The role of drug treatment and recovery services: an opportunity to address injection initiation assistance in Tijuana, Mexico
Bibliographic record
Abstract
BACKGROUND: In the U.S. and Canada, people who inject drugs' (PWID) enrollment in medication-assisted treatment (MAT) has been associated with a reduced likelihood that they will assist others in injection initiation events. We aimed to qualitatively explore PWID's experiences with MAT and other drug treatment and related recovery services in Tijuana Mexico, a resource-limited setting disproportionately impacted by injection drug use. METHODS: PReventing Injecting by Modifying Existing Responses (PRIMER) seeks to assess socio-structural factors associated with PWID provision of injection initiation assistance. This analysis drew on qualitative data from Proyecto El Cuete (ECIV), a Tijuana-based PRIMER-linked cohort study. In-depth qualitative interviews were conducted with a subset of study participants to further explore experiences with MAT and other drug treatment services. Qualitative thematic analyses examined experiences with these services, including MAT enrollment, and related experiences with injection initiation assistance provision. RESULTS: At PRIMER baseline, 607(81.1%) out of 748 participants reported recent daily IDU, 41(5.5%) reported recent injection initiation assistance, 92(12.3%) reported any recent drug treatment or recovery service access, and 21(2.8%) reported recent MAT enrollment (i.e., methadone). Qualitative analysis (n = 21; female = 8) revealed that, overall, abstinence-based recovery services did not meet participants' recovery goals, with substance use-related social connections in these contexts potentially shaping injection initiation assistance. Themes also highlighted individual-level (i.e., ambivalence and MAT-related stigma) and structural-level (i.e., cost and availability) barriers to MAT enrollment. CONCLUSION: Tijuana's abstinence-based drug treatment and recovery services were viewed as unable to meet participants' recovery-related goals, which could be limiting the potential benefits of these services. Drug treatment and recovery services, including MAT, need to be modified to improve accessibility and benefits, like preventing transitions into drug injecting, for PWID.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".