Examining Barriers as Risk Factors for Relapse: A focus on the Canadian Treatment and Recovery System of Care
Bibliographic record
Abstract
ABSTRACT Objectives: In 2016, the Canadian Centre on Substance Use and Addiction (CCSA) conducted the first survey of individuals in recovery from addiction in Canada. The findings revealed that many individuals in recovery lead meaningful lives, contributing to their families and society. However, participants also identified a number of barriers to starting and maintaining recovery. The current study examined the relationship between the barriers experienced and relapse during recovery. Methods: Data from the 2016 Life in Recovery (LIR) from Addiction in Canada survey were analyzed using descriptive and logistic regression analyses. Participants comprised 855 individuals (Mage = 47.3 years), all of whom self-reported being in recovery from addiction. Results: Logistic regressions revealed that upon starting recovery, long delays for treatment, odds ratio (OR) = 1.77, 95% confidence interval (CI) = 1.21–2.60,P < 0.01, and not having stable housing, OR = 1.83, 95% CI = 1.14–2.95,P < 0.05, were associated with increased risk of relapse. Moreover, upon examining barriers to maintaining recovery, a lack of supportive social networks, OR = 2.10, 95% CI = 1.26–3.48,p < 0.01, a lack of programs or supports, OR = 1.75, 95% CI = 1.03–2.98,P < 0.05, and the costs of recovery services OR = 1.73, 95% CI = 1.02–2.91,P < 0.05 were associated with increased risk of relapse. Conclusions: Targeted investments to address the treatment-related barriers that most strongly relate to relapse, could significantly improve the lives of individuals struggling with addiction and those beginning and maintaining their recovery journey. Objectifs: En 2016, le Centre canadien de lutte contre l’alcoolisme et les toxicomanies (CCLAT) a mené un premier sondage auprès des personnes en rétablissement à la suite d’une dépendance au Canada. Les résultats ont révélé que de nombreuses personnes en rétablissement mènent des vies significatives, contribuant ainsi à leur famille et à la société. Cependant, les participants ont également identifié un certain nombre d’obstacles au démarrage et au maintien du rétablissement. La présente étude a examiné la relation entre les obstacles rencontrés et la rechute pendant le rétablissement. Méthodes: Les données de l’enquête Life in Recovery (LIR) de l’Enquête sur la toxicomanie au Canada de 2016 ont été analysées à l’aide d’analyses de régression descriptives et logistiques. Les participants comprenaient 855 individus (Moyenne d’âge = 47,3 ans), qui ont tous déclaré être en rétablissement après une dépendance. Résultats: Les régressions logistiques ont révélé qu’au début du rétablissement, de longs délais de traitement, chance de réussite (CR) = 1,77, intervalle de confiance à 95% (IC) = 1,21-2,60,p < 0,01, et n’ayant pas de logement stable, CR = 1,83, IC 95% = 1,14-2,95,p < 0,05, étaient associés à un risque accru de rechute. De plus, en examinant les obstacles au maintien du rétablissement, un manque de réseaux sociaux de soutien, CR = 2.10, IC à 95% = 1.26-3.48,p < 0.01, manque de programmes ou de soutien, CR = 1.75, IC à 95% = 1.03–2,98,p < 0,05, et les coÛts des services de récupération CR = 1,73, IC 95% = 1,02–2,91,p < 0,05 étaient associés à un risque accru de rechute. Conclusions: Des investissements ciblés visant à surmonter les obstacles liés au traitement les plus étroitement liés à la rechute pourraient améliorer considérablement la vie des personnes aux prises avec une dépendance et de celles qui amorcent et poursuivent leur chemin vers le rétablissement.
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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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.009 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".