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Record W1899241846 · doi:10.1186/1471-2458-7-336

Rates, risk factors & methods of self harm among minority ethnic groups in the UK: a systematic review

2007· review· en· W1899241846 on OpenAlexaff
Kamaldeep Bhui, Kwame McKenzie, Farhat Rasul

Bibliographic record

VenueBMC Public Health · 2007
Typereview
Languageen
FieldPsychology
TopicSuicide and Self-Harm Studies
Canadian institutionsCentre for Addiction and Mental Health
Fundersnot available
KeywordsBiostatisticsMedicineEthnic groupHarmPublic healthEpidemiologyEnvironmental healthDemographyInternal medicineSocial psychologyNursingPsychology

Abstract

fetched live from OpenAlex

BACKGROUND: Studies suggest that the rates of self harm vary by ethnic group, but the evidence for variation in risk factors has not been synthesised to inform preventive initiatives. METHODS: We undertook a systematic literature review of research about self harm that compared at least two ethnic groups in the United Kingdom. RESULTS: 25 publications from 1765 titles and abstracts met our inclusion criteria. There was higher rate of self harm among South Asian women, compared with South Asian men and White women. In a pooled estimate from two studies, compared to their white counterparts, Asian women were more likely to self harm (Relative Risk 1.4, 95%CI: 1.1 to 1.8, p = 0.005), and Asian men were less likely to self harm (RR 0.5, 95% CI: 0.4 to 0.7, p < 0.001). Some studies concluded that South Asian adults self-harm impulsively in response to life events rather than in association with a psychiatric illness. Studies of adolescents showed similar methods of self harm and interpersonal disputes with parents and friends across ethnic groups. There were few studies of people of Caribbean, African and other minority ethnic groups, few studies took a population based and prospective design and few investigated self harm among prisoners, asylum seekers and refugees. CONCLUSION: This review finds some ethnic differences in the nature and presentation of self harm. This argues for ethnic specific preventive actions. However, the literature does not comprehensively cover the UK's diverse ethnic groups.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.044
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.787
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0440.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0080.001
Bibliometrics0.0010.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.353
GPT teacher head0.525
Teacher spread0.173 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSystematic review
Domainnot available
GenreReview

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".

Quick stats

Citations116
Published2007
Admission routes1
Has abstractyes

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