Predictors of quit intentions among adult smokers in Mauritius: Findings from the ITC Mauritius Survey
Bibliographic record
Abstract
Mauritius has one of the highest rates of smoking in Africa. Smoking cessation is a priority for preventing tobacco-related morbidity and mortality. The purpose of this study is to identify the predictors of quit intentions among smokers in Mauritius in order to strengthen tobacco control policies and inform the development and delivery of services that may increase the likelihood of successful quitting. METHODS Data were drawn from Wave 1 (2009) of the International Tobacco Control (ITC) Mauritius Survey, a face-to-face cohort survey of a nationally representative sample of 598 adult smokers who were randomly selected from nine geographic districts in Mauritius using a multistage sampling procedure. RESULTS The vast majority of smokers (77.8%) had plans to quit smoking. Longer duration of past quit attempts (6 months or less), perceiving benefits of quitting, worrying about smoking damaging health in the future, and not enjoying smoking were significantly associated with quit intentions. However, socio-demographic characteristics, past quit attempts, overall attitude about smoking, and Heaviness of Smoking Index (HSI) were not associated with quit intentions. CONCLUSIONS The predictors of quit intentions among Mauritian smokers were generally similar to those found among smokers in other high-and middle-income countries. However, in contrast to findings in those other countries, nicotine dependence as measured by the HSI was not a significant predictor of quit intentions among Mauritian smokers. These findings highlight the need to consider the predictors of quit intentions when developing and delivering smoking cessation support services in Mauritius.
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 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 | 0.002 | 0.002 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".