Implementing intravenous iron for maternal anemia in Nigeria: A qualitative study of healthcare provider experiences using the Normalization Process Theory
Bibliographic record
Abstract
Abstract Background Maternal anemia remains a significant public health challenge in Nigeria, affecting approximately 25-46% of pregnant women and contributing to adverse maternal and neonatal outcomes. Intravenous (IV) iron provides a promising alternative to conventional oral iron supplementation for managing moderate to severe maternal anemia; however, its implementation in resource-limited settings faces numerous challenges. This study aimed to understand how the implementation of IV iron became embedded in everyday practice, including factors influencing skilled healthcare providers’ (SHPs) engagement, workflow integration processes, and sustainability. Methods This was a qualitative study embedded within the Implementation Research for Intravenous Iron Use in Pregnant and Postpartum Women in Nigeria (IVON-IS) project across six healthcare facilities in Lagos, Nigeria. Eighteen key informant interviews were conducted with purposively sampled SHPs across the six IVON-IS facilities. The data were analyzed deductively based on the Normalization Process Theory (NPT) constructs (coherence, cognitive participation, collective action, and reflexive monitoring), and inductively to identify themes related to each of these constructs. Results Our study revealed strong coherence among SHPs regarding the purpose and benefits of IV iron compared to traditional treatments. Cognitive participation varied across facilities, with leadership support and patient-centred motivation emerging as critical facilitators. Collective action was faced with challenges, including workflow disruptions, staffing constraints, and space limitations, despite adequate resource provision. Reflexive monitoring processes were robust, with providers continuously evaluating effectiveness through clinical outcomes and patient feedback while expressing concerns about long-term sustainability. Conclusion The implementation of IV iron for maternal anemia in Nigeria demonstrated variability across NPT constructs, with strong coherence and reflexive monitoring but challenges in cognitive participation and collective action. Critical success factors included strong leadership support, adequate resource provision, continuous quality improvement processes, and proactive sustainability planning. These findings provide valuable guidance for scaling up IV iron use as part of comprehensive maternal health services in Nigeria and similar resource-constrained settings.
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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 | 0.012 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.007 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| 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".