Preventive Medicine 69 (2014) 126–131

Contents lists available at ScienceDirect

Preventive Medicine

j ourna l homepage: www.e lsev ie r .com/ locate /ypmed

Predictors of cessation treatment outcome and treatment moderatorsamong smoking parents receiving quitline counselling orself-help material

Kathrin Schuck a,⁎, Roy Otten a, Marloes Kleinjan a, Jonathan B. Bricker b,c, Rutger C.M.E. Engels a,d

a Behavioural Science Institute, Radboud University Nijmegen, Montessorilaan 3, P.O. Box 9104, 6500 HE Nijmegen, The Netherlandsb Fred Hutchinson Cancer Research Center, 1100 Fairview Avenue, P.O. Box 19024, Seattle, WA 98109, USAc University of Washington, Department of Psychology, P.O. Box 351525, Seattle, WA 98195, USAd Trimbos Institute, Netherlands National Institute of Mental Health and Addiction, PO Box 725, 3500 AS Utrecht, The Netherlands

⁎ Corresponding author at: Radboud University Nijme9104, 6500 HE Nijmegen, The Netherlands. Fax: +31 24 3

E-mail address: k.schuck@bsi.ru.nl (K. Schuck).

http://dx.doi.org/10.1016/j.ypmed.2014.09.0140091-7435/© 2014 Elsevier Inc. All rights reserved.

a b s t r a c t

a r t i c l e i n f o

Available online 30 September 2014

Keywords:Smoking cessationQuitline supportQuitline counsellingSelf-helpTreatment outcomePredictorsModerators

Objective. Several cessation treatments effectively enhance cessation, but it is not always clear which treat-ment may be most suitable for a particular client. We examined predictors of treatment outcome and treatmentmoderators among smoking parents in the Netherlands.

Method. We conducted secondary analyses of a randomized controlled trial in which smoking parents re-ceived either quitline counselling (n = 256) or a self-help brochure (n = 256). Data collection was completedin October 2012. Endpoints were 7-day point prevalence abstinence and 6-month prolonged abstinence at 12-month follow-up. Potential predictors and moderators included socio-demographic characteristics, smoking-related variables, and child-related variables.

Results.Male gender, higher employment status, lower daily cigarette consumption, higher levels of confi-

dence in quitting, presence of a child with a chronic respiratory illness, and wanting to quit for the health ofone's child predicted abstinence at 12 months. Significant treatment moderators were intention to quit and ed-ucational level. Quitline counselling was effective regardless of intention to quit and educational level, but self-help material was less effective among less motivated and lower educated parents.

Conclusion. Certain subgroups of smokers, such as parents who are concerned about the health of their child,are particularly receptive to cessation support. Individual characteristics should be considered in treatmentselections.

© 2014 Elsevier Inc. All rights reserved.

Introduction

Connecting smokers to effective cessation services is a public healthpriority. Smoking parents constitute a high-priority population,accounting for 20–40% of adult smokers (Hitchman et al., 2011; Ottenet al., 2005; Schuck et al., 2012;Winickoff et al., 2006). Tobacco smokingis detrimental, not only to the parent, but also to the child who isexposed to second-hand smoke and who is at an increased risk ofsmoking initiation in adolescence (DiFranza et al., 2004; Leonardi-Beeet al., 2011). Parents who quit smoking will not only improve theirown health, but also reduce the risk of their children's physical illness(Halterman et al., 2004), smoking initiation (Otten et al., 2007), andregular smoking (Bricker et al., 2003).

Research suggests that smoking parents may be particularlymotivated to quit (Halterman et al., 2010; Hitchman et al., 2011;

gen, Montessorilaan 3, Postbus612776.

