INTERPERSONAL COMMUNICATION AND ...

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Running Head: INTERPERSONAL COMMUNICATION AND SMOKING CESSATION

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Forthcoming in Journal of Health Communication

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Interpersonal Communication and Smoking Cessation in the Context of an Incentive-Based Program: Survey Evidence from a Telehealth Intervention in a Low-Income Population

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Michael J. Parks, PhD1

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Jonathan S. Slater, PhD1,2

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Alexander J. Rothman, PhD2

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Christina L. Nelson, MPH1

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Minnesota Department of Health, Saint Paul, MN, USA 2

University of Minnesota, Minneapolis, MN, USA

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Corresponding author: Michael J. Parks, Minnesota Department of Health, 85 East 7th Street,

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Saint Paul, MN 55164, USA. Email: [email protected] Phone: 651-201-5285.

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Acknowledgements: Project funded through Centers for Disease Control and Prevention

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(American Recovery and Reinvestment Act; Patient Protection and Affordable Care Act). We

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thank QUITPLAN® Helpline staff, Shelly Madigan, Sage patient navigators, Janis Taramelli, and

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Michelle Waste for their efforts. The authors declare that they have no conflict of interest.

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Keywords: smoking cessation; financial incentives; low-income; telehealth; interpersonal communication; population-level interventions

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Abstract

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The tobacco epidemic disproportionately affects low-income populations, and telehealth is an

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evidence-based strategy for extending tobacco cessation services to underserved populations. A

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public health priority is to establish incentive-based interventions at the population level in order

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to promote long-term smoking cessation in low-income populations. Yet randomized clinical

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trials show that financial incentives tend to encourage only short-term steps of cessation, not

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continuous smoking abstinence. One potential mechanism for increasing long-term cessation is

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interpersonal communication (IPC) in response to population-level interventions. However, more

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research is needed on IPC and its influence on health behavior change, particularly in the context

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of incentive-based, population-level programs. This study used survey data gathered after a

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population-level telehealth intervention that offered $20 incentives to low-income smokers for

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being connected to Minnesota’s free quitline in order to examine how perceived incentive

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importance and IPC about the incentive-based program relate to both short-term and long-term

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health behavior change. Results show that IPC was strongly associated with initial quitline

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utilization and continuous smoking abstinence as measured by 30-day point prevalence rates at

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seven-month follow-up. Perceived incentive importance had weak associations with both

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measures of cessation, and all associations were non-significant in models adjusting for IPC.

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These results were found in descriptive analyses, logistic regression models, and Heckman probit

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models that adjusted for participant recruitment. In sum, a behavioral telehealth intervention

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targeting low-income smokers that offered a financial incentive inspired IPC, and this social

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response was strongly related to utilization of intervention services as well as continuous

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smoking abstinence.

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Introduction

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Tobacco use is the leading preventable cause of mortality and morbidity in the U.S. and

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abroad (World Health Organization, 2012). Annually, smoking is estimated to be responsible for

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five million deaths worldwide as it is causally linked to cardiovascular disease and multiple

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forms of cancer (McAfee, Davis, Alexander, Pechacek, & Bunnell, 2013). The tobacco epidemic

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disproportionally affects people of low socioeconomic status. Smoking prevalence among adults

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below the federal poverty level is 28% whereas prevalence at or above poverty level is 17%

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(CDC, 2014). Disproportionately high smoking rates persist among low-income women (Stewart

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et al., 2010), and it is estimated that smoking accounts for up to half of male mortality disparities

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associated with low socioeconomic status in countries such as the U.S. (Jha et al., 2006).

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Consequently, increasing smoking cessation within low socioeconomic groups can save millions

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of lives and decrease mortality disparities (Holford et al., 2014; Jha et al., 2006; Thomas et al.,

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2008).

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There is a critical need to develop population-level smoking cessation programs for low-

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income populations that go beyond clinic-based settings as clinics have limited access to low-

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income populations who underutilize preventive services, are geographically isolated, and

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inadequately insured (see Chokshi & Farley, 2014; Bryant et al., 2011; Wilson, 1987).

