Predictors of Access To Sexual And Reproductive Health Services By Urban Refugees In Kampala City, Uganda
Bibliographic record
Abstract
Abstract Background: The influx of over 1.3 million refugees in Uganda, with over 10% settling in the capital city Kampala, challenges the ability of urban refugees to access Sexual and Reproductive Health services (SRH) and family planning (FP) amidst the multiple uncertainties of a precarious everyday life. Utilization of SRH services remains low among urban refugees despite the fact that these services are essential to those of reproductive age and vulnerable to unwanted pregnancies and its consequences and contracting sexually transmitted infections (STIs) including HIV. Mildmay Uganda conducted a multimethod outreach program to establish the predictors of access to SRH services by urban refugees in Kampala city. This paper reports on social demographic characteristics that influenced the uptake of SRH services by urban refugees.Methods: A participatory, gender based, community-led, empowerment approach known as Gender Action Learning Systems (GALS) was employed to deliver SRH including family planning services to urban refugees in Kampala between March 2018 and September 2019. Urban refugees enrolled in GALS were interviewed at the beginning and end of the GALS intervention, where both qualitative and quantitative data were collected. Univariate, bivariate, and multivariate analyses were conducted to determine social demographic factors influencing the uptake of SRH services by urban refugees.Results: The study enrolled 867 participants, with 605 remaining to the end. Median age was 29 (IQR:22-36) years with a standard deviation of 10.7, 52% of the participants had never married. Retention in the study of the sexually active age cohort of primary interest (15 -34) was higher than the 35-54 cohort for both men and women. There were significant associations between SRH use and age, religion and education level among the urban refugees. Pentecostal religion (Adjusted OR 7.9; 3.5-18) and education level of primary (Adjusted OR 3.4; 1.1-11) were associated with uptake of SRH and FP. Conclusion: The participatory, peer-led community approach to delivering SRH services to urban refugees in this research project boosted uptake by the refugees and supported its successful completion and ability to address previously unknown predictors. A continuous awareness campaign using tested models such as GALS to promote services to refugees is needed to successfully integrate newcomers into Uganda’s general healthcare 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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".