Prevalence and Correlates of Clinically Elevated Depressive Symptoms in a Nationwide Sample of Transgender, Nonbinary, and Gender Diverse Young Adults in the United States: Cross-Sectional Survey Study
Bibliographic record
Abstract
Background: In the United States, transgender, nonbinary, and gender diverse (TGD) young adults experience a higher risk of depression compared to their cisgender peers. Understanding factors associated with increased risk of depression within the TGD young adult population is important to guide clinical care as well as inform the development of interventions to reduce mental health disparities. Objective: This exploratory study investigated the prevalence and correlates of positive screening for depressive symptoms among TGD young adults to inform the design, development, and implementation of national interventions aimed at improving mental health in this at-risk population. Methods: In August 2022, a cross-sectional, nationwide online survey was conducted among TGD young adults aged 18-25 (N=104) in the United States. Measures included sociodemographic variables, family characteristics, mental health care utilization, and the two-item Patient Health Questionnaire-2 (PHQ-2) screener for depression. Poisson regression models with robust variance estimation were fitted to estimate adjusted prevalence ratios (aPR) and 95% CI for correlates of PHQ-2 depression (score ≥3). Results: The study sample had a mean age of 22 (SD 2) years; 48/104 (46%) individuals identified as Black, Indigenous, or other People of Color, and 69/104 (66%) were nonbinary. Overall, 44 (42%) individuals screened positive for depression using PHQ-2. In a multivariable model adjusted for age, race and ethnicity, US census region, and health insurance status, factors associated with increased depression prevalence using PHQ-2 included low versus high family support (aPR 1.54, 95% CI 1.05-2.27) and identifying with a nonChristian religion versus being unaffiliated (aPR 1.66, 95% CI 1.04-2.63). Factors associated with reduced depression prevalence included living in a rural versus suburban area (aPR 0.48, 95% CI 0.26-0.92) and receiving mental health therapy versus not (aPR 0.71, 95% CI 0.53-0.97). Conclusions: The high prevalence of depressive symptoms among TGD young adults in this study sample highlights the need for comprehensive mental health evaluation and support in this population. Depression risk is increased among certain subgroups, such as those with low family support. These findings are valuable in informing the development of interventions that aim to improve mental health outcomes among TGD young people.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.013 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".