’More of the same, but worse than before’: A qualitative study of the challenges encountered by people who use drugs in Nova Scotia, Canada during COVID-19
Bibliographic record
Abstract
BACKGROUND: To learn about the experiences of people who use drugs, specifically opioids, in the Halifax Regional Municipality (HRM), in Nova Scotia, Canada during the COVID-19 pandemic through qualitative interviews with people who use drugs and healthcare providers (HCP). This study took place within the HRM, a municipality of 448,500 people [1]. During the pandemic many critical services were interrupted while overdose events increased. We wanted to understand the experiences of people who use drugs as well as their HCPs during the first year of the pandemic. METHODOLOGY: We conducted a qualitative study using semi-structured interviews with 13 people who use drugs and 6 HCPs, including physicians who work in addiction medicine (3), a pharmacist, a nurse, and a community-based opioid agonist therapy (OAT) program staff member. Participants were recruited within HRM. Interviews were held via phone or videoconference due to social distancing directives. Interviews focused on the challenges people who use drugs and HCPs faced during the pandemic as well as elicited perspectives on a safe supply of drugs and the associated barriers and facilitators to the provision of a safe supply. RESULTS: Of the 13 people who use drugs who participated in this study, ages ranged from 21-55 years (mean 40). Individuals had spent on average 17 years in HRM. Most people who use drugs (85%, n = 11) utilized income assistance, the Canadian Emergency Response Benefit, or disability support. Many had experienced homelessness (85%, n = 11) and almost half (46%, n = 6) were currently precariously housed in the shelter system. The main themes among interviews (people who use drugs and HCPs) were housing, accessing healthcare and community services, shifts in the drug supply, and perspectives on safe supply. CONCLUSIONS: We identified several challenges that people who use drugs face in general, but especially during the COVID-19 pandemic. Access to services, housing support, and interventions to use safely at home were limited. As many challenges faced by people who use drugs exist outside of COVID-19, we concluded that the formal and informal interventions and changes in practice that were made to support people who use drugs should be sustained well past the end of the pandemic. The need for enhanced community supports and a safe supply of drugs, despite its complicated nature, is essential for the health and safety of people who use drugs in HRM, especially during COVID-19.
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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 | 0.008 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.026 | 0.020 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".