Exploring the impact of COVID-19 on substance use patterns and service access of street involved individuals in Kingston, Ontario: a qualitative study
Bibliographic record
Abstract
This study aims to understand the experiences of street-involved individuals during the COVID-19 pandemic regarding substance use patterns and service access. With the collision of the COVID-19 pandemic and Canadian opioid epidemic came an increase in opioid related overdoses and increased barriers in accessing essential services since March 2020. Semi-structured interviews were conducted in June and July 2021, with 30 street-involved individuals in Kingston, Ontario. Analysis followed a phenomenological approach to qualitative research. Themes were coded by two independent researchers using NVIVO12. COVID-19 had detrimental effects on the lives of street-involved folks who use substances. Increased substance use to combat feelings of isolation and hopelessness related to loss of income and housing was commonly described. Increased fentanyl usage was considered the major contributor to the rise in overdoses over the pandemic. Restrictions on public access to businesses and services disproportionately impacted individuals with limited means. Harm reduction services and mental health support were considered extremely important throughout the pandemic. The coinciding COVID-19 pandemic and opioid epidemic place street-involved individuals who use substances in a uniquely dangerous position. As such, it is imperative that public policy decision-makers consider the differential needs of street-involved community members to provide safe, relevant, and compassionate solutions in future public health emergencies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".