Conversational AgentNCT07906249
Comparing the Efficacy of a Conversational Agent (QuitBot) Versus Standard Health Education on Smoking Cessation Among Medical Students; A Randomized Controlled Trial.
A study testing Conversational agent and Standard health education in people with Conversational Agent and Smoking Cessation, run by Cairo University at 1 site in Egypt.
Trial summary
Comparing the efficacy of conversational agent and standard health education in promoting smoking cessation among medical students in Cairo university Read more about this study
- Who is it for?
- Ages 19 to 24 years
- Conditions the study is for
- Conversational Agent, Smoking Cessation
- What is being tested?
- Conversational agent and Standard health education
- Type of treatment
- Lifestyle or therapy programme
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 180 participants
- Where
- 1 siteEgypt
- Study dates
- 10 Dec 2026to 31 Dec 2027
- 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 19 to 24 years
- All sexes
- No healthy volunteers
- Adult
Who may be able to join
- Enrolled adult medical student at Cairo University with age range (19 - 25) years old. The age range will be from 19 years old to fulfill WHO definition of adulthood.
- Current smoker (defined as smoking at least one cigarette- cigarette or vaping per day in the past month).
- Motivated to quit smoking within the next six months.
- Able to communicate in English sufficiently to use the chatbot.
- Has access to a smartphone with internet connection.
- Provides informed consent to participate.
Who cannot join
- Students currently enrolled in another smoking cessation program or using pharmacological cessation aids.
- Students with known severe psychiatric illness or cognitive impairment that may interfere with chatbot interaction identified by self-report.
- Students unable or unwilling to provide consent.
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
Doha Ramadan Mahmoud, Msc degree in family medicine contact
Egypt1 site
Cairo university
Cairo, Cairo Governorate
Cairo university
Doha Ramadan Mahmoud, Msc
About this study
Comparing the efficacy of conversational agent and standard health education in promoting smoking cessation among medical students in Cairo university
Read the detailed description
Tobacco smoking remains one of the leading causes of preventable morbidity and mortality worldwide, accounting for more than 8 million deaths annually (world health organization, 2023). Smoking among medical students represents a critical paradox in public health. As future physicians, they are expected to be role models and champions of preventive health, yet global studies indicate a persistent and concerning prevalence of tobacco use within this group, with rates varying from 5% to over 30% in different regions (AlSairafi \& AlKandari, 2023). In Egypt, the situation is particularly pressing; a recent systematic review estimated the pooled prevalence of smoking among medical students to be approximately 18.5%, with some studies reporting rates as high as 28% among males (El-Masry et al., 2023). This high prevalence is often attributed to intense academic stress, social factors, and the normalization of smoking in certain environments (Bassiony et al., 2015). This behavior undermines their personal health and future professional credibility and effectiveness in tobacco cessation counseling Digital health technologies have emerged as effective and scalable tools for behavior change interventions. Mobile applications, web-based programs, and short message service (SMS) based interventions have demonstrated modest but significant effects on smoking cessation outcomes (whittaker et al., 2019). Among these digital approaches, conversational agents, or chatbots, offer unique advantages through real-time, interactive, and personalized communication (abdullah et al., 2023). Chatbots simulate human conversation and can provide continuous motivational and cognitive-behavioral support using natural language processing algorithms. Their 24/7 availability, anonymity, and ability to tailor responses based on user input make them highly suitable for youth and young adults who are digitally literate and familiar with online interaction (prochaska et al., 2021).
So, This study hypothesizes that medical students who smoke and receive the combined intervention of the "QuitBot" conversational agent plus an evidence-based cessation guidelines will demonstrate a statistically significant higher rate of day point prevalence smoking abstinence and prolonged abstinence at 1 and 3months respectively post-intervention, compared to those who receive the evidence-based handbook alone. Since many similar studies have been conducted in high-income countries, there is very limited evidence from low- and middle-income contexts such as Egypt (el-amin et al., 2021). Medical students in Egypt are an ideal population for testing the feasibility of such a digital intervention, given their high rates of smartphone ownership and social media use. So, implementing quitbot among medical students could provide valuable insights into the acceptability, usability, and effectiveness of chatbot-based smoking cessation tools. Furthermore, this approach aligns with the global public health objective of integrating artificial intelligence-driven behavioral interventions into preventive healthcare strategies (world health organization, 2023).
