Tobacco dependence treatment provision by tuberculosis physicians in Armenia
Bibliographic record
Abstract
Introduction The integration of tobacco dependence treatment interventions into routine tuberculosis (TB) services is broadly acknowledged as an important measure to tackle the dual burden of TB and tobacco. The study aimed to explore TB physicians’ practice of tobacco dependence treatment based on the recommended 5 “A’s” model. Methods A cross-sectional study was conducted among TB physicians from inpatient and out-patient TB facilities throughout Armenia. Self-administered questionnaire included questions on demographics, knowledge, attitude, practice and confidence in providing tobacco dependence treatment. The predictors of the high practice score (number of activities always performed during physicians’ daily practice) were assessed using multiple linear regression analysis. Results Overall, 91 TB physicians completed the survey. The mean self-reported practice score was 5.71 (max=15). Majority of TB physicians always asked about smoking status of their patients (72.53%) and always advised smoking patients to quit (93.41%). About half of them always assessed patients’ willingness to quit (54.95%). Conversely, less than half of physicians always assisted their patients in smoking cessation (43.96%) and only few respondents (3.30%) mentioned about always arranging follow-up to review patients’ progress in quitting. Regression analysis revealed that TB physicians’ knowledge on smoking cessation (β=0.22) and monthly number of their patients (β=-0.05) were significantly associated with practice score. Conclusions Recommended interventions were not fully implemented into routine TB services. TB physicians with higher knowledge score on smoking cessation and lower patient load were more likely to have higher practice score. These predictors should be targeted for future interventions improving tobacco dependence treatment practices.
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 | 0.000 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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; both teacher heads agree on what is shown here.
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".