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Record W3214952802 · doi:10.1007/s10578-021-01289-1

Examining the Mental Health Presentations of Treatment-Seeking Transgender and Gender Nonconforming (TGNC) Youth

2021· article· en· W3214952802 on OpenAlexafffundabout
Shannon L. Stewart, Jocelyn N. Van Dyke, Jeffrey W. Poss

Bibliographic record

VenueChild Psychiatry & Human Development · 2021
Typearticle
Languageen
FieldPsychology
TopicLGBTQ Health, Identity, and Policy
Canadian institutionsUniversity of WaterlooWestern University
FundersPublic Health Agency of Canada
KeywordsMental healthTransgenderPsychologyClinical psychologyDepression (economics)AnxietyPsychiatry

Abstract

fetched live from OpenAlex

Recent research suggests that transgender and/or gender nonconforming (TGNC) youth present with heightened levels of mental health problems compared to peers. This study seeks to examine the mental health needs of a large sample of treatment-seeking TGNC youth by comparing them to cisgender males and females. Participants were 94,804 children and youth ages 4-18 years (M = 12.1, SD = 3.72) who completed the interRAI Child and Youth Mental Health Instrument (ChYMH) or Screener (ChYMH-S) at participating mental health agencies in the Ontario, Canada. Overall, the mental health presentations of TGNC youth were similar to cisgender females but at higher acuity levels. TGNC youth showed significantly higher levels of anxiety, depression, social disengagement, positive symptoms, risk of suicide/self-harm, and were more likely to report experiencing emotional abuse, past suicide attempts, and a less strong, supportive family relationship than cisgender females and males. Clinical implications of these findings are discussed.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.162
Threshold uncertainty score0.323

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.106
GPT teacher head0.374
Teacher spread0.267 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations21
Published2021
Admission routes3
Has abstractyes

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