- ICH GCP
- US Clinical Trials Registry
- Clinical Trial NCT05997901
Helping People Adhere to Their Varenicline Treatment by Co-creating a Conversational Agent: A Feasibility Study
The goal of this feasibility study is to co-create and evaluate a theory informed, evidence-based, patient-centered healthbot aimed at helping people adhere to their varenicline regimen. The main research questions it aims to answer are:
- What are the challenges to varenicline adherence and strategies to overcome such challenges from the perspective of service users and service providers?
- What features of a healthbot would help improve adherence to varenicline?
Does a healthbot developed to improve varenicline adherence meet the implementation outcomes and increase medication adherence as well as smoking cessation? The study will be conducted using the Discover Design Build and Test framework.
- In the Discover phase, a literature review, 20 service user interviews, and 20 healthcare provider interviews will help inform the challenges to varenicline adherence, strategies to overcome them using the Capability, Opportunity, Motivation, and Behavior framework, and the ways in which a healthbot might help improve adherence.
- In the Design, Build and Test phase, 40 participants will interact with a preliminary healthbot using the Wizard of Oz method, then provide feedback about their experiences in a follow up interview; and team members, including clinicians and researchers, will beta test and validate a more refined healthbot.
In the last phase, a non-randomized single arm feasibility study, 40 participants will interact with the healthbot for 12 weeks and provide feedback about the acceptability, appropriateness, fidelity, adoption, and usability of the healthbot; and researchers will assess participants' medication adherence and smoking status.
Study Overview
Status
Conditions
Intervention / Treatment
Detailed Description
A: Co-design a theory informed healthbot to support patients' adherence to varenicline:
The investigators will employ a user-centred approach to build the healthbot in order to optimize user experience and achieve the best uptake and utilization. Following the Discover, Design and Build, and Test (DDBT) framework, the investigators will use a three-step approach to co-design the core functionality of the healthbot: 1) review the literature and conduct interviews with potential users (Discovery Phase); 2) design the healthbot and conduct Wizard of Oz testing (Design/Build Phase); 3) Train and test the healthbot (Test Phase).
Literature review:
The aim of this rapid review is two folded: 1) to identify the barriers and facilitators to varenicline adherence, in people using varenicline for smoking cessation (the investigators will use the Theoretical Domains Framework (TDF) to organize the data extraction), and 2) to identify the behaviour change techniques (BCTs) that are associated with helping people adhere to their varenicline treatment (the investigators will use BCTT v1. to organize the data extraction). The study was registered with PROSPERO (# CRD42022321838).
Semi-Structured Interviews with people who use varenicline:
To gain in-depth understanding of the challenges and solutions people who use varenicline encounter and to understand what features users would like to see in a healthbot designed to help adhere to varenicline.
Semi-Structured Interviews with health care providers who help people who want to quit smoking:
There is little guidance regarding health care providers' (HCP) perspectives in recommending digital health solutions to their patients. Understanding the perspectives of HCPs is crucial to facilitate the effective delivery and uptake of the healthbot. These interviews will explore: (1) barriers/facilitators influencing HCPs provision of digital health solutions to patients prescribed varenicline; (2) Identify theoretical domains to target for behaviour change; (3) Select BCTs to include in the healthbot.
Wizard of Oz Method:
The purpose of this stage is to test a minimum viable product to determine whether the product needs a pivot. Pivots are structured improvements designed to test new fundamental hypotheses about products, strategies, and growth engines and often occur in the early stages of product development. The Wizard of Oz (WoZ) method is a popular approach wherein research participants interact with a computer system they believe is autonomous; however, responses are actually generated by an unseen human being (the wizard). It is useful in iterative development as it is very easy to change and evolve the wizard's responses.
Building the healthbot (Build Phase):
Following guidance from the Nonadoption, abandonment, scale-up, spread, and sustainability (NASSS) framework, the investigators will build the healthbot choosing the simplest sensible solution for the design. For this study, the investigators will build a rule-based healthbot, that has capabilities to determine the meaning of users' words. The rules will come from the literature review, the interviews, and WoZ testing. Specifically, following the discovery phase, the research team will rate all BCTs identified as possible contributors to helping people adhere to their varenicline based on whether it is affordable, practical, effective, acceptable, safe and equitable (APEASE criteria).
