Smoking remains one of the leading preventable causes of morbidity and mortality worldwide and is strongly associated with chronic respiratory diseases, cardiovascular disease, cancer, and premature death. Physicians play a central role in tobacco control through the delivery of smoking cessation counseling, and even brief physician advice has been shown to significantly increase smoking quit rates. The evidence-based 5A's model (Ask, Advise, Assess, Assist, and Arrange) is widely recommended as the standard framework for smoking cessation counseling.
Despite the availability of effective counseling strategies and pharmacological interventions, smoking cessation counseling remains infrequently used in routine clinical practice. Recent studies have demonstrated gaps in physicians' knowledge, confidence, and implementation of smoking cessation interventions. In Egypt, a recent study among resident physicians reported deficiencies in smoking cessation knowledge and counseling practices, while another study demonstrated low rates of referral for smoking cessation counseling among healthcare workers. Traditional educational approaches often rely on passive learning methods that may not adequately develop practical counseling skills. Interactive case-based learning has been shown to improve clinical communication skills and smoking cessation counseling performance among healthcare trainees. Furthermore, recent advances in artificial intelligence have enabled the development of interactive educational tools capable of simulating realistic clinical meeting and providing structured feedback. AI-assisted simulation has shown promising results in smoking cessation education and medical training. However, evidence regarding the effectiveness of AI-assisted interactive case-based training for improving smoking cessation counseling performance among practicing physicians remains limited. Therefore, this study aims to evaluate the effect of AI-assisted interactive case-based training on smoking cessation counseling performance among medicals interns using a randomized controlled educational design.
Study Type
INTERVENTIONAL
Allocation
RANDOMIZED
Purpose
OTHER
Masking
Participants will receive AI-assisted interactive case-based training in addition to the standard educational materials. The intervention will consist of a series of standardized clinical scenarios related to smoking cessation counseling, followed by structured AI-generated educational feedback based on the 5A model
Participants will receive standard guideline-based smoking cessation training consisting of educational materials covering the 5A smoking cessation counseling model, nicotine dependence, pharmacological treatment options, and smoking cessation referral strategies.
Assuit University Hospiatal
Asyut, Assuit, Egypt
RECRUITINGChange in smoking cessation counseling performance score
Smoking cessation counseling performance will be assessed using standardized clinical cases and a predefined 5A a standardized scoring system (Ask, Advise, Assess, Assist, and Arrange). each item of 5A model will be assessed on a scale from 0 to 2, where 0=not performed, 1=partially assessed, 2= completely assessed with the total score range from 0 to 10, The primary outcome will be the change in total 5A performance score from baseline to post-intervention assessment, where 0 is the lowest performance, and 10 is the highest performance.
Time frame: 1 month
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SINGLE
Enrollment
140