Predictors of participation in a telephone-based Acceptance and Commitment Therapy for smoking cessation study

Yim Wah Mak, Paul H Lee, Alice Yuen Loke, Yim Wah Mak, Paul H Lee, Alice Yuen Loke

Abstract

Background: Little is known about factors that influence participation in smoking cessation trials among Chinese populations. The aim of this study is to explore the characteristics of individuals who chose to participate and those who chose not to participate in a proactive telephone-based acceptance and commitment therapy program for smoking cessation within a Chinese sample, and to identify predictors of program participation. Understanding the factors that predict participation in smoking cessation trials may allow researchers and healthcare professionals to target their recruitment efforts to increase the enrollment of smokers in smoking cessation programs.

Methods: Participants were proactively recruited from six primary healthcare centers. Current cigarette smokers were screened for eligibility and then invited to complete a baseline questionnaire for the trial. The differences in characteristics between participants and non-participants as well as factors predictive of participation were analyzed using Chi-square tests and logistics regression.

Results: A total of 30,784 clinic attendees were approached. From these, 3,890 (12.6%) smokers were screened and identified. Of the 3,890 smokers, 420 (10.8%) were eligible to participate and completed the baseline questionnaires. The analysis showed that participants (n = 142) and non-participants (n = 278) differed significantly in terms of demographics, smoking-related, and psychological variables. The following characteristics were found to predict program participation: those with a relatively high level of dependence on nicotine (OR = 3.75; 95% CI = 1.25-11.23), those in the contemplation (OR = 7.86; 95% CI = 2.90-21.30) or preparation (OR = 24.81; 95% CI = 8.93-68.96) stages of change, and those who had abstained for one month or less in a previous attempt at quitting (OR = 3.77; 95% CI = 1.68-8.47).

Conclusions: The study shed light on the factors predictive of participation in a counseling-based smoking cessation program among a Chinese population. The results were encouraging, as most significant predictors (e.g., nicotine dependence, stage of change in smoking cessation) can be feasibly addressed or modified with interventions. No significant predictive relationships were found between psycho-social variables or socio-demographic variables and participation. Efforts should be made to increase the enrollment of smokers who are seemingly not yet ready to quit, and to tailor the program to fit the program's participants.

