Patterns of cognitive dissonance-reducing beliefs among smokers: a longitudinal analysis from the International Tobacco Control (ITC) Four Country Survey
Bibliographic record
Abstract
OBJECTIVE: The purpose of this paper is to assess whether smokers adjust their beliefs in a pattern that is consistent with Cognitive Dissonance Theory. This is accomplished by examining the longitudinal pattern of belief change among smokers as their smoking behaviours change. METHODS: A telephone survey was conducted of nationally representative samples of adult smokers from Canada, the USA, the UK and Australia from the International Tobacco Control Four Country Survey. Smokers were followed across three waves (October 2002 to December 2004), during which they were asked to report on their smoking-related beliefs and their quitting behaviour. FINDINGS: Smokers with no history of quitting across the three waves exhibited the highest levels of rationalisations for smoking. When smokers quit smoking, they reported having fewer rationalisations for smoking compared with when they had previously been smoking. However, among those who attempted to quit but then relapsed, there was once again a renewed tendency to rationalise their smoking. This rebound in the use of rationalisations was higher for functional beliefs than for risk-minimising beliefs, as predicted by social psychological theory. CONCLUSIONS: Smokers are motivated to rationalise their behaviour through the endorsement of more positive beliefs about smoking, and these beliefs change systematically with changes in smoking status. More work is needed to determine if this cognitive dissonance-reducing function has an inhibiting effect on any subsequent intentions to quit.
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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 | 0.005 |
| 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".