Impact of the COVID-19 Pandemic on Persons Living with HIV in Western Washington: Examining Lived Experiences of Social Distancing Stress, Personal Buffers, and Mental Health
Bibliographic record
Abstract
Pandemic-related stressors may disproportionately affect the mental health of people with HIV (PWH). Stratified, purposive sampling was used to recruit 24 PWH who participated in a quantitative survey on COVID-19 experiences for in-depth interviews (IDIs). IDIs were conducted by Zoom, audio recorded and transcribed. Thematic analysis was used to develop an adapted stress-coping model. Participants experienced acute stress following exposure events and symptoms compatible with COVID-19. Social isolation and job loss were longer-term stressors. While adaptive coping strategies helped promote mental health, participants who experienced multiple stressors simultaneously often felt overwhelmed and engaged in maladaptive coping behaviors. Healthcare providers were important sources of social support and provided continuity in care and referrals to mental health and social services. Understanding how PWH experienced stressors and coped during the COVID-19 pandemic can help healthcare providers connect with patients during future public health emergencies, address mental health needs and support adaptive coping strategies.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".