“A complex interface: Exploring sickle cell disease from a parent’s perspective, after moving from Sub-Saharan Africa to North America”
Bibliographic record
Abstract
INTRODUCTION: Sickle cell disease (SCD) is an inherited, multi-system, chronic disease with the highest prevalence affecting people of Sub-Saharan African descent. While major advances in SCD care have occurred over the last few decades in many African countries these advances are not readily available. Prior literature from Ghana and Kenya describe stigma, despair, and economic burden as well as hope when a child has SCD. When people migrate to North America with a child with SCD it is unknown whether their perception of the disease changes. We asked, "How do immigrant parents of children with SCD from Sub-Saharan Africa perceive, and manage the disease in the context of western medical care?" METHODS: The research question was explored with qualitative methodology, specifically focused ethnography. Semi-structured interviews were conducted with parent(s). The interviews were audio recorded, transcribed, and open coded. Rigor was determined through methodological coherence, appropriate and sufficient sampling, and iterative data collection and analysis. RESULTS: Twelve interviews were conducted. Identified themes are as follows: memories of SCD in Africa, the emotional journey towards acceptance, and parental approach to care for their child. CONCLUSIONS: Healthcare providers should be responsive to an immigrant families' needs and not expect linear progression of emotional acceptance to the diagnosis. Healthcare providers patience with the process helps establish trust, works to facilitate and encourage hope and acknowledges the strength of the families, and their dedication to their family member. Healthcare providers should acknowledge parents' sources of support (religion/family) and ensure parents are aware of medical advances.
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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 | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.009 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".