A qualitative assessment of tablet injectable opioid agonist therapy (TiOAT) in rural and smaller urban British Columbia, Canada: Motivations and initial impacts
Bibliographic record
Abstract
BACKGROUND: The evolving and unpredictable unregulated drug market has driven an unprecedented overdose crisis that requires effective intervention. Growing evidence suggests that novel opioid agonist treatments, such as tablet injectable opioid agonist therapy (TiOAT), have potential to prevent overdoses and other drug-related harms. More evidence is needed to characterize their utility in achieving these outcomes. The current article is an analysis of two TiOAT programs implemented in British Columbia, Canada, to assess impact on health and well-being, including overdose risk. Moreover, we explored participants' enrollment goals and if they were achieved. METHODS: The study employed qualitative methods to evaluate the TiOAT program in two sites between October 2021 and April 2022. We developed a semi-structured interview tool to guide in depth interviews. All interviews (n = 32) took place on teleconference software or in person. Thematic analysis allowed for the emergence of themes associated with TiOAT participation. RESULTS: Participants discussed various motivations for enrolling in TiOAT, which included gaining financial stability, reducing or eliminating drug use, addressing withdrawal symptoms, wanting to work, and improving social circumstances. An assessment of initial programmatic impacts revealed that many participant-identified motivators were achieved. Participants also reported fewer or no overdoses since starting TiOAT, and many reported switching from injecting to smoking drugs. Some challenges included adequate dosing as evidenced by ongoing withdrawal and pain. Some participants requested additional opioids, such as diacetylmorphine, to aid in reducing illicit drug use. CONCLUSION: Participants described how TiOAT helped them to achieve many of their goals. Suggested programmatic improvements include enhanced patient-provider co-design with respect to dosing to address ongoing withdrawal and pain. As the unpredictability the unregulated drug market worsens, novel options, such as TiOAT, ought to be implemented broadly to reduce overdose events and improve quality of life for people 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 | 0.000 | 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".