five

Model fit indices for the latent class models.

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NIAID Data Ecosystem2026-05-01 收录
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https://figshare.com/articles/dataset/Model_fit_indices_for_the_latent_class_models_/25220879
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Objective To identify latent classes of positive coping behaviors during the COVID-19 pandemic and examine associations with alcohol-related and mental health outcomes across participants with and without a history of alcohol use disorder (AUD). Methods Baseline data from 463 participants who were enrolled in the NIAAA COVID-19 Pandemic Impact on Alcohol (C19-PIA) Study were analyzed. Latent class analysis (LCA) was applied to five positive coping behaviors during COVID-19: taking media breaks, taking care of their body, engaging in healthy behaviors, making time to relax, and connecting with others. Latent class differences and the moderating role of history of AUD on six alcohol-related and mental health outcomes were examined using multiple regression models. Results LCA revealed two latent classes: 83.4% High Positive Coping and 16.6% Low Positive Coping. Low Positive Coping was associated with higher levels of perceived stress, anxiety symptoms, and loneliness. A history of AUD was consistently associated with higher levels of alcohol-related and mental health outcomes. Significant interactions between Coping Latent Classes and history of AUD indicated that the associations of Low Positive Coping with problematic alcohol use, depressive symptoms, and drinking to cope motives were either stronger or only significant among individuals with a history of AUD. Conclusions Individuals with a history of AUD may be particularly vulnerable to depressive symptoms and alcohol-related outcomes, especially when they do not utilize positive coping strategies. The promotion of positive coping strategies is a promising avenue to address alcohol-related and mental health problems during a public health crisis and warrants future research.
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2024-02-14
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