3 Self-care and coping behaviours among trans and gender-diverse adolescents in clinical care: A mixed methods study
Bibliographic record
Abstract
Abstract Background Referrals for transgender and gender-diverse (TGGD) youth to Canadian clinics providing gender-affirming medical care (GAMC) have grown rapidly over time. GAMC includes hormone suppression and/or hormone therapy as safe and effective strategies to modify secondary sexual characteristics and improve psychiatric outcomes in electing TGGD individuals. There are limited data on the types of coping and self-care behaviours TGGD youth in clinical care use to reduce distress and increase wellness. Objectives This research describes the coping and self-care behaviours of TGGD youth in clinical care across Canada and identifies potential self-care and coping behavioural profiles. Design/Methods This mixed methods study uses data from two companion studies. Trans Youth CAN! (TYC!) is a prospective cohort study of pubertal/post-pubertal youth <16 years naïve to gender-affirming hormone therapy (N=174) referred to one of ten clinics across Canada for hormone suppression and/or hormone therapy recruited from 2017-2019. Stories of Gender-Affirming Care administered semi-structured interviews to youth-parent dyads for youth 9 to 17 years (N=36) at three clinics participating in TYC! from November 2017 to August 2018. Quantitative measures included mental health, self-care, and coping behaviours. Qualitative interview guide asked about youths’ adversities and their self-care and coping behaviours. A latent class analysis (LCA) was used to identify latent classes of survey weight-adjusted TGGD youth engaging in self-care and coping behaviours (N=174). Chi-square tests assessed for differences across demographic variables (α=0.05). Qualitative data was previously coded using adapted Grounded Theory methodology and analyzed using integrated Thematic Analysis to expand upon quantitative findings. Results Our analysis suggests the emergence of five classes: Avoidant, self-harming, alcohol use, and legal document changes (Class 1: 21%); Non-avoidant diverse coping and self-harm behaviours (Class 2: 30%); Avoidant, self-harming, and nicotine/substance use behaviours (Class 3: 9%); Atypical and gender-focused coping behaviours (Class 4: 11%); and Gendered-space avoidant and self-harm behaviours (Class 5: 29%). Chi-square tests revealed no significant differences in age (p=0.2510), gender identity (p=0.5646), and income (p=0.9906) between latent classes. There were significant differences between class 2 and each of the other 4 classes for sex assigned at birth (p<0.0001). Pairwise comparisons also revealed a significant difference in immigration background between classes 2 and 5 (p=0.0030). Qualitative data expanded on quantitative findings. Conclusion This study identifies behavioural profiles of TGGD youth in clinical care and demographic variables across which coping and self-care behaviours might vary. This research can inform tailored interventions and supports at the personal/interpersonal, environmental, and structural levels to promote healthy coping strategies.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".