Body image dissatisfaction among immigrant children and adolescents in Canada and the United States: A scoping review
Bibliographic record
Abstract
OBJECTIVE: To systematically summarize the literature examining body image dissatisfaction (BID) among immigrant children and adolescents living in Canada and the United States (US). METHOD: Sources were identified by entering search terms into six electronic databases and by completing an electronic hand search of research journals focusing on body image. Eligible sources were those published between 1946 and November 2012, conducted within Canada or the US, included immigrant children or adolescents (<18 years), and measured BID through self-report. Synthesis followed the principles of thematic and content analysis (Vaismoradi et al., Nurs Health Sci, 2013,15,398-405). RESULTS: A total of 12 sources were included in our synthesis, spanning years 1991 to 2010. These studies indicate that immigrant children and adolescents experience BID. However, the literature is plagued by a disproportionate focus on females, Latino/Hispanic immigrants, and inadequate attention to issues of measurement. DISCUSSION: There is no evidence about the BID experiences of immigrant children and adolescents in Canada and limited information has stemmed from the US. A more robust evidence-base should include the use of advanced methods to examine the influence of acculturation and acculturative stress on BID among immigrant male and female children and adolescents.
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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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.015 | 0.016 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".