Smoking CessationNCT07650721
Smoking Cessation Counseling Performance Among Medical Interns
A study testing Artificial Intelligence assisted interactive case-based training for smoking cessation counselling and standard guideline-based smoking cessation training in people with Smoking Cessation, run by Assiut University at 1 site in Egypt.
Trial summary
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. Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Smoking Cessation
- What is being tested?
- Artificial Intelligence assisted interactive case-based training for smoking cessation counselling and standard guideline-based smoking cessation training
- Type of treatment
- Medical device
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 140 participants
- Where
- 1 siteEgypt
- Study dates
- 30 Jun 2026to 1 Oct 2026
- Phase
- Interventional
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Who may be able to join
- 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.
Who cannot join
- 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.
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
Egypt1 site, 1 recruiting
- Recruiting
Assuit University Hospiatal
Asyut, Assuit, 71515
waleed gamal, Ass. Prof, +201006519722, waleedgamalddin@yahoo.com
About this study
Official title: Effect of Artificial Intelligence-Assisted Interactive Case-Based Training on 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.
Read the detailed description
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.
- Conditions
- Smoking Cessation
- Being tested
- Artificial Intelligence assisted interactive case-based training for smoking cessation counselling, standard guideline-based smoking cessation training
- Keywords
- Smoking Cessation, Artificial Intelligence, Medical Interns
- Medical subject headings
- Smoking Cessation
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Artificial Intelligence assisted interactive case-based training for smoking cessation counsellingDevice
Also called AI assisted educational case based training
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 trainingDevice
Also called guideline-based educational smoking cessation training
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.
| Study group | Role | What they receive |
|---|---|---|
| Artificial Intelligience assisted interactive case-based training | Experimental | 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 Receives: Device: Artificial Intelligence assisted interactive case-based training for smoking cessation counselling |
| standard guideline-based smoking cessation training | Active comparator | 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 Receives: Device: standard guideline-based smoking cessation training |
What is being measured
The primary outcome is the main question the study is designed to answer.
Change 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.
Measured: 1 month
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted16 Jun 2026
- Study start30 Jun 2026
- Primary completion1 Sep 2026 (estimated)
- Study completion1 Oct 2026 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (3)Papers the sponsor has linked to this study.
- Other trials for Smoking CessationStudies of the same condition, open and under way.
- More trials run by Assiut UniversityThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Other
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Single blind
- Who is masked
- Outcomes assessor
- Enrolment
- 140 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Assiut University
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Waleed Gamal Elddin Khaleel, Assiut University
- Investigators
- waleed gamal, ass. prof, Principal investigator, Assiut University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07650721
- Sponsor's protocol ID
- WGEK-AI-Cessation
- Status last verified
- Aug 2026
- First submitted
- 11 Jun 2026
- Last updated
- 19 Aug 2026
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Publications
Stead LF, Buitrago D, Preciado N, Sanchez G, Hartmann-Boyce J, Lancaster T. Physician advice for smoking cessation. Cochrane Database Syst Rev. 2013 May 31;2013(5):CD000165. doi: 10.1002/14651858.CD000165.pub4.
PubMed 23728631Park KY, Park HK, Hwang HS. Group randomized trial of teaching tobacco-cessation counseling to senior medical students: a peer role-play module versus a standardized patient module. BMC Med Educ. 2019 Jun 25;19(1):231. doi: 10.1186/s12909-019-1668-x.
PubMed 31238920Chinwong D, Penthinapong T, Chinwong S. Integrating ChatGPT for smoking cessation counseling practice in pharmacy education: A single group quasi-experimental study. Tob Induc Dis. 2025 Nov 21;23. doi: 10.18332/tid/211706. eCollection 2025.
PubMed 41281586
Study at a glance
From the registry record, last updated by the sponsor on 19 Aug 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Effect of Artificial Intelligence-Assisted Interactive Case-Based Training on Smoking Cessation Counseling Performance Among Medical Interns
- ClinicalTrials.gov ID
- NCT07650721
- Acronym / sponsor ID
- WGEK-AI-Cessation
- Conditions
- Smoking Cessation
- Keywords
- Smoking Cessation, Artificial Intelligence, Medical Interns
- Study type
- Interventional
- Recruitment status
- Recruiting
- Enrolment
- 140 participants (estimated)
- Lead sponsor
- Assiut UniversityUniversity, hospital or other
- Study start
- 30 Jun 2026 (actual)
- Primary completion
- 1 Sep 2026 (estimated)
- Study completion
- 1 Oct 2026 (estimated)
- First posted
- 16 Jun 2026 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Detailed description
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 design
- Primary purpose
- Other
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Single blind (outcomes assessor)
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Artificial Intelligience assisted interactive case-based training | Experimental | Device: Artificial Intelligence assisted interactive case-based training for smoking cessation counsellingParticipants 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 | Active comparator | Device: standard guideline-based smoking cessation trainingParticipants 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 |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (2 listed)
- 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.
Key exclusion criteria (5 listed)
- 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.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Artificial Intelligence assisted interactive case-based training for smoking cessation counsellingAlso: AI assisted educational case based trainingParticipants 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 | Device | Artificial Intelligience assisted interactive case-based training |
| standard guideline-based smoking cessation trainingAlso: guideline-based educational smoking cessation trainingParticipants 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. | Device | standard guideline-based smoking cessation training |
Primary outcome
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 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.
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 19 Aug 2026.
- Background: PubMed 23728631Stead LF, Buitrago D, Preciado N, Sanchez G, Hartmann-Boyce J, Lancaster T. Physician advice for smoking cessation. Cochrane Database Syst Rev. 2013 May 31;2013(5):CD000165. doi: 10.1002/14651858.CD000165.pub4.
- Background: PubMed 31238920Park KY, Park HK, Hwang HS. Group randomized trial of teaching tobacco-cessation counseling to senior medical students: a peer role-play module versus a standardized patient module. BMC Med Educ. 2019 Jun 25;19(1):231. doi: 10.1186/s12909-019-1668-x.
- Background: PubMed 41281586Chinwong D, Penthinapong T, Chinwong S. Integrating ChatGPT for smoking cessation counseling practice in pharmacy education: A single group quasi-experimental study. Tob Induc Dis. 2025 Nov 21;23. doi: 10.18332/tid/211706. eCollection 2025.
- Individual participant dataSharing planned: No
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
waleed gamal, ass. prof principal investigator
Assiut University
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Artificial Intelligence assisted interactive case-based training for smoking cessation counselling and standard guideline-based smoking cessation training in people with Smoking Cessation, run by Assiut University at 1 site in Egypt.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 2 inclusion and 5 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: looking for participants now, as of the sponsor's last update on 19 Aug 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Egypt. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact waleed gamal, ass. prof (+201006519722, waleedgamalddin@yahoo.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Change in smoking cessation counseling performance score (time frame: 1 month). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT07650721, which also lists 3 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 19 Aug 2026.