Associations between Practitioner Personality and Client Quit Rates in Smoking Cessation Behavioural Support Interventions
Bibliographic record
Abstract
Introduction: There is wide variation in the success rates of practitioners employed to help smokers to stop, even once a range of potential confounding factors has been taken into account. Aim: This paper examined whether personality characteristics of practitioners might play a role success rates. Methods: Data from 1,958 stop-smoking treatment episodes in two stop-smoking services (SSS) involving 19 stop-smoking practitioners were used in the analysis. The outcome measure was clients’ biochemically verified quit status 4 weeks after the target quit date. The five dimensions of personality, as assessed by the Ten-Item Personality Inventory, were included as predictor variables: openness, conscientiousness, agreeableness, extraversion, and neuroticism. A range of client and other practitioner characteristics were used as covariates. A sensitivity analysis was conducted to determine if managers' ratings of practitioner personality were also associated with clients’ quit status. Results: Multi-level random intercept models indicated that clients of practitioners with a higher extraversion score had greater odds of being abstinent at four weeks (self-assessed: OR = 1.10, 95% CI = 1.01–1.19; manager-assessed: OR = 1.32, 95% CI = 1.21–1.44). Conclusions: More extraverted stop smoking practitioners appear to have greater success in advising their clients to quit smoking. Findings need to be confirmed in larger practitioner populations, other SSS, and in different smoking cessation contexts. If confirmed, specific training may be needed to assist more introverted stop smoking practitioners.
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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 | 0.004 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".