Coping Patterns Among Primary Informal Dementia Caregivers in Singapore and Its Impact on Caregivers-Implications of a Latent Class Analysis.

BACKGROUND AND OBJECTIVES: Existing studies typically explore the factor structure of coping strategies among dementia caregivers. However, this approach overlooks the fact that caregivers often use different coping strategies simultaneously. This study aims to explore the coping patterns of primary informal dementia caregivers in Singapore, examine their significant correlates, and investigate whether different patterns would affect the depressive symptoms of caregivers. RESEARCH DESIGN AND METHODS: Two hundred eighty-one primary informal caregivers of persons with dementia (PWD) were assessed. Coping strategies were measured by the Brief Coping Orientation to Problem Experienced inventory. A latent class analysis was performed to explore caregivers' coping patterns, followed by logistic regressions to identify the significant correlates and the relationships between coping patterns and caregiver depression. RESULTS: The latent class analysis suggested a three-class solution that was featured by the frequency and variety of coping strategies used by caregivers-high coping (36.3%), medium coping (37.7%), and low coping (26.0%). Factors influencing the coping patterns of our sample were mainly related to caregivers' individual resources such as personal characteristics and caregiving stressors like PWD's problematic behaviors and caregiving burden. Compared to caregivers in the low coping group, those in the medium coping group had significantly higher risks of potential depression. DISCUSSION AND IMPLICATIONS: The current study confirmed that there are distinct coping patterns among primary informal dementia caregivers, and caregivers with the low coping pattern had fewer depressive symptoms. Future research is needed to explore if coping patterns from our sample are generalizable to dementia caregivers elsewhere.

Staging dementia based on caregiver reported patient symptoms: Implications from a latent class analysis.

BACKGROUND: Tailoring interventions to the needs of caregivers is an important feature of successful caregiver support programs. To improve cost-effectiveness, group tailoring based on the stage of dementia could be a good alternative. However, existing staging strategies mostly depend on trained professionals. OBJECTIVE: This study aims to stage dementia based on caregiver reported symptoms of persons with dementia. METHODS: Latent class analysis was used. The classes derived were then mapped with disease duration to define the stages. Logistic regression with receiver operating characteristic curve was used to generate the optimal cut-offs. RESULTS: Latent class analysis suggested a 4-class solution, these four classes were named as early (25.9%), mild (25.2%), moderate (16.7%) and severe stage (32.3%). The stages based on the cut-offs generated achieved an overall accuracy of 90.8% compared to stages derived from latent class analysis. CONCLUSION: The current study confirmed that caregiver reported patient symptoms could be used to classify persons with dementia into different stages. The new staging strategy is a good complement of existing dementia clinical assessment tools in terms of better supporting informal caregivers.

Comparing disease-specific and generic quality of life measures in patients with schizophrenia.

The current study aimed to compare the use of a disease-specific and a generic quality of life (QOL) measure in a group 251 outpatients with a schizophrenia spectrum disorder by examining their relationships with symptoms of schizophrenia, psychiatric and medical comorbidities, and other factors, as well as to determine which of these factors will be associated with the measurement discrepancy between the two measures. QOL was assessed with the generic Healthy Utility Index Mark 3 (HUI3) and disease-specific Schizophrenia Quality of Life Scale (SQLS), and symptom severity was determined using the Positive and Negative Syndrome Scale (PANSS). Symptom severity predicted both SQLS and HUI3, while psychiatric comorbidity predicted only the HUI3. Ethnicity, employment and PANSS depression factor were significantly associated with the measurement discrepancy. Using domain scores of the two QOL measures, the HUI3 appears to be superior in discriminating PANSS cognitive factor scores and medical comorbidity status compared to SQLS. Although the use of disease-specific QOL is generally preferred to track treatment progress in clinical settings, the two types of instruments measure non-overlapping aspects of QOL and the generic scales may better reflect QOL impairment due to overall clinical presentation.