Challenges of Male Contraceptive Uptake in Indonesia: Opinion of Married Couples
Bibliographic record
Abstract
For more than a decade, the adoption of male contraceptive methods in Indonesia was very low compared to female methods. Yet, in some settings family planning programs focused heavily on female contraceptive services, while male contraceptive services tend to be ignorant. Information from both husbands and wives is needed to obtain an accurate understanding of contraceptive use-behavior within married-couples. Hence, the objective of this study is to investigate factors associated with male contraceptive use among Indonesian couples. This study uses the couple-matched data from the 2017 Indonesia Demographic and Health Survey (IDHS). The analytical sample included 8,427 couples. Chi-square tests and binary logistic regression models were utilized for data analysis. Findings from the bivariate and binary logistic regressions indicate that couples lived in urban areas, couples who attained secondary and higher education, couples who do not want another child, couples who discuss family planning with their spouses, and couples whose wives experienced side effect of female contraception were significantly associated with male contraceptive uptake among Indonesian couples. The results suggest that increasing male contraceptive uptake should be encouraged through spousal communication about family planning.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".