- Conditions
- Conversational Agent, Smoking Cessation
- Being tested
- Conversational agent, Standard health education
- Keywords
- Smoking cessation
- Medical subject headings
- Smoking Cessation
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Conversational agentBehavioural
Conversational Agent Behavioral Participants use an AI-powered conversational chatbot for smoking cessation support
Standard health educationBehavioural
Standard health education according to USPSTF guidelines
| Study group | Role | What they receive |
|---|---|---|
| conversational agent arm | Experimental | Participants are medical students who smoke, and will receive smoking cessation intervention through an AI conversational chatbot. Receives: Behavioral: Conversational agent |
| Standard health education | Active comparator | Standard health education Receives: Behavioral: Standard health education |
What is being measured
The primary outcome is the main question the study is designed to answer.
Comparing the effectiveness of the quitbot conversational chatbot in promoting smoking cessation versus traditional cessation education among medical students in Cairo University
Varying cessation by direct asking after 3 months
Measured: 3 months
Secondary outcomes (1)
To determine User satisfaction, feasibility and usability score. To evaluate the perceived effectiveness of the chatbot in promoting smoking cessation among the intervention group.
Conversational agent arm will fill a questionnaire to determine satisfaction, feasibility and usability Both arm will fill a qutionaaire for perceived effectiveness
Measured: 3 months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted30 Oct 2026
- Study start10 Dec 2026 (estimated)
- Primary completion30 Dec 2027 (estimated)
- Study completion31 Dec 2027 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (1)Papers the sponsor has linked to this study.
- Other trials for Conversational AgentStudies of the same condition, open and under way.
- More trials run by Cairo 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
- Treatment
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Model description
- Participants receive access to the quitbot conversational Chabot. "QuitBot" an AI-powered conversational chatbot app designed to help individuals quit smoking,
- Masking
- Single blind
- Who is masked
- Outcomes assessor
- Enrolment
- 180 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Cairo University
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Doha Ramadan, Cairo University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07906249
- Sponsor's protocol ID
- MD-472-2025
- Status last verified
- Oct 2026
- First submitted
- 24 Oct 2026
- Last updated
- 30 Oct 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Publications
- References: Abdullah, M., Ong, J., & Toh, M. (2023) 'Conversational Agents In Digital Health Interventions: Effectiveness And Engagement Outcomes', Journal Of Medical Internet Research, 25, E45629. AlSairafi, M., & AlKandari, N. (2023). Prevalence of smoking among medical students worldwide: A systematic review and meta-analysis. Tobacco Prevention & Cessation, 9(Supplement), A100. https://doi.org/10.18332/tpc/162752 Bassiony, M. M., Salah El-Deen, G. M., Yousef, U., Raya, Y., Abdel-Ghani, M. M., El-Gohari, H., & Weiss, M. G. (2015). Smoking and perceived stress in Egyptian medical students. Journal of Addiction Medicine, 9(4), 309-314. https://doi.org/10.1097/ADM.0000000000000135 Bricker, J. B., Mull, K. E., & Peterson, A. V. (2024) 'Conversational Chatbot For Cigarette Smoking Cessation: Methods And Findings From A Randomized Trial', JMIR Mhealth And Uhealth, 12(1), E57318. Brooke, J. (1986) SUS: A "Quick And Dirty" Usability Scale. Hewlett-Packard. El-Amin, S. E., El-Ansary, D., & Nassar, H. (2021) 'Prevalence And Determinants Of Tobacco Use Among University Students In Egypt', BMC Public Health, 21(1), 2142. El-Masry, R., El-Mohandes, A., & Nabil, M. (2023). Prevalence and determinants of smoking among medical students in Egypt: A systematic review and meta-analysis. Journal of the Egyptian Public Health Association, 98(1), 15. https://doi.org/10.1186/s42506-023-00139-3 Fred Hutch. (n.d.-b). https://www.fredhutch.org/en/investors/business-development/available-technologies/technology-details.fh_bds_technology_id_23-151.quitbot-an-innovative-chat-app-to-assist-smoking-cessation.html Heatherton, T.F., Kozlowski, L.T., Frecker, R.C. And Fagerström, K.O. (1991) 'The Fagerström Test For Nicotine Dependence: A Revis
Study at a glance
From the registry record, last updated by the sponsor on 30 Oct 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Comparing the Efficacy of a Conversational Agent (QuitBot) Versus Standard Health Education on Smoking Cessation Among Medical Students; A Randomized Controlled Trial.