Training and testing (Test Phase):
The interviews and WoZ data will serve to help train the healthbot. In addition, once the investigators have a working prototype of the healthbot, team members including clinicians and researchers will interact with the healthbot to beta test and validate it.
B: Evaluate the implementation outcomes; examine medication adherence and smoking cessation success among participants who use the healthbot:
The investigators will conduct a non-randomized single arm feasibility study. It will only have an intervention group (with no control group) and is designed to examine important study procedures (e.g., patient recruitment, retention, missing data), in advance of a larger randomized controlled trial (RCT) testing the effectiveness of the healthbot.
Interested individuals will contact research staff, who will explain the study and assess for inclusion criteria. If eligible, participants will be sent a consent form and scheduled for a phone-based consent discussion. Once consent is received, an in person or virtual baseline visit will be scheduled where participants (n=40) will be asked a few baseline questions related to socio-demographic characteristics, smoking dependency, and an adapted scale to measure varenicline adherence self-efficacy. They will have a virtual or in person visit with a healthcare provider for eligibility confirmation and obtain a prescription for varenicline for the first four weeks (one tablet [0.5 mg] daily for the first three days, one tablet [0.5 mg] twice daily for the next four days, and one tablet [1 mg] twice daily for three weeks). In addition, research staff will show participants how to use the healthbot on their phones. A follow up visit will be scheduled at two weeks where healthcare providers will assess the participant's tolerance of varenicline and provide a prescription for the remaining eight weeks (one tablet (1 mg) twice daily or a different dose depending on the tolerance of each participant). Medication will be provided in person or mailed to the participants based on the format of their baseline and follow up healthcare provider visit. Any unanticipated problems due to varenicline use (i.e., adverse events that are unexpected in terms of severity, nature or frequency; related, or possibly related to participation in the research; and suggest that the research places other research participants at greater risk of harm) will be documented as applicable and reported to the Research Ethics Board and adverse drug reactions will be reported to the Market Authorization Holder (APOTEX) as applicable.
The healthbot will provide: 1) reminders for varenicline dosing and schedule; 2) information and suggestions on managing known side effects (the most frequently cited reason for varenicline non-adherence is experiencing side effects); 3) answers to questions about medication use (e.g., what to do if a dose is missed); 4) tracking medication intake and smoking; 5) support and encouragement to increase participants' motivation to continue their quit attempts. During the next 12 weeks, participants will be reminded by the healthbot to take their varenicline at the appropriate times and will be able to interact with the healthbot when they want.
At 1, 4, 8, and 12 weeks, participants will complete a survey. All participants who do not complete the follow-up survey within the timeframe allowed will be contacted by phone from research staff. In addition, after the 12 weeks of using the healthbot, participants will participate in a 1-hour semi-structured phone interview.
Study Type
Enrollment (Actual)
Phase
- Not Applicable
Contacts and Locations
Study Locations
-
-
Ontario
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Toronto, Ontario, Canada, M6J1H4
- Centre for Addiction and Mental Health
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-
Participation Criteria
Eligibility Criteria
Ages Eligible for Study
- Adult
- Older Adult
Accepts Healthy Volunteers
Description
Inclusion Criteria:
- Treatment-seeking smokers who are willing to start taking varenicline and continue it for 12 weeks, and set a quit date in the next 30 days;
- Smoke cigarettes daily (10 or more cigarettes a day)
- Age ≥ 18 years;
- Speak/read English;
- Have a smartphone with data plan;
- Report being committed to answering questions during follow-up;
- Live in Ontario.
Exclusion Criteria:
- Have contraindication(s) to varenicline use;
- Are pregnant/planning to become pregnant/breastfeeding;
- Participated in the co-design phase.
Study Plan
How is the study designed?
Design Details
- Primary Purpose: Treatment
- Allocation: N/A
- Interventional Model: Single Group Assignment
- Masking: None (Open Label)
Arms and Interventions
Participant Group / Arm |
Intervention / Treatment |
|---|---|
|
Experimental: Varenicline healthbot
While the exact healthbot features will be based on results from the rapid review, interviews and Wizard of OZ testing, the investigators know from the existing literature on medication adherence, and behaviour change interventions, that the healthbot will provide: 1) reminders for varenicline dosing and schedule; 2) information and suggestions on managing known side effects (the most frequently cited reason for varenicline non-adherence is experiencing side effects); 3) answers to questions about medication use (e.g., what to do if a dose is missed); and 4) support to increase participants' motivation to continue their quit attempts.
