Smoking‐specific compensatory health beliefs and the readiness to stop smoking in adolescents
Bibliographic record
Abstract
OBJECTIVE: Compensatory health beliefs (CHBs) are defined as beliefs that negative consequences of unhealthy behaviours can be compensated for by engaging in other health behaviours. CHBs have not yet been investigated in detail regarding smoking. Smoking might cause cognitive dissonance in smokers, if they are aware that smoking is unhealthy and simultaneously hold the general goal of staying healthy. Hence, CHBs are proposed as one strategy for smokers to resolve such cognitive dissonance. The aim of the present study was to develop a scale to measure smoking-specific CHBs among adolescents and to test whether CHBs are related to a lower readiness to stop smoking. DESIGN: For the main analyses, cross-sectional data were used. In order to investigate the retest-reliability follow-up data, 4 months later were included in the analysis. METHOD: A newly developed scale for smoking-specific CHBs in adolescents was tested for its validity and reliability as well as its predictive value for the readiness to stop smoking in a sample of 244 smokers (15-21 years) drawn from different schools. Multilevel modelling was applied. RESULTS: Evidence was found for the reliability and validity of the smoking-specific CHB scale. Smoking-specific CHBs were significantly negatively related to an individual's readiness to stop smoking, even after controlling for other predictors such as self-efficacy or conscientiousness. CONCLUSIONS: CHBs may provide one possible explanation for why adolescents fail to stop smoking.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.002 | 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".