A longitudinal investigation of the effects of the COVID-19 pandemic on 2SLGBTQ+ youth experiencing homelessness
Bibliographic record
Abstract
INTRODUCTION: The objective of this study was to examine the impacts of the coronavirus 2019 (COVID-19) pandemic on various dimensions of wellbeing among 2SLGBTQ+ youth experiencing homelessness over a 12-month period during the COVID-19 pandemic. METHODS: 2SLGBTQ+ youth (recruited using a convenience sampling method) participated in three online surveys to assess mental health (depression, anxiety, suicidality), substance and alcohol use, health care access, and violence for 12-months between 2021-2022. Quantitative data analysis included non-parametric one-sample proportion tests, paired t-test and McNemar's test. Longitudinal data collected across all three timepoints were treated as paired data and compared to baseline data using non-parametric exact multinomial tests, and if significant, followed by pairwise post-hoc exact binomial tests. For the purposes of analysis, participants were grouped according to their baseline survey based on pandemic waves and public health restrictions. RESULTS: 2SLGBTQ+ youth experiencing homelessness (n = 87) reported high rates of mental health challenges, including anxiety and depression, over 12-months during the pandemic. Youth participants reported experiencing poor mental health during the early waves of the pandemic, with improvements to their mental health throughout the pandemic; however, results were not statistically significant. Likewise, participants experienced reduced access to mental health care during the early waves of the pandemic but mental health care access increased for youth throughout the pandemic. CONCLUSION: Study results showed high rates of mental health issues among 2SLGBTQ+ youth, but reduced access to mental health care, due to the COVID-19 pandemic. Findings highlight the need for 2SLGBTQ+ inclusive and affirming mental health care and services to address social and mental health issues that have been exacerbated by the pandemic.
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 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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 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".