Change in Finances, Peer Access, and Mental Health Among Trans and Nonbinary People During the COVID-19 Pandemic
Bibliographic record
Abstract
ABSTRACT Purpose COVID-related stressors associated with loss of income and community are compounded with gender minority stress among trans and non-binary people (TNB) – which may result in mental health burden. The present study examined the effect of COVID-related change in finances and TNB gathering access on anxiety and depression among TNB people. Methods Participants were 18 years and older ( M age = 30) who completed both pre-pandemic baseline (Fall 2019) and pandemic follow-up (Fall 2020) surveys in the Trans PULSE Canada study. Multivariable regression analyses examined associations between change in (1) finances and (2) access to TNB peers and mental health during the pandemic. Results Of 780 participants, 50% reported that COVID had a negative effect on personal income and 58.3% reported loss in access to TNB peer or friend gatherings (in person or online). Depression and anxiety symptoms increased from pre-pandemic to follow-up, and most participants were above measurement cut-offs for clinical levels during the pandemic. Changes in finances and access to peer gatherings were associated with depression symptoms during the pandemic, but effects depended on level of pre-pandemic depression. For participants with high pre-pandemic depression, financial stability was not protective against increased depression at follow-up. Participants experiencing unprecedentedly high levels of depression during COVID may have pursued more TNB gatherings. Neither financial change nor access to TNB gatherings were associated with pandemic anxiety. Conclusion Findings suggest need for a multifaceted approach to mental health programmes and services to address structural barriers, including financial support and meaningful TNB community engagement.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".