The Autonomy Over Smoking Scale.
Bibliographic record
Abstract
Our goal was to create an instrument that can be used to study how smokers lose autonomy over smoking and regain it after quitting. The Autonomy Over Smoking Scale was produced through a process involving item generation, focus-group evaluation, testing in adults to winnow items, field testing with adults and adolescents, and head-to-head comparisons with other measures. The final 12-item scale shows excellent reliability (alphas = .91-.97), with a one-factor solution explaining 59% of the variance in adults and 61%-74% of the variance in adolescents. Concurrent validity was supported by associations with age of smoking initiation, lifetime use, smoking frequency, daily cigarette consumption, history of failed cessation, Hooked on Nicotine Checklist scores, and Diagnostic and Statistical Manual of Mental Disorder (4th ed., text rev.; American Psychiatric Association, 2000) nicotine dependence criteria. Potentially useful features of this new instrument include (a) it assesses tobacco withdrawal, cue-induced craving, and psychological dependence on cigarettes; (b) it measures symptom intensity; and (c) it asks about current symptoms only, so it could be administered to quitting smokers to track the resolution of symptoms.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".