Top

Gepubliceerd in:

19-07-2018

Predictors of engagement in post-discharge quitline counseling among hospitalized smokers

Auteurs: Taneisha S. Scheuermann, Kristopher J. Preacher, Beatriz H. Carlini, Terry Bush, Brooke Magnusson, Niaman Nazir, Kimber P. Richter

Gepubliceerd in: Journal of Behavioral Medicine | Uitgave 1/2019

Abstract

Quitlines provide evidence-based tobacco treatment and multiple calls yield higher quit rates. This study aimed to identify subgroups of smokers with greater quitline engagement following referral during hospitalization. Data were from a randomized clinical trial assessing the effectiveness of fax referral (referral faxed to proactive quitline) versus warm handoff (patient connected to quitline at bedside) (n = 1054). Classification and regression trees analyses evaluated individual and treatment/health system-related variables and their interactions. Among all participants, warm handoff, higher ratings of the tobacco treatment care transition, and being older predicted completing more quitline calls. Among patients enrolled in the quitline, higher transition of care ratings, being older, and use of cessation medication post-discharge predicted completing more calls. Three of the four factors influencing engagement were characteristics of treatment within the hospital (quality of tobacco treatment care transition and referral method) and therapy (use of cessation medications), suggesting potential targets to increase quitline engagement post-discharge.

vorige artikel Are sleep hygiene practices related to the incidence, persistence and remission of insomnia? Findings from a prospective community study

volgende artikel Early socioeconomic adversity and cardiometabolic risk in young adults: mediating roles of risky health lifestyle and depressive symptoms

Alleen toegankelijk voor geautoriseerde gebruikers

Adams, S. T., & Leveson, S. H. (2012). Clinical prediction rules. BMJ, 344, d8312. https://doi.org/10.1136/bmj.d8312 CrossRefPubMed

An, L. C., Schillo, B. A., Kavanaugh, A. M., Lachter, R. B., Luxenberg, M. G., Wendling, A. H., et al. (2006). Increased reach and effectiveness of a statewide tobacco quitline after the addition of access to free nicotine replacement therapy. Tobacco Control, 15, 286–293. https://doi.org/10.1136/tc.2005.014555 CrossRefPubMedPubMedCentral

Bentz, C. J., Bayley, K. B., Bonin, K. E., Fleming, L., Hollis, J. F., & McAfee, T. (2006). The feasibility of connecting physician offices to a state-level tobacco quit line. American Journal of Preventive Medicine, 30, 31–37. https://doi.org/10.1016/j.amepre.2005.08.043 CrossRefPubMed

Bernstein, S. L., Weiss, J.-M., Toll, B., & Zbikowski, S. M. (2016). Association between utilization of quitline services and probability of tobacco abstinence in low-income smokers. Journal of Substance Abuse Treatment, 71, 58–62. https://doi.org/10.1016/j.jsat.2016.08.014 CrossRefPubMedPubMedCentral

Burns, E. K., Levinson, A. H., & Deaton, E. A. (2012). Factors in nonadherence to quitline services: Smoker characteristics explain little. Health Education and Behavior, 39, 596–602. https://doi.org/10.1177/1090198111425186 CrossRefPubMed

Bush, K., Kivlahan, D. R., McDonell, M. B., Fihn, S. D., & Bradley, K. A. (1998). The AUDIT alcohol consumption questions (AUDIT-C): An effective brief screening test for problem drinking. Archives of Internal Medicine, 158, 1789–1795. https://doi.org/10.1001/archinte.158.16.1789 CrossRefPubMed

Calvocoressi, L., Stolar, M., Kasl, S. V., Claus, E. B., & Jones, B. A. (2005). Applying recursive partitioning to a prospective study of factors associated with adherence to mammography screening guidelines. American Journal of Epidemiology, 162, 1215–1224. https://doi.org/10.1093/aje/kwi337 CrossRefPubMed

