Addictive Behaviors 39 (2014) 717–720
Contents lists available at ScienceDirect
Addictive Behaviors
Short Communication
Small financial incentives increase smoking cessation in homeless smokers: A pilot study Michael S. Businelle a,b,⁎, Darla E. Kendzor a,b, Anshula Kesh a, Erica L. Cuate a, Insiya B. Poonawalla a, Lorraine R. Reitzel c, Kolawole S. Okuyemi d, David W. Wetter e a
University of Texas Health Science Center School of Public Health, 5323 Harry Hines Blvd., Dallas, TX, 75390, USA University of Texas Southwestern Harold C. Simmons Comprehensive Cancer Center, Population Science and Cancer Control Program, 5323 Harry Hines Blvd., Dallas, TX, 75390, USA c University of Houston, Department of Educational Psychology, 491 Farish Hall, Houston, TX, 77204-5029, USA d University of Minnesota, Family Medicine and Community Health, 717 Delaware St SE, Ste 166, Minneapolis, MN, 55414, USA e University of Texas MD Anderson Cancer Center, Department of Health Disparities Research, PO Box 301402, Unit 1440, Houston, TX, 77230, USA b
H I G H L I G H T S • Small financial incentives for smoking cessation in homeless smokers were examined. • Compared to usual care, incentives increased biologically verified abstinence. • This adjunctive treatment may increase cessation success in homeless smokers.
a r t i c l e
i n f o
Keywords: Homeless Smoking cessation Financial incentives Contingency management
a b s t r a c t Although over 70% of homeless individuals smoke, few studies have examined the effectiveness of smoking cessation interventions in this vulnerable population. The purpose of this pilot study was to compare the effectiveness of shelter-based smoking cessation clinic usual care (UC) to an adjunctive contingency management (CM) treatment that offered UC plus small financial incentives for smoking abstinence. Sixty-eight homeless individuals in Dallas, Texas (recruited in 2012) were assigned to UC (n = 58) or UC plus financial incentives (CM; n = 10) groups and were followed for 5 consecutive weeks (1 week pre-quit through 4 weeks postquit). A generalized linear mixed model regression analysis was conducted to compare biochemically-verified abstinence rates between groups. An additional model examined the interaction between time and treatment group. The participants were primarily male (61.8%) and African American (58.8%), and were 49 years of age on average. There was a significant effect of treatment group on abstinence overall, and effects varied over time. Follow-up logistic regression analyses indicated that CM participants were significantly more likely than UC participants to be abstinent on the quit date (50% vs. 19% abstinent) and at 4 weeks post-quit (30% vs. 1.7% abstinent). Offering small financial incentives for smoking abstinence may be an effective way to facilitate smoking cessation in homeless individuals. © 2013 Elsevier Ltd. All rights reserved.
1. Introduction Although the prevalence of smoking has declined to 19.3% among U.S. adults, over 70% of homeless individuals currently smoke (Baggett & Rigotti, 2010; Centers for Disease Control and Prevention, 2012; Lee et al., 2005; Sachs-Ericsson, Wise, Debrody, & Paniucki, 1999). The high smoking prevalence among homeless individuals is a major contributor to their higher rates of disease, shorter life expectancies, and high health care costs (Arnsten, Reid, Bierer, & Rigotti, 2004; Butler ⁎ Corresponding author at: University of Texas School of Public Health, 6011 Harry Hines Blvd., V8.112, Dallas, TX, 75390-9128. Tel.: +1 214 648 1070; fax: +1 214 648 1081. E-mail address: [email protected] (M.S. Businelle). 0306-4603/$ – see front matter © 2013 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.addbeh.2013.11.017
et al., 2002; Hwang & Henderson, 2010; Hwang et al., 2009). Unfortunately, very little is known about smoking cessation in this population (Okuyemi, Thomas, et al., 2006). Research has indicated that over 70% of homeless smokers plan to make a cessation attempt within the next six months (Butler et al., 2002; Okuyemi, Caldwell, et al., 2006) and have similar numbers of cessation attempts compared to the general population of smokers (Butler et al., 2002). However, only a handful of studies have evaluated the efficacy of smoking cessation interventions in homeless smokers (Bonevski, Baker, Twyman, Paul, & Bryant, 2012; Okuyemi et al., 2013; Shelley et al., 2010; Spector, Alpert, & Karam-Hage, 2007). Most of these studies had very small samples (i.e., 10 to 58 participants) and abstinence rates were low. The most recent and largest study examining smoking cessation in homeless smokers
718
M.S. Businelle et al. / Addictive Behaviors 39 (2014) 717–720
compared 6-sessions of motivational interviewing to a brief cessation advice condition (Okuyemi et al., 2013). All participants received 8 weeks of nicotine replacement therapy. Abstinence rates at the 6 month follow-up visit were not significantly different between groups (9.3% vs. 5.6%). More research is needed to develop effective smoking cessation interventions for homeless smokers. Many studies have demonstrated that the tangible reinforcement (e.g., money, prizes) of abstinence (i.e., contingency management [CM]) increases smoking cessation rates (Dunn et al., 2010; Heil et al., 2008; Tevyaw et al., 2009; Volpp et al., 2006, 2009). However, studies have yet to evaluate the CM approach for smoking cessation among the homeless. Plausibly, the CM approach would hold particular appeal for homeless individuals who possess few monetary resources. The primary objective of this pilot study was to compare the outcomes of usual shelter-based smoking cessation clinic care (i.e., support groups + cessation medication) to an adjunctive contingency management intervention that reinforced biochemically-verified abstinence with low-value gift cards.