During the next 12 weeks, participants will be reminded by the healthbot to take their varenicline at the appropriate times, and will be able to interact with the healthbot when they want.
|
The intervention is a healthbot that will provide information, reminders, answers to questions, and support to participants using varenicline for smoking cessation.
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What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Acceptability of Intervention Measure (AIM)
Time Frame: 12 weeks
|
The extent to which an innovation is agreeable, palatable, or satisfactory to a stakeholder. In order to measure acceptability, we used the four-item Acceptability of Intervention Measure (AIM) in the follow up surveys. The Acceptability of Intervention Measure (AIM) is a 4-item scale assessing perceived acceptability. Each item is rated from 1 (strongly disagree) to 5 (strongly agree). The total AIM score is the sum of the four items, yielding a range of 4-20, with higher scores indicating greater acceptability. Unit of Measure: score on a scale (4-20). |
12 weeks
|
|
Appropriateness
Time Frame: 12 weeks
|
The perceived fit or compatibility of an innovation with a practice setting or context. For this study, appropriateness will be measured at the individual level (e.g., alignment with users' attitudes, needs, and background) in the 12 week survey, with the Intervention Appropriateness Measure (IAM), a validated 4-item intervention appropriateness scale. The IAM includes 4 items, each rated on a 5-point Likert scale from 1 ("Completely disagree") to 5 ("Completely agree"). Item responses are summed to generate a total IAM score ranging from 4 to 20, with higher scores indicating greater perceived appropriateness of the intervention. |
12 weeks
|
|
Adoption
Time Frame: 12 weeks
|
The intention, decision, or initiation of use for an evidence-based practice, characterizing it at the level of the provider or organization. Given that the concept of adoption aligns with constructs of actual system use, researchers examining behavioural intervention technologies (such as the healthbot) have expanded this level of analysis to that of the consumer. In this study, the investigators will measure the adoption of the healthbot by examining analytics data, which the healthbot will passively collect in in-app logs, during the 12 weeks that the participant is scheduled to take the varenicline. The investigators will measure adoption through multiple healthbot analytics, including when (day/time) the user interacted with the healthbot, which features were used, and time spent engaged. If the mean use is ≤20 time, it will be considered as the cutoff point to not progress to a randomized controlled trial. |
12 weeks
|
|
Usability
Time Frame: 12 weeks
|
Will be assessed using the System Usability Scale (SUS). The SUS consists of 10 items rated on a 5-point Likert scale ranging from 1 ("Strongly disagree") to 5 ("Strongly agree"), with alternating positively and negatively worded items. Responses are summed and converted to a total score ranging from 0 to 100, with higher scores indicating better perceived usability. A SUS score of 68 is considered average usability, with scores above 68 indicating above-average usability and scores below 68 suggesting usability concerns. Scores above approximately 80 are typically interpreted as excellent usability, while scores below 50 indicate poor usability. SUS scores |
12 weeks
|
Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Medication Adherence
Time Frame: 12 weeks
|
The Timeline Follow-Back (TLFB) method was used to assess adherence to varenicline. TLFB is a validated, calendar-based retrospective reporting method in which participants indicate the number of varenicline pills taken since their previous study visit. TLFB surveys were collected at Weeks 1, 4, 8, and 12. For each interval, adherence was calculated as: (Number of pills reportedly taken ÷ Number of pills prescribed for that interval) Participants were classified as adherent if they took ≥80% of their prescribed varenicline doses during each interval. The reported outcome reflects the number of participants who, at the 12-week assessment, were ≥80% adherent at Weeks 1, 4, 8, and 12. |
12 weeks
|
|
Smoking Status
Time Frame: 12 weeks
|
Smoking abstinence was assessed during the follow-up survey at 12 weeks. Abstinence was defined using the dichotomous 7-day point-prevalence question: "Have you had a cigarette, even a puff, in the last seven days?" Participants who responded "No" were classified as abstinent. The outcome reflects the number of participants who had quit smoking at the 12-week assessment. |
12 weeks
|
Collaborators and Investigators
Investigators
- Principal Investigator: Nadia Minian, PhD, CAMH
Publications and helpful links
General Publications
- Michie S, van Stralen MM, West R. The behaviour change wheel: a new method for characterising and designing behaviour change interventions. Implement Sci. 2011 Apr 23;6:42. doi: 10.1186/1748-5908-6-42.
