Knowledge of the ovulatory cycle and its determinants among women of reproductive age in Papua New Guinea: Insights from a population-based study
Bibliographic record
Abstract
BACKGROUND: Correct knowledge of the ovulatory cycle is crucial for preventing unintended pregnancies and improving women's reproductive health. However, the factors affecting this knowledge among women in Papua New Guinea (PNG) remain unclear. This study aimed to assess the prevalence and determine the factors influencing women's knowledge of the ovulatory cycle in PNG. METHODS: Data from the PNG Demographic and Health Survey (DHS) was analyzed. Multivariable logistic regressions were used to determine factors associated with women's knowledge of the ovulatory cycle. Adjusted odds ratios (aOR) with their 95% Confidence Intervals (CI) were reported. A p ≤ 0.05 was considered statistically significant. RESULTS: Of 12,580 women in this study sample, 22% (n = 2,773) had correct knowledge of the ovulatory cycle. Women from the Highlands region (aOR 1.31, 95% CI: 1.00-1.88) and the Momase region (aOR 1.56, 95% CI: 1.15-2.13), those who identified as Christians (aOR 3.01, 95% CI: 1.38-6.59), owned a mobile phone (aOR 1.29, 95% CI: 1.04-1.59), read a newspaper or magazine (aOR 1.30, 95% CI: 1.10-1.54), and had Internet access (aOR 1.21, 95% CI: 1.00-1.85) had higher odds of correct knowledge of the ovulatory cycle. Similarly, those who knew any contraceptive method (aOR 2.13, 95% CI: 1.58-2.87) and currently used the modern method (aOR 1.26, 95% CI: 1.02-1.56) or traditional/folkloric method (aOR 1.82, 95% CI: 1.36-2.43) were more likely to have correct knowledge of the ovulatory cycle. However, knowledge of the ovulatory cycle remained lower among women aged 15-24 and 25-34, those with lower education levels, and those from the Southern region. CONCLUSIONS: In this study, less than a quarter of women had correct knowledge of the ovulatory cycle. Promoting reproductive health knowledge and awareness through educational curricula and mass media platforms could enhance women's understanding of the ovulatory cycle, particularly among younger and less educated and empower them to make informed decisions about their reproductive health.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.003 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".