All the participants were instructed to quit smoking by 10:00 p.m. on the night before their quit date visit. Thus, abstinent participants had a minimum of 13 h of smoking abstinence when assessed during the quit date visit. On the quit date, participants were considered abstinent if they self-reported abstinence from smoking (not even a puff) since 10:00 p.m. the evening prior and had an expired carbon monoxide level of b 10 ppm. On weeks 1, 2, 3, and 4 post-quit, the participants were considered abstinent if they self-reported abstinence from smoking (not even a puff) during the previous 7 days and had an expired carbon monoxide levels of b8 ppm. Those who did not attend a visit were considered non-abstinent at that visit.
2. Methods
2.5. Statistical analyses
2.1. Sample and procedure
Analysis of variance (ANOVA) and x2 tests were used to identify baseline differences between the treatment groups. Given the dependency of repeated abstinence measurements nested within participants (Singer & Willett, 2003), a generalized linear mixed model (GLMM) regression analysis (McCulloch & Searle, 2001) was used to evaluate the overall impact of treatment on abstinence. An additional GLMM evaluated whether the effect of treatment varied over time (via the addition of a treatment group × time interaction term). Follow-up
Participants were recruited from a homeless shelter in Texas. Individuals were eligible to participate if they were ≥18 years of age, had N6th grade reading level (assessed via the Rapid Estimate of Adult Literacy in Medicine; Davis et al., 1991), smoked ≥5 cigarettes per day, had a carbon monoxide level ≥ 8 parts per million (ppm) at baseline, and were able to attend 6 weekly assessment sessions (i.e., baseline [1 week pre-quit], quit date, and weeks 1, 2, 3, and 4 post-quit). Enrollment in the shelter-based smoking cessation program and residence in the transitional shelter were required for study participation. Smokers interested in quitting were referred to the shelter-based smoking cessation program by shelter staff. Individuals who attended the orientation visit for the smoking cessation program were provided with detailed information about the current study and were given the opportunity to ask questions prior to enrollment. Informed consent was obtained from all interested individuals. 2.2. Interventions Participants who enrolled in the study from January 11, 2012 through October 17, 2012 were assigned to the Usual Care group, and those who enrolled between October 18, 2012 and November 7, 2012 were assigned to the Usual Care + Contingency Management group (CM). Usual Tobacco Clinic Care (UC) at the shelter is consistent with the recommendations of the Clinical Practice Guideline (Fiore et al., 2008) and included weekly smoking cessation therapy/support groups (approximately 45 min each) and access to smoking cessation medications when prescribed by the on-site physician. CM participants had the opportunity to earn a $20 gift card for biochemically-verified abstinence on the quit date. An escalating reinforcement schedule was used to encourage continuous abstinence (Roll et al., 2006), such that the amount of gift card payments increased by $5 with each consecutive week of abstinence (i.e., up to $40 at 4 weeks post-quit). Non-abstinent participants were able to earn incentives at the next visit if abstinence criteria were met, but the gift card payment was reset to the starting level (i.e., $20). Contingent financial incentives were distributed during assessment visits. 2.3. Assessments The participants were compensated for completing 4 of the 6 study assessment visits (i.e., baseline, quit date, week 1 post-quit, and week 4 post-quit). Participants were not paid for completing the brief (i.e., 5 min) week 2 and week 3 post-quit assessment visits. Demographic
(e.g., age, gender, race/ethnicity), smoking (e.g., years of smoking, cigarettes smoked per day, heaviness of smoking index; Borland, Yong, O'Connor, Hyland, & Thompson, 2010), and homelessness characteristics were assessed at the baseline visit (see Table 1). 2.4. Abstinence
Table 1 Baseline participant characteristics. Variable
Demographic characteristics Age⁎ Male Race/ethnicity⁎ Black White Hispanic More than 1 race Married or Partnered Years of Education REALM Family income past year Uninsured⁎ Homelessness characteristics Age first time homeless Separate homeless occasions Lifetime homelessness (months) Reasons for homelessness (% yes) Job Loss Eviction Substance abuse Mental illness Medical bills Family problems Legal problems Natural disaster Other Smoking characteristics Cigarettes per day Years smoking Lifetime quit attempts ≥24 h Smoke menthol cigarettes (% yes) Heaviness of Smoking Index
