Common Mental Disorders in Primary Health Care Units
Bibliographic record
Abstract
BACKGROUND: Considering the high worldwide prevalence of common mental disorders (CMDs), characterizing the association between CMD and quality of life (QoL) constitute a valuable measure to gauge patient's functional impairment due to CMD symptoms. OBJECTIVE: To investigate factors associated with the incidence of CMD and its impact on the QoL in primary health care (PHC) patients. DESIGN: Cross-sectional study completed in a municipality in Brazil. Standardized tools included the Self-Reporting Questionnaire-20 to detect CMDs and the WHOQOL-brief to assess QoL, in addition to a sociodemographic and treatment-related questionnaire. RESULTS: A total of 41.4% of the patients met cutoff scores for a CMD, and the presence of a CMD was associated with female gender and marital status. Patients with CMDs had lower QoL scores than patients who were negative for a CMD. CONCLUSIONS: CMDs are highly prevalent in PHC settings and affect patients' QoL. The high frequency of CMD in those that seek care through PHC necessitate incorporating mental health services into the range of available services.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.000 |
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".