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Telehealth, or the use of “telecommunications and information technology to provide access to

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health assessment, diagnosis, intervention, consultation, supervision, education, and information

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across distance” (Nickelson, 1998: 527), is effective for delivering health services to underserved

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and low-income populations (Wootton, Jebamani, & Dow, 2005; McBride & Rimer, 1999). Free

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state telephone tobacco quitlines are exemplars of telehealth’s potential. Free telephone quitlines

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are evidence-based techniques for increasing smoking abstinence rates, particularly in low-

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income and non-White populations (Stead, Perera, & Lancaster, 2007; Burns, Deaton, &

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Levinson, 2011; Fiore et al., 2008), but utilization rates are low across the U.S. (Zhu, Lee,

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Zhuang, Gamst, & Wolfson, 2012).

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Another promising strategy for extending health services to underserved populations is

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financial incentives (Oliver, 2009). Designing incentive-based, population-level interventions in

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order to sustain long-term changes in health behaviors like smoking cessation has become a

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public health priority, particularly in low-income populations (Blumenthal et al., 2013). This is

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exemplified by the Affordable Care Act’s section 4108 and the Centers for Medicare and

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Medicaid Services’ authority to provide grants to states to test the effectiveness of incentives in

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improving health behaviors such as tobacco cessation (Blumenthal et al., 2013: 497-498).

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Financial incentives have been shown to increase health enhancing behaviors (e.g., Slater et al.,

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2005; Gneezy, Meier, & Rey-Biel, 2011), and low-income smokers tend to be responsive to

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incentives (Bryant et al., 2011). However, incentives tend to be effective for encouraging

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preventive care that requires only a single activity or “simple” behavior but not “complex”

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actions that require additional engagement beyond initial intervention services (see Kane,

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Johnson, Town, & Butler, 2004). Smoking cessation requires prolonged engagement (Prochaska,

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DiClemente, & Norcross, 1992), and while incentives can influence short-term cessation in the

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context of a clinical trial (Volpp et al., 2009; Sigmon & Patrick, 2012) less is known about how

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incentives can encourage or be used to promote long-term cessation in population-level

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interventions within low-income populations (Blumenthal et al., 2013).

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Research in behavioral economics demonstrates that financial incentives typically have

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an effect on short-term behavior change through the “direct price effect” that makes incentivized

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behaviors more attractive (Gneezy et al., 2011). The direct price effect is often explained by its

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influence on extrinsic motivation to engage in a target behavior and it tends to be less effective

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for promoting behavior maintenance once incentives are removed. A second type of effect,

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known as the “indirect psychological effect,” can have both positive and negative influences on

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incentivized behaviors (Gneezy et al., 2011: 11). Multiple social and psychological factors can

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alter the effects of a financial incentive presentation in terms of promoting or unintentionally

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discouraging the incentivized behavior (see e.g., Babcock, Bedard, Charness, Hartman, & Royer,

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2011).

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Two specific factors are particularly relevant for population-level interventions, and they

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have implications for both short-term and long-term behavior change. The first is that the

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incentive’s effect depends on the context within which it is presented. If presented in a private

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context within a controlled environment (e.g., randomized clinical trials), social influences are

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limited, such as informal social control or social image processes. Alternatively, incentives

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offered in more public settings can activate social influences (Gneezy et al., 2011). Public

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settings are marked by the presence of others, and this can influence individuals’ behavior by

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inspiring social responses to incentives instead of strictly monetary responses. For example,

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social reactions such as interpersonal discussions about the incentive can activate behavior based

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on social image maintenance or prevailing social norms (Gneezy et al., 2011: 11). A second and

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related factor is that incentives can interact with social networks. Evidenced by past research on

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exercise maintenance, incentives can not only increase exercise, but social groups (e.g., friends)

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who jointly receive incentives are more likely to exhibit long-term behavior maintenance

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(Charness & Gneezy, 2009; Babcock et al., 2011). Addressing the relational context of health

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behaviors through network-oriented strategies has become a priority for prevention programs

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(Gest, Osgood, Feinberg, Bierman, & Moody, 2011), and this is especially true for smoking

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cessation interventions because social dynamics operating within networks strongly influence the

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cessation process (Christakis & Fowler, 2008; Valente, 2010; Burns, Rothman, Fu, Lindgren, &

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Joseph, 2014). Yet less is known about how these social mechanisms may influence long-term

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health behavior change in response to population-level interventions, and particularly incentive-

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based interventions.

