Helping People Adhere to Their Varenicline Treatment by Co-creating a Conversational Agent: A Feasibility Study

Smoking Cessation Clinical Trial

Official title:

Helping People Adhere to Their Varenicline Treatment by Co-creating a Conversational Agent: A Feasibility Study

Clinical Trial Details — Status: Recruiting

Administrative data

• NCT number: NCT05997901
• Other study ID #: PJT-180405
• Status: Recruiting
• Phase: N/A
• Start date: October 12, 2022
• Est. completion date: September 12, 2025

Study information

• Verified date: January 2024
• Source: Centre for Addiction and Mental Health
• Contact: Nadia Minian, PhD
• Phone: 4165358501
• Email: Nadia.Minian2[@]camh.ca
• Is FDA regulated: No
• Study type: Interventional

Clinical Trial Summary

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:

1. What are the challenges to varenicline adherence and strategies to overcome such challenges from the perspective of service users and service providers?

2. What features of a healthbot would help improve adherence to varenicline?

3. 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.

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. At the beginning of the study, participants will be able to choose if they answer the questions through the healthbot or online. All participants who do not complete the online/healthbot follow-up 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.

Recruitment information / eligibility

• Status: Recruiting
• Enrollment: 40
• Est. completion date: September 12, 2025
• Est. primary completion date: March 12, 2025
• Accepts healthy volunteers: Accepts Healthy Volunteers
• Gender: All
• Age group: 18 Years and older

Eligibility

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.

Related Conditions & MeSH terms

• Medication Adherence
• Smoking Cessation

Intervention

Other:
• Varenicline healthbot
The intervention is a healthbot that will provide information, reminders, answers to questions, and support to participants using varenicline for smoking cessation.

Locations

Country	Name	City	State
Canada	Centre for Addiction and Mental Health	Toronto	Ontario

Sponsors (3)

Lead Sponsor	Collaborator
Centre for Addiction and Mental Health	Canadian Cancer Society (CCS), Canadian Institutes of Health Research (CIHR)

Country where clinical trial is conducted

Canada, 

References & Publications (27)

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. — View Citation

Booke J. SUS-A quick and dirty usability scale. In Jordan P, Thomas B, (Eds). Usability Evaluation In Industry: Taylor and Francis 1996.

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.

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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.

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. Erratum In: Curr Ther Res Clin Exp. 2010;71(1):89. — View Citation

Kelley JF. An iterative design methodology for user-friendly natural language office information applications. ACM Transactions on Information Systems. 1984;2(1)

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. Erratum In: JMIR Res Protoc. 2020 Mar 4;9(3):e18241. — View Citation

Michie S, Atkins L, West R. The behaviour change wheel: a guide to designing interventions. 2014. Great Britain: Silverback Publishing. 2015.

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

Ries E. The Lean Startup: How Today's Entrepreneurs Use Continuous Innovation to Create Radically Successful Businesses: Crown Business 2011.

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

* Note: There are 27 references in all — Click here to view all references

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Acceptability	The extent to which an innovation is agreeable, palatable, or satisfactory to a stakeholder. In order to measure acceptability, the investigators will utilize the four-item Acceptability of Intervention Measure (AIM) in the follow up surveys and a score of =8 will be considered as the cutoff point to not progress to a randomized controlled trial. The acceptability will also be assessed through open ended questions in the semi-structured interviews.	12 weeks
Primary	Appropriateness	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, and a score of =8 will be considered as the cutoff point to not progress to a randomized controlled trial. The appropriateness will also be assessed in-depth in the semi-structured interviews.	12 weeks
Primary	Fidelity	The extent to which an intervention is used as intended. For this study, the investigators will explore in the semi-structured interviews what functions of the healthbot participants used, what they used the healthbot for (e.g., answer questions, receive support), frequency of use, and quality, i.e., whether the healthbot delivered the correct information according to the user.	12 weeks
Primary	Adoption	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.; We will also explore participants' perceived use of the hea	12 weeks
Primary	Usability	Will be assessed using the System Usability Scale (SUS). The SUS is a 10-item measure assessing usability and user satisfaction with technology. A score of =40 will be considered as the cutoff point to not progress to a randomized controlled trial.	12 weeks
Secondary	Medication Adherence	Participants will be asked about their medication adherence using timeline follow-back (TLFB) in the surveys collected at 1, 4, 8, and 12 weeks. Participants will report the number of pills taken since the previous assessment. Participants will be asked to send pictures of the blister packs via email at 1, 4, 8, and 12 weeks. These two methods will be used to assess the feasibility of measuring adherence through these different methods, to help understand which method would be most appropriate for any follow up RCT. Participants who used the healthbot to log their medications will be able to import this data to the survey. We selected TLFB to measure adherence since the 12 week TLFB measure is moderately correlated with saliva varenicline levels, and is considered the best practical measure of varenicline adherence.	12 weeks
Secondary	Smoking Status	Smoking abstinence will be assessed during the follow up surveys at 1, 4, 8 and 12 weeks, and will be defined by a negative response to the dichotomous 7-day point prevalence question, "Have you had a cigarette, even a puff, in the last seven days?"	12 weeks