Winickoff et al., 2003a). Offering cessation support to smoking parentsin ‘teachable settings’ such as paediatric clinics, birth clinics, andphysician offices can engage a high proportion of parents (Winickoffet al., 2003a). A variety of interventions have demonstrated efficacy inincreasing parental smoking cessation and decreasing exposure toparental second-hand smoke among children (Rosen et al., 2012). Werecently reported results from a randomized controlled trial whichcompared the effectiveness of intensive quitline counselling to astandard self-help brochure in enhancing smoking cessation ratesamong smoking parents (Schuck et al., 2014). High abstinence rateswere observed in both conditions (34% vs. 18% at 12 months offollow-up). Intensive quitline counselling was significantly moreeffective than standard self-help material (OR = 2.35, CI = 1.56–3.54). Recent trials have also shown high abstinence rates amongsmokers receiving quitline counselling (Ferguson et al., 2012; Smithet al., 2013). The abstinence rates observed among smoking parents inthe present trial were comparable to the abstinence rates observedamong inpatients with a smoking-related illness who were offeredquitline counselling following hospital admission (Smith et al., 2013).

127K. Schuck et al. / Preventive Medicine 69 (2014) 126–131

Yet, the majority of smokers attempt cessation with minimal assistance(Shiffman et al., 2008). A meta-analytic review concluded that self-helpmaterials have a small benefit compared with no intervention(Lancaster and Stead, 2005). Therefore, self-help materials mayconstitute a less intensive treatment alternative to support otherwiseunaided quit attempts, which can be easily distributed and may bemore readily used than more intensive interventions.

To improve the effectiveness of available cessation treatments,treatment selections should be guided by knowledge about whichtreatment is likely to yield the greatest efficacy. Currently, treatmentselections in clinical trials and clinical practice are usually based onrandom allocation or patient preference and do not routinely considerindividual characteristics of the client. Up to this point, researchinvestigating moderators of outcome (i.e., pre-treatment variables thatpredict treatment outcome) among evidence-based smoking cessationtreatments is scarce. To match clients to the optimal treatment, morework is needed to understand general predictors of treatment outcomeas well as treatment moderators. General predictors of treatment out-come clarify which subgroups of clients will respond more or lessfavourably to treatment in general. Treatment moderators can identifysubgroups of clients who are likely to benefit more from one treatmentthan another (Wolitzky-Taylor et al., 2012).

In this study, we compared two treatment modalities delivered tothe population segment of smoking parents: intensive quitline counsel-ling versus a standard self-help brochure. Both intervention modalitieshave demonstrated efficacy (Lancaster and Stead, 2005; Stead et al.,2013) and are characterized by potentially high reach, thus yieldinghigh potential public health impact (Glasgow et al., 1999). Bothtreatments are based on principles from cognitive–behaviour therapy.In addition, quitline counselling also included the use of MotivationalInterviewing (MI), which is a client-centred and directive method toenhance intrinsic motivation for behavioural change (Miller, 2002).While standard self-help materials may be an easy-to-disseminate,low-threshold treatment for smokers who display a high readiness toquit and high levels of self-efficacy, intensive quitline counseling maybe particularly beneficial among smokers who are ambivalent aboutquitting or who are not yet ready to quit.

We examined potential general outcome predictors and treatmentmoderators using established predictors of smoking cessation (e.g., keysocio-demographic variables and smoking-related variables) (Gwaltneyet al., 2009; Hymowitz et al., 1997; Rose et al., 1996; Schnoll et al.,2011; Tzelepis et al., 2013). In addition, we also examined the role ofchild-related variables (e.g., child health). Previous research indicatedthat certain subgroups of clients (e.g., smokers with a tobacco-related ill-ness, smokers living with children) show greater improvement in onetreatment compared to another (Strecher et al., 2006). The aim of thisstudy was to examine whether key socio-demographic characteristics,smoking-related characteristics, and child-related characteristics consti-tute general predictors of treatment outcome or treatment moderatorsamong smoking parents receiving cessation support (quitline counsellingor self-help material).

Methods

Trial design

The present study was a two-arm randomized, controlled trial conductedamong smoking parents. The study is registered in the Netherlands Trial Regis-ter (NTR2707), the full study protocol is publicly available (Schuck et al. 2011),and the primary outcomes of the trial have been published in accordance withthe Consolidated Standards of Reporting Trials (CONSORT) (Schuck et al.,2014). The baseline measurement took place between January and July 2011(participants completed a questionnaire via a website or on paper). After thebaseline assessment, parentswere randomly assigned to either the quitline con-dition (n = 256) or the self-help condition (n = 256). Within two weeks afterthe baseline assessment, parents were either called to schedule the firstcounselling call or they received the self-help brochure. The follow-up

measurement took place twelve months after start of the intervention. A totalof 219 participants (85.5%) and 235 participants (91.8%) completed thefollow-up in the quitline condition and in the self-help condition, respectively(p = .03).

