Tobacco dependence and motivation to quit among patients with schizophrenia in Morocco
Bibliographic record
Abstract
Purpose This study aims to describe and analyze the factors associated with dependence and motivation to stop smoking in patients with schizophrenia. Design/methodology/approach This descriptive, analytical study was conducted between October 2021 and April 2023 at two psychiatric centers in Morocco. The study population consisted of 274 smokers diagnosed with schizophrenia, who were examined just before their discharge. In addition to sociodemographic and economic data, tobacco use status and clinical information, the authors assessed dependence with Fagerström Test for Nicotine Dependence (FTND), motivation to quit and depression. Findings Around three-quarters (74%) smoked more than 10 cigarettes a day, with a mean FTND score of 5.61 (±1.94). Dependence was reported in 76% of smokers. More than two-thirds (69%) had made at least one attempt to quit, and almost all participants (99%) had done so without medical assistance. Nicotine dependence was associated with income, illness duration, motivation to stop smoking and depression. In addition, lower income, level of education, number of hospitalizations, attempts to stop smoking and nicotine dependence were associated with motivation to quit tobacco use. However, depression was not associated with motivation to stop smoking. Research limitations/implications The present study has the following limitations: the cross-sectional nature of the study does not allow for temporal evaluation, the sampling technique does not allow for generalization of the results, participants’ responses may be subjective despite the use of validated psychometric scales. Practical implications The results of this research have important public health implications: Duration of schizophrenia progression was associated with nicotine dependence – highlighting the need to offer help as soon as possible after diagnosis, as a preventative measure; Calgary depression score was a factor associated with increased dependence – suggesting that screening and additional help for people with co-existing mental health problems could be important. Similarly, the onset of depression after the development of schizophrenia should be monitored. Originality/value The authors have further searched the literature and have not found similar studies. The absence of such studies justifies the significance of this research, and its results will be valuable for publication to guide researchers in the treatment of tobacco dependence and, furthermore, to guide the preventive efforts of health authorities in Morocco. Additionally, to the best of the authors’ knowledge, this study is the first of its kind in Morocco and among the few in North Africa.
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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 | 0.001 | 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".