Integrated online services for smokers and drinkers? Use of the Check Your Drinking assessment screener by participants of the Stop Smoking Center
Bibliographic record
Abstract
The functional overlap of smoking and problem drinking has led researchers to speculate on the need for integrated treatment models. What of online services? With the burgeoning growth of Web-based interventions for smokers and the increasingly common online services for problem drinkers, there is the potential to provide options for smokers to also deal with any alcohol concerns. The integration of these services might also help increase smoking cessation rates, because alcohol consumption is a known trigger to smoking and also for relapse to smoking. This paper presents results of the use of an online personalized feedback assessment for drinking (Check Your Drinking, CYD) by smokers who were recruited from the Stop Smoking Center (SSC; www.stopsmokingcenter.net). Registered users of the SSC (N= 7,741) were invited to complete the CYD (now located as part of an online alcohol reduction program freely available at www.alcoholhelpcenter.net). A total of 963 SSC users responded to the invitation, providing information about their drinking as well as a summary of their current smoking and past experiences of alcohol functioning as a trigger for smoking. One-third of current daily smokers were problem drinkers (24% of occasional smokers and 22% of former smokers were current problem drinkers). Most (82%) daily smokers who were current drinkers reported they frequently or always experienced a strong urge, desire or thoughts about smoking when they drank alcohol. This brief report will explore the implications of the overlap of smoking and drinking by these online participants and will discuss the potential benefits of providing an integrated service for smokers and problem drinkers.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".