How the COVID-19 Pandemic Influenced HIV Care: Are We Prepared Enough for Future Pandemics? An Assessment of Factors Influencing Access, Utilization, Affordability, and Motivation to Engage with HIV Services amongst African, Caribbean, and Black Women
Bibliographic record
Abstract
The COVID-19 pandemic resulted in disruption in healthcare delivery for people living with human immunodeficiency virus (HIV). African, Caribbean, and Black women living with HIV (ACB WLWH) in British Columbia (BC) faced barriers to engage with HIV care services prior to the COVID-19 pandemic that were intensified by the transition to virtual care during the pandemic. This paper aims to assess which factors influenced ACB WLWH's access to, utilization and affordability of, and motivation to engage with HIV care services. This study utilized a qualitative descriptive approach using in-depth interviews. Eighteen participants were recruited from relevant women's health, HIV, and ACB organizations in BC. Participants felt dismissed by healthcare providers delivering services only in virtual formats and suggested that services be performed in a hybrid model to increase access and utilization. Mental health supports, such as support groups, dissolved during the pandemic and overall utilization decreased for many participants. The affordability of services pertained primarily to expenses not covered by the provincial healthcare plan. Resources should be directed to covering supplements, healthy food, and extended health services. The primary factor decreasing motivation to engage with HIV services was fear, which emerged due to the unknown impact of the COVID-19 virus on immunocompromised participants.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".