Acceptability of Technological Solutions for Overdose Monitoring: Perspectives of People who Use Drugs
Bibliographic record
Abstract
Introduction Rising overdose deaths are a devastating problem across the United States and Canada. Despite the availability of observed consumption sites in British Columbia (BC), data suggest people who use drugs (PWUD) alone in private residences are most at risk of overdose death. These individuals may not use consumption sites due to fear of stigmatization, lack of privacy, or personal preference. It is this population that would benefit from overdose monitoring alternatives. Methods This 2018 study employed two sources of data. (1) A provincial harm reduction distribution site client survey administered at 27 sites across BC asked about cell phone possession and functionality. (2) Structured interviews with PWUD in Vancouver gathered perspectives regarding monitoring devices and alerting systems. Results The client survey was administered to 486 individuals. Among 443 respondents, 48% ( n = 212) owned a cellphone and 68% ( n = 115) of individuals with a cellphone with access to internet ( n = 168) would use an application to mitigate opioid-related overdose deaths. Thirty qualitative interviews were performed; thematic analysis of the responses identified three major themes – safety, public versus private drug use, and technological monitoring and function. The relevance of technological devices was affected by the inconsistent availability of cellphones, concerns about anonymity, as well as personal comfort while using drugs. Conclusions Technological applications may not be suitable for clients with transient lifestyles, no permanent home, and lack of consistent access to a mobile device. Thorough needs assessments, considerations of lifestyle limitations, and understanding perceptions around cellphone and overdose monitoring can increase the potential that devices will be used. Highlights • 45% ( n = 219) of client survey respondents owned a cellphone • Out of cellphone owners, 59% ( n = 102) of client survey respondents had access to internet • Of 168 with internet access, 68% willing to use any applications for overdose response • Applications not suitable for transient lifestyles, no permanent home, and lack of consistent access to cellphone
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".