Assessing effective smoking cessation intervention in primary care
Bibliographic record
Abstract
Over the past 20 years, the provision of smoking cessation intervention in primary care has been on the rise. While early reports in late 1980's and 90's have documented that less than 50% of smokers were ever advised to quit (Anda et al., 1987, Goldstein et al., 1997), more recent surveys of both smokers and physicians have revealed that close to 90% of patients are asked of their smoking status and now more than three quarters are advised to quit (AAMC, 2007, King et al., 2013). Evaluating data from the 2009–2010 United States National Adult Tobacco Survey, King et al. recently documented strong provider compliance with the ask and advise components of the 5A's model of physician smoking cessation practice guidelines (Fiore et al., 2008); however, moderate to weak compliance with the assessment, assist and arrangement of follow-up components (King et al., 2013). Of particular note, the study also found that 78.2% of all smokers were offered any assistance and approximately half (49.5%) were provided with 2 or more forms of assistance in the past 12 months, consisting of brief intervention (e.g. booklets, websites), cessation program referral, or medication prescription. Our results from a Canadian population survey conducted in the context of an ongoing trial (study protocol — Cunningham et al., 2011), similarly indicate that 43.3% of adult regular smokers with an intent to quit in the next 6 months (n = 1242) had received brief intervention and nicotine replacement therapy (NRT) or medication, and only 15% had reported receiving both counseling and NRT or medication. While these rates indicate that the provision of some assistance is now more commonplace, offers of combined or alternate lines of support following a failed quit attempt are far from the norm. More importantly however, the above rates are only reflective of smokers being provided with two or more forms of intervention sometime in the past year and do not necessarily speak to the best practice guideline of combined provision of behavioral and pharmacotherapeutic interventions (Fiore et al., 2008, Hurt et al., 1994). In fact, no population or physician surveys to date have reported on the concurrent provision of several smoking cessation interventions. As such, it is striking that population level prevalence rates on the provision of the most effective form of primary care cessation support are simply unknown. Identifying physician compliance with best practice guidelines is necessary and certainly highly encouraged for future population surveys. While the number of received interventions may be telling of physician resourcefulness and persistence in tailoring a treatment plan, the concurrent provision of interventions would be more indicative of physician training and implementation of evidence-based interventions. Documenting the concurrent provision of cessation interventions in particular, is not only important for current indices of physician practices but also for evaluating effectiveness of recent system-wide changes to the provision of tobacco-related interventions in primary care (Kunyk et al., 2014, Land et al., 2012). As more jurisdictions adopt the integrated, multicomponent systems pathway to tobacco treatment, a comprehensive assessment of the types, frequency, duration, as well as combined provision of smoking cessation assistance can help provide a deeper understanding of the gaps and barriers in effective delivery of cessation interventions.
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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 | 0.002 | 0.001 |
| 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 | 0.000 |
| 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 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".