Views and Attitudes of Patients in Mental Facilities Regarding Smoking
Bibliographic record
Abstract
INTRODUCTION: Smoking rates amongst people with a mental health disorder are significantly higher than in the general population and there is growing evidence to show a strong association between smoking and mental health disorders. The aim of the present study was to investigate views and attitudes of mental patients regarding smoking. MATERIAL & METHODS: The sample is composed of 356 patients treated in the Attica Psychiatric Hospital (a.k.a. "Dafni") as well as in other Units affiliated with the Hospital. The 'Smoking in psychiatric hospitals-a survey of patients' views' questionnaire was used in the form of semi-structured interviews. The PASW 18 (SPSS Inc.) package was used for the statistical analysis and statistical significance was set to p= 0.05. RESULTS: Overall, 40% of the participants were in-patients, the rest being treated in other settings, the average length of hospital stay was 4.4 years, and the most common diagnosis (61.5.%) was schizophrenia (F20, according to ICD-10), while almost all of the participants (97.5%) were smokers. Most patients (58.8%) said they had had a hard time trying to quit smoking although they had sufficient information and encouragement (≈90%); they also reported that watching the staff smoking did not affect them inasmuch as watching other patients smoking (41 % vs 54.8%). 75.5% of the patients felt that they had no particular difficulty to quit smoking. Men smoked significantly more cigarettes per day compared to females (36.70 vs 30.82, p=0.002). There were no significant differences among males and females regarding previous attempts to quit smoking. Information gathered from such studies should be taken into account when designing systematic smoking management plans in mental institutions. CONCLUSION: Although almost all mental patients smoke, they seem to be receptive to quitting smoking, since two thirds of them have already tried to quit, but one-third of the patients find smoking a little or not at all dangerous.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.003 | 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".