving Analytical Travel Time Estimation for Transportation Planning Models

This dissertation aimed to improve travel time estimation for the purpose of transportation planning by developing a travel time estimation method that incorporates the effects of signal timing plans, which were difficult to consider in planning models. For this purpose, an analytical model has been developed. The model parameters were calibrated based on data from CORSIM microscopic simulation, with signal timing plans optimized using the TRANSYT-7F software. Independent variables in the model are link length, free-flow speed, and traffic volumes from the competing turning movements. The developed model has three advantages compared to traditional link-based or node-based models. First, the model considers the influence of signal timing plans for a variety of traffic volume combinations without requiring signal timing information as input. Second, the model describes the non-uniform spatial distribution of delay along a link, this being able to estimate the impacts of queues at different upstream locations of an intersection and attribute delays to a subject link and upstream link. Third, the model shows promise of improving the accuracy of travel time prediction. The mean absolute percentage error (MAPE) of the model is 13% for a set of field data from Minnesota Department of Transportation (MDOT); this is close to the MAPE of uniform delay in the HCM 2000 method (11%). The HCM is the industrial accepted analytical model in the existing literature, but it requires signal timing information as input for calculating delays. The developed model also outperforms the HCM 2000 method for a set of Miami-Dade County data that represent congested traffic conditions, with a MAPE of 29%, compared to 31% of the HCM 2000 method. The advantages of the proposed model make it feasible for application to a large network without the burden of signal timing input, while improving the accuracy of travel time estimation. An assignment model with the developed travel time estimation method has been implemented in a South Florida planning model, which improved assignment results.