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NCT Number: NCT07650721

Smoking Cessation Counseling Performance Among Medical Interns

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.

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Key information

Conditions

Smoking Cessation Behavior Health Behavior

Age range

18 year and older

Sex eligibility

All sexes

Study type

Interventional

Phase

Not applicable

Primary location

About this study

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.

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • Medical interns enrolled in the internship training program at the Faculty of Medicine, Assiut University during the study period.
  • Able to attend the training session and complete all study assessments, including the pre-test and post-test evaluations.

Exclusion criteria

  • Previous formal structured training in smoking cessation counseling based on the 5A model.
  • Previous participation in a smoking cessation counseling educational program within the preceding 12 months.
  • Failure to complete the assigned educational intervention.
  • Failure to complete either the pre-test or post-test assessment.
  • Withdrawal of consent at any stage of the study.

Treatment and study plan

Artificial Intelligence assisted interactive case-based training for smoking cessation counselling

Other

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

standard guideline-based smoking cessation training

Other

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.

Primary outcomes

  1. Change in smoking cessation counseling performance score

    Time frame: 1 month

    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 case scenario will be scored out of 10 points, with a total possible score of 30 points for three clinical cases. The primary outcome will be the change in total 5A performance score from baseline to post-intervention assessment

Study contacts

Contact information is provided by the study sponsor or research team.

Montaser gamal, Lecturer

CONTACT

[email protected]

+201008951058

waleed gamal, ass. prof

CONTACT

[email protected]

+201006519722

Sponsors and collaborators

Lead sponsor

Assiut University

Other

Registry information

Official study title

Effect of Artificial Intelligence-Assisted Interactive Case-Based Training on Smoking Cessation Counseling Performance Among Medical Interns

Important dates

Study start
2026
Primary completion
2026
Study completion
2026
First posted
Jun 16, 2026
Registry last updated
Jun 16, 2026

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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