A Qualitative Analysis of Knowledge, Attitudes, and Perceptions of Family Planning Among Syrian Refugees in Lebanon
Bibliographic record
Abstract
Introduction: The Syrian conflict has displaced approximately 1.5 million people to Lebanon. In this setting of forced displacement, child marriage, insecurity, and limited access to sexual and reproductive health services can lead to increased rates of adolescent pregnancy, which have been linked to exacerbated maternal morbidity and mortality. Family planning can help to delay childbirth, increase time between pregnancies, and empower women to make their own reproductive health choices. To date, there is limited research on the knowledge of, and attitudes towards, family planning among Syrian refugees in Lebanon.Objective: Identify knowledge, attitudes, and perceptions towards family planning among Syrian refugees with the overarching goal of informing response strategies to improve sexual and reproductive health for displaced Syrian families in Lebanon.Methods: A thematic qualitative analysis of focus group discussions conducted in Lebanon in January 2017 by the ABAAD Resource Center for Gender Equality. The sample of 99 participants included Syrian women, girls and men.Results: While contraceptive use was generally deemed acceptable by women and girls, husbands’ and mother-inlaws’ attitudes towards fertility influenced their decisions about its use in practice. Additionally, reliable family planning services and sexual and reproductive health education were perceived as seldom available to Syrian refugees in Lebanon. Participants suggested that family planning awareness programs were needed for both parents and girls.Discussion: Changes at the policy, service, community, and individual levels are required to increase knowledge regarding and access to family planning services for Syrian refugees in Lebanon. In the interim, non governmental organizations may play a role in providing educational and supportive services for displaced Syrian girls and women.
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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 | 0.009 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.006 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".