Trabalho docente e saúde mental de professores brasileiros na pandemia covid-19
Bibliographic record
Abstract
In recent years, there has been significant growth in mental disorders among teachers. Additionally, due to the Covid-19 pandemic, the transition from in-person to remote teaching has accentuated the precariousness of teaching work and, in many cases, has led to increased workload, flexibility processes, and work intensification. The objective of this research is to investigate the predictors of Common Mental Disorders (CMDs) among basic education teachers during the Covid-19 pandemic, considering the work context, variables related to experiences during this period, and sociodemographic characteristics. A total of 14,374 teachers participated in this study. The majority of respondents were from the Northeast region (62.5%), followed by the Southeast (23.6%), Midwest (6.5%), North (5.6%), and South (1.8%) regions. Data collection utilized the Self-Reporting Questionnaire (SRQ-20) for screening Common Mental Disorders, the Remote Teaching Work Context Assessment Scale (EACTDR), along with sociodemographic questions and questions related to the pandemic context. The results showed that approximately a quarter of the sample exhibited indications of CMDs, and regarding the predictors, the variables with the largest effect sizes were, in this order, work organization, socio-professional relationships, age, and gender.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".