Hostname: page-component-78c5997874-8bhkd Total loading time: 0 Render date: 2024-11-14T22:09:10.610Z Has data issue: false hasContentIssue false

Predicting Engagement in Smoking Cessation Treatment Following a Brief Telephone Evaluation and Referral Session

Published online by Cambridge University Press:  11 July 2018

Angela Petersen
Affiliation:
Psychology Service, Veterans Affairs San Diego Healthcare System, San Diego, CA Department of Psychiatry, University of California, San Diego, CA
Suraya Jabaiah
Affiliation:
School of Pharmacy, University of California, San Diego, CA
Timothy Chen
Affiliation:
Department of Psychiatry, University of California, San Diego, CA
Neal Doran
Affiliation:
Psychology Service, Veterans Affairs San Diego Healthcare System, San Diego, CA Department of Psychiatry, University of California, San Diego, CA
Mark Myers*
Affiliation:
Psychology Service, Veterans Affairs San Diego Healthcare System, San Diego, CA Department of Psychiatry, University of California, San Diego, CA
*
Address for correspondence: Mark Myers, Ph.D., Department of Psychology Service, Veterans Affairs San Diego Healthcare System 116B, VASDHS, 3350 La Jolla Village Dr, San Diego, CA 92161. Email: mgmyers@ucsd.edu

Abstract

Introduction: Smoking cessation treatment combining medication and counselling yields the best outcomes; however, few smokers employ both modalities.

Aims: The purpose of this study was to examine variables predicting treatment attendance.

Methods: This was a chart review of US military Veterans (N = 340; 89% male, 59% non-Hispanic white) referred for smoking cessation, who completed a telephone call to encourage treatment utilization. Treatment engagement was defined as attending a smoking cessation session within 30 days following telephone contact. A logistic regression analysis examined predictors (demographics, smoking variables, and psychiatric diagnoses) of treatment engagement.

Results/Findings: Greater age (Odds Ratio [OR] = 1.04, 95% confidence interval [CI] 1.01–1.06), more cigarettes (OR = 1.03, 95% CI 1.00–1.06), and higher perceived importance of quitting (OR = 1.11, 95% CI 1.00–1.23) predicted engaging in treatment within 30 days (all p values < 0.05).

Conclusion: Veterans who attended treatment were older, smoked more cigarettes, and perceived quitting as more important than those who did not attend. These findings are consistent with prior studies examining factors associated with treatment utilization. Results highlight the need to identify strategies for engaging into treatment smokers who are younger, smoke fewer cigarettes, and view quitting as less important.

Type
Original Articles
Creative Commons
This is a work of the U.S. Government and is not subject to copyright protection in the United States.
Copyright
Copyright © The Author(s) 2018

