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Record W1823284910 · doi:10.1007/s00787-015-0764-7

Poor peer relations predict parent- and self-reported behavioral and emotional problems of adolescents with gender dysphoria: a cross-national, cross-clinic comparative analysis

2015· article· en· W1823284910 on OpenAlexaffabout
A. de Vries, Thomas D. Steensma, Peggy T. Cohen‐Kettenis, Doug P. VanderLaan, Kenneth J. Zucker

Bibliographic record

VenueEuropean Child & Adolescent Psychiatry · 2015
Typearticle
Languageen
FieldPsychology
TopicLGBTQ Health, Identity, and Policy
Canadian institutionsUniversity of TorontoCentre for Addiction and Mental Health
FundersNederlandse Organisatie voor Wetenschappelijk Onderzoek
KeywordsCBCLChild Behavior ChecklistGender dysphoriaChild and adolescent psychiatryPsychologyDysphoriaClinical psychologyDevelopmental psychologyPsychiatryAnxietySocial psychologyGender identity

Abstract

fetched live from OpenAlex

This study is the third in a series to examine behavioral and emotional problems in children and adolescents with gender dysphoria in a comparative analysis between two clinics in Toronto, Ontario, Canada and Amsterdam, the Netherlands. In the present study, we report Child Behavior Checklist (CBCL) and Youth Self-Report (YSR) data on adolescents assessed in the Toronto clinic (n = 177) and the Amsterdam clinic (n = 139). On the CBCL and the YSR, we found that the percentage of adolescents with clinical range behavioral and emotional problems was higher when compared to the non-referred standardization samples but similar to the referred adolescents. On both the CBCL and the YSR, the Toronto adolescents had a significantly higher Total Problem score than the Amsterdam adolescents. Like our earlier studies of CBCL data of children and Teacher's Report Form data of children and adolescents, a measure of poor peer relations was the strongest predictor of CBCL and YSR behavioral and emotional problems in gender dysphoric adolescents.

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)0.002
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 score0.035
Threshold uncertainty score0.070

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
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)0.0010.000

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 head0.084
GPT teacher head0.393
Teacher spread0.308 · 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

Citations159
Published2015
Admission routes2
Has abstractyes

Explore more

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