A Systematic Review of COVID-19 Risk Factors Impact on the Mental Health of LGBTQ+ Youth
Bibliographic record
Abstract
Youth who identify as lesbian, gay, bisexual, transgender, and queer or questioning (LGBTQ+) are a growing population in the U.S. and are disproportionately impacted by mental health disparities. The COVID-19 pandemic has been associated with increased depression, anxiety, and other psychological issues among the general population. The purpose of this review was to examine risk factors exacerbated by COVID-19 and their effects on the mental health of LGBTQ+ youth. The PRISMA (Preferred Reporting Items for Systematic Review and Meta-Analyses) method for reporting was used to identify, analyze, and synthesize the selected literature. Thirteen studies were identified that met the inclusion criteria. COVID-19 risk factors were categorized at the individual, relational, community, and societal levels. The results suggest that the following factors were associated with poorer mental health: individual factors of less education, income, and employment; concerns about COVID-19; pre-existing mental health issues and being a sexual or gender minority; and relationship factors of reduced socialization and spending more time with unsupportive family. Additionally, loss of safe spaces (school, youth organizations, etc) at the community level, social distancing policies, and a loss of access to gender-affirming care at the societal level were detrimental to mental health. LGBTQ+ youth can benefit from resources which allow them to stay connected to peers, friends, community resources, the LGBTQ+ community, and supportive educational environments during “stay at home” orders. The COVID-19 pandemic worsened many risk factors for LGBTQ+ youth, making mental health resources vital for this group.
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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 | 0.009 | 0.043 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.010 |
| Bibliometrics | 0.009 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".