Adherence to the 5A and 5R smoking cessation counselling models among Turkish family physicians: a multicenter cross-sectional study

BACKGROUND: The 5A and 5R counselling models are widely recommended frameworks for smoking cessation; however, their implementation in primary care remains inconsistent. OBJECTIVE: This multicenter cross-sectional study assessed the use of these models among 203 family physicians in Istanbul and examined the factors associated with counselling performance. METHOD: A structured questionnaire was used to evaluate demographics, smoking-related behaviors, knowledge of cessation methods, and the frequency of applying each step of the 5A and 5R models (10-item dichotomous responses with excellent internal consistency; KR-20 = 0.83, α = 0.83, and strong item-total correlations r = 0.46-0.75). Logistic regression and machine learning clustering were used to identify the predictors and patterns of counselling behavior. RESULTS: Physicians most frequently implemented the Ask (52.7%) and Advise (70.9%) steps, whereas the Assess, Assist, and Arrange steps were applied infrequently. Among the 5R components, Relevance (70.0%) and Risks (54.7%) were more commonly used than Rewards, Repetition, or Roadblocks. While 12.8% of physicians frequently performed very brief interventions (Ask-Advise-Assess), adherence declined markedly for more comprehensive models, with only 5.9% applying all 5A steps, 17.2% all 5R components, and 5.4% the full 5A-5R framework. Current smoking was 8.9%, and 15.8% of participants reported intermittent tobacco use. Older age (≥30 years) increased the likelihood of applying Ask and Reward, whereas exposure to parental smoking during childhood reduced the likelihood of using the Assist step. Male physicians were less likely to use repetition. Knowledge of motivational interviewing was consistently associated with higher adherence to several 5A and 5R steps. Machine learning revealed three counselling clusters, with 83.7% of physicians demonstrating low counseling competence. CONCLUSION: Adherence to smoking cessation counselling models among family physicians remains suboptimal, showing a gap between guidelines and practice. These findings provide baseline data before the nationwide cessation training program for 26,000 family physicians in Türkiye, highlighting areas for targeted interventions.

Authors

Institutions

Publication Details

Journal
Journal of Addictive Diseases
Published
2026-04-03
DOI
https://doi.org/10.1080/10550887.2026.2642733
Primary Topic
Smoking Behavior and Cessation
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Adherence to the 5A and 5R smoking cessation counselling models among Turkish family physicians: a multicenter cross-sectional study

Melike Mercan Başpinar, Haydar Keskin, Umut Cindiloglu
Journal of Addictive Diseases
Smoking Behavior and Cessation
article

Adherence to the 5A and 5R smoking cessation counselling models among Turkish family physicians: a multicenter cross-sectional study

Melike Mercan Başpinar, Haydar Keskin, Umut Cindiloglu
article en

Abstract

BACKGROUND: The 5A and 5R counselling models are widely recommended frameworks for smoking cessation; however, their implementation in primary care remains inconsistent. OBJECTIVE: This multicenter cross-sectional study assessed the use of these models among 203 family physicians in Istanbul and examined the factors associated with counselling performance. METHOD: A structured questionnaire was used to evaluate demographics, smoking-related behaviors, knowledge of cessation methods, and the frequency of applying each step of the 5A and 5R models (10-item dichotomous responses with excellent internal consistency; KR-20 = 0.83, α = 0.83, and strong item-total correlations r = 0.46-0.75). Logistic regression and machine learning clustering were used to identify the predictors and patterns of counselling behavior. RESULTS: Physicians most frequently implemented the Ask (52.7%) and Advise (70.9%) steps, whereas the Assess, Assist, and Arrange steps were applied infrequently. Among the 5R components, Relevance (70.0%) and Risks (54.7%) were more commonly used than Rewards, Repetition, or Roadblocks. While 12.8% of physicians frequently performed very brief interventions (Ask-Advise-Assess), adherence declined markedly for more comprehensive models, with only 5.9% applying all 5A steps, 17.2% all 5R components, and 5.4% the full 5A-5R framework. Current smoking was 8.9%, and 15.8% of participants reported intermittent tobacco use. Older age (≥30 years) increased the likelihood of applying Ask and Reward, whereas exposure to parental smoking during childhood reduced the likelihood of using the Assist step. Male physicians were less likely to use repetition. Knowledge of motivational interviewing was consistently associated with higher adherence to several 5A and 5R steps. Machine learning revealed three counselling clusters, with 83.7% of physicians demonstrating low counseling competence. CONCLUSION: Adherence to smoking cessation counselling models among family physicians remains suboptimal, showing a gap between guidelines and practice. These findings provide baseline data before the nationwide cessation training program for 26,000 family physicians in Türkiye, highlighting areas for targeted interventions.

Journal of Addictive Diseases
Tokat Gaziosmanpaşa Üniversitesi (TR), Gazi Hastanesi (TR), Gaziosmanpaşa Taksim Eğitim ve Araştırma Hastanesi (TR), Gazi University (TR)
Good health and well-being
Openalex Percentile: Top 24%
Smoking Behavior and Cessation
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.