Engagement With and Acceptability of Telephone-based Telemedicine in Addiction Care in Vancouver, Canada, 2020–2023
Bibliographic record
Abstract
Objectives: Telemedicine-based addiction medicine care expanded during the COVID-19 pandemic. We characterize the engagement with and acceptability of these services in Vancouver, Canada. Methods: Using longitudinal self-report data from participants who were prescribed medications to address cravings and withdrawal of any substances in 2020–2023 in 3 cohorts of community-recruited people who use drugs in Vancouver, we performed a multivariable generalized estimating equation analysis to identify factors associated with telemedicine use for substance use medications in the past 6 months (vs in-person care). We also explored participant perceptions of their telemedicine engagement. Results: Among 871 eligible participants, 428 (49.1%) were prescribed substance use medications through telemedicine at the first interview during the study period. Compared with those who did not use telemedicine, telemedicine use in a 6-month period was positively associated with continuing to be prescribed substance use medications from the previous 6-month period (adjusted odds ratio [AOR]=1.53; 95% CI: 1.11–2.11) and negatively associated with homelessness (AOR=0.71, 95% CI: 0.54–0.92) and daily opioid use (AOR=0.78, 95% CI: 0.64–0.94). With each subsequent assessment, participants were less likely to have used telemedicine (AOR=0.86, 95% CI: 0.81–0.91). Of the 255 participants who preferred telemedicine (59.6%), 214 (83.9%) cited convenience as the reason. Conclusions: Telemedicine use was preferred to in-person care among most of our participants, but less likely among participants showing markers of structural vulnerability and higher intensity substance use. Future research should investigate the efficacy of telemedicine versus in-person addiction medicine care.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".