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In sum, randomized clinical trials demonstrate that incentive-based interventions can

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encourage short-term behavioral engagement involving an incentivized behavior, and past

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behavioral economic research implies that financial incentives offered in population-level

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interventions can potentially encourage social responses and indirect effects due to the context of

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the intervention. Population-level interventions occur in relatively public settings in conjunction

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with naturally occurring psychosocial dynamics, and these processes could have implications for

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both short-term and long-term behavior change. In terms of long-term behavior change such as

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sustained smoking cessation, a social response to an incentive-based program at the population-

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level could be a marker of naturally occurring social mechanisms that have inherent capacity to

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promote sustained behavioral engagement.

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Past population-level smoking cessation interventions provide empirical support (see e.g.,

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McAfee et al., 2013; Donovan, Boulter, Borland, Jalleh, & Carter, 2003; van den Putte, Yzer,

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Southwell, de Bruijn, & Willemsen, 2011). Smoking cessation programs have demonstrated that

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long-term smoking cessation is indirectly influenced by social reactions measured by

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interpersonal communication about the smoking cessation program (van den Putte, et al., 2011).

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Supported by communication theories (see Katz & Lazarsfeld, 1955; Southwell & Yzer, 2007),

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interpersonal communication about a health promotion or prevention program can catalyze

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mechanisms embedded within social interactions, potentially cultivating intentions to change

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behavior, activating normative pressure, and making health behavior decisions more cognitively

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salient (see e.g., Montano & Kasprzyk, 2008; Southwell, 2013). Yet further examination of

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interpersonal communication and health behavior change in response to population-level

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interventions remains an important gap in research, particularly in the context of incentive-based

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programs (van den Putte, et al., 2011; Southwell, Slater, Nelson, & Rothman, 2012).

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The Current Study

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This paper reports results of a survey conducted after a population-level intervention that

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offered financial incentives to low-income smokers for being connected to Minnesota’s free

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QUITPLAN® Helpline. The survey captured self-report measures of interpersonal

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communication about the incentive-based program as well as perceived importance of the

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incentive for the incentivized behavior (i.e., being connected to a quitline). The analysis focuses

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on the cessation process measured by short-term and long-term behavioral engagement. Using

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North American Quitline Consortium (NAQC) evidence-based measures (see NAQC, 2011) the

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cessation process is measured by (1) initial utilization of quitline services, and (2) continuous

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smoking abstinence measured by 30 consecutive smoke-free days at seven-month follow-up. The

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main focus of the analysis is on how these two measures of the cessation process relate to both

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interpersonal communication and perceived incentive importance.

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Based on past research on the effects of interpersonal communication in response to

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smoking cessation interventions, we hypothesize that interpersonal communication in the context

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of the current incentive-based telehealth intervention will be related to utilization of smoking

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cessation services as well as subsequent efforts to quit smoking (i.e., seven-month follow-up 30-

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day point prevalence rates). This hypothesis is also based on past research demonstrating that

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incentives presented in more public settings can inspire social and psychological mechanisms,

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and that these mechanisms are potentially conducive to long-term behavioral engagement. In

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light of past research on financial incentives and smoking cessation in randomized clinical trials

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as well as the direct price effect of incentives on incentivized behaviors, we note that incentives

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are more likely to influence short-term behavior change rather than long-term smoking cessation.

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Therefore, we hypothesize that perceived incentive importance will relate to initial steps of

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cessation measured by utilization of quitline services, and that perceived incentive importance

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will be less likely to impact continuous smoking abstinence.

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Method Participants and Procedures Intervention context. From September 2010 to September 2012, a behavioral telehealth

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intervention was implemented through Minnesota’s National Breast and Cervical Cancer Early

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Detection Program (NBCCEDP) called “Sage.” Sage serves low-income individuals

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experiencing health-related disparities. Specifically, Sage provides free cancer screening services

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to individuals who are ages 40 years or older, have household incomes at or below 250% of the

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federal poverty level, and are inadequately insured. Unique among NBCCEDPs, Sage has a call

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center staffed by “patient navigators” (see Freund et al., 2008) who are fluent in English and

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other languages relevant for Sage’s target population. More details on NBCCEDPs and Sage

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have been published elsewhere (Lee et al., 2014; Slater et al., 2005).

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Intervention. The current intervention offered a $20 incentive for being connected to

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Minnesota’s QUITPLAN® Helpline (QL) via a three-way phone call conducted by Sage patient

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navigators. Relying on participant-initiated phone contact (see Soet & Basch, 1997), we

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employed two recruitment strategies: (1) a direct mail (DM) campaign and (2) an opportunistic

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referral with connection (ORC) call transfer system from within the Sage Call Center.

