Health Provider and Sexual and Gender Minority Service User Perspectives on Provision of Mental Health Services During the Early Phase of the COVID-19 Pandemic in British Columbia, Canada
Bibliographic record
Abstract
While the COVID-19 pandemic impacted everyone, social determinants of health and structural inequities have had compounding effects that shaped the experiences of some sub-populations during the pandemic. Stigmatization, discrimination, and exclusion contribute to a disproportionately high burden of mental health concerns among sexual minority (i.e., lesbian, gay, bisexual, queer, and other sexually-diverse) and gender minority people. Pre-pandemic, these health inequities are exacerbated by barriers to adequate mental health services including cost, waitlists, and experiences of sexual and gender minority stigma when accessing providers. During the COVID-19 pandemic, these barriers were further complicated by drastic changes in service delivery and access during the pandemic—i.e., a shift to online/virtual provision of care to reduce risk of COVID-19 transmission. To better understand the experiences of sexual and gender minority people accessing mental health services during the first three to nine months of the COVID-19 pandemic, we conducted semi-structured interviews with a purposive sample of 15 health care providers and administrators (summer 2020) and 14 sexual and gender minority individuals interested in accessing mental health services (fall 2020) in British Columbia, Canada. We used interpretive description to inductively analyze interview data. Triangulating between the provider and service user datasets, we examined changes in mental health and coping during the COVID-19 pandemic. We recorded increases in isolation and lack of identity affirmation; inequities in accessing mental health services during the pandemic, perceived opportunities for mental health support, and avenues for reducing mental health inequities through system-level changes that deserve particular attention during the pandemic.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.018 | 0.004 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".