Validation of the adolescent menstrual poverty questionnaire
Bibliographic record
Abstract
Background: Menstrual poverty is the inability to obtain menstrual products due to financial, social, cultural, and political barriers to accessing menstrual products. It affects 65% of adolescents in Nova Scotia, but its impact on adolescents in Canada remains unknown. The adolescent Menstrual Poverty Questionnaire (aMPQ) was designed to assess the impact of menstrual poverty on adolescents living in countries with higher socioeconomic status. This study aims to translate the aMPQ into French and to validate it in both English and French to facilitate nationwide use. Methods: The aMPQ was translated to French using forward translation by a professional translation service, then backward translation by a bilingual investigator. English and French speaking physicians specialized in adolescence care were recruited to participate in content validity assessment of the English and French aMPQs by completing a web-based survey containing rating scales from 1 to 4 on both clarity and relevance for each of the 27 items of the aMPQ. The Content Validity Index (CVI) for each Item (I-CVI) and for the general Scale (S-CVI) were calculated. An I-CVI of 0.78 or higher and an S-CVI of 0.90 or higher supports content validity. Results: Twelve physicians completed content validity surveys for the English and French aMPQ. Each question on the aMPQ had an I-CVI above 0.78 for both relevance and clarity. The S-CVI was 0.98. Conclusion: Content validity of the aMPQ in both English and French was established. The aMPQ is a valid bilingual tool and can be used for nationwide assessment of the impact of menstrual poverty on adolescents.
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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 | 0.008 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".