The mental health needs of refugee children: A review of literature and implications for nurse practitioners
Bibliographic record
Abstract
PURPOSE: To review the current literature regarding the mental health needs of refugee children resettled in the United States and provide recommendations for clinicians working with refugee children and their families. DATA SOURCES: An extensive review of journal articles published from research conducted in first-world countries such as the United States, the United Kingdom, Australia, the Netherlands, and Canada. CONCLUSIONS: Review of the current literature suggests that while some refugee children will suffer poor mental health outcomes, such as post-traumatic stress disorder, depression, and anxiety, others may not. Several groups of researchers concluded that refugee children are actually a high functioning group. Many coping and protective factors as well as risk factors for poor outcomes have been identified by the research. IMPLICATIONS FOR PRACTICE: Because many refugee children will experience adverse psychosocial outcomes during the resettlement period, it is essential that the mental health screenings be performed during each primary care visit. Nurse practitioners have the unique opportunity to make a difference in the lives of refugee children because they play a pivotal role in the assessment, screening, and referral of children for mental health services.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".