Lessons learned from a sexual and reproductive health and rights peer education program to prevent adolescent pregnancies in high schools in Rwanda.
Bibliographic record
Abstract
Adolescent pregnancies that occur in schools remain a major public concern in Rwanda. Sexual and Reproductive Health and Rights (SRHR) school based programs are less effective and discussing sexual health with adolescents is considered as taboo in Rwandan societies. Yet, adolescents still seek information about SRHR from their peers and research shows that peers are often incorrectly informed about SRHR topics. One of the effective strategies to reduce adolescent pregnancies in secondary schools is equipping adolescents with accurate and reliable knowledge. In 2019, we conducted our first network event with different stakeholders. The stakeholders included: school directors, head teachers, biology teachers, local political delegates, religious people among others to help gain insights into SRHR. A survey was conducted and administered to in-school adolescents in Kirehe district (S3 - S6 level, n=563) with the aim of examining adolescents' level of knowledge and attitudes regarding SRHR. In addition, six focus group discussions (FGDs) were conducted to obtain a deeper understanding of the SRHR needs and the possible contributions and content of a peer -to- peer education program (PEP). The lessons learned included: a) engaging parents in the network event and development of PEP; b) constant communication utilizing the different social media platforms, c) enhanced collaboration between the project implementers and stakeholders a facet of bottom-up approaches to expedite this project; and d) the project should have better anticipated on possible and unforeseen external barriers. Implementing a PEP in Kirehe secondary schools resulted in substantive changes such as positively transforming peer educators (PEs) and the elimination of teenage pregnancies in the selected schools. Overall, the number of PEs was not adequate to cover the number of students and anti-bullying training should have been provided to all students before the project implementation.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| 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".