- ClinicalTrials.gov ID
- NCT07906249
- Acronym / sponsor ID
- MD-472-2025
- Conditions
- Conversational Agent, Smoking Cessation
- Keywords
- Smoking cessation
- Study type
- Interventional
- Recruitment status
- Not yet recruiting
- Enrolment
- 180 participants (estimated)
- Lead sponsor
- Cairo UniversityUniversity, hospital or other
- Study start
- 10 Dec 2026 (estimated)
- Primary completion
- 30 Dec 2027 (estimated)
- Study completion
- 31 Dec 2027 (estimated)
- First posted
- 30 Oct 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.
Comparing the efficacy of conversational agent and standard health education in promoting smoking cessation among medical students in Cairo university
Detailed description
Tobacco smoking remains one of the leading causes of preventable morbidity and mortality worldwide, accounting for more than 8 million deaths annually (world health organization, 2023). Smoking among medical students represents a critical paradox in public health. As future physicians, they are expected to be role models and champions of preventive health, yet global studies indicate a persistent and concerning prevalence of tobacco use within this group, with rates varying from 5% to over 30% in different regions (AlSairafi \& AlKandari, 2023). In Egypt, the situation is particularly pressing; a recent systematic review estimated the pooled prevalence of smoking among medical students to be approximately 18.5%, with some studies reporting rates as high as 28% among males (El-Masry et al., 2023). This high prevalence is often attributed to intense academic stress, social factors, and the normalization of smoking in certain environments (Bassiony et al., 2015). This behavior undermines their personal health and future professional credibility and effectiveness in tobacco cessation counseling Digital health technologies have emerged as effective and scalable tools for behavior change interventions. Mobile applications, web-based programs, and short message service (SMS) based interventions have demonstrated modest but significant effects on smoking cessation outcomes (whittaker et al., 2019). Among these digital approaches, conversational agents, or chatbots, offer unique advantages through real-time, interactive, and personalized communication (abdullah et al., 2023). Chatbots simulate human conversation and can provide continuous motivational and cognitive-behavioral support using natural language processing algorithms. Their 24/7 availability, anonymity, and ability to tailor responses based on user input make them highly suitable for youth and young adults who are digitally literate and familiar with online interaction (prochaska et al., 2021).
So, This study hypothesizes that medical students who smoke and receive the combined intervention of the "QuitBot" conversational agent plus an evidence-based cessation guidelines will demonstrate a statistically significant higher rate of day point prevalence smoking abstinence and prolonged abstinence at 1 and 3months respectively post-intervention, compared to those who receive the evidence-based handbook alone. Since many similar studies have been conducted in high-income countries, there is very limited evidence from low- and middle-income contexts such as Egypt (el-amin et al., 2021). Medical students in Egypt are an ideal population for testing the feasibility of such a digital intervention, given their high rates of smartphone ownership and social media use. So, implementing quitbot among medical students could provide valuable insights into the acceptability, usability, and effectiveness of chatbot-based smoking cessation tools. Furthermore, this approach aligns with the global public health objective of integrating artificial intelligence-driven behavioral interventions into preventive healthcare strategies (world health organization, 2023).
Study design
- Primary purpose
- Treatment
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Single blind (outcomes assessor)
- Number of arms
- 2
- Model description
- Participants receive access to the quitbot conversational Chabot. "QuitBot" an AI-powered conversational chatbot app designed to help individuals quit smoking,
| Arm | Type | Receives |
|---|---|---|
| conversational agent arm | Experimental | Behavioral: Conversational agentParticipants are medical students who smoke, and will receive smoking cessation intervention through an AI conversational chatbot. |
| Standard health education | Active comparator | Behavioral: Standard health educationStandard health education |
Who may qualify
- Ages
- 19 to 24 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult
Key inclusion criteria (6 listed)
- Enrolled adult medical student at Cairo University with age range (19 - 25) years old. The age range will be from 19 years old to fulfill WHO definition of adulthood.
