The Effectiveness of Tobacco Dependence Education in Health Professional Students’ Practice: A Systematic Review and Meta-Analysis of Randomized Controlled Trials
Bibliographic record
Abstract
The objective of this study was to perform a systematic review to examine the effectiveness of tobacco dependence education versus usual or no tobacco dependence education on entry-level health professional student practice and client smoking cessation. Sixteen published databases, seven grey literature databases/websites, publishers’ websites, books, and pertinent reference lists were searched. Studies from 16 health professional programs yielded 28 RCTs with data on 4343 healthcare students and 3122 patients. Two researchers independently assessed articles and abstracted data about student knowledge, self-efficacy, performance of tobacco cessation interventions, and patient smoking cessation. All forms of tobacco were included. We did not find separate interventions for different kinds of tobacco such as pipes or flavoured tobacco. We computed effect sizes using a random-effects model and applied meta-analytic procedures to 13 RCTs that provided data for meta-analysis. Students’ counseling skills increased significantly following the 5As model (SMD = 1.03; 95% CI 0.07, 1.98; p < 0.00001, I2 94%; p = 0.04) or motivational interviewing approach (SMD = 0.90, 95% CI 0.59, 1.21; p = 0.68, I2 0%; p < 0.00001). With tobacco dependence counseling, 78 more patients per 1000 (than control) reported quitting at 6 months (OR 2.02; 95% CI 1.49, 2.74, I2 = 0%, p = 0.76; p < 0.00001), although the strength of evidence was moderate or low. Student tobacco cessation counseling improved guided by the above models, active learning strategies, and practice with standardized patients.
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 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 | 0.029 | 0.073 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.025 | 0.037 |
| Bibliometrics | 0.009 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| 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".