The reliability and predictive validity of the Heaviness of Smoking Index and its two components: Findings from the International Tobacco Control Four Country study
Bibliographic record
Abstract
BACKGROUND: There is increasing recognition that the two measures in the Heaviness of Smoking Index (HSI), time to first cigarette of the day (TTFC) and daily consumption (cigarettes per day [CPD]), are strong predictors of quitting behavior. METHODS: Use of Waves 1-4 of International Tobacco Control cohort with around 8,000 respondents per wave and 6,000 for prediction of quit outcomes at the next wave. We measured TTFC and CPD at each wave and quit outcomes at the next wave. We also looked at the relative utility of the standard categorical scoring compared with a continuous score using the square root of CPD minus the natural log of TTFC in minutes. RESULTS: We found considerable consistency of the measures across years with a small decrease as duration between measurements increased. For a 3-year gap, the correlations were .72 and .70 for the continuous and categorical composite HSI measures, respectively, and were at least .63 for the individual components. Both TTFC and CPD independently predicted maintenance of quit attempts (for at least 1 month) in each of the three wave-to-wave replications, and these effects were maintained when controlling for demographic factors. CPD also predicted making attempts consistently, but the results for TTFC was not consistently significant. DISCUSSION: Both TTFC and CPD are fairly reliable over time and are important predictors of quitting. There are only small effects of mode of computing the scores, and the two items can be used either individually or combined as the HSI.
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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 | 0.015 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".