Usual Care % or CM % or M M (SD) (SD) (n = 58) (n = 10)
Total % or M (SD) (N = 68)
50.0 (7.7) 65.5%
44.3 (11.1) 40%
49.2 (8.4) 61.8%
55.2% 34.5% 3.4% 6.9% 13.8% 12.5 (2.0) 61.8 (4.9) $1520 ($2856) 87.9%
80.0% 0.0% 10.0% 10.0% 10.0% 12.2 (0.6) 62.4 (3.7) $1922 ($2211) 60.0%
58.8% 30.9% 4.4% 10.3% 13.2% 12.4 (1.9) 61.9 (4.7) $1577 ($2761) 83.8%
41.1 (12.6) 3.5 (7.1) 37.0 (44.3)
33.3 (14.1) 3.5 (2.3) 39.0 (26.3)
40.0 (13.1) 3.5 (6.6) 37.3 (42.0)
41.1% 34.5% 29.3% 36.2% 6.9% 39.7% 13.8% 1.7% 20.7%
50.0% 20% 40% 30% 0.0% 40% 0.0% 0.0% 30.0%
42.6% 32.4% 30.9% 35.3% 5.9% 39.7% 11.8% 1.5% 22.1%
18.1 (10.6) 29.3 (10.6) 4.2 (3.3) 51.7% 2.9 (1.4)
15.5 (5.1) 29.9 (12.6) 2.7 (1.6) 80.0% 3.3 (1.5)
17.7 (10.0) 29.4 (10.8) 4.0 (3.1) 55.9% 3.0 (1.5)
REALM: Rapid Estimate of Adult Literacy in Medicine; CM: Contingency Management. ⁎ ANOVA or chi square analyses indicated significant group differences at the p b .05 level.
M.S. Businelle et al. / Addictive Behaviors 39 (2014) 717–720
bivariate logistic regression analyses examined treatment effects at each follow-up visit separately (i.e., quit date, and weeks 1, 2, 3, and 4) to better understand variations in the treatment effects over time. Logistic regression analyses controlled for age, gender, race/ethnicity, and insurance status and GLMM models additionally controlled for time. Analyses were conducted using SAS version 9.3 (SAS Institute, Cary, NC). 3. Results Of the 99 individuals who were screened, 68 qualified and were enrolled (UC, n = 58; CM, n = 10). Participant characteristics are presented in Table 1. Over the 5 week study period, the participants attended 30% of the possible 6 treatment counseling sessions. The UC group attended significantly more treatment sessions as compared to the CM group (1.9 vs. 1.1; p = .030). Meeting with the clinic physician for a medication consultation (all participants were encouraged to do this) and self-reported medication use was examined. By the 1 week follow-up visit, 51% of all the participants had met with the clinic physician and were prescribed medication to aid with smoking cessation and 37% of the participants who were prescribed medication reported taking their medication as prescribed. There were no significant group differences in the number of participants who met with the clinic physician or self-reported medication compliance. Attendance rates at assessment visits ranged from 96% (quit date and 1 week post-quit) to 75% (week 2 post-quit). There were no differences in assessment visit attendance rates by treatment group. 3.1. Post-quit smoking status GLMM analyses indicated that, controlling for time, age, gender, race/ethnicity, and insurance status, the CM group was more likely to be abstinent at the follow up visits than those assigned to the UC group (AOR = 0.097; 95% CI = 0.014, 0.660, p = .018). Importantly, a separate, fully adjusted, GLMM analysis indicated that the group by time interaction was significant (p = .035). To determine if intent to treat smoking abstinence rates differed by treatment group at each of the post-quit visits, multiple logistic regression analyses were conducted. All analyses controlled for age, gender, race/ethnicity, and insurance status. Compared to the CM participants, the UC participants were less likely to be abstinent on their quit date (50% abstinent vs. 19%; AOR = 0.119; 95% CI = 0.019, 0.743, p = .022) and week 4 post-quit visits (30% abstinent vs. 1.7% abstinent; AOR = 0.032; 95% CI = 0.001, 0.932, p = .045). Abstinence rates were not significantly different at the week 1, 2, or 3 visits. Fig. 1 displays biochemically confirmed point prevalence abstinence rates for the treatment groups. On average, CM
719
participants earned $42 (±$47) for smoking abstinence across the 5 post-quit visits (range = $0 to $150). 4. Discussion Smoking prevalence is very high among homeless individuals, yet few studies have examined the effectiveness of smoking cessation interventions in this vulnerable population. The goal of this pilot study was to demonstrate the potential utility of adding small incentives for smoking cessation to the usual care offered at a shelter-based smoking cessation clinic. Results indicated that individuals who were assigned to the CM group were more likely to be abstinent on the quit date and at the 4 week post-quit follow-up visit than those assigned to UC. Thus, CM may be a cost-effective way (i.e., CM group members received an average of $42 in abstinence contingent financial incentives across the 5 post-quit visits) to increase smoking cessation success in this