Perceptions of Problem Gambling Among Methadone Maintenance Treatment Clients and Counsellors
Bibliographic record
Abstract
Problem gambling is highly prevalent and rarely treated among clients who attend methadone maintenance treatment programs (MMTPs). Compared with those of the general population, rates of gambling disorder have been found to be elevated among individuals receiving methadone maintenance treatment. Our study aims were to (a) develop a clearer understanding of the gambling experience of clients and counsellors at a methadone clinic and (b) gain insight into the current treatment options and obstacles to treatment in the clinic. Semi-structured interviews focusing on gambling issues were conducted with 8 clients and 8 counsellors at an MMTP located in an urban area. Participants were asked questions to gain an understanding about their perspectives on, treatment options for, and treatment barriers to problem gambling in the clinic. Data were coded by 4 investigators by using a constant comparison, open coding approach. The findings revealed important differences between clients and counsellors: Opinions differed on the definition of problem gambling, obstacles to treatment, and optimal treatment settings. Clients and counsellors also agreed on some elements, including the negative impact that problem gambling can have on recovery from substance use. This examination of responses of counsellors and client feedback provides a useful mechanism to better understand problem gambling in MMTPs. In addition, the findings have important clinical implications, including a need for more effective screening and treatment in MMTPs and to provide substance use counsellors with training related to problem gambling.RésuméLe jeu compulsif est hautement répandu et rarement traité parmi les clients qui suivent un programme de traitement d’entretien à la méthadone. Comparés à ceux de la population en général, les taux de jeu pathologique ont jugé élevés chez les personnes qui suivent un tel traitement. Les objectifs de notre étude étaient de deux ordres : a) mieux comprendre l’expérience de jeu des clients et les connaissances en cette matière des conseillers d’une clinique de traitement à la méthadone, et b) avoir une meilleure compréhension des options de traitement actuelles et des obstacles au traitement en clinique. Des entretiens semi-structurés portant sur les problèmes de jeu ont été menés auprès de 8 clients et de 8 conseillers dans un centre de traitement, situé en zone urbaine. On a posé des questions aux participants pour mieux comprendre leurs points de vue sur les options et les obstacles au traitement contre le jeu problématique à la clinique. Les données ont été codées par quatre chercheurs en utilisant une approche de codification ouverte à comparaison constante. Les résultats ont révélé des différences importantes entre les clients et les conseillers : les opinions divergeaient quant à la définition du jeu problématique, les obstacles au traitement et les paramètres de traitement optimaux. Les clients et les conseillers ont par ailleurs été d’accord sur certains éléments, notamment l’impact négatif que le jeu problématique peut avoir sur le rétablissement d’une consommation abusive. L’examen des réponses des conseillers et des commentaires des clients constitue un mécanisme efficace pour mieux comprendre le jeu problématique dans les programmes de traitement d’entretien à la méthadone. De plus, les résultats ont d’importantes répercussions cliniques, notamment la nécessité d’un dépistage et d’un traitement d’entretien à la méthadone plus efficaces et d’une formation sur le jeu problématique pour les conseillers en toxicomanie.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".