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Record W4399299506 · doi:10.1007/s11920-024-01508-1

Eating Disorders in Sexual and Gender Minority Adolescents

2024· review· en· W4399299506 on OpenAlexaff
Jason M. Nagata, E. T. Stuart, Jacqueline O. Hur, Smriti Panchal, Patrick Low, Anita V. Chaphekar, Kyle T. Ganson, Jason M. Lavender

Bibliographic record

VenueCurrent Psychiatry Reports · 2024
Typereview
Languageen
FieldPsychology
TopicEating Disorders and Behaviors
Canadian institutionsUniversity of Toronto
FundersNational Institute of General Medical SciencesNational Institutes of Health
KeywordsEating disordersSexual minorityClinical psychologyPsychologySexual orientationPsychiatryMedicineSocial psychology

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: To consolidate recent literature addressing eating disorders and disordered eating behaviors among sexual and gender minority (SGM) adolescents, including but not limited to lesbian, gay, bisexual, transgender, and queer (LGBTQ) adolescents. RECENT FINDINGS: Sexual and gender minority adolescents are at heightened vulnerability to eating disorders and disordered eating behaviors compared to their cisgender and heterosexual peers, potentially due to minority stress, gender norms, objectification, and the influence of the media, peers, and parents. We report findings from recent literature on the epidemiology and prevalence, assessment, mental health comorbidity, quality of life and psychosocial functioning, risk and protective factors, and treatment and interventions for eating disorders in sexual and gender minority adolescents. Addressing eating disorders in sexual and gender minority adolescents requires an integrated approach consisting of screening, tailored treatment, and comprehensive support to address intersectional challenges. Gender-affirming and trauma-informed care approaches may be considered.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.927
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.074
GPT teacher head0.414
Teacher spread0.340 · 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 designNot applicable
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

Citations35
Published2024
Admission routes1
Has abstractyes

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