- Weiner BJ, Lewis CC, Stanick C, Powell BJ, Dorsey CN, Clary AS, Boynton MH, Halko H. Psychometric assessment of three newly developed implementation outcome measures. Implement Sci. 2017 Aug 29;12(1):108. doi: 10.1186/s13012-017-0635-3.
- Fagerstrom K. Determinants of tobacco use and renaming the FTND to the Fagerstrom Test for Cigarette Dependence. Nicotine Tob Res. 2012 Jan;14(1):75-8. doi: 10.1093/ntr/ntr137. Epub 2011 Oct 24. No abstract available.
- Michie S, Richardson M, Johnston M, Abraham C, Francis J, Hardeman W, Eccles MP, Cane J, Wood CE. The behavior change technique taxonomy (v1) of 93 hierarchically clustered techniques: building an international consensus for the reporting of behavior change interventions. Ann Behav Med. 2013 Aug;46(1):81-95. doi: 10.1007/s12160-013-9486-6.
- Proctor E, Silmere H, Raghavan R, Hovmand P, Aarons G, Bunger A, Griffey R, Hensley M. Outcomes for implementation research: conceptual distinctions, measurement challenges, and research agenda. Adm Policy Ment Health. 2011 Mar;38(2):65-76. doi: 10.1007/s10488-010-0319-7.
- Cane J, O'Connor D, Michie S. Validation of the theoretical domains framework for use in behaviour change and implementation research. Implement Sci. 2012 Apr 24;7:37. doi: 10.1186/1748-5908-7-37.
- Nadarzynski T, Miles O, Cowie A, Ridge D. Acceptability of artificial intelligence (AI)-led chatbot services in healthcare: A mixed-methods study. Digit Health. 2019 Aug 21;5:2055207619871808. doi: 10.1177/2055207619871808. eCollection 2019 Jan-Dec.
- Hermes ED, Lyon AR, Schueller SM, Glass JE. Measuring the Implementation of Behavioral Intervention Technologies: Recharacterization of Established Outcomes. J Med Internet Res. 2019 Jan 25;21(1):e11752. doi: 10.2196/11752.
- Abimbola S, Patel B, Peiris D, Patel A, Harris M, Usherwood T, Greenhalgh T. The NASSS framework for ex post theorisation of technology-supported change in healthcare: worked example of the TORPEDO programme. BMC Med. 2019 Dec 30;17(1):233. doi: 10.1186/s12916-019-1463-x.
- Yardley L, Morrison L, Bradbury K, Muller I. The person-based approach to intervention development: application to digital health-related behavior change interventions. J Med Internet Res. 2015 Jan 30;17(1):e30. doi: 10.2196/jmir.4055.
- Kelley JF. An iterative design methodology for user-friendly natural language office information applications. ACM Transactions on Information Systems. 1984;2(1)
- Ries E. The Lean Startup: How Today's Entrepreneurs Use Continuous Innovation to Create Radically Successful Businesses: Crown Business 2011.
- Michie S, Atkins L, West R. The behaviour change wheel: a guide to designing interventions. 2014. Great Britain: Silverback Publishing. 2015.
- Fucito LM, Toll BA, Salovey P, O'Malley SS. Beliefs and attitudes about bupropion: implications for medication adherence and smoking cessation treatment. Psychol Addict Behav. 2009 Jun;23(2):373-9. doi: 10.1037/a0015695.
- Fernandez S, Chaplin W, Schoenthaler AM, Ogedegbe G. Revision and validation of the medication adherence self-efficacy scale (MASES) in hypertensive African Americans. J Behav Med. 2008 Dec;31(6):453-62. doi: 10.1007/s10865-008-9170-7. Epub 2008 Sep 11.
- Tseng TY, Krebs P, Schoenthaler A, Wong S, Sherman S, Gonzalez M, Urbina A, Cleland CM, Shelley D. Combining Text Messaging and Telephone Counseling to Increase Varenicline Adherence and Smoking Abstinence Among Cigarette Smokers Living with HIV: A Randomized Controlled Study. AIDS Behav. 2017 Jul;21(7):1964-1974. doi: 10.1007/s10461-016-1538-z.
