Self-assessed puberty is reliable in a low-income setting in rural Pakistan
Bibliographic record
Abstract
Objectives Staging sexual maturation is an integral component of adolescent research. The Pubertal Development Scale (PDS) is commonly used as a puberty self-assessment tool because it avoids the use of images. Among the youth living in rural Pakistan, we determined the accuracy of self-reported pubertal assessments using a modified PDS compared to the 'gold standard' of physically assessed Tanner stages by a physician. Methods The strength of agreement between self-assessed puberty using a modified PDS and the 'gold' standard of physician-assessed Tanner stages was reported using weighted kappa (κ w) for girls (n = 723) of 9.0-14.9 years of age or boys (n = 662) of 10.0-15.9 years of age living in the rural District of Matiari. Results Agreement between the gold standard and self-assessment for puberty was substantial, with a κ w of 0.73 (95% confidence interval [CI]: 0.67; 0.79) for girls and a κ w of 0.61 (95% CI: 0.55; 0.66) for boys. Substantial agreement was observed for both boys and girls classified as thinness but only for girls with a normal body mass index. Those who were classified as severely thin had moderate agreement. The prevalence of overestimation was 18.5% (95% CI: 15.9-21.5) for girls and 2.7% (95% CI: 1.7-4.3) for boys, while the prevalence of underestimation estimation was 8.0% (95% CI: 6.2-10.2) for girls and 29.0% (95% CI: 25.8-32.6) for boys. Conclusions Most girls and boys assessed their pubertal development with substantial agreement with physician assessment. Girls were better able to assess their puberty, but they were more likely to overestimate. Agreement for boys was also substantial, but they were more likely to underestimate their pubertal development. In this rural Pakistan population, the PDS seems to be a promising tool for self-assessed puberty.
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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 | 0.002 | 0.008 |
| 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".