Participants and procedure

Smoking parents were recruited through primary schools across theNetherlands. Participants were daily or weekly smokers and parents orcaretakers of a child between 9 and 12 years old. They were considering quit-ting smoking (currently or in the future) and provided informed consent forstudy participation. A total of 512 smoking parents participated. Full reports ofthe study design and the recruitment method are published elsewhere(Schuck et al., 2011, 2013, 2014).

Measures

Potential moderators at baseline

Socio-demographic variables. These variables included age, gender, education(low, medium, high), marital status (never married, married, divorced/widowed), and employment status (unemployed, casually employed, part-time employed, full-time) employed.

Smoking-related variables. These variables included the number of cigarettessmoked per day, years of smoking, nicotine dependence level (FTND;Fagerstrom and Furberg, 2008), past quit attempt (never, ever, in past12 months), intention to quit (Hitchman et al., 2011), current smoking statusof partner (smoker, non-smoker), and presence of a chronic respiratory illnesssuch as asthma (no, yes). Also, confidence in quitting and importance of quittingwere assessed on a ten-point scale.

Child-related variables. These variables included the number of children living inthe household, the presence of a chronic respiratory illness such as asthma inchild (no, yes), and wanting to quit for the health of the child (no, yes).

Treatment condition

Intensive quitline counselling. Participants in the quitline counselling conditionreceived up to seven counsellor-initiated phone calls (i.e., one 30-minute intakecall and up to six additional 10-minute calls) across a period of three months.Counselling calls were conducted by counsellors of the Dutch national quitline.To support the initiation and maintenance of abstinence, emphasis was put oncognitive–behavioural skill building. To increase the participant's intrinsicmoti-vation to quit smoking, emphasis was put on techniques fromMI (Miller, 2002).Use of nicotine replacement therapy (NRT) or pharmacotherapy (varenicline,buprobrion) was recommended if participants smoked ten cigarettes per dayor more. All participants in the quitline counselling condition also receivedthree accompanying booklets titled Smoke-free parents, which were designedfor this study as tailored supplementarymaterials and included ‘parent-relevantinformation’ (e.g., effects of SHS on children). For further details, see Schucket al. (2014).

Self-help brochure. Participants received a 40-page, colour-printed self-helpbrochure including didactic information on nicotine dependence and the healthbenefits associatedwith quitting smoking, tips and advice onhow to initiate andmaintain abstinence, instruction in the use of cognitive and behavioural skills toavoid triggers to smoke and cope with urges to smoke, and strategies formanaging a lapse or relapse to smoking. Also, information on the use of NRTand pharmacotherapy was provided.

Outcome measuresEndpoints were 7-day point prevalence abstinence at 12-months assess-

ment (measured as ‘Have you smoked during the past seven days, even a singlepuff?’ and ‘Have you used any other form of tobacco during the past sevendays?’) and 6-months prolonged abstinence at 12-months assessment (definedas 7-day point prevalence abstinence and report of abstinence for a period of atleast six months). In accordance with the Russell Standard criteria, loss tofollow-up was classified as current smoking (West et al., 2005).

128 K. Schuck et al. / Preventive Medicine 69 (2014) 126–131

Statistical analyses

Statistical analyses were conducted using SPSS 19. To identify generalpredictors of treatment effectiveness among smoking parents, we used astepwise regression procedure (i.e., predictors were entered into a bivariatelogistic regression model at a time and included in the multivariate logisticregression model if statistically significant). To identify treatment-specificmoderators, we conducted moderation analyses using hierarchical logisticregression. Treatment conditionwas entered on thefirst step, the putativemod-erator was entered on the second step, and the interaction term between treat-ment condition and the putative moderator was entered on the third step.Statistical analysis of moderators was performed following the guidelines ofKraemer and colleagues (Kraemer et al., 2002) for evaluating moderators oftreatment-effects in randomized trials.

