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Assessing Outcomes of Dementia Caregivers Using Cross-Sectional Design and Linear Regression Models

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By: Published: 2020 | Product: SAGE Research Methods Cases: Medicine and Health
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Abstract

With a projected increase in the prevalence of Alzheimer’s disease (AD) and related dementias, family caregiving is steadily increasing. Caring for an individual with AD is characterized as a “career,” and within this career are a number of key transitions, including the onset of caregiving. Research reveals a number of negative emotional health outcomes for AD caregivers, including depression and role overload, but less research has examined the influence of key transitions on the emotional adaptation of caregivers. The purpose of this study was to examine how different patterns of caregiving onset (gradual and abrupt) impact emotional health outcomes for AD caregivers. Cross-sectional, quantitative data from 100 caregivers completing self-administered surveys were used. A series of multiple linear regression analyses were conducted to address how care-recipient cognition and behavioral problems moderated the relationship between caregiving onset and emotional health outcomes for caregivers who experienced a more abrupt entry into the caregiving role. Results suggest the importance of considering different onset transitions and moderating factors within the caregiving career to target clinical interventions. This case study highlights important factors to consider in dementia caregiving research, including the use of linear regression models when examining multiple variables in the caregiving context, ensuring well-defined participant inclusion criteria, careful selection of moderating variables, and recognizing challenges with participant recruitment.

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Regression analysis

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