The health of internally displaced children in sub-Saharan Africa: a scoping review
Bibliographic record
Abstract
BACKGROUND: Internally displaced children are those who have been forced to flee their homes due to severe unfavourable conditions (war, violence or disasters) but have not crossed international borders. Emerging research shows these children face multiple health challenges. However, we found no review focused solely on the health of such internally displaced children. Thus, this review sought to examine what is known about their health and their health concerns. METHODS: A scoping review of the literature was conducted. A total of 10 databases were searched in January 2019, yielding 6602 articles after duplicates were eliminated. Two research assistants independently selected articles that met inclusion criteria. A numerical summary and thematic analysis were conducted to facilitate data extraction and data analysis. RESULTS: A total of 25 articles met the inclusion criteria, including 16 quantitative, 6 qualitative and 3 mixed methods studies. The findings reveal elevated mental health problems and infectious diseases in this population. Findings on the nutritional status of internally displaced children as a broad group are mixed, with some studies showing poorer nutritional status among the children in this group and others showing poorer nutritional health status among host society children. Internally displaced children also experience challenges with access to health services. Premigration factors (trauma) and postmigration factors (humanitarian assistance on displacement) all contribute to the health of internally displaced children. CONCLUSION: Findings provide insight into the complex array of factors influencing the health of internally displaced children. More intervention studies are required to address the needs of this population.
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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 | 0.005 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| 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".