Gambling treatment service providers’ views about contingency management: a thematic analysis
Bibliographic record
Abstract
BACKGROUND: There is a need to improve retention and outcomes for treatment of problem gambling and gambling disorder. Contingency management (CM) is a behavioural intervention involving identification of target behaviours (such as attendance, abstinence, or steps towards recovery) and the provision of incentives (such as vouchers or credits towards the purchase of preferred items) contingent on objective evidence of these behaviours. Contingency management for abstinence and attendance in substance misuse treatment has a substantial evidence base but has not been widely adopted or extended to other addictive behaviours such as gambling. Potential barriers to the widespread adoption of CM may relate to practitioners' perceptions about this form of incentive-based treatment. The present study sought to explore United Kingdom (UK) gambling treatment providers' views of CM for treatment of problem gambling and gambling disorder. METHODS: We conducted semi-structured interviews with 30 treatment providers from across the UK working with people with gambling problems. Participants were provided with an explanation of CM, several hypothetical scenarios, and a structured questionnaire to facilitate discussion. Thematic analysis was used to interpret findings. RESULTS: Participants felt there could be a conflict between CM and their treatment philosophies, that CM was similar in some ways to gambling, and that the CM approach could be manipulated and reduce trust between client and therapist. Some participants were more supportive of implementing CM for specific treatment goals than others, such as for incentivising attendance over abstinence due to perceived difficulties in objectively verifying abstinence. Participants favoured providing credits accruing to services relevant to personal recovery rather than voucher-based incentives. CONCLUSIONS: UK gambling treatment providers are somewhat receptive to CM approaches for treatment of problem gambling and gambling disorder. Potential barriers and obstacles are readily addressable, and more research is needed on the efficacy and effectiveness of CM for gambling.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.011 | 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".