Results

Descriptive statistics at baseline

Table 1 displays descriptive statistics for all potential predictors/moderators at baseline. No significant differences between the quitlinecondition and the self-help brochure condition were observed on anyof these variables. Previous research showed that treatment adherence

Table 1Descriptive statistics for all potential baseline predictors.

Characteristics Totalsample

Quitlinecounselling

Self-helpbrochure

p

Socio-demographicAge (M, SD) 42.2 (5.4) 42.3 (5.6) 42.0 (5.1) .59Gender (%)

Female 52.5 51.2 53.9 .54Education (%)

Low 15.2 16.4 14.1Medium 56.6 56.3 57.0High 26.2 25.4 27.0 .74

Employment status (%)Unemployed 15.8 14.5 17.2Casual 3.5 3.9 3.1Part time 37.5 35.2 39.8Full time 43.0 46.5 39.5 .38

Marital status (%)Never married 12.5 12.9 12.1Married 67.6 67.6 67.6Divorced/widowed 19.7 19.5 19.9 .97

Smoking-relatedCigarettes per day (M, SD) 16.2 (7.8) 15.7 (8.0) 16.8 (7.7) .14Years of smoking (M, SD) 24.9 (7.7) 25.1 (7.4) 24.6 (8.0) .43FTND score (M, SD) 4.0 (2.4) 4.0 (2.4) 4.0 (2.4) .80Quit attempt (%)

Never 4.7 4.3 5.1Ever, but not in past year 59.6 57.8 61.3In past year 35.7 37.9 33.6 .58

Intention to quit (%)Not within twelve months 9.8 10.9 8.6Within twelve months 23.4 20.3 26.6Within six months 33.0 35.2 30.9Within one month 33.6 33.6 33.6 .31

Partner smoking (%)Yes 33.4 30.9 35.9 .20

Confidence in quitting (0–10) 6.1 (2.0) 6.1 (1.9) 6.1 (2.0) .82Importance of quitting (0–10) 8.9 (1.6) 8.9 (1.5) 8.9 (1.6) .98Chronic respiratory illness

Yes 7.8 7.0 8.6 .51

Child-relatedChronic respiratory illness child (%)

Yes 14.6 14.5 14.8 .90Number of children in household(M, SD)

2.2 (0.7) 2.2 (0.7) 2.2 (0.7) .66

Wanting to quit for child (%)Yes 85.0 87.1 82.8 .18

Note. FTND = Fagerström Test for Nicotine Dependence.

was high in both treatment conditions. Of smokers allocated to quitlinecounselling, 88% accepted at least one counselling call. The averagenumber of calls taken was high (5.7 out of 7 calls). Of smokers allocatedto receive self-help material, 84% read at least some parts of the bro-chure (Schuck et al., 2013). Previous research showed that 48% of thestudy participants receiving telephone counselling reported use ofNRT compared to 21% of the study participants receiving the self-helpbrochure (Schuck et al., 2014).

Abstinence at follow-up

In the quitline condition, 87 participants (34.0%) reported 7-daypoint prevalence abstinence at follow-up and 60 participants (23.4%)reported 6-months prolonged abstinence at follow-up. In the self-help, 46 participants (18.0%) reported 7-day point prevalenceabstinence at follow-up and 15 participants (5.9%) reported 6-monthsprolonged abstinence at follow-up (Schuck et al., 2014).

