Current practices and perceived barriers to tobaccotreatmentdelivery among healthcare professionals from 15European countries. The EPACTT Plus project
Bibliographic record
Abstract
INTRODUCTION: The latest evidence-based Guidelines for Treating Tobacco Dependence highlight the significant role of healthcare professionals in supporting smokers interested to quit. This study aimed to identify the current practices of healthcare professionals in Europe and perceived barriers in delivering tobacco treatment to their patients who smoke. METHODS: In the context of EPACTT-Plus, collaborating institutions from 15 countries (Albania, Armenia, Belgium, Italy, France, Georgia, Greece, Kosovo, Romania, North Macedonia, Russia, Serbia, Slovenia, Spain, Ukraine) worked for the development of an accredited eLearning course on Tobacco Treatment Delivery available at http://elearning-ensp.eu/. In total, 444 healthcare professionals from the wider European region successfully completed the course from December 2018 to July 2019. Cross-sectional data were collected online on healthcare professionals' current practices and perceived barriers in introducing tobacco-dependence treatment into their daily clinical life. RESULTS: At registration, 41.2% of the participants reported having asked their patients if they smoked. Advise to quit smoking was offered by 47.1% of the participants, while 29.5% reported offering assistance to their patients who smoked in order to quit. From the total number of participants, 39.9% regarded the lack of patient compliance as a significant barrier. Other key barriers were lack of: interest from the patients (37.4%), healthcare professionals training (33.1%), community resources to refer patients (31.5%), and adequate time during their everyday clinical life (29.7%). CONCLUSIONS: The identification of current practices and significant barriers is important to build evidence-based guidelines and training programs (online and/or live) that will improve the performance of healthcare professionals in offering tobacco-dependence treatment for their patients who smoke.
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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 | 0.000 | 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) | 0.000 | 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".