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Individuals identified as smokers in Sage’s database were recruited using DM mailers designed

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to prompt cigarette smokers to call Sage’s toll-free phone number. The DM mailers consisted of

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a folded card with emotionally evocative messages and graphics as well as a small insert card

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advertising the financial incentive. The mailers were strategically constructed based on past

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research (see Rothman & Salovey, 1997) and included two rounds of mailings (see Slater et al.,

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2005).

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For ORC recruitment, Sage’s patient navigators obtained the smoking status of

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individuals who called the Sage Call Center for cancer screening information or appointments.

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Callers identified as smokers were then opportunistically presented the QL referral offer (i.e., a

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$20 incentive for being connected to the QL). Patient navigators handled phone calls for both

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intervention groups, and once participants agreed to be transferred, patient navigators put

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participants on hold and called QL operators. Patient navigators then confirmed with QL

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operators that an individual from Sage would be connected to the QL via three-way calls. Once

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QL operators agreed, patient navigators remained on the line until QL operators and intervention

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participants were connected and communication between participants and QL operators was

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confirmed.

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QL services included free smoking cessation telephone counseling with a maximum of

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five sessions within a six-month period. The QL provided self-help materials and free nicotine

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replacement therapy for those who requested them. A total of 5,420 callers were offered the

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intervention from the Sage Call Center (DM=870, ORC=4,550), with 2,456 completing QL

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transfers. Of those transferred, 66% were ORC (N=1,612) compared to DM (N=844).

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Survey data. Participants who completed QL connections were interviewed via

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telephone by trained staff at least seven months after each participant’s QL connection in

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compliance with recommended, evidence-based practices (see NAQC, 2011). All participants

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who completed QL connections were targeted for the survey; 10 call attempts were made before

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participants were deemed unresponsive. A total of 1,218 participants completed the survey.

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Since not all participants were offered QL services after being connected by Sage patient

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navigators, the current analyses focused on individuals who were offered QL services (N=995)

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with complete data, comprising an analytic sample of 970. Individuals not offered services were

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excluded because they were not subsequently asked about smoking cessation in the survey (e.g.,

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utilization of QL services). No significant differences were found between individuals offered

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and not offered services in terms of demographic and smoking characteristics, except for age

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(M=53.7 vs. M=52.2, p=.01). Of those not offered services, about 40% reported it was due to

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their insurance coverage, and 60% reported miscellaneous reasons associated with program

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fidelity (e.g., accidental disconnection after patient navigator transfer, reported not receiving a

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call back from QL).

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Measures. Following past research, two dichotomous outcomes for short- and long-term

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behavioral steps associated with smoking cessation were employed: (1) QL utilization and (2)

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being smoke-free for 30 consecutive days at seven-month follow-up (see NAQC, 2011;

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DiClement et al., 1991). For QL utilization, respondents were asked whether they had used the

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tools and services that were offered from the QL (1=yes, 0=no). For continuous smoking

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abstinence (“continuous cessation”), participants were asked if they had not smoked for 30

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consecutive days (in interviews conducted at least seven months after being connected to the QL)

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(1=yes; 0=no).

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Incentive influence was captured by measuring whether participants reported the

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incentive to be important for their QL connection (1=important, 0=not important).1 Interpersonal

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communication about the incentive-based program was measured as whether or not participants

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“told others about the Sage offer that rewards smokers $20 for being connected with a tobacco

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quitline through the Sage Call Center” (1=yes, 0=no).

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Background characteristics included age, sex, education, race/ethnicity, and smoking

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history. Age was measured in continuous years; sex and race/ethnicity were dichotomous

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measures (1=male, 0=female; 1=white, 0=non-white). Education was an ordinal scale, ranging

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from 1 (completed 8th grade or less) to 6 (graduate school). Smoking characteristics included a

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continuous measure of years smoked, whether or not participants smoked on a daily basis 1

Empirically, we tested the credibility of this measure by comparing answers to the question about how important the incentive was for the individual to an additional question that asked how important the incentive was for the Minnesota Department of Health to get smokers to connect to the QL in general. We created a scale out of the two measures, which had a reliability measure of .901. Results using this alternative measure were not different from main analyses that utilized the dichotomous measure, and therefore we only report the results for the dichotomous measure described here.

