“Healthy Bodies, Healthy Minds”: Barriers and solutions to implementing a menstrual hygiene management program in South Sudan
Bibliographic record
Abstract
<title>Abstract</title> <bold>Background:</bold> Menstrual hygiene management (MHM) can be challenging for women and girls living in conflict-affected low- and middle-income countries, where access to menstrual products, soap, water, and private sanitation facilities is often limited. In response to these challenges, the Canadian Red Cross, in partnership with the South Sudan Red Crescent and the South Sudanese Government, implemented the Healthy Bodies Healthy Minds (HBHM) program from 2020-2023 to support MHM in South Sudan. Despite growing attention to MHM needs, few studies have examined the on-the-ground realities of implementing MHM programming in fragile settings. To address this gap, this study aimed to (i) describe the implementation of HBHM, (ii) identify barriers faced during implementation, (iii) identify potential solutions to overcome barriers, and (iv) understand the impact of the COVID-19 pandemic on program delivery. <bold>Methods:</bold> Data was collected through key informant interviews with individuals involved in program design and implementation and were analyzed via thematic analysis. A total of 14 respondents were interviewed. <bold>Results:</bold> Respondents identified several interrelated and compounding barriers, including resource constraints, logistical challenges, competing stakeholder interests/priorities, ongoing conflict, and climate change. To mitigate these barriers and improve the delivery of MHM programs, respondents recommended solutions and strategies such as extending implementation timelines, planning program activities around anticipated climate events, and strengthening inter-organizational collaboration. The COVID-19 pandemic introduced additional barriers, particularly by restricting the movement of people and goods. However, it also yielded unexpected benefits, notably expanding the project’s reach beyond the target group of girls to the broader community. <bold>Conclusions:</bold> Implementation of the HBHM program was impacted by several interrelated and compounding factors including resource constraints and logistical challenges, protracted conflict, climate change, and COVID-19, however, collaboration between implementing partners and agility in the approach to program roll out support enhance program reach. International partnerships enabled community-level implementation which proved especially effective, offering key insights for future MHM programs in South Sudan and similar contexts.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".