Qualidade de vida de gestantes assistidas pela estratégia saúde da família
Bibliographic record
Abstract
The Family Health Strategy responds to a new conception of health, not more focused on assistance to the disease, but mainly focused on promoting Quality of Life. Gestation is composed of many changes not only physical but also psychological. The prenatal care is a health promotion action held in the FHS, therefore it should comply with the principle of improving the Quality of Life of pregnant women attended by him. The aim of this study was to evaluate the Quality of Life of pregnant women, examining the potential of the WHOQOL-bref instrument in order to contribute to the promotion of women's health in the FHS. This is a qualitative research with a study case design, where the assessment of Quality of Life was through the WHOQOL-bref instrument. It was evaluated 73% of the women ascribed to four teams of the FHS. 43% of pregnant women were in the second quarter and 40% in the third quarter. 86% began prenatal care in the first quarter. 86% of women used prenatal care exclusively in the FHS and 14% supplemented with the private sector. The score of the overall Quality of Life was 75; of the physical Quality of Life was 57.65; of the psychological Quality of Life was 68.75; the Social Relations Quality of Life was 77.98, and the Environmental Quality of Life was 59.75. The Family Health Strategy should improve prenatal care in not only the physical side of pregnancy, but also in the psychological, widening his eyes to the social inclusion of the pregnant women, the potential for strengthening and wear of them, and the family support in gestational period. The WHOQOL-bref instrument could be used as a monitoring technology in expanded clinic in the prenatal care.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".