vulnerable, underserved, and understudied population of smokers. Overall, quit rates were discouraging among those who received the usual smoking cessation clinic care (i.e., 1.7% were abstinent at the 1 month follow-up). Other studies of smoking cessation interventions for homeless smokers have demonstrated slightly better cessation outcomes than those reported in the current study (Burling, Burling, & Latini, 2001; Okuyemi et al., 2013; Shelley et al., 2010). There are likely multiple reasons for this difference. For example, individuals in the current study had to wait in long lines to see the clinic physician, and take a shuttle to the pharmacy to fill their smoking cessation medication prescriptions. These barriers likely reduced interest in obtaining smoking cessation medications in many patients. Given that the current sample of homeless smokers resided in the transitional shelter and was on site on a daily basis, identifying ways to better integrate cessation services into daily living might be particularly useful in increasing cessation success in this population. Examples might include making smoking cessation medications available at the shelter, offering group medication checks with the clinic physician, and holding cessation classes in the evening. The findings of this pilot study are tempered by the small sample size, short follow-up period, and significant baseline differences between treatment groups. Although analyses controlled for baseline group differences, groups may have differed on other unmeasured, but substantive variables. In addition, participants were recruited from a single transitional homeless shelter. Thus, results may not generalize to other homeless populations. Finally, the non-randomized design used in this study (i.e., the first 58 subjects received UC and the next 10 subjects received CM) may further limit generalizability of the results. Future studies should examine the effectiveness of offering financial incentives for smoking cessation in a larger sample of homeless smokers who are followed for a longer period of time and randomized
60
*
CM
50
% Abstinent
UC 40
* 30 20 10 0 Quit Date
Week +1
Week +2
Week +3
Week +4
Fig. 1. Carbon monoxide confirmed abstinence rates for Usual Care (UC) and Contingency Management (CM) groups. * indicates p b .05.
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to treatment groups in order to determine if the observed treatment effects can be repeated and sustained beyond the 1 month follow-up period. Nonetheless, the results of the current study suggest that CM may be a very promising treatment approach among a very vulnerable, high risk population. In conclusion, the present study is the first to demonstrate the utility of adjunctive financial incentives for smoking abstinence in homeless smokers seeking cessation treatment. Small incentives may help sheltered homeless smokers to overcome the overwhelming barriers to cessation that are commonly experienced by this group (e.g., exposure to over 40 smokers each day (Businelle, Cuate, Kesh, Poonawalla, & Kendzor, 2013)). Offering small financial incentives for smoking abstinence may be an effective way to reduce the prevalence of smoking in homeless individuals, thereby improving the overall health and life expectancy of this population. Role of funding sources This work was supported by the University of Texas School of Public Health. The data analysis and manuscript preparation were additionally supported through American Cancer Society grants MRSGT-12-114-01-CPPB (to MSB) and MRSGT-10-104-01-CPHPS (to DEK). The funding sources had no role in the study design, collection, analysis or interpretation of the data, writing the manuscript, or the decision to submit the paper for publication.
Contributors Dr. Businelle designed the parent study and led the data analyses and manuscript preparation. Drs. Kendzor, Reitzel, Okuyemi, and Wetter assisted with the study conceptualization and manuscript preparation. Erica Cuate, Anshula Kesh, and Insiya Poonawalla led the data collection and helped to draft the manuscript. All the authors have read and approved the final draft of the manuscript.
Conflict of Interest The authors declare no conflicts of interest pertaining to this work.
Acknowledgments We thank the staff at the Bridge Homeless Assistance Center for their work and support throughout the data collection portion of this project. In addition, we thank Jay Dunn (Bridge CEO) and Neil Phillips (Bridge smoking cessation program coordinator and counselor) for their notable efforts that enabled this research. We would like to thank Nga Nguyen for her advice on the statistical analyses.