General predictors of 7-day point prevalence abstinence and 6-monthprolonged abstinence at 12-months of follow-up

Table 2 displays the effects of potential predictors of outcome on 7-day point prevalence abstinence and prolonged abstinence at12 months of assessment. In the multivariate model predicting 7-daypoint prevalence abstinence, gender (OR = 1.60, CI = 1.04–2.46),number of cigarettes smoked per day (OR = 0.94, CI = 0.90–0.98),intention to quit (OR = 1.32, CI = 1.03–2.46), confidence in beingable to quit (OR = 1.14, CI = 1.00–1.29), presence of a child with achronic respiratory illness (OR = 1.91, CI = 1.09–3.34), and wantingto quit for the health of the child (OR = 2.55, CI = 1.19–5.48) weresignificant outcome predictors across treatment conditions. In themultivariate model predicting prolonged abstinence, employmentstatus (OR = 1.32, CI = 1.00–1.73), number of cigarettes smoked perday (OR = 0.93, CI = 0.88–0.98), presence of a child with a chronicrespiratory illness (OR = 2.14, CI = 1.17–3.92), and wanting to quitfor the health of the child (OR= 2.74, CI= 1.04–7.22) were significantoutcome predictors across treatment conditions.1

Treatment moderators of 7-day point prevalence abstinence and 6-monthprolonged abstinence at 12 months of follow-up

Table 3 displays the effects of potential predictors of outcome on 7-day point prevalence abstinence and prolonged abstinence at 12-months assessment for the quitline counselling condition and the self-help brochure condition. In the prediction of 7-day point prevalenceabstinence, there was a significant interaction between treatment con-dition and educational level (OR = .36, CI = .18–.71, p b .01). In thequitline counselling condition, educational level was not predictive ofabstinence (OR= .78, CI = .52–1.16). In the self-help condition, highereducational level was associated with an increased likelihood of absti-nence (OR = 2.15, CI = 1.25–3.68). Also, there was a significant inter-action between treatment condition and intention to quit (OR = 0.62,CI = 0.38–1.00, p = .05). In the quitline counselling condition, inten-tion to quit was not predictive of abstinence (OR = 1.26, CI = 0.96–1.65). In the self-help condition, higher intention to quit was associatedwith an increased likelihood of abstinence (OR= 2.03, CI= 1.37–3.02).In the prediction of prolonged abstinence, there was a marginallysignificant interaction between treatment condition and intention toquit (OR = 0.53, CI = 0.27-1.03). In the quitline counselling condition,

1 When controlling for the effect of using NRT or pharmacotherapy, the significance ofthe reported effects remained the same, except for two instances. First, the effect of genderin the prediction of 7-day point prevalence abstinence changed from significant to mar-ginally significant (OR = 1.51, CI = .96–2.36, p = .07). Second, the effect of wanting toquit for the health of the child in the prediction of prolonged abstinence changed from sig-nificant to marginally significant (OR = 2.56, CI = .96–6.80, p = .06).

Table 2Odd ratios (OR) and 95% confidence intervals (CI) of baseline characteristics on 7-day point prevalence abstinence and 6-months prolonged abstinence at 12 months of follow-up mea-surement among smoking parents.

Baseline characteristics 7-day point-prevalence abstinence 6-Monts prolonged abstinence

Crude Model Crude Model

Socio-demographicAge 1.01 (0.98–1.05) n/a 1.04 (0.99–1.08) n/aGender 1.50 (1.01–2.23) 1.60 (1.04–2.46) 1.59 (0.99–2.56) n/aEducation 1.11 (0.81–1.51) n/a 0.92 (0.64–1.33) n/aEmployment status 1.21 (0.99–1.48) n/a 1.29 (1.00–1.65) 1.32 (1.00–1.73)Marital status 0.98 (0.69–1.39) n/a 0.87 (0.58–1.32) n/aChronic respiratory illness 1.80 (0.92–3.53) n/a 0.89 (0.36–2.20) n/a

Smoking-relatedCigarettes per day 0.93 (0.91–0.96) 0.94 (0.90–0.98) 0.94 (0.91–0.97) 0.93 (0.88–0.98)Years of smoking 0.98 (0.96–1.01) n/a 1.00 (0.97–1.03) n/aNicotine dependence 0.85 (0.78–0.92) 0.97 (0.86–1.11) 0.90 (0.82–0.99) 1.08 (0.93–1.27)Quit attempt 0.93 (0.61–1.40) n/a 0.83 (0.54–1.26) n/aIntention to quit 1.48 (1.19–1.84) 1.32 (1.03–2.46) 1.40 (1.08–1.81) 1.27 (0.96–1.68)Partner smoking 0.77 (0.50–1.18) n/a 0.66 (0.39–1.12) n/aConfidence in quitting 1.23 (1.10–1.37) 1.14 (1.00–1.29) 1.14 (1.00–1.29) 1.06 (0.92–1.22)Importance of quitting 1.02 (0.90–1.16) n/a 0.99 (0.86–1.15) n/a

