Abstract

The purpose of this study was to test a model of the resident and community factors that are associated with quality of care interactions among nursing home (NH) residents living with dementia and test for invariance between model fit when tested with the Black versus White residents and female versus male residents. It was hypothesized that resident age, gender, race, pain, comorbidities, quality of life, resistiveness to care, function, cognition, community profit status, overall community star rating, community size, and staffing star rating would be directly and/or indirectly associated with quality of care interactions. It was also hypothesized that the model fit would be invariant by resident race and gender. This was a secondary data analysis using baseline, cross-sectional data from the Evidence Integration Triangle for Behavioral and Psychological Symptoms of Dementia (EIT-4-BPSD) intervention study. The study included 528 residents from 55 NH facilities. Descriptive statistics and structural equation modeling was used to test the proposed model. The results showed that the final model with significant paths only had a poor fit to the data (χ2/df= 10.79, comparative fit index= 0.57, Tucker-Lewis index= 0.15, normed fit index= 0.57, root mean square error of approximation= 0.13). However, the findings indicated that comorbidities, pain, profit status, and overall community star rating were significantly associated with quality of care interactions. There was no difference in model fit between Black residents versus White residents, and between male versus female residents. This study suggests factors that may influence quality of care interactions. Managing comorbidities, managing pain, and supporting higher quality of care in NH communities will likely help increase the frequency of positive care interactions. These findings can inform future interventions and training curricula for NH care staff to promote positive care interactions.

Full Text
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