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Contents lists available at ScienceDirect
Addictive Behaviors
Short Communication
Small financial incentives increase smoking cessation in homeless smokers: A pilot study Michael S. Businelle a,b,⁎, Darla E. Kendzor a,b, Anshula Kesh a, Erica L. Cuate a, Insiya B. Poonawalla a, Lorraine R. Reitzel c, Kolawole S. Okuyemi d, David W. Wetter e a
University of Texas Health Science Center School of Public Health, 5323 Harry Hines Blvd., Dallas, TX, 75390, USA University of Texas Southwestern Harold C. Simmons Comprehensive Cancer Center, Population Science and Cancer Control Program, 5323 Harry Hines Blvd., Dallas, TX, 75390, USA c University of Houston, Department of Educational Psychology, 491 Farish Hall, Houston, TX, 77204-5029, USA d University of Minnesota, Family Medicine and Community Health, 717 Delaware St SE, Ste 166, Minneapolis, MN, 55414, USA e University of Texas MD Anderson Cancer Center, Department of Health Disparities Research, PO Box 301402, Unit 1440, Houston, TX, 77230, USA b
H I G H L I G H T S • Small financial incentives for smoking cessation in homeless smokers were examined. • Compared to usual care, incentives increased biologically verified abstinence. • This adjunctive treatment may increase cessation success in homeless smokers.
a r t i c l e
i n f o
Keywords: Homeless Smoking cessation Financial incentives Contingency management
a b s t r a c t Although over 70% of homeless individuals smoke, few studies have examined the effectiveness of smoking cessation interventions in this vulnerable population. The purpose of this pilot study was to compare the effectiveness of shelter-based smoking cessation clinic usual care (UC) to an adjunctive contingency management (CM) treatment that offered UC plus small financial incentives for smoking abstinence. Sixty-eight homeless individuals in Dallas, Texas (recruited in 2012) were assigned to UC (n = 58) or UC plus financial incentives (CM; n = 10) groups and were followed for 5 consecutive weeks (1 week pre-quit through 4 weeks postquit). A generalized linear mixed model regression analysis was conducted to compare biochemically-verified abstinence rates between groups. An additional model examined the interaction between time and treatment group. The participants were primarily male (61.8%) and African American (58.8%), and were 49 years of age on average. There was a significant effect of treatment group on abstinence overall, and effects varied over time. Follow-up logistic regression analyses indicated that CM participants were significantly more likely than UC participants to be abstinent on the quit date (50% vs. 19% abstinent) and at 4 weeks post-quit (30% vs. 1.7% abstinent). Offering small financial incentives for smoking abstinence may be an effective way to facilitate smoking cessation in homeless individuals. © 2013 Elsevier Ltd. All rights reserved.
1. Introduction Although the prevalence of smoking has declined to 19.3% among U.S. adults, over 70% of homeless individuals currently smoke (Baggett & Rigotti, 2010; Centers for Disease Control and Prevention, 2012; Lee et al., 2005; Sachs-Ericsson, Wise, Debrody, & Paniucki, 1999). The high smoking prevalence among homeless individuals is a major contributor to their higher rates of disease, shorter life expectancies, and high health care costs (Arnsten, Reid, Bierer, & Rigotti, 2004; Butler ⁎ Corresponding author at: University of Texas School of Public Health, 6011 Harry Hines Blvd., V8.112, Dallas, TX, 75390-9128. Tel.: +1 214 648 1070; fax: +1 214 648 1081. E-mail address: [email protected] (M.S. Businelle). 0306-4603/$ – see front matter © 2013 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.addbeh.2013.11.017
et al., 2002; Hwang & Henderson, 2010; Hwang et al., 2009). Unfortunately, very little is known about smoking cessation in this population (Okuyemi, Thomas, et al., 2006). Research has indicated that over 70% of homeless smokers plan to make a cessation attempt within the next six months (Butler et al., 2002; Okuyemi, Caldwell, et al., 2006) and have similar numbers of cessation attempts compared to the general population of smokers (Butler et al., 2002). However, only a handful of studies have evaluated the efficacy of smoking cessation interventions in homeless smokers (Bonevski, Baker, Twyman, Paul, & Bryant, 2012; Okuyemi et al., 2013; Shelley et al., 2010; Spector, Alpert, & Karam-Hage, 2007). Most of these studies had very small samples (i.e., 10 to 58 participants) and abstinence rates were low. The most recent and largest study examining smoking cessation in homeless smokers
718
M.S. Businelle et al. / Addictive Behaviors 39 (2014) 717–720
compared 6-sessions of motivational interviewing to a brief cessation advice condition (Okuyemi et al., 2013). All participants received 8 weeks of nicotine replacement therapy. Abstinence rates at the 6 month follow-up visit were not significantly different between groups (9.3% vs. 5.6%). More research is needed to develop effective smoking cessation interventions for homeless smokers. Many studies have demonstrated that the tangible reinforcement (e.g., money, prizes) of abstinence (i.e., contingency management [CM]) increases smoking cessation rates (Dunn et al., 2010; Heil et al., 2008; Tevyaw et al., 2009; Volpp et al., 2006, 2009). However, studies have yet to evaluate the CM approach for smoking cessation among the homeless. Plausibly, the CM approach would hold particular appeal for homeless individuals who possess few monetary resources. The primary objective of this pilot study was to compare the outcomes of usual shelter-based smoking cessation clinic care (i.e., support groups + cessation medication) to an adjunctive contingency management intervention that reinforced biochemically-verified abstinence with low-value gift cards.
