OBJECTIVE: To translate the theoretical constructs from a model of resilience into a structural equation model and evaluate relationships among the model's theoretical constructs associated with resilience and the occurrence of depressive symptoms. DESIGN: Quantitative descriptive research design using structural equation modeling (SEM). PARTICIPANTS: Two-hundred and fifty-five individuals with SCI recruited from the Canadian Paraplegic Association (CPA). OUTCOME MEASURES: Outcome was measured by the Center for Epidemiologic Studies-Depression Scale. RESULTS: The resilience model fit the data relatively well: χ² (200, N = 255) = 451.57, p < .001; χ²/df = 2.26; CFI = .92, RMSEA = 0.070 (90% CI: 0.062-0.079), explaining 77% of the variance in depressive symptomatology. Severity of SCI-related stressors significantly influenced perceived stress (β = .60) and perceived stress, in turn, affected depressive symptoms (β = .66), characteristics of resilience (β = -.43), and social support (β = -.26). The resilience characteristics had an inverse relationship with depressive symptoms (β = -.29). No direct relationship was found between severity of SCI-related stressors and depressive symptoms. CONCLUSIONS: Findings provide support for the resilience model and suggests characteristics of resilience "buffer" the perceptions of stress on depressive symptoms. The resilience model may be useful to guide clinical interventions designed to improve the mental health of individuals with SCI.
OBJECTIVE: To translate the theoretical constructs from a model of resilience into a structural equation model and evaluate relationships among the model's theoretical constructs associated with resilience and the occurrence of depressive symptoms. DESIGN: Quantitative descriptive research design using structural equation modeling (SEM). PARTICIPANTS: Two-hundred and fifty-five individuals with SCI recruited from the Canadian Paraplegic Association (CPA). OUTCOME MEASURES: Outcome was measured by the Center for Epidemiologic Studies-Depression Scale. RESULTS: The resilience model fit the data relatively well: χ² (200, N = 255) = 451.57, p < .001; χ²/df = 2.26; CFI = .92, RMSEA = 0.070 (90% CI: 0.062-0.079), explaining 77% of the variance in depressive symptomatology. Severity of SCI-related stressors significantly influenced perceived stress (β = .60) and perceived stress, in turn, affected depressive symptoms (β = .66), characteristics of resilience (β = -.43), and social support (β = -.26). The resilience characteristics had an inverse relationship with depressive symptoms (β = -.29). No direct relationship was found between severity of SCI-related stressors and depressive symptoms. CONCLUSIONS: Findings provide support for the resilience model and suggests characteristics of resilience "buffer" the perceptions of stress on depressive symptoms. The resilience model may be useful to guide clinical interventions designed to improve the mental health of individuals with SCI.
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