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(1=yes, 0=no), whether they lived with a smoker (1=yes, 0=no), whether they made a quit

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attempt in the past with medication (1=yes, 0=no), and whether they were unlikely to contact the

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QL without the current intervention (1=yes, 0=no). Variables used to assess recruitment

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differences were (1) a dichotomous measure for DM vs ORC, and (2) a measure of whether the

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participant had past involvement with Sage (1=Sage, 0=non-Sage). Approximately 65% of the

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analytic sample was recruited via ORC (ORC=629; DM=341), and 62% had previous contact

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with Sage.

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Analytic strategy. The first set of analyses of the analytic sample of surveyed

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respondents consisted of descriptive statistics and cross-tabulations. These descriptive analyses

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focused on bivariate relationships for (1) both cessation outcomes and interpersonal

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communication, and (2) both cessation outcomes and incentive importance. We then explored

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these relationships more systematically via logistic regression models for each dichotomous

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outcome. It is important to note that DM and ORC recruitment groups likely differed in their

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behavioral stage or “readiness” in terms of smoking cessation. This is because the DM group

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called Sage seeking smoking cessation services whereas the ORC group called regarding

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unrelated health matters and were unexpectedly offered cessation services. As a result, we ran

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logistic regression models that included a dummy variable for DM versus ORC group

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membership, as well as supplementary analyses that consisted of a sub-sample analysis that

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adjusted for differences between DM and ORC groups in terms of their likelihood of group

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membership (see Heckman, 1979; Bushway, Johnson, & Slocum, 2007).

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The supplementary analysis consisted of maximum likelihood bivariate probit with selection models (Heckman probit models). In Heckman probit models, recruitment groups were

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used as a bivariate selection criterion (DM vs. ORC)—“outcome” models in Heckman probit

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models censored unobserved objects from the “selection” model (i.e., ORC individuals). This

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generated an analysis of QL utilization and 30-day point prevalence quit status for a subgroup

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potentially more prepared for smoking cessation (i.e., DM) while adjusting for the likelihood of

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DM membership (see Puhani, 2000; Bushway et al., 2007). Outcome models are presented in

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table form and within the text, but selection models are not reported (selection models included

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all variables in outcome models except for an exclusion restriction variable). Multivariate

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logistic regression and Heckman probit models were run in Stata, version 12. Cluster-adjusted

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robust standard errors were used in both logistic regression and Heckman probit models in order

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to account for clustering within patient navigators as well as for heteroscedasticity (Bushway et

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al., 2007).

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Results Participants Participant characteristics are detailed in Table 1. The analytic sample was

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overwhelmingly low-income female smokers because low-income, inadequately insured women

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are Sage’s target population. It included a limited number of males primarily as a result of

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information sharing about the intervention.

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The sample was primarily White (75%); 15% were African American, 5% were Native

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American, 2% were Hispanic, and the remaining were other races or ethnicities (3%), providing

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evidence that the intervention disproportionately reached racial and ethnic minorities in

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Minnesota (U.S. Census Bureau, 2012), which is also Sage’s target population. Average

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education level was a high school diploma or equivalent. About 12% of the sample did not

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complete high school and all individuals met income guidelines for receiving Sage services,

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reflecting the relatively low socioeconomic status of the sample.

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The majority of participants were intense smokers. Years smoked was normally

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distributed with an average of 30.94. Over 50% had made a quit attempt with medication in the

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past, 94% smoked every day, and about 38% lived with a smoker. Most participants were

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unlikely to have contacted a QL without having been reached with the current intervention

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(72%).

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[TABLE 1 ABOUT HERE] Survey Results Of the surveyed participants who were offered QL services, 643 individuals (66%) were

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connected to the QL and utilized the services, such as receiving telephone counseling or self-help

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materials. In terms of 30-day point prevalence quit rates, about 19% reported continuous

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cessation seven months after QL connection (184 individuals). About 50% engaged in

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interpersonal communication about the incentive-based program (IPC), and almost 69% noted

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the incentive was important for their QL connection (see Table 1).

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QL utilization. The associations between QL utilization and IPC, and between utilization

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and incentive importance, are displayed in the left-hand portion of Table 2. Interpersonal

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communication about the incentive-based program was associated with QL utilization (2=32.32;

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p