References

    1. The health consequences of smoking—50 years of progress: a report of the Surgeon General. Atlanta: US Department of Health and Human Services, Centers for Disease Control and Prevention, National Center for Chronic Disease Prevention and Health Promotion, Office on Smoking and Health. 2014; 17.
    1. A report of the Surgeon General. How tobacco smoke causes disease: what it means to you. Atlanta: US Department of Health and Human Services, Centers for Disease Control and Prevention. National Center for Chronic Disease Prevention and Health Promotion, Office on Smoking and Health; 2010.
    1. Cahill K, Stevens S, Perera R, Lancaster T. Pharmacological interventions for smoking cessation: an overview and network meta‐analysis. Cochrane Database Syst Rev. 2013;5:CD009329.
    1. Lancaster T, Stead LF. Individual behavioural counselling for smoking cessation. Cochrane Database Syst Rev. 2005; CD001292.
    1. Stead LF, Lancaster T. Group behaviour therapy programmes for smoking cessation. Cochrane Database Syst Rev. 2002; CD001007.
    1. Zhu S-H, Melcer T, Sun J, Rosbrook B, Pierce JP. Smoking cessation with and without assistance: a population-based analysis. Am J Prev Med. 2000;18(4):305–11. doi: 10.1016/S0749-3797(00)00124-0.
    1. Center for Disease Control and Prevention Quitting smoking among adults—United States, 2001–2010. MMWR Morb Mortal Wkly Re. 2011;60(44):1513.
    1. Lichtenstein E, Hollis J. Patient referral to a smoking cessation program: who follows through? J Fam Practice. 1992;34:739–44.
    1. McDonald PW. Population-based recruitment for quit-smoking programs: an analytic review of communication variables. Prev Med. 1999;28(6):545–57. doi: 10.1006/pmed.1998.0479.
    1. Wewers ME, Stillman FA, Hartman AM, Shopland DR. Distribution of daily smokers by stage of change: Current Population Survey results. Prev Med. 2003;36(6):710–20. doi: 10.1016/S0091-7435(03)00044-6.
    1. Skov-Ettrup L, Dalum P, Ekholm O, Tolstrup J. Reach and uptake of Internet- and phone-based smoking cessation interventions: Results from a randomized controlled trial. Prev Med. 2014;62:38–43. doi: 10.1016/j.ypmed.2014.01.020.
    1. Prochaska JO, Velicer WF, Fava JL, Rossi JS, Tsoh JY. Evaluating a population-based recruitment approach and a stage-based expert system intervention for smoking cessation. Add Behav. 2001;26(4):583–602. doi: 10.1016/S0306-4603(00)00151-9.
    1. Ahluwalia JS, Richter K, Mayo MS, Ahluwalia HK, Choi WS, Schmelzle KH, et al. African American smokers interested and eligible for a smoking cessation clinical trial: predictors of not returning for Randomization. Ann Epidemiol. 2002;12(3):206–12. doi: 10.1016/S1047-2797(01)00305-2.
    1. Audrain-McGovern J, Halbert CH, Rodriguez D, Epstein LH, Tercyak KP. Predictors of participation in a smoking cessation program among young adult smokers. Cancer Epid Biomar. 2007;16(3):617–9. doi: 10.1158/1055-9965.EPI-06-0791.
    1. Woods MN, Harris KJ, Mayo MS, Catley D, Scheibmeir M, Ahluwalia JS. Participation of African Americans in a smoking cessation trial: a quantitative and qualitative study. J Natl Med Assoc. 2002;94(7):609.
    1. Graham A, Papandonatos G, DePue J, Pinto B, Borrelli B, Neighbors C, et al. Lifetime characteristics of participants and non-participants in a smoking cessation trial: implications for external validity and public health impact. Ann Behav Med. 2008;35(3):295–307. doi: 10.1007/s12160-008-9031-1.
    1. Troyer MB, Ferketich AK, Murray DM, Paskett ED, Wewers ME. Characteristics of rural Appalachian women who enroll in a tobacco dependence treatment clinical trial. Nicotine Tob Res. 2011;13(9):880–5. doi: 10.1093/ntr/ntr071.
    1. Graham AL, Bock BC, Cobb NK, Niaura R, Abrams DB. Characteristics of smokers reached and recruited to an internet smoking cessation trial: a case of denominators. Nicotine Tob Res. 2006;8(Suppl 1):S43–8. doi: 10.1080/14622200601042521.
    1. Mak YW, Loke AY, Lam TH, Abdullah AS. Predictors of the participation of smoking parents in a proactive telephone-based smoking cessation program. Add Behav. 2006;31(10):1731–43. doi: 10.1016/j.addbeh.2005.12.018.
    1. Li Q, Hsia J, Yang G. Prevalence of smoking in China in 2010. N Engl J Med. 2011;364:2469–70. doi: 10.1056/NEJMc1102459.
    1. Centre for Health Protection, Hong Kong. Statistics on behavioral risk factors. Available online: . (assessed on 23 November 2015).
    1. Hong Kong Council on Smoking and Health. Smoking (Public Health) Ordinance. Legislations in Hong Kong. Available online: (assessed on 23 November 2015).
    1. Hong Kong Council on Smoking and Health: Cessation: Services. Available online:. (assessed on 23 November 2015).
    1. Glasgow RE, Vogt TM, Boles SM. Evaluating the public health impact of health promotion interventions: the RE-AIM framework. Am J Public Health. 1999;89(9):1322–7. doi: 10.2105/AJPH.89.9.1322.
    1. Hymowitz N, Cummings KM, Hyland A, Lynn WR, Pechacek TF, Hartwell TD. Predictors of smoking cessation in a cohort of adult smokers followed for five years. Tobacco Control. 1997;6(suppl 2):S57–62. doi: 10.1136/tc.6.suppl_2.S57.
    1. Hyland A, Li Q, Bauer JE, Giovino GA, Steger C, Cummings KM. Predictors of cessation in a cohort of current and former smokers followed over 13 years. Nicotine Tob Res. 2004;6(Suppl 3):S363–9. doi: 10.1080/14622200412331320761.
    1. Moy F, Atiya A, Wong M. Perceived risks, barriers and stages of change on smoking cessation among the Malay security guards in a public university in Kuala Lumpur. Int Med J Malaysia. 2008;7(2):9–14.
    1. Yang T, Fisher KJ, Li F, Danaher BG. Attitudes to smoking cessation and triggers to relapse among Chinese male smokers. BMC Public Health. 2006;6(1):65. doi: 10.1186/1471-2458-6-65.
    1. Gross JJ, John OP. Individual differences in two emotion regulation processes: implications for affect, relationships, and well-being. J Pers Soc Psychol. 2003;85(2):348. doi: 10.1037/0022-3514.85.2.348.
    1. Szasz PL, Szentagotai A, Hofmann SG. Effects of emotion regulation strategies on smoking craving, attentional bias, and task persistence. Behav Res and Ther. 2012;50(5):333–40. doi: 10.1016/j.brat.2012.02.010.
    1. Toll BA, Sobell MB, Wagner EF, Sobell LC. The relationship between thought suppression and smoking cessation. Add Behav. 2001;26(4):509–15. doi: 10.1016/S0306-4603(00)00140-4.
    1. Fucito LM, Juliano LM, Toll BA. Cognitive reappraisal and expressive suppression emotion regulation strategies in cigarette smokers. Nicotine Tob Res. 2010;12:1156–61. doi: 10.1093/ntr/ntq146.
    1. Mak YW, Loke AY. The acceptance and commitment therapy for smoking cessation for smokers from primary health care settings: study protocol. BMC-Public Health. 2015;15:105. doi: 10.1186/s12889-015-1485-z.
    1. Ware J, Kosinski M, Turner-Bowker D, Gandek B. How to score version 2 of the SF-12-v2 health survey. Quality Metric Incorporated: Lincoln; 2002.
    1. Heatherton TF, Kozlowski LT, Frecker RC, Fagerstrom KO. The Fagerström test for nicotine dependence: a revision of the Fagerstrom Tolerance Questionnaire. Br J Addict. 1991;86(9):1119–27. doi: 10.1111/j.1360-0443.1991.tb01879.x.
    1. Prochaska J, Goldstein M. Process of smoking cessation. Implications for clinicians. Clin Chest Med. 1991;12(4):727–35.
    1. Abdullah ASM, Mak YW, Loke AY, Lam TH. Smoking cessation intervention in parents of young children: a randomised controlled trial. Addiction. 2005;100(11):1731–40. doi: 10.1111/j.1360-0443.2005.01231.x.
    1. IBM Corp. IBM SPSS Statistics for Windows, Version 21.0. Arnonk, NY: IBM Corp.; Released 2012.
    1. Rubin DB. Multiple imputations for nonresponse in surveys. volume 81. New York: Wiley; 2004.
    1. Census and Statistics Department, Hong Kong. 2011 Population Census. Available online: . (Assessed on 11 December 2015).
    1. Abdullah A, Lam T, Chan S, Hedley A. Which smokers use the smoking cessation Quitline in Hong Kong, and how effective is the Quitline? Tob Control. 2004;13(4):415–21. doi: 10.1136/tc.2003.006460.

Source: PubMed

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