Women’s multiple uses of an overdose prevention technology to mitigate risks and harms within a supportive housing environment: a qualitative study
Bibliographic record
Abstract
BACKGROUND: North America is amidst an opioid overdose epidemic. In many settings, particularly Canada, the majority of overdose deaths occur indoors and impact structurally vulnerable people who use drugs alone, making targeted housing-based interventions a priority. Mobile applications have been developed that allow individuals to solicit help to prevent overdose death. We examine the experiences of women residents utilizing an overdose response button technology within a supportive housing environment. METHODS: In October 2019, we conducted semi-structured qualitative interviews with 14 residents of a women-only supportive housing building in an urban setting where the overdose response button technology was installed. Data was analyzed thematically and framed by theories of structural vulnerability. RESULTS: While participants described the utility and disadvantages of the technology for overdose response, most participants, unexpectedly described alternate adoptions of the technology. Participants used the technology for other emergency situations (e.g., gender-based violence), rather than its intended purpose of overdose response. CONCLUSIONS: Our findings highlight the limitations of current technologies while also demonstrating the clear need for housing-based emergency response interventions that address not just overdose risk but also gender-based violence. These need to be implemented alongside larger strategies to address structural vulnerabilities and provide greater agency to marginalized women who use drugs.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".