Consistency in self-reported age at first sex and marriage among adolescents and young adults in Northwestern Tanzania: insights from repeated responses
Bibliographic record
Abstract
Introduction: Adolescents and young adults face unique sexual and reproductive health (SRH) challenges, with early sex and marriage linked to negative outcomes. Reported ages at first sex (AFS) and first marriage (AFM) are crucial indicators for SRH and HIV intervention programs. This study aimed to assess the consistency of AFS and AFM reports among adolescents and young adults with repeated responses across eight survey rounds (1994-2016) from the Magu Health and Demographic Surveillance System (Magu HDSS). Methods: A serial cross-sectional survey comprising 58,654 observations from 33,177 individuals in the Magu HDSS, conducted between 1994 and 2016, was analysed. Structured face-to-face interviews were used for data collection. A fixed-effects panel regression model was applied to assess within- and between-individual variability. Reported AFS and AFM were categorized as consistent or inconsistent across survey rounds. Variability and consistency were further analysed across different age groups, sexes, residence area, education, pregnancy and HIV status. Results: The study revealed significant within-individual variability, with nearly half of the variation due to individual-specific reporting changes over time. Among 2,637 individuals aged 15-24 who reported AFS more than once, 1,312 (49.8%) provided consistent values. For AFM, 621 out of 920 individuals (67.5%) reported same age values across multiple surveys. In other words, 49.8% of individuals provided the same AFS values each time, while 67.5% reported the same AFM values; the rest reported different values. Sub-analysis showed that age, sex, residence, HIV status, pregnancy, and education influenced variability and consistency. Females exhibited higher consistency in AFS (56.7%) and AFM (61.0%) compared to males (43.5% and 44.9%, respectively). Adolescents (15-19 years) reported more consistently with lower variability than young adults (20-24 years) and adults (25-49 years). Conclusion: This study assesses the extent of consistency in reported ages among young individuals and identifies the challenge of self-reported AFS and AFM data due to inherent variability and inconsistency. It highlights the need to scrutinize the consistency of these reported events each time these indicators are used to evaluate trends and progress in SRH and HIV programs. A systematic analytical approach is essential for improving data quality and obtaining accurate estimates.
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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 | 0.022 |
| 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 | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".