1484 Meeting the health needs of unaccompanied asylum seeking children: a scoping review of routine health assessment
Bibliographic record
Abstract
Background Approximately, 34 million of 79.5 million forcibly displaced persons globally are minors, many of whom are unaccompanied asylum seeking children (UASC). UASC often experience unmet health needs, physical harm or emotional trauma in their birth country, or during their journey to seek asylum. International guidelines recommend health screening for all migrant children. Objectives Scope the literature on UASC routine health assessment across Australia, European Economic Area, Canada, New Zealand, Switzerland, United Kingdom and United States (n=36). Analyse health screening programmes to inform future health policy. Methods Literature published (2010-March 2021) was systematically searched across MEDLINE, Web of Science, Cochrane and CINAHL. Records were screened against the inclusion criteria. A framework analysis across national and international organizations’ websites identified additional documents. Results 33 of 1432 records were included. UASC screening was reported across 13/36 countries, summarised in table 1. Commonly, studies were observational reports lacking references to clinical guidelines. Tuberculosis disease screening was offered in 12/13 countries. 8/13 countries used a risk-based approach, meaning UASC exposed to risk factors or from areas endemic for conditions (such as tuberculosis, hepatitis or parasites) were screened. Non-communicable disease screening guidance was present across 10/13 countries. 7/13 proposed blood testing for anaemia and nutritional deficiencies. Dental checks and developmental assessments were suggested in 7/13. Mental health screening was recommended in 6/13 countries. Conclusions Studies reporting UASC health assessment were not found for all countries. We found considerable procedural variation, which can exacerbate health inequalities. While we do not assume UASC health needs in these countries are not addressed, it raises concerns of the standards followed. Countries reporting screening may represent settings where optimal assessment is being followed. However, no audit data are available to compare guideline implementation and effectiveness. Frequently, emphasis was placed on infectious disease screening whilst other health components like mental health were less commonly addressed. UASC health should be prioritised, guidelines must include mental and social wellbeing parallel to communicable disease assessment. The UN Convention on the Rights of the Child recognises children’s right to the highest attainable standard of health. Voluntary comprehensive health assessments could ensure no child is deprived of their rights.
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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 | 0.019 | 0.091 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.027 | 0.029 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".