Training General Practitioners in Evidence-Based Tobacco Treatment: An Evaluation of the Tobacco Treatment Training Network in Crete (TiTAN-Crete) Intervention
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Bibliographic record
Abstract
BACKGROUND: Rates of tobacco treatment delivery in primary care are suboptimal. AIMS: We report on the effectiveness of the TiTAN Crete intervention on rates of patient-reported 4As (ask, advise, assist, arrange) tobacco treatment and general practitioner's (GP) knowledge, attitudes, self-efficacy, and intentions. METHODS: A quasi-experimental pilot study with pre-post evaluation was conducted in Crete, Greece (2015-2016). GPs ( n = 24) intervention and control group and a cross-sectional sample of their patients ( n = 841) were surveyed before the implementation of the intervention. GPs in the intervention group received training, practice, and patient tools to support the integration of the 4As treatment into clinical routines. Intervention group GPs ( n = 14) and a second cross-sectional sample of patients ( n = 460) were surveyed 4 months following the intervention to assess changes in outcomes of interest. Multilevel modeling was used to analyze data. RESULTS: Among GPs exposed to the intervention, significant increases in knowledge, self-efficacy, and rates of 4As delivery were documented between the pre- and postassessment and compared with those of the control group. Specifically, the adjusted odds ratios (AORs) and 95% confidence intervals (CIs) for 4As delivery between the pre-and postassessment among GPs exposed to the TiTAN intervention were as follows: Ask AOR 3.66 (95% CI [2.61, 5.14]); Advise AOR 4.21 (95% CI [3.02, 5.87]); Assist AOR 13.10 (95% CI [8.83, 19.42]) and Arrange AOR 4.75 (95% CI [2.67, 8.45]). CONCLUSION: We found significant increases in rates at which GPs delivered evidence-based tobacco treatment following exposure to the TiTAN intervention. Future research should examine methods for supporting broader dissemination of well-designed training interventions in general practice.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 it