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Abrams, D. B., Graham, A. L., Levy, D. T., Mabry, P. L., & Orleans, C. T. (2010). Boosting population quits through evidence-based cessation treatment and policy. American Journal of Preventive Medicine, 38 (Suppl. 3), S351–S363. doi:10.1016/j.amepre.2009.12.011.Google Scholar
Al Delaimy, W. K., Leas, E., Myers, M. G., Strong, D., Hofstetter, R., Linke, S. et al. (2014). California smokers cohort study: Smoking behaviors and predictors of quitting among California smokers 2011–2012. La Jolla, CA: University of California, San Diego.Google Scholar
Boudreaux, E., Sullivan, A., Abar, B., Bernstein, S., Ginde, A., & Camargo, C. (2012). Motivation rulers for smoking cessation: A prospective observational examination of construct and predictive validity. Addiction Science & Clinical Practice, 7 (1), 8. doi:10.1186/1940-0640-7-8.Google Scholar
Collins, L. M., & Graham, J. W. (2002). The effect of the timing and spacing of observations in longitudinal studies of tobacco and other drug use: Temporal design considerations. Drug and Alcohol Dependence, 68 (Suppl. 1), S85– S96.Google Scholar
Danan, E. R., Joseph, A. M., Sherman, S. E., Burgess, D. J., Noorbaloochi, S., Clothier, B. et al. (2016). Does motivation matter? Analysis of a randomized trial of proactive outreach to VA smokers. Journal of General Internal Medicine, 31 (8), 878887. doi:10.1007/s11606-016-3687-1.Google Scholar
Fiore, M. C., Jaén, C. R., Baker, T. B., Bailey, W. C., Benowitz, N. L., Curry, S. J. et al. (2008). Treating tobacco use and dependence: 2008 update. Rockville, MD: US Department of Health and Human Services.Google Scholar
Fu, S. S., van Ryn, M., Burgess, D. J., Nelson, D., Clothier, B., Thomas, J. L. et al. (2014). Proactive tobacco treatment for low income smokers: Study protocol of a randomized controlled trial. BMC Public Health, 14, 337. doi:10.1186/1471-2458-14-337.Google Scholar
Fu, S. S., van Ryn, M., Sherman, S. E., Burgess, D. J., Noorbaloochi, S., Clothier, B. et al. (2014). Proactive tobacco treatment and population-level cessation: A pragmatic randomized clinical trial. JAMA Internal Medicine, 174 (5), 671677. doi:10.1001/jamainternmed.2014.177.Google Scholar
Hamlett-Berry, K., Davison, J., Kivlahan, D. R., Matthews, M. H., Hendrickson, J. E., & Almenoff, P. L. (2009). Evidence-based national initiatives to address tobacco use as a public health priority in the Veterans health administration. Military Medicine, 174 (1), 2934.Google Scholar
Heatherton, T. F., Kozlowski, L. T., Frecker, R. C., Rickert, W., Robinson, J. (1989). Measuring the heaviness of smoking: using self-reported time to the first cigarette of the day and number of cigarettes smoked per day. British Journal of Addiction, 84, 791799.Google Scholar
Huang, G., Kim, S., Gasper, J., Xu, Y., Bosworth, T., & May, L. (2017). 2016 survey of veteran enrollees’ health and use of health care (GS-23F-8144H). Rockville, MD: Westat.Google Scholar
Hung, W. T., Dunlop, S. M., Perez, D., & Cotter, T. (2011). Use and perceived helpfulness of smoking cessation methods: Results from a population survey of recent quitters. BMC Public Health, 11, 592. doi:10.1186/1471-2458-11-592.Google Scholar
Jamal, A., King, B. A., Neff, L. J., Whitmill, J., Babb, S. D., & Graffunder, C. M. (2016). Current cigarette smoking among adults - United States, 2005–2015. Morbidity and Mortality Weekly Reports, 65 (44), 12051211. doi:10.15585/mmwr.mm6544a2.Google Scholar
Japuntich, S. J., Sherman, S. E., Joseph, A. M., Clothier, B., Noorbaloochi, S., Danan, E. et al. (2017). Proactive tobacco treatment for individuals with and without a mental health diagnosis: Secondary analysis of a pragmatic randomized controlled trial. Addictive Behaviors, 76, 1519. doi:10.1016/j.addbeh.2017.07.024.Google Scholar
Kelly, M. M., Sido, H., & Rosenheck, R. (2016). Rates and correlates of tobacco cessation service use nationally in the Veterans Health Administration. Psychological Services, 13 (2), 183192. doi:10.1037/ser0000076.Google Scholar
Kotz, D., Fidler, J., & West, R. (2009). Factors associated with the use of aids to cessation in English smokers. Addiction, 104 (8), 14031410. doi:10.1111/j.1360-0443.2009.02639.x.Google Scholar
Menard, S. (1995). Applied logistic regression analysis, Quantitative applications in the social sciences. Thousand Oaks, CA: Sage.Google Scholar
Myers, M. G., Chen, T., & Schweizer, C. A. (2016). Factors associated with accepting assistance for smoking cessation among military Veterans. Nicotine & Tobacco Research, 18 (12), 22882292. doi:10.1093/ntr/ntw163.Google Scholar
Myers, M. G., Strong, D. R., Linke, S. E., Hofstetter, C. R., & Al-Delaimy, W. K. (2015). Predicting use of assistance when quitting: A longitudinal study of the role of quitting beliefs. Drug and Alcohol Dependence, 149, 220224. doi:10.1016/j.drugalcdep.2015.02.003.Google Scholar
Pan, Y, & Jackson, R. T. (2008). Ethnic difference in the relationship between acute inflammation and serum ferritin in US adult males. Epidemiology and Infection, 136, 421431.Google Scholar
Shiffman, S., Brockwell, S. E., Pillitteri, J. L., & Gitchell, J. G. (2008a). Use of smoking-cessation treatments in the United States. American Journal of Preventive Medicine, 34 (2), 102111.Google Scholar
Shiffman, S., Brockwell, S. E., Pillitteri, J. L., & Gitchell, J. G. (2008b). Individual differences in adoption of treatment for smoking cessation: Demographic and smoking history characteristics. Drug and Alcohol Dependence, 93 (1–2), 121131. doi:10.1016/j.drugalcdep.2007.09.005.Google Scholar
Stead, L. F., & Lancaster, T. (2012). Behavioural interventions as adjuncts to pharmacotherapy for smoking cessation. Cochrane Database of Systematic Reviews, 12, CD009670. doi:10.1002/14651858.CD009670.pub2.Google Scholar
Travaglini, T. E., Li, L., Brown, C. H., & Bennett, M. E. (2017). Predictors of smoking cessation group treatment engagement among Veterans with serious mental illness. Addictive Behaviors, 75, 103107.Google Scholar
Twyman, L., Bonevski, B., Paul, C., & Bryant, J. (2014). Perceived barriers to smoking cessation in selected vulnerable groups: A systematic review of the qualitative and quantitative literature. BMJ Open, 4 (12), e006414. doi:10.1136/bmjopen-2014-006414.Google Scholar
U.S. Surgeon General's Advisory Committee on Smoking and Health (1964). Smoking and health; Report of the Advisory Committee to the Surgeon General of the Public Health Service. Washington, DC: U.S. Surgeon General's Advisory Committee on Smoking and Health.Google Scholar
Velicer, W. F., Fava, J. L., Prochaska, J. O., Abrams, D. B., Emmons, K. M., & Pierce, J. P. (1995). Distribution of smokers by stage in three representative samples. Preventive Medicine, 24 (4), 401411. doi:10.1006/pmed.1995.1065.Google Scholar
Zhu, S., Melcer, T., Sun, J., Rosbrook, B., & Pierce, J. P. (2000). Smoking cessation with and without assistance: A population-based analysis. American Journal of Preventive Medicine, 18, 305311.Google Scholar