Barriers and facilitators to accessing post sexual-based violence health services among young women attending higher education institutions in Nigeria
Bibliographic record
Abstract
BACKGROUND: Post sexual-based violence (SBV) services are crucial for mitigating SBV-induced consequences. However, these services are reportedly rare and often underutilized, particularly by young women in Sub-Saharan Africa. This study aimed to explore the barriers and facilitators to accessing post-SBV services among young women (18-24 years) attending higher education institutions in Nigeria. METHODS: An online survey, using a piloted questionnaire, was administered to a purposive sample of 114 participants recruited from social media platforms between the 8th and 22nd March 2022. Descriptive statistics were used to summarize the study findings. RESULTS: The majority (71.1%) of the participants were between the ages of 21 and 24 years. Of the 37 participants who indicated they have had their first sexual intercourse, a quarter (9, 24.3%) indicated it was non-consensual. Also, 1 in 5 respondents did not identify SBV/abuse as abnormal. Half of the participants (50.9%) strongly agreed that a post-SBV health service should be the first place to seek care following an incident of rape, however, over half (53.2%) reported a lack of awareness of existing post-SBV health services as a key barrier affecting access. Less than half of the participants strongly agreed that healthcare workers could provide the post-SBV services highlighted in the study, including emergency contraceptives to prevent pregnancy (42.9%) and post-exposure prophylaxis (PEP) to prevent human immunodeficiency virus (HIV) (39.6%), highlighting awareness gaps. Other significant barriers included stigma, shame, and a lack of support systems. Key facilitators included assurance of confidentiality and access to free post-SBV health services. CONCLUSION: Significant barriers and facilitators affect access to post-SBV health services in Nigeria, particularly among young women. Multilevel efforts by families, civil society organizations, communities, and governments are essential to address these barriers and improve access to post-SBV health services.
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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 | 0.003 |
| 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) | 0.004 | 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".