Eating disorders in minority ethnic populations in Australia, Canada, Aotearoa New Zealand and the UK: a scoping review
Bibliographic record
Abstract
BACKGROUND: Historically, eating disorder (ED) research has largely focused on White girls and women, with minority ethnic populations underrepresented. Most research exploring EDs in minority ethnic populations has been conducted in the United States (US). The aim of this scoping review, the first of its kind, was to systematically examine research on disordered eating and EDs among minority ethnic populations in Australia, Canada, Aotearoa New Zealand and the United Kingdom (UK), four countries with shared sociocultural and healthcare characteristics. An inequity lens was applied to highlight gaps in research, access, and treatment experiences. METHOD: Five databases (Medline, Embase, PsycINFO, CINHAL and Web of Science) were searched up to March 7, 2024. Two independent reviewers screened titles and abstracts and full texts against eligibility criteria resulting in the inclusion of 87 records (76 peer-reviewed articles and 11 theses). Included studies were charted according to their focus, study design, sample characteristics and findings, with a particular focus placed on prevalence, access to treatment and treatment experience. RESULTS: The majority of identified studies were conducted in the UK (61%, 53 studies). There was a notable lack of studies investigating assessment, diagnosis and intervention. Methodologies varied, though most studies utilised cross-sectional survey designs. Most samples were non-clinical, exclusively or predominantly girls and women, and focused on adolescents and young adults. Asian populations were the most frequently studied minority ethnic group. Understanding of prevalence and treatment experience amongst minority ethnic groups was limited. CONCLUSION: There is a need for further research addressing inequities in ED prevalence, service access, and treatment experiences among minority ethnic and Indigenous groups, especially in Australia, Canada and Aotearoa New Zealand. Improved ethnicity data collection and culturally sensitive approaches to assessment, diagnosis and treatment are essential. Recommendations for future research and clinical practice are provided.
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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 | 0.010 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.027 | 0.033 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.003 |
| 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".