All the participants were instructed to quit smoking by 10:00 p.m. on the night before their quit date visit. Thus, abstinent participants had a minimum of 13 h of smoking abstinence when assessed during the quit date visit. On the quit date, participants were considered abstinent if they self-reported abstinence from smoking (not even a puff) since 10:00 p.m. the evening prior and had an expired carbon monoxide level of b 10 ppm. On weeks 1, 2, 3, and 4 post-quit, the participants were considered abstinent if they self-reported abstinence from smoking (not even a puff) during the previous 7 days and had an expired carbon monoxide levels of b8 ppm. Those who did not attend a visit were considered non-abstinent at that visit.
2. Methods
2.5. Statistical analyses
2.1. Sample and procedure
Analysis of variance (ANOVA) and x2 tests were used to identify baseline differences between the treatment groups. Given the dependency of repeated abstinence measurements nested within participants (Singer & Willett, 2003), a generalized linear mixed model (GLMM) regression analysis (McCulloch & Searle, 2001) was used to evaluate the overall impact of treatment on abstinence. An additional GLMM evaluated whether the effect of treatment varied over time (via the addition of a treatment group × time interaction term). Follow-up
Participants were recruited from a homeless shelter in Texas. Individuals were eligible to participate if they were ≥18 years of age, had N6th grade reading level (assessed via the Rapid Estimate of Adult Literacy in Medicine; Davis et al., 1991), smoked ≥5 cigarettes per day, had a carbon monoxide level ≥ 8 parts per million (ppm) at baseline, and were able to attend 6 weekly assessment sessions (i.e., baseline [1 week pre-quit], quit date, and weeks 1, 2, 3, and 4 post-quit). Enrollment in the shelter-based smoking cessation program and residence in the transitional shelter were required for study participation. Smokers interested in quitting were referred to the shelter-based smoking cessation program by shelter staff. Individuals who attended the orientation visit for the smoking cessation program were provided with detailed information about the current study and were given the opportunity to ask questions prior to enrollment. Informed consent was obtained from all interested individuals. 2.2. Interventions Participants who enrolled in the study from January 11, 2012 through October 17, 2012 were assigned to the Usual Care group, and those who enrolled between October 18, 2012 and November 7, 2012 were assigned to the Usual Care + Contingency Management group (CM). Usual Tobacco Clinic Care (UC) at the shelter is consistent with the recommendations of the Clinical Practice Guideline (Fiore et al., 2008) and included weekly smoking cessation therapy/support groups (approximately 45 min each) and access to smoking cessation medications when prescribed by the on-site physician. CM participants had the opportunity to earn a $20 gift card for biochemically-verified abstinence on the quit date. An escalating reinforcement schedule was used to encourage continuous abstinence (Roll et al., 2006), such that the amount of gift card payments increased by $5 with each consecutive week of abstinence (i.e., up to $40 at 4 weeks post-quit). Non-abstinent participants were able to earn incentives at the next visit if abstinence criteria were met, but the gift card payment was reset to the starting level (i.e., $20). Contingent financial incentives were distributed during assessment visits. 2.3. Assessments The participants were compensated for completing 4 of the 6 study assessment visits (i.e., baseline, quit date, week 1 post-quit, and week 4 post-quit). Participants were not paid for completing the brief (i.e., 5 min) week 2 and week 3 post-quit assessment visits. Demographic
(e.g., age, gender, race/ethnicity), smoking (e.g., years of smoking, cigarettes smoked per day, heaviness of smoking index; Borland, Yong, O'Connor, Hyland, & Thompson, 2010), and homelessness characteristics were assessed at the baseline visit (see Table 1). 2.4. Abstinence
Table 1 Baseline participant characteristics. Variable
Demographic characteristics Age⁎ Male Race/ethnicity⁎ Black White Hispanic More than 1 race Married or Partnered Years of Education REALM Family income past year Uninsured⁎ Homelessness characteristics Age first time homeless Separate homeless occasions Lifetime homelessness (months) Reasons for homelessness (% yes) Job Loss Eviction Substance abuse Mental illness Medical bills Family problems Legal problems Natural disaster Other Smoking characteristics Cigarettes per day Years smoking Lifetime quit attempts ≥24 h Smoke menthol cigarettes (% yes) Heaviness of Smoking Index