Coleman, E. A., & Berenson, R. A. (2004). Lost in transition: Challenges and opportunities for improving the quality of transitional care. Annals of Internal Medicine, 141, 533–599.CrossRefPubMed

Coleman, E. A., Mahoney, E., & Parry, C. (2005). Assessing the quality of preparation for posthospital care from the patient’s perspective: The care transitions measure. Medical Care, 43, 246–255.CrossRefPubMed

Coleman, E. A., Smith, J. D., Frank, J. C., Eilertsen, T. B., Thiare, J. N., & Kramer, A. M. (2002). Development and testing of a measure designed to assess the quality of care transitions. International Journal of Integrated Care, 2, e02.PubMedPubMedCentral

Critchley, J. A., & Capewell, S. (2003). Mortality risk reduction associated with smoking cessation in patients with coronary heart disease: A systematic review. JAMA, 290, 86–97. https://doi.org/10.1001/jama.290.1.86 CrossRefPubMed

de Leon, J., Diaz, F. J., Becona, E., Gurpegui, M., Jurado, D., & Gonzalez-Pinto, A. (2003). Exploring brief measures of nicotine dependence for epidemiological surveys. Addictive Behaviors, 28, 1481–1486.CrossRefPubMed

Dominick, G. M., Papas, M. A., Rogers, M. L., & Rakowski, W. (2015). Classification tree analysis to examine influences on colorectal cancer screening. Cancer Causes and Control, 26, 443–454. https://doi.org/10.1007/s10552-015-0523-6 CrossRefPubMed

Faseru, B., Turner, M., Casey, G., Ruder, C., Befort, C. A., Ellerbeck, E. F., et al. (2011). Evaluation of a hospital based tobacco treatment service: Outcomes and lessons learned. Journal of Hospital Medicine, 6, 211–218. https://doi.org/10.1002/jhm.835 CrossRefPubMed

Fiore, M. C., Goplerud, E., & Schroeder, S. A. (2012). The joint commission’s new tobacco-cessation measures—will hospitals do the right thing? New England Journal of Medicine, 366, 1172–1174.CrossRefPubMed

Gaalema, D. E., Savage, P. D., Rengo, J. L., Cutler, A. Y., Elliott, R. J., Priest, J. S., et al. (2017). Patient characteristics predictive of cardiac rehabilitation adherence. Journal of Cardiopulmonary Rehabilitation and Prevention, 37, 103–110. https://doi.org/10.1097/hcr.0000000000000225 CrossRefPubMedPubMedCentral

Hollis, J. F., McAfee, T. A., Fellows, J. L., Zbikowski, S. M., Stark, M., & Riedlinger, K. (2007). The effectiveness and cost effectiveness of telephone counselling and the nicotine patch in a state tobacco quitline. Tobacco Control, 16, i53–i59. https://doi.org/10.1136/tc.2006.019794 CrossRefPubMedPubMedCentral

King, M. W., & Resick, P. A. (2014). Data mining in psychological treatment research: A primer on classification and regression trees. Journal of Consulting and Clinical Psychology, 82, 895–905. https://doi.org/10.1037/a0035886 CrossRefPubMed

Kroenke, K., Spitzer, R. L., & Williams, J. B. (2003). The patient health questionnaire-2: Validity of a two-item depression screener. Medical Care, 41, 1284–1292. https://doi.org/10.1097/01.MLR.0000093487.78664.3C CrossRefPubMed

Lemon, S. C., Roy, J., Clark, M. A., Friedmann, P. D., & Rakowski, W. (2003). Classification and regression tree analysis in public health: Methodological review and comparison with logistic regression. Annals of Behavioral Medicine, 26, 172–181. https://doi.org/10.1207/s15324796abm2603_02 CrossRefPubMed

Leuthard, J. L., Beebe, L. A., Halstead, L., Olson, K. D., & Roysdon, J. W. (2015). Increased evidence-based tobacco treatment through Oklahoma hospital system changes. American Journal of Preventive Medicine, 48, S65–S70. https://doi.org/10.1016/j.amepre.2014.09.017 CrossRefPubMed