- Hollands GJ, Naughton F, Farley A, Lindson N, Aveyard P. Interventions to increase adherence to medications for tobacco dependence. Cochrane Database Syst Rev. 2019 Aug 16;8(8):CD009164. doi: 10.1002/14651858.CD009164.pub3.
- Scott-Sheldon LA, Lantini R, Jennings EG, Thind H, Rosen RK, Salmoirago-Blotcher E, Bock BC. Text Messaging-Based Interventions for Smoking Cessation: A Systematic Review and Meta-Analysis. JMIR Mhealth Uhealth. 2016 May 20;4(2):e49. doi: 10.2196/mhealth.5436.
- Jackson C, Eliasson L, Barber N, et al. Applying COM-B to medication adherence: A suggested framework for research and interventions. The European Health Psychologist 2014.
- Catz SL, Jack LM, McClure JB, Javitz HS, Deprey M, Zbikowski SM, McAfee T, Richards J, Swan GE. Adherence to varenicline in the COMPASS smoking cessation intervention trial. Nicotine Tob Res. 2011 May;13(5):361-8. doi: 10.1093/ntr/ntr003. Epub 2011 Feb 24.
- Peng AR, Swardfager W, Benowitz NL, Ahluwalia JS, Lerman C, Nollen NL, Tyndale RF. Impact of early nausea on varenicline adherence and smoking cessation. Addiction. 2020 Jan;115(1):134-144. doi: 10.1111/add.14810. Epub 2019 Nov 5.
- Booke J. SUS-A quick and dirty usability scale. In Jordan P, Thomas B, (Eds). Usability Evaluation In Industry: Taylor and Francis 1996.
- Heatherton TF, Kozlowski LT, Frecker RC, Rickert W, Robinson J. Measuring the heaviness of smoking: using self-reported time to the first cigarette of the day and number of cigarettes smoked per day. Br J Addict. 1989 Jul;84(7):791-9. doi: 10.1111/j.1360-0443.1989.tb03059.x.
- Brown RA, Burgess ES, Sales SD, et al. Reliability and validity of a smoking timeline follow-back interview. Psychology of Addictive Behaviors. 1998;12(2):101-112.
- Peng AR, Morales M, Wileyto EP, Hawk LW Jr, Cinciripini P, George TP, Benowitz NL, Nollen NL, Lerman C, Tyndale RF, Schnoll R. Measures and predictors of varenicline adherence in the treatment of nicotine dependence. Addict Behav. 2017 Dec;75:122-129. doi: 10.1016/j.addbeh.2017.07.006. Epub 2017 Jul 12.
- Lyon AR, Munson SA, Renn BN, Atkins DC, Pullmann MD, Friedman E, Arean PA. Use of Human-Centered Design to Improve Implementation of Evidence-Based Psychotherapies in Low-Resource Communities: Protocol for Studies Applying a Framework to Assess Usability . JMIR Res Protoc. 2019 Oct 9;8(10):e14990. doi: 10.2196/14990.
- Kaur K, Kaushal S, Chopra SC. Varenicline for smoking cessation: A review of the literature. Curr Ther Res Clin Exp. 2009 Feb;70(1):35-54. doi: 10.1016/j.curtheres.2009.02.004.
- Minian N, Mehra K, Earle M, Hafuth S, Ting-A-Kee R, Rose J, Veldhuizen S, Zawertailo L, Ratto M, Melamed OC, Selby P. AI Conversational Agent to Improve Varenicline Adherence: Protocol for a Mixed Methods Feasibility Study. JMIR Res Protoc. 2023 Dec 11;12:e53556. doi: 10.2196/53556.
Study record dates
Study Major Dates
Study Start (Actual)
Primary Completion (Actual)
Study Completion (Actual)
Study Registration Dates
First Submitted
First Submitted That Met QC Criteria
First Posted (Actual)
Study Record Updates
Last Update Posted (Actual)
Last Update Submitted That Met QC Criteria
Last Verified
More Information
Terms related to this study
Additional Relevant MeSH Terms
- Behavior
- Treatment Adherence and Compliance
- Health Behavior
- Patient Compliance
- Patient Acceptance of Health Care
- Smoking Cessation
- Medication Adherence
- Physiological Effects of Drugs
- Neurotransmitter Agents
- Molecular Mechanisms of Pharmacological Action
- Cholinergic Agents
- Nicotinic Agonists
- Cholinergic Agonists
- Varenicline
Other Study ID Numbers
- PJT-180405
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.
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