Une perception négative des sanitaires scolaires par les élèves est-elle un facteur de risque de survenue de troubles pelvi-périnéaux ?
Bibliographic record
Abstract
Context : Nowadays, perineal disorders in children are a major public health issue. About 15% of the 7 years old children suffer from urination disorders and functional constipation represents 3% of the complaints in pediatric consultations. With these numbers and the time students spend at school, it seems essential to evaluate the risk factors to which they are exposed, especially the conditions of the school toilets. Objective : To determine whether a negative perception of the school toilets is a risk factor for perineal disorders for children at school. Method : In order to conduct this study, research was based on two databases (PubMed and Cochrane). Studies on the impact of bad conditions in school toilets on perineal functions in school children were selected. Their methodological quality was evaluated using the Newcastle Ottawa Scale. Results : Six cross-sectional studies were included. In total, 28 627 pupils were evaluated and the results of these studies show that there is a statistically significant link between being exposed to toilets deficient in terms of hygiene, security or intimacy and the development of perineal disorders such as terminal functional constipation, urinary incontinence, and urination disorders. Conclusion : The sanitary conditions of the school toilets can cause perineal disorders in children. Physiotherapists have an important role in prevention and promoting health in schools.
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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 | 0.005 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".