A Pilot Study of Family Planning Perspectives and Practices among Syrian Child Brides in Lebanon
Bibliographic record
Abstract
Child marriage is associated with adolescent pregnancy, which increases maternal and child health risks and rates of child marriage have increased among families affected by the Syrian conflict. Although contraception reduces these risks, data about contraception practices among Syrian child brides is sparse. This cross sectional, descriptive pilot study examined contraceptive knowledge, attitudes, barriers, needs and practices among young Syrian brides. A convenience sample of female Syrian refugees aged 13-25 who had married before the age of 18 was recruited through a civil society organization in Lebanon. Among the 32 participants, there were significant knowledge gaps and negative attitudes towards contraception, with approximately one fifth of participants (18.8%) unaware of contraceptive methods and 84.4% unaware of emergency contraception. Negative attitudes towards contraception were common, including beliefs that it was physically harmful (47.0%), contradicted religious views (43.8%), and lacked support by husbands (50%). The majority of participants (53.1%) had never used contraception with the most common reason being fear of side effects (47%). Approximately one-third (30%) of participants with two or more children reported sub-optimal birth spacing of less than a year and almost one-quarter of participants (24.1%) reported a history of terminating a pregnancy. Notably, one-fifth of participants (20.8%) had an unmet need for contraception, and unwanted pregnancies were common among women who were currently (42.9%) or previously (48.1%) pregnant. Results from this small convenience sample of Syrian child brides in Lebanon identify an urgent need to further explore contraception use among this population and to inform interventions for increased contraception usage to decrease adolescent pregnancies and improve maternal and child health.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| 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".