Usual Care % or CM % or M M (SD) (SD) (n = 58) (n = 10)
Total % or M (SD) (N = 68)
50.0 (7.7) 65.5%
44.3 (11.1) 40%
49.2 (8.4) 61.8%
55.2% 34.5% 3.4% 6.9% 13.8% 12.5 (2.0) 61.8 (4.9) $1520 ($2856) 87.9%
80.0% 0.0% 10.0% 10.0% 10.0% 12.2 (0.6) 62.4 (3.7) $1922 ($2211) 60.0%
58.8% 30.9% 4.4% 10.3% 13.2% 12.4 (1.9) 61.9 (4.7) $1577 ($2761) 83.8%
41.1 (12.6) 3.5 (7.1) 37.0 (44.3)
33.3 (14.1) 3.5 (2.3) 39.0 (26.3)
40.0 (13.1) 3.5 (6.6) 37.3 (42.0)
41.1% 34.5% 29.3% 36.2% 6.9% 39.7% 13.8% 1.7% 20.7%
50.0% 20% 40% 30% 0.0% 40% 0.0% 0.0% 30.0%
42.6% 32.4% 30.9% 35.3% 5.9% 39.7% 11.8% 1.5% 22.1%
18.1 (10.6) 29.3 (10.6) 4.2 (3.3) 51.7% 2.9 (1.4)
15.5 (5.1) 29.9 (12.6) 2.7 (1.6) 80.0% 3.3 (1.5)
17.7 (10.0) 29.4 (10.8) 4.0 (3.1) 55.9% 3.0 (1.5)
REALM: Rapid Estimate of Adult Literacy in Medicine; CM: Contingency Management. ⁎ ANOVA or chi square analyses indicated significant group differences at the p b .05 level.
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bivariate logistic regression analyses examined treatment effects at each follow-up visit separately (i.e., quit date, and weeks 1, 2, 3, and 4) to better understand variations in the treatment effects over time. Logistic regression analyses controlled for age, gender, race/ethnicity, and insurance status and GLMM models additionally controlled for time. Analyses were conducted using SAS version 9.3 (SAS Institute, Cary, NC). 3. Results Of the 99 individuals who were screened, 68 qualified and were enrolled (UC, n = 58; CM, n = 10). Participant characteristics are presented in Table 1. Over the 5 week study period, the participants attended 30% of the possible 6 treatment counseling sessions. The UC group attended significantly more treatment sessions as compared to the CM group (1.9 vs. 1.1; p = .030). Meeting with the clinic physician for a medication consultation (all participants were encouraged to do this) and self-reported medication use was examined. By the 1 week follow-up visit, 51% of all the participants had met with the clinic physician and were prescribed medication to aid with smoking cessation and 37% of the participants who were prescribed medication reported taking their medication as prescribed. There were no significant group differences in the number of participants who met with the clinic physician or self-reported medication compliance. Attendance rates at assessment visits ranged from 96% (quit date and 1 week post-quit) to 75% (week 2 post-quit). There were no differences in assessment visit attendance rates by treatment group. 3.1. Post-quit smoking status GLMM analyses indicated that, controlling for time, age, gender, race/ethnicity, and insurance status, the CM group was more likely to be abstinent at the follow up visits than those assigned to the UC group (AOR = 0.097; 95% CI = 0.014, 0.660, p = .018). Importantly, a separate, fully adjusted, GLMM analysis indicated that the group by time interaction was significant (p = .035). To determine if intent to treat smoking abstinence rates differed by treatment group at each of the post-quit visits, multiple logistic regression analyses were conducted. All analyses controlled for age, gender, race/ethnicity, and insurance status. Compared to the CM participants, the UC participants were less likely to be abstinent on their quit date (50% abstinent vs. 19%; AOR = 0.119; 95% CI = 0.019, 0.743, p = .022) and week 4 post-quit visits (30% abstinent vs. 1.7% abstinent; AOR = 0.032; 95% CI = 0.001, 0.932, p = .045). Abstinence rates were not significantly different at the week 1, 2, or 3 visits. Fig. 1 displays biochemically confirmed point prevalence abstinence rates for the treatment groups. On average, CM
719
participants earned $42 (±$47) for smoking abstinence across the 5 post-quit visits (range = $0 to $150). 4. Discussion Smoking prevalence is very high among homeless individuals, yet few studies have examined the effectiveness of smoking cessation interventions in this vulnerable population. The goal of this pilot study was to demonstrate the potential utility of adding small incentives for smoking cessation to the usual care offered at a shelter-based smoking cessation clinic. Results indicated that individuals who were assigned to the CM group were more likely to be abstinent on the quit date and at the 4 week post-quit follow-up visit than those assigned to UC. Thus, CM may be a cost-effective way (i.e., CM group members received an average of $42 in abstinence contingent financial incentives across the 5 post-quit visits) to increase smoking cessation success in this vulnerable, underserved, and understudied population