Child-relatedChild chronic respiratory illness 1.88 (1.12–3.16) 1.91 (1.09–3.34) 2.12 (1.19–3.77) 2.14 (1.17–3.92)Number of children in household 1.22 (0.90–1.66) n/a 0.94 (0.66–1.37) n/aWanting to quit for child 2.64 (1.31–5.30) 2.55 (1.19–5.48) 3.20 (1.25–8.17) 2.74 (1.04–7.22)R2 0.16 0.12

129K. Schuck et al. / Preventive Medicine 69 (2014) 126–131

intention to quit was not predictive of prolonged abstinence (OR=1.21,CI = 0.90–1.63). In the self-help condition, higher intention to quit wasassociated with an increased likelihood of prolonged abstinence (OR=2.29, CI = 1.26–4.17). Smoking cessation rates by level of moderatorwithin the quitline counselling condition and the self-help brochurecondition are displayed in Table 4.

Discussion

This study examined general predictors of treatment outcome andtreatmentmoderators among smoking parents receiving either quitlinecounselling or self-help material. General predictors of treatment asso-ciated with both point prevalence abstinence and prolonged abstinencewere a lower number of cigarettes smoked per day, the presence of achild with a chronic respiratory illness, and wanting to quit for thehealth of one's child. Additionally, male gender, a higher intention toquit, and higher confidence in being able to quit predicted point preva-lence abstinence and higher employment status predicted prolongedabstinence among smoking parents. Similar findings have beenobserved in previous studies on unaided and aided smoking cessation(Ferguson et al., 2005; Haug et al., 2010; Hymowitz et al., 1997; Roseet al., 1996; Tucker et al., 2002; Tzelepis et al., 2013; Velicer et al.,2007). The present study extends previous research by examining therole of parent-specific characteristics in responses to cessationtreatment. Among smoking parents, having a childwith a chronic respira-tory illness and wanting to quit for the health of one's child were associ-ated with an increased likelihood of being abstinent at one-year follow-up. Previous studies indicated that parents of children with a smoking-

Table 3Odd ratios (OR) and 95% confidence intervals (CI) of moderators on 7-day point prevalence absthe quitline counselling condition and the self-help brochure condition.

Outcome Moderator

7-Day point-prevalence abstinence Intention to quit

Educational level

6-Month prolonged abstinence Intention to quit

Educational level

related illness display a particularly high motivation to quit (Haltermanet al., 2010; Winickoff et al., 2003a,b). This study is the first to show thatchild-related factors do not only increasemotivation to quit, but also suc-cess in quitting. Interestingly, the child-related characteristics emerged asthe strongest predictors compared to socio-demographic and smoking-related characteristics (i.e., parents who had a child with a chronic respi-ratory illness and parents whowanted to quit for the health of their childwere more than twice as likely to successfully quit smoking).

Moreover, the findings indicate that certain subgroups of smokersmay respond better to one treatment compared to another. Intentionto quit was found to be a consistent treatment moderator, which is inline with previous research (Ferguson et al., 2005; Spencer et al.,2002; Velicer et al., 2007). Specifically, quitline counsellingwas effectiveregardless of intention to quit, but self-help material was less effectiveamong parents with a lower motivation to quit. Standard self-helpmaterial may not be as potent as individual counseling in increasingintrinsic motivation for behavioural change and subsequent success inquitting among smokers with a lower motivation to quit.