Loh, W.-Y., Piper, M. E., Schlam, T. R., Fiore, M. C., Smith, S. S., Jorenby, D. E., et al. (2012). Should all smokers use combination smoking cessation pharmacotherapy? Using novel analytic methods to detect differential treatment effects over 8 weeks of pharmacotherapy. Nicotine & Tobacco Research, 14, 131–141. https://doi.org/10.1093/ntr/ntr147 CrossRef

Merkle, E. C., & Shaffer, V. A. (2011). Binary recursive partitioning: background, methods, and application to psychology. British Journal of Mathematical and Statistical Psychology, 64, 161–181. https://doi.org/10.1348/000711010X503129 CrossRefPubMed

North American Quitline Consortium. (2011). Moving quitlines forward: North American quitline consortium 2008/2009 annual report. Retrieved from Oakland, CA.

Parsons, A., Daley, A., Begh, R., & Aveyard, P. (2010). Influence of smoking cessation after diagnosis of early stage lung cancer on prognosis: Systematic review of observational studies with meta-analysis. BMJ, 340, b5569. https://doi.org/10.1136/bmj.b5569 CrossRefPubMedPubMedCentral

Piper, M. E., Loh, W. Y., Smith, S. S., Japuntich, S. J., & Baker, T. B. (2011). Using decision tree analysis to identify risk factors for relapse to smoking. Substance Use and Misuse, 46, 492–510. https://doi.org/10.3109/10826081003682222 CrossRefPubMed

R Core Team. (2015). R: A language and environment for statistical computing. Vienna, Austria: R Foundation. Retrieved from https://www.r-project.org/

Richter, K. P., Faseru, B., Mussulman, L. M., Ellerbeck, E. F., Shireman, T. I., Hunt, J. J., et al. (2012). Using “warm handoffs” to link hospitalized smokers with tobacco treatment after discharge: study protocol of a randomized controlled trial. Trials, 13, 127.CrossRefPubMedPubMedCentral

Richter, K. P., Faseru, B., Shireman, T. I., Mussulman, L. M., Nazir, N., Bush, T., et al. (2016). Warm handoff versus fax referral for linking hospitalized smokers to quitlines. American Journal of Preventive Medicine, 51, 587–596. https://doi.org/10.1016/j.amepre.2016.04.006 CrossRefPubMedPubMedCentral

Rigotti, N. A., Clair, C., Munafo, M. R., & Stead, L. F. (2012). Interventions for smoking cessation in hospitalised patients. Cochrane Database Systematic Review, 5, Cd001837. https://doi.org/10.1002/14651858.CD001837.pub3 CrossRef

Sabaté, E. (Ed.). (2003). Adherence to long-term therapies: Evidence for action Geneva. Switzerland: World Health Organization.

Shi, Y., & Warner, D. O. (2010). Surgery as a teachable moment for smoking cessation. Anesthesiology, 112, 102–107. https://doi.org/10.1097/ALN.0b013e3181c61cf9 CrossRefPubMed

Skov-Ettrup, L. S., Dalum, P., Ekholm, O., & Tolstrup, J. S. (2014). Reach and uptake of Internet- and phone-based smoking cessation interventions: results from a randomized controlled trial. Preventive Medicine, 62, 38–43. https://doi.org/10.1016/j.ypmed.2014.01.020 CrossRefPubMed

Swan, G. E., Jack, L. M., Javitz, H. S., McAfee, T., & McClure, J. B. (2008). Predictors of 12-month outcome in smokers who received bupropion sustained-release for smoking cessation. CNS Drugs, 22, 239–256.CrossRefPubMed

Swan, G. E., Javitz, H. S., Jack, L. M., Curry, S. J., & McAfee, T. (2004). Heterogeneity in 12 month outcome among female and male smokers. Addiction, 99, 237–250.CrossRefPubMed

