Innovations in residential treatment that promote multi-drug addiction recovery
Bibliographic record
Abstract
Abstract Background As the drug addiction crisis deepens in many countries across the globe, governments are rapidly expanding publicly funded treatment facilities. At the same time, the illicit drug market has evolved with many substances now containing multiple addictive drugs that complicate recovery. The evidence base for treatment remains primarily focused on single substances. The purpose of this study was to examine the lived experience of adults who attended in-patient treatment centres for multi-drug addiction in Canada. Methods This qualitative study was conducted in 2022 with 32 adults who voluntarily attended an in-patient treatment centre for drug addiction (44% female, 23-53 years). All had been addicted to multiple substances including opioids, crack and methamphetamines. Most (70%) were homeless before treatment. In 1-hour semi-structured interviews adults described the structures and programming that helped them recover in these facilities. Many tried multiple facilities and thus had a rich history of lived experience to draw from. Narrative inquiry was used to characterize qualitative themes across interviews using a phenomenological lens. Results Seven qualitative themes emerged from the data. Residential treatment centres that were effective at helping adults recover from multi-drug addiction: (1) provided flexible stays up to 100 days; (2) felt like a home not a prison; (3) permitted opioid replacement therapies; (4) provided a variety of recovery tools (e.g., cognitive behavioural therapy, Narcotics Anonymous, cultural supports); (5) helped adults reunite with family, find a safe place to stay, and find work before discharge; (6) provided transitional housing after discharge if needed; and (7) provided free long-term recovery support and check-ins after discharge. Conclusions The findings of this study highlight 7 actions that treatment facilities can adopt and test with their own clients in an effort to better support multi-drug addiction recovery. Key messages • A stronger evidence base is needed to inform in-patient multi-drug addiction treatment. • Findings underline 7 actions treatment facilities can take to promote multi-drug addiction recovery.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".