Better Off Alone Than With a Smoker: The Influence of Partner’s Smoking Behavior in Later Life
Bibliographic record
Abstract
OBJECTIVES: We examine how the likelihood of smoking cessation among smokers and patterns of adherence to smoking cessation differ by partnership status, partnership changes, and partners' smoking behavior. The data are a nationally representative sample of smokers in middle and older age from the Health and Retirement Study (1992-2010). METHOD: We use multivariate logistic regression models to analyze the likelihood of smoking cessation among smokers and then estimate adherence to smoking cessation using discrete-time event history models. RESULTS: Those partnered with smokers and those whose partners relapse into smoking are much less likely than the unpartnered to quit smoking and adhere to smoking cessation. Respondents partnered with non-smokers and those whose partners quit smoking are more likely to quit smoking than the unpartnered. Those recently widowed, divorced, and repartnered have similar smoking changes to the consistently unpartnered. DISCUSSION: Being partnered does not always mean healthier behavior changes. Rather, the association between partnership status and smoking changes depends greatly on the health behavior changes of the partner. The partnership context at the time of smoking cessation sets the stage for longer term patterns of adherence, shaping health in older age.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".