What are the ethical implications of using prize-based contingency management in substance use? A scoping review
Bibliographic record
Abstract
BACKGROUND: The area of substance use is notable for its early uptake of incentives and wealth of research on the topic. This is particularly true for prize-based contingency management (PB-CM), a particular type of incentive that uses a fishbowl prize-draw design. Given that PB-CM interventions are gaining momentum to address the dual public health crises of opiate and stimulant use in North America and beyond, it is imperative that we better understand and critically analyze their implications. PURPOSE: The purpose of this scoping review paper is to identify the characteristics of PB-CM interventions for people who use substances and explore ethical implications documented in the literature as well as emerging ethical implications that merit further consideration. METHODS: The PRISMA-ScR checklist was used in conjunction with Arksey and O'Malley's methodological framework to guide this scoping review. We completed a two-pronged analysis of 52 research articles retrieved through a comprehensive search across three key scholarly databases. After extracting descriptive data from each article, we used 9 key domains to identify characteristics of the interventions followed by an analysis of ethical implications. RESULTS: We analyzed the characteristics of PB-CM interventions which were predominantly quantitative studies aimed at studying the efficacy of PB-CM interventions. All of the interventions used a prize-draw format with a classic magnitude of 50%. Most of the interventions combined both negative and positive direction to reward processes, behaviors, and/or outcomes. One ethical implication was identified in the literature: the risk of gambling relapse. We also found three emerging ethical implications by further analyzing participant characteristics, intervention designs, and potential impact on the patient-provider relationship. These implications include the potential deceptive nature of PB-CM, the emphasis placed on the individual behaviors to the detriment of social and structural determinants of health, and failures to address vulnerability and power dynamics. CONCLUSIONS: This scoping review offers important insights into the ethics on PB-CM and its implications for research ethics, clinical ethics, and public health ethics. Additionally, it raises important questions that can inform future research and dialogues to further tease out the ethical issues associated with PB-CM.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".