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Profiles of Teacher Context and Competence to Predict Emotional State: Latent Profile Analysis
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Thesis/Dissertation
Date
2023
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School Psychology
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http://dx.doi.org/10.34944/dspace/8932
Abstract
This dissertation study reports on a survey of teacher wellbeing during the COVID-19 pandemic. Using an ecological, strengths-based adaptation to Herman and colleagues’ (2020) 3C model for teacher wellbeing, the current study examined teachers’ contexts, working conditions supporting their feelings of competence, and coping (i.e., positive emotional state). Measures included the Measure of Stressors and Supports for Teachers (MOST) and COVID-19-specific measures created by the research team. The research was guided by the following questions: (1) What profiles emerge from teachers’ ratings of their context and competence? (2) Do these profiles of context and competence predict teachers’ abilities to cope, as measured by their positive emotional state? I hypothesized that four profiles would emerge: high context-high competence, low context-low competence, high context-low competence, and low context-high competence and that these profiles would be predictive of teachers’ emotional states. Using latent profile analysis, I found that the best-fitting solution had three profiles with high, medium, or low scores across all measures. A four-profile solution is also discussed. I discuss the findings and future research directions aimed at promoting teacher well-being in schools.
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