Mental health among transgender and gender diverse youth: An exploration of effects during the COVID-19 pandemic.
Bibliographic record
Abstract
Objective: The coronavirus 2019 (COVID-19) pandemic is raising concerns about mental health across the population Because transgender and gender-diverse youth have particular mental health vulnerabilities, this study examines their mental health challenges during the early stages of the pandemic Method: A cross-sectional survey was conducted in the early COVID-19 pandemic period, which included 29 transgender and gender-diverse youth and 593 cisgender youth Descriptive statistics, Fisher's exact tests, and logistic regression analyses were conducted to understand the differential impact of COVID-19 on mental health and related constructs Results: Results show that transgender and gender diverse youth are more greatly affected by mental health challenges during the COVID-19 pandemic than cisgender youth (p = 001) They report more mental health and substance use service disruptions (p < 001) and less social support from their families (p = 007) compared with cisgender youth A large proportion (63 0%) report unmet needs for mental health and substance use during the early pandemic period, compared with 27 9% of cisgender youth (p = 008) Conclusions: Transgender and gender-diverse youth constitute a vulnerable population during the COVID-19 pandemic and are experiencing substantial mental health impacts, in conjunction with high levels of service disruption and less support from family members Researchers and service planners are encouraged to engage directly with transgender and gender diverse youth to understand how their support needs evolve over the course of the pandemic and how services can be adapted to meet their needs (PsycInfo Database Record (c) 2021 APA, all rights reserved) Impact Statement Because the COVID-19 pandemic is raising concerns about mental health, especially among vulnerable populations, we examined mental health during COVID-19 among youth with cisgender versus transgender and gender-diverse identities Results show that transgender and gender-diverse youth are experiencing substantial negative mental health impacts from the pandemic, more so than cisgender youth They also report more mental health and substance use service disruptions and less social support from their families compared with cisgender youth Researchers and service planners are encouraged to work directly with transgender and gender-diverse youth to understand how services can be adapted to meet their needs (PsycInfo Database Record (c) 2021 APA, all rights reserved)
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".