of smokers. Overall, quit rates were discouraging among those who received the usual smoking cessation clinic care (i.e., 1.7% were abstinent at the 1 month follow-up). Other studies of smoking cessation interventions for homeless smokers have demonstrated slightly better cessation outcomes than those reported in the current study (Burling, Burling, & Latini, 2001; Okuyemi et al., 2013; Shelley et al., 2010). There are likely multiple reasons for this difference. For example, individuals in the current study had to wait in long lines to see the clinic physician, and take a shuttle to the pharmacy to fill their smoking cessation medication prescriptions. These barriers likely reduced interest in obtaining smoking cessation medications in many patients. Given that the current sample of homeless smokers resided in the transitional shelter and was on site on a daily basis, identifying ways to better integrate cessation services into daily living might be particularly useful in increasing cessation success in this population. Examples might include making smoking cessation medications available at the shelter, offering group medication checks with the clinic physician, and holding cessation classes in the evening. The findings of this pilot study are tempered by the small sample size, short follow-up period, and significant baseline differences between treatment groups. Although analyses controlled for baseline group differences, groups may have differed on other unmeasured, but substantive variables. In addition, participants were recruited from a single transitional homeless shelter. Thus, results may not generalize to other homeless populations. Finally, the non-randomized design used in this study (i.e., the first 58 subjects received UC and the next 10 subjects received CM) may further limit generalizability of the results. Future studies should examine the effectiveness of offering financial incentives for smoking cessation in a larger sample of homeless smokers who are followed for a longer period of time and randomized
60
*
CM
50
% Abstinent
UC 40
* 30 20 10 0 Quit Date
Week +1
Week +2
Week +3
Week +4
Fig. 1. Carbon monoxide confirmed abstinence rates for Usual Care (UC) and Contingency Management (CM) groups. * indicates p b .05.
720
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to treatment groups in order to determine if the observed treatment effects can be repeated and sustained beyond the 1 month follow-up period. Nonetheless, the results of the current study suggest that CM may be a very promising treatment approach among a very vulnerable, high risk population. In conclusion, the present study is the first to demonstrate the utility of adjunctive financial incentives for smoking abstinence in homeless smokers seeking cessation treatment. Small incentives may help sheltered homeless smokers to overcome the overwhelming barriers to cessation that are commonly experienced by this group (e.g., exposure to over 40 smokers each day (Businelle, Cuate, Kesh, Poonawalla, & Kendzor, 2013)). Offering small financial incentives for smoking abstinence may be an effective way to reduce the prevalence of smoking in homeless individuals, thereby improving the overall health and life expectancy of this population. Role of funding sources This work was supported by the University of Texas School of Public Health. The data analysis and manuscript preparation were additionally supported through American Cancer Society grants MRSGT-12-114-01-CPPB (to MSB) and MRSGT-10-104-01-CPHPS (to DEK). The funding sources had no role in the study design, collection, analysis or interpretation of the data, writing the manuscript, or the decision to submit the paper for publication.
Contributors Dr. Businelle designed the parent study and led the data analyses and manuscript preparation. Drs. Kendzor, Reitzel, Okuyemi, and Wetter assisted with the study conceptualization and manuscript preparation. Erica Cuate, Anshula Kesh, and Insiya Poonawalla led the data collection and helped to draft the manuscript. All the authors have read and approved the final draft of the manuscript.
Conflict of Interest The authors declare no conflicts of interest pertaining to this work.
Acknowledgments We thank the staff at the Bridge Homeless Assistance Center for their work and support throughout the data collection portion of this project. In addition, we thank Jay Dunn (Bridge CEO) and Neil Phillips (Bridge smoking cessation program coordinator and counselor) for their notable efforts that enabled this research. We would like to thank Nga Nguyen for her advice on the statistical analyses.
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