Identity change among smokers and ex-smokers: Findings from the ITC Netherlands Survey.
Bibliographic record
Abstract
Successful smoking cessation appears to be facilitated by identity change, that is, when quitting or nonsmoking becomes part of smokers' and ex-smokers' self-concepts. The current longitudinal study is the first to examine how identity changes over time among smokers and ex-smokers and whether this can be predicted by socioeconomic status (SES) and psychosocial factors (i.e., attitude, perceived health damage, social norms, stigma, acceptance, self-evaluative emotions, health worries, expected social support). We examined identification with smoking (i.e., smoker self-identity) and quitting (i.e., quitter self-identity) among a large sample of smokers (n = 742) and ex-smokers (n = 201) in a cohort study with yearly measurements between 2009 and 2014. Latent growth curve modeling was used as an advanced statistical technique. As hypothesized, smokers perceived themselves more as smokers and less as quitters than do ex-smokers, and identification with smoking increased over time among smokers and decreased among ex-smokers. Furthermore, psychosocial factors predicted baseline identity and identity development. Socioeconomic status (SES) was particularly important. Specifically, lower SES smokers and lower SES ex-smokers identified more strongly with smoking, and smoker and quitter identities were more resistant to change among lower SES groups. Moreover, stronger proquitting social norms were associated with increasing quitter identities over time among smokers and ex-smokers and with decreasing smoker identities among ex-smokers. Predictors of identity differed between smokers and ex-smokers. Results suggest that SES and proquitting social norms should be taken into account when developing ways to facilitate identity change and, thereby, successful smoking cessation. (PsycINFO Database Record
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".