Escala de Avaliação de Sintomas-40 (EAS-40): validade e precisão em amostra não-clínica
Bibliographic record
Abstract
A EAS-40, uma escala de 40 itens, de tipo auto-relato, visa avaliar sintomas psicopatológicos e foi adaptada do Symptom Checklist-90-R (SCL-90-R) para pacientes ambulatoriais brasileiros de hospitais gerais. O objetivo da pesquisa foi estimar a validade de grupos comparados, validade concorrente e precisão de teste e reteste da EAS-40 para população não-clínica. A amostra de 113 universitários (99 M e 14 H) respondeu a EAS-40 e à versão brasileira da Toronto Alexithymia Scale (TAS) (critério externo). Os resultados sugerem que a EAS-40 pode ser útil para a avaliação de sintomas psicológicos de universitários com boa estabilidade temporal, permitindo discriminar populações com diferentes perfis. Quanto à validade concorrente, as dimensões da EAS-40 mostraram-se correlacionadas de formas diversas com os componentes da TAS. Novas pesquisas devem ser realizadas, envolvendo uma melhor distribuição das amostras quanto ao sexo.
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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 | 0.030 | 0.051 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".