Identifying substitute activities for alcohol consumption: a preliminary analysis
Bibliographic record
Abstract
Individuals with alcohol use disorder may excessively value alcohol reinforcement over other types of rewards and may seek out environments supportive of alcohol consumption despite negative consequences. Therefore, examining ways to increase engagement in substance-free activities may be useful in treating alcohol use disorder. Past research has focused on preference and frequency of engagement in alcohol-related versus alcohol-free activities. However, no study to-date has examine the incompatibility of such activities with alcohol consumption, an important step in preventing possible adverse consequences during treatment for alcohol use disorder and for ensuring that activities do not function in a complementary fashion with alcohol consumption. The present study was a preliminary analysis comparing a modified activity reinforcement survey with the inclusion of a suitability question to determine the incompatibility of common survey activities with alcohol consumption. Participants recruited from Amazon’s Mechanical Turk (N = 146) were administered an established activity reinforcement survey, questions regarding the incompatibility of the activities with alcohol consumption, and measures of alcohol-related problems. We found that activity surveys may identify activities that are enjoyable without alcohol, but that some of these activities were still compatible with alcohol. For many of the activities examined, participants who rated those activities as suitable with alcohol also reported higher alcohol severity, with the largest effect size differences for physical activity, school or work, and religious activities. The results of this study are an important preliminary analysis for determining how activities may function as substitutes, and may hold implications for harm reduction interventions and public policy.
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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 | 0.008 | 0.059 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.005 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.015 | 0.002 |
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".