Intersectionality analysis of young people’s experiences and perceptions of discrimination in primary health centers in Ebonyi State, Southeast Nigeria
Bibliographic record
Abstract
BACKGROUND: Young people (aged 10 to 24 years) in sub-Saharan Africa bear a huge and disproportionate burden of poor sexual and reproductive health (SRH) outcomes due to inequalities and discrimination in accessing sexual and reproductive health services (SRHS). This study assessed the experiences and perceptions of discrimination among young people seeking SRH services in Primary Health Centers (PHCs) using an intersectionality lens. METHODS: A cross-sectional mixed-methods study was undertaken in six local government areas (LGAs) in Ebonyi State, southeast Nigeria. The LGAs comprise both urban and rural locations. The study population for the quantitative survey consisted of 1025 randomly selected young boys and girls aged 15-24 years. Eleven focus group discussions (FGDs) were conducted with the young people. Descriptive and inferential analyses were performed for quantitative data, while thematic analysis was performed for the qualitative data, using NVivo. RESULTS: A total of 16.68% participants in the survey reported that young girls/women were treated badly/unfairly compared to young boys/men when seeking SRH services in PHCs; 15.22% reported that young clients get treated badly/unfairly from adults; and 12.49% reported that young clients with poor economic status were treated unfairly. Respondents also reported that young clients with disability (12.12%), and those who are poorly educated or uneducated (10.63%) are treated badly by healthcare providers when they access SRH services. Young people in urban areas were about 7 times more likely to believe that girls/young women are treated badly than boys/young men when seeking SRH services in PHCs compared to those who live in rural areas (p < 0.001). Among the young girls/women, residing in urban areas, being poor and in school increased the likelihood of getting treated badly/unfairly when receiving SRH services by 4 times (p < 0.001). The qualitative results revealed that health workers were generally harsh to young people seeking SRH services and the level of harshness or unfriendliness of the health workers varied depending on the young person's social identity. CONCLUSION: There are varieties of intersecting factors that contribute to the discrimination of young clients in PHCs. This underscores the urgent need to prioritize intersectional perspectives in the design and implementation of interventions that will improve access and use of SRH services by young people.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".