Therneau, T., & Atkinson, E. (2018). An introduction to recursive partitioning using the RPART routines. Division of Biostatistics, Mayo Foundation. Retrieved from https://cran.r-project.org/web/packages/rpart/vignettes/longintro.pdf

Therneau, T., Atkinson, B., & Ripley, B. (2015). rpart: Recursive partitioning and regression trees, 2014 (Version 4.1-8). Retrieved from Available at CRAN. R-project. org/package = rpart

United Kingdom Small Aneurysm Trial Participants. (2002). Long-term outcomes of immediate repair compared with surveillance of small abdominal aortic aneurysms. New England Journal of Medicine, 346, 1445–1452. https://doi.org/10.1056/NEJMoa013527 CrossRef

Venkatasubramaniam, A., Wolfson, J., Mitchell, N., Barnes, T., JaKa, M., & French, S. (2017). Decision trees in epidemiological research. Emerging Themes in Epidemiology, 14, 11. https://doi.org/10.1186/s12982-017-0064-4 CrossRefPubMedPubMedCentral

Warner, D. O., Nolan, M. B., Kadimpati, S., Burke, M. V., Hanson, A. C., & Schroeder, D. R. (2016). Quitline tobacco interventions in hospitalized patients: A randomized trial. American Journal of Preventive Medicine. https://doi.org/10.1016/j.amepre.2016.03.005 CrossRefPubMed

Ylioja, T., Reddy, V., Ambrosino, R., Davis, E. M., Douaihy, A., Slovenkay, K., et al. (2017). Using bioinformatics to treat hospitalized smokers: Successes and challenges of a tobacco treatment service. The Joint Commission Journal on Quality and Patient Safety, 43, 621–632. https://doi.org/10.1016/j.jcjq.2017.06.010 CrossRefPubMed

Zbikowski, S. M., Hapgood, J., Smucker Barnwell, S., & McAfee, T. (2008). Phone and web-based tobacco cessation treatment: Real-world utilization patterns and outcomes for 11,000 tobacco users. Journal of Medical Internet Research, 10, e41. https://doi.org/10.2196/jmir.999 CrossRefPubMedPubMedCentral

Zbikowski, S. M., Jack, L. M., McClure, J. B., Deprey, M., Javitz, H. S., McAfee, T. A., et al. (2011). Utilization of services in a randomized trial testing phone- and web-based interventions for smoking cessation. Nicotine & Tobacco Research, 13, 319–327. https://doi.org/10.1093/ntr/ntq257 CrossRef

Zhu, S. H., Stretch, V., Balabanis, M., Rosbrook, B., Sadler, G., & Pierce, J. P. (1996). Telephone counseling for smoking cessation: Effects of single-session and multiple-session interventions. Journal of Consulting and Clinical Psychology, 64, 202–211.CrossRefPubMed

Titel: Predictors of engagement in post-discharge quitline counseling among hospitalized smokers
Auteurs: Taneisha S. Scheuermann
Kristopher J. Preacher
Beatriz H. Carlini
Terry Bush
Brooke Magnusson
Niaman Nazir
Kimber P. Richter
Publicatiedatum: 19-07-2018
Uitgeverij: Springer US
Gepubliceerd in: Journal of Behavioral Medicine / Uitgave 1/2019
Print ISSN: 0160-7715
Elektronisch ISSN: 1573-3521
DOI: https://doi.org/10.1007/s10865-018-9951-6

Bohn Stafleu van Loghum

Deel dit onderdeel of sectie (kopieer de link)

Abstract

Log in om toegang te krijgen

Andere artikelen Uitgave 1/2019

Key milestones during 40 years of behavioral medicine at the National Institutes of Health

The role of group cohesion in a group-based behavioral weight loss intervention

Introduction to the special series—behavioral medicine at 40: origins, achievements, and future directions

Historical perspective on behavioral medicine’s success in bringing different disciplines to the table

Translating behavioral medicine evidence to public policy

The history and future of digital health in the field of behavioral medicine