Characteristics Associated with Reliability in Reporting of Contraceptive Use: Assessing the Reliability of the Contraceptive Calendar in Seven Countries
Bibliographic record
Abstract
Although the reproductive calendar is the primary tool for measuring contraceptive dynamics in low-income settings, the reliability of calendar data has seldom been evaluated, primarily due to the lack of longitudinal panel data. In this research, we evaluated the reproductive calendar using data from the Performance Monitoring for Action Project. We used population-based longitudinal data from nine settings in seven countries: Burkina Faso, Nigeria (Kano and Lagos States), Democratic Republic of Congo (Kinshasa and Kongo Central Provinces), Kenya, Uganda, Cote d'Ivoire, and India. To evaluate reliability, we compared the baseline cross-sectional report of contraceptive use (overall and by contraceptive method), nonuse, or pregnancy with the retrospective reproductive calendar entry for the corresponding month, measured at follow-up. We use multivariable regressions to identify characteristics associated with reliability or reporting. Overall, we find that the reliability of the calendar is in the "moderate/substantial" range for nearly all geographies and tests (Kappa statistics between 0.58 and 0.81). Measures of the complexity of the calendar (number of contraceptive use episodes, using the long-acting method at baseline) are associated with reliability. We also find that women who were using contraception without their partners/husband's knowledge (i.e., covertly) were less likely to report reliably in several countries.
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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 | 0.010 | 0.032 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".