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Record W4403681573 · doi:10.1093/pch/pxae067.005

05 The experience of youth on the waitlist for gender-affirming care in Manitoba

2024· article· en· W4403681573 on OpenAlexaboutno aff
Jennifer L. Bhatla, Kristin James, Kaylen A E Lamb, Chrystal Neault-Lount, Jennifer L. P. Protudjer, Shayne D. Reitmeier, Megan Cooney, Brandy Wicklow

Bibliographic record

VenuePaediatrics & Child Health · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicHealthcare innovation and challenges
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyGender studiesSociology

Abstract

fetched live from OpenAlex

Abstract Background Waitlist times are often two years for youth to be seen for initial assessment for gender-affirming hormone therapy in Manitoba, Canada. It is well known that transgender youth awaiting hormone therapy have high rates of mental health challenges, including depression, anxiety, and suicidal ideation. Accessing care that is affirming and supportive, including primary care and counselling, can also be a challenge. Objectives The purpose of this study was to understand the experiences of youth and their caregivers on the waitlist for the Winnipeg, Manitoba-based Gender Diversity Affirmation and Action for Youth (GDAAY) clinic, the provincial transgender health clinic. Specifically, we were interested in what community based resources youth were accessing, mental health impacts, and suggestions for improvements. Design/Methods Qualitative, semi-structured interviews were conducted. Youth aged 14-17 years on the waitlist for 12-24 months for gender-affirming hormone therapy assessment and their caregivers were recruited. Separate interviews were conducted for youth and their caregivers. All interviews were virtual, recorded, and transcribed prior to thematic analysis. Results Youth (n=8) and caregivers (n=9) described barriers to supported transition. The first theme, “In a Black Hole” describes frustration and disappointment with the lack of regular ongoing communications from GDAAY. It also extends to the mental health challenges faced by youth and caregivers alike. Anxiety and self-harm were consistently described, with caregivers volunteering more information on self-harm and suicidality than youth. Youth described dysphoria and two youth found alternative providers for hormone therapy while on the waitlist. Our second theme, “Structural Transphobia”, describes the attitudinal, technological, physical, and architectural barriers faced by the participants. For example, one caregiver described a hospital admission for suicide attempt during which the hospital bracelet displayed the wrong gender, the wrong name, contributing to frequent mis-gendering. Frustration with the inability to change the name and gender marker in provincial charting systems was similarly of concern. Our final theme, “Manitoba: An Information Desert” describes the systemic barriers faced including lack of knowledgeable providers and reliable information within the province. Youth and caregivers described concerns with identifying primary care and councilors that understood challenges specific to transgender youth. Conclusion Although delays in gender-affirming therapy were noted, youth socially transitioned and accessed existing resources. However, mental health concerns persisted and participants felt frustrated and unsupported during their extensive wait times. Improved experiences may be achieved by additional communication from the clinic, hands-on assistance with accessing relevant resources, and an improved online presence. Potential competing interests Funding was obtained by a resident research small grant from the University of Manitoba. A similar abstract was submitted to CPEG but it focuses on a new intervention of a phone call from social work when a youth is added to the waitlist.

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)0.001
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.436
Threshold uncertainty score0.878

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0130.003
Scholarly communication0.0030.001
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.110
GPT teacher head0.376
Teacher spread0.266 · 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 designQualitative
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".

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Citations0
Published2024
Admission routes1
Has abstractyes

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