- Current smoker (defined as smoking at least one cigarette- cigarette or vaping per day in the past month).
- Motivated to quit smoking within the next six months.
- Able to communicate in English sufficiently to use the chatbot.
- Has access to a smartphone with internet connection.
Key exclusion criteria (3 listed)
- Students currently enrolled in another smoking cessation program or using pharmacological cessation aids.
- Students with known severe psychiatric illness or cognitive impairment that may interfere with chatbot interaction identified by self-report.
- Students unable or unwilling to provide consent.
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 |
|---|---|---|
| Conversational agentConversational Agent Behavioral Participants use an AI-powered conversational chatbot for smoking cessation support | Behavioural | conversational agent arm |
| Standard health educationStandard health education according to USPSTF guidelines | Behavioural | Standard health education |
Primary outcome
Comparing the effectiveness of the quitbot conversational chatbot in promoting smoking cessation versus traditional cessation education among medical students in Cairo University
Time frame: 3 months
Varying cessation by direct asking after 3 months
1 secondary outcome
To determine User satisfaction, feasibility and usability score. To evaluate the perceived effectiveness of the chatbot in promoting smoking cessation among the intervention group.
Time frame: 3 months
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 30 Oct 2026.
- Results publication- References: Abdullah, M., Ong, J., & Toh, M. (2023) 'Conversational Agents In Digital Health Interventions: Effectiveness And Engagement Outcomes', Journal Of Medical Internet Research, 25, E45629. AlSairafi, M., & AlKandari, N. (2023). Prevalence of smoking among medical students worldwide: A systematic review and meta-analysis. Tobacco Prevention & Cessation, 9(Supplement), A100. https://doi.org/10.18332/tpc/162752 Bassiony, M. M., Salah El-Deen, G. M., Yousef, U., Raya, Y., Abdel-Ghani, M. M., El-Gohari, H., & Weiss, M. G. (2015). Smoking and perceived stress in Egyptian medical students. Journal of Addiction Medicine, 9(4), 309-314. https://doi.org/10.1097/ADM.0000000000000135 Bricker, J. B., Mull, K. E., & Peterson, A. V. (2024) 'Conversational Chatbot For Cigarette Smoking Cessation: Methods And Findings From A Randomized Trial', JMIR Mhealth And Uhealth, 12(1), E57318. Brooke, J. (1986) SUS: A "Quick And Dirty" Usability Scale. Hewlett-Packard. El-Amin, S. E., El-Ansary, D., & Nassar, H. (2021) 'Prevalence And Determinants Of Tobacco Use Among University Students In Egypt', BMC Public Health, 21(1), 2142. El-Masry, R., El-Mohandes, A., & Nabil, M. (2023). Prevalence and determinants of smoking among medical students in Egypt: A systematic review and meta-analysis. Journal of the Egyptian Public Health Association, 98(1), 15. https://doi.org/10.1186/s42506-023-00139-3 Fred Hutch. (n.d.-b). https://www.fredhutch.org/en/investors/business-development/available-technologies/technology-details.fh_bds_technology_id_23-151.quitbot-an-innovative-chat-app-to-assist-smoking-cessation.html Heatherton, T.F., Kozlowski, L.T., Frecker, R.C. And Fagerström, K.O. (1991) 'The Fagerström Test For Nicotine Dependence: A Revis
- 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.
Doha Ramadan Mahmoud, Msc degree in family medicine contact
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Conversational agent and Standard health education in people with Conversational Agent and Smoking Cessation, run by Cairo 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 6 inclusion and 3 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: opening soon, as of the sponsor's last update on 30 Oct 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 Doha Ramadan Mahmoud, Msc degree in family medicine (01019164696 ext. 01019164696, doharamadan5782@gmail.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Comparing the effectiveness of the quitbot conversational chatbot in promoting smoking cessation versus traditional cessation education among medical students in Cairo University (time frame: 3 months). 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 NCT07906249, which also lists 1 linked publication.
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 30 Oct 2026.