RESUMO
BACKGROUND: During the COVID-19 pandemic, teachers quickly shifted to remote teaching with many teachers experiencing increased work demands with limited resources, affecting both mental health and work. METHODS: Within a cross-sectional study, we evaluated the relationship between one type of work demand, non-standard work schedule characteristics, and depressive and burnout symptoms in kindergarten through 8th grade U.S. teachers working remotely in May 2020. We further assessed the impact of COVID-19 and work resources. Work schedule characteristics were self-assessed across six domains on a 5-point frequency scale from always (1) to never (5). We used multilevel Poisson models to calculate prevalence ratios (PRs) and 95% confidence intervals (CIs). RESULTS: In fully adjusted models, frequently working unexpectedly was associated with a higher prevalence of depressive symptoms (PR = 1.18, 95% CI = 1.07-1.31, p < 0.01), high emotional exhaustion (PR = 1.17, 95% CI = 1.05-1.30, p < 0.01), and high depersonalization (PR = 1.40, 95% CI = 1.02-1.92, p = 0.03). Remote work resources were significantly associated with a lower prevalence of depressive symptoms (PR = 0.88, 95% CI = 0.79-0.98, p = 0.02). There was a linear association between low coworker support and a low sense of personal accomplishment (PR = 0.68, 95% CI = 0.53-0.87, p < 0.01). CONCLUSIONS: Frequently having to work unexpectedly while remote teaching was associated with symptoms of depression and burnout during the COVID-19 pandemic. Workplaces should support predictable working times to lessen the disruption caused by unexpected work to promote worker well-being.
Assuntos
Esgotamento Profissional , COVID-19 , Humanos , Saúde Mental , Teletrabalho , Estudos Transversais , Pandemias , COVID-19/epidemiologia , Esgotamento Profissional/epidemiologia , Esgotamento Profissional/psicologia , Admissão e Escalonamento de PessoalRESUMO
This study tested the assumption that the Bayley Scales of Infant and Toddler Development, Fourth Edition (Bayley-4) functions similarly for boys and girls and for four age groups. The Bayley-4 American norming sample of 1,700 children ages 0-42 months (3.5 years) was used, which included 50% boys and girls. Fifty-three percent of the children identified as White, 22.1% as Hispanic, 12.5% as Black, 8.5% as other, and 4.0% as Asian. A confirmatory factor analysis demonstrated the three-factor structure of cognitive, language, and motor abilities fit the data well (comparative fit index = .99, root-mean-square of error of approximation = .08, standardized root-mean-square residual = .02) and fit significantly better than the two- and one-factor models. The correlations between the latent factors were moderate (r = .73) to large sized (r = .81). Measurement and structural invariance were tested for boys and girls and four age groups (0-5, 6-13, 14-25, and 26-42 months). Residual invariance was supported for girls and boys, and intercept invariance was supported for the four age groups. The measurement invariance results suggest the Bayley-4 is not biased toward these gender and age groups, and group comparisons and decision making can be made with the Bayley-4 scores. Structural invariance findings suggested some differences for gender and age groups. The relations between the cognitive, language, and motor factors and factor variances were equal across girls and boys but differed significantly across the four age groups. Girls scored significantly higher on the three latent means, but these differences were small to negligible. (PsycInfo Database Record (c) 2024 APA, all rights reserved).
RESUMO
Accurately assessing youth mental health involves obtaining reports from multiple informants who typically display low levels of correspondence. This low correspondence may reflect situational specificity. That is, youth vary as to where they display mental health concerns and informants vary as to where and from what perspective they observe youth. Despite the frequent need to understand and interpret these informant discrepancies, no consensus guidelines exist for integrating informants' reports. The path to building these guidelines starts with identifying factors that reliably predict the level and form of these informant discrepancies, and do so for theoretically and empirically relevant reasons. Yet, despite the knowledge of situational specificity, few approaches to integrating multi-informant data are well-equipped to account for these factors in measurement, and those that claim to be well-positioned to do so have undergone little empirical scrutiny. One promising approach was developed roughly 20 years ago by Kraemer and colleagues (2003). Their Satellite Model leverages principal components analysis (PCA) and strategic selection of informants to instantiate situational specificity in measurement, namely components reflecting variance attributable to the context in which informants observe behavior (e.g., home/non-home), the perspective from which they observe behavior (e.g., self/other), and behavior that manifests across contexts and perspectives (i.e., trait). The current study represents the first construct validation test of the Satellite Model. A mixed-clinical/community sample of 134 adolescents and their parents completed six parallel surveys of adolescent mental health. Adolescents also participated in a series of simulated social interactions with research personnel trained to act as same-age, unfamiliar peers. A third informant (unfamiliar untrained observer) viewed these interactions and completed the same surveys as parents and adolescents. We applied the Satellite Model to each set of surveys and observed high internal consistency estimates for each of the six-item trait (α = 0.90), context (α = 0.84), and perspective (α = 0.83) components. Scores reflecting the trait, context, and perspective components displayed distinct patterns of relations to a battery of criterion variables that varied in the context, perspective, and source of measurement. The Satellite Model instantiates situational specificity in measurement and facilitates unifying conceptual and measurement models of youth mental health.