Sexual and reproductive health of adolescent Syrian refugee girls in Lebanon: a qualitative study of healthcare provider and educator perspectives
Bibliographic record
Abstract
BACKGROUND: Adolescent Syrian refugee girls in Lebanon are thought to experience a disproportionate risk of poor sexual and reproductive health, related in part to conflict and displacement. The purpose of this qualitative study was to explore healthcare provider and educator perceptions of the sexual and reproductive health determinants and care-seeking behaviors of this vulnerable population. The findings of the study will inform a health intervention that aims to reduce early marriage and improve access to sexual and reproductive health information and services. METHODS: In-depth interviews and focus group discussions were conducted with stakeholders who work with adolescent Syrian refugee girls in an under-resourced area of eastern Lebanon bordering Syria. Data analysis followed principles of Clarke and Braun's thematic analysis. RESULTS: Study participants perceived adolescent pregnancy, reproductive tract infections, and sexual- and gender-based violence as major population health needs. The study also identified a number of influencing structural and sociocultural determinants of health, including early marriage, adolescent disempowerment, and men's disengagement from care. A conceptual framework based upon the Gelberg-Andersen Behavioral Model for Vulnerable Populations was developed to relate these determinants and guide pathways for potential interventions. CONCLUSIONS: Adolescent sexual and reproductive health interventions among Syrian refugees in Lebanon should adopt a multi-pronged, community-based approach to address underlying health determinants and engage with men and parents of adolescents. Special attention should be given to provider biases in healthcare settings accessible to adolescents, as these may reflect underlying tensions between host and refugee populations and discourage adolescents from seeking care.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".