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Record W4412148816 · doi:10.3390/healthcare13141659

Psychological and Physical Health Outcomes Associated with Gender-Affirming Medical Care for Transgender and Gender-Diverse Youth: A Critical Review

2025· review· en· W4412148816 on OpenAlexafffundabout
Terri A. Croteau, Jan Gelech, Melanie A. Morrison, Todd G. Morrison

Bibliographic record

VenueHealthcare · 2025
Typereview
Languageen
FieldPsychology
TopicLGBTQ Health, Identity, and Policy
Canadian institutionsUniversity of Saskatchewan
FundersSocial Sciences and Humanities Research CouncilSocial Sciences and Humanities Research Council of Canada
KeywordsTransgenderMental healthPsychologySexual minorityPopulationAnxietyLegislationClinical psychologyMedicinePsychiatryPolitical scienceSexual orientationSocial psychologyEnvironmental health

Abstract

fetched live from OpenAlex

Introduction: Access of transgender and gender diverse (TGD) youth to gender-affirming medical care (GAMC) has become a contentious topic in the West, with many members of the general population, politicians, and even some experts and academic researchers voicing concerns about possible adverse effects of GAMC on the mental and physical health of TGD youth. Due to these concerns, recent years have seen a significant rise in legislation restricting TGD youth from accessing GAMC in countries such as the United States, the United Kingdom, and Canada. However, in this critical review of the literature on the psychological (e.g., anxiety, depression, suicide, and body satisfaction) and physical (e.g., bone health, cognitive function, and fertility) health outcomes associated with GAMC among TGD youth, we argue that, given the state of current research, youth should not be restricted from accessing GAMC. Conclusions: Our findings reinforce the importance of close monitoring by doctors, counselling for TGD youth with respect to potential risks, and increased studies on the topic, especially those focusing on reproductive health.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.725
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0050.001
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.381
GPT teacher head0.556
Teacher spread0.175 · 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

Citations2
Published2025
Admission routes3
Has abstractyes

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