In addition, educational level (an indicator of socio-economic status;SES) was a significant treatment moderator in the prediction of pointprevalence abstinence (but not prolonged abstinence). Althoughcaution should be exercised in interpreting this finding, it seems thatparents with a lower educational level may benefit less from a self-help brochure than parents with a higher educational level. Althoughself-help materials can be beneficial even in smokers with low socio-economic status (Brandon et al., 2012), it is possible that low SESsmokers would benefit more from an intervention that can makeup for some of the inherent disadvantages of their social status

tinence and 6-months prolonged abstinence at 12-months of follow-upmeasurement for

Condition OR (95%-CI) p-Value

Quitline counselling 1.26 (0.96–1.65) .10Self-help brochure 2.03 (1.37–3.02) b .001Quitline counselling 0.78 (0.52–1.16) .22Self-help brochure 2.15 (1.25–3.68) b .01Quitline counselling 1.21 (0.90–1.63) .22Self-help brochure 2.29 (1.26–4.17) b .01Quitline counselling 0.91 (0.59–1.42) .69Self-help brochure 1.03 (0.51–2.09) .93

Table 4Smoking cessation rates by level of moderator within the quitline counselling condition and the self-help brochure condition.

Outcome Moderator Level Quitline counselling Self-help brochure

7-Day point-prevalence abstinence Intention to quit Within one month 40.7% 29.1%Within six months 32.2% 16.5%Within twelve months 30.8% 11.8%Not within twelve months 25.0% 0%

Educational level Low 40.5% 8.3%Medium 35.4% 15.8%High 29.2% 24.6%

6-Month prolonged abstinence Intention to quit Within one month 26.7% 15.1%Within six months 27.8% 6.3%Within twelve months 19.2% 4.4%Not within twelve months 17.9% 0%

Educational level Low 28.5% 5.6%Medium 24.3% 9.6%High 24.6% 7.2%

130 K. Schuck et al. / Preventive Medicine 69 (2014) 126–131

(e.g., more intensive or guided interventions). Possibly, content andreading level of self-help material may not match the needs of lowerSES smokers. Inter-individual differences in needs may be better ad-dressed in individual counselling.

Several limitations should be acknowledged. First, endpoints weredetermined by self-report, which may be subject to reporting biases(e.g., social desirability). Furthermore, generalizability of the findingsmay be limited by the specific sample characteristics (e.g., a highereducational level of study participants compared to the generalpopulation). Moreover, this study examined only two interventionmodalities. The results may not generalize to other interventions(e.g., pharmacological interventions). Similarly, this study examinedonly a limited number of predictor variables. While these variableswere selected based on theory and literature, it is possible that other rel-evant variables may not have been included. Finally, it should be notedthat multiple analyses were conducted, which may result in an inflatedtype I error (chance findings). However, examining the role of child-related characteristics had an exploratory objective (i.e., aiming togenerate hypotheses rather than testing them). The findings will needto be replicated in future research.

This study has key implications. This study is the first to show thatsmoking parents who have a child with a chronic respiratory illness orwho report that they want to quit for the health of their child areparticularly receptive to cessation support. The findings highlight thepotential of targeting the subpopulation of smoking parents in tobaccocontrol efforts and addressing smokers as parents during smokingcessation interventions. Furthermore, the findings indicate that clientcharacteristics can provide predictive information about treatment re-sponses and that certain subgroups of smokers respond better to onetreatment compared to another. The findings suggest that individualcharacteristics (e.g., educational level, motivation to quit) should beconsidered when selecting a treatment for a particular client. In thearea of alcoholism, research provided support for the usefulness ofmatching clients to treatment based on personal characteristics. Arecentmulti-site alcoholism study found that themajority of individualswith lower baseline motivation had better outcomes if assigned tomotivation enhancement treatment compared to those assigned tocognitive behavioural treatment (Witkiewitz et al., 2010), although asimilar study did not find an advantage of Client Treatment Matching(UKATT Research Team, 2008). De Leon et al. (2010) reported evidencefor the effectiveness of a client-treatment matching paradigm(i.e., matching clients to treatment intensity based on the severity oftheir problems). In particular, they emphasize the need to identifyclients at risk for under-treatment. Also, there are indications thatclient-treatment matching can be useful in improving treatmentadherence (Melnick et al., 2001). In clinical practice, a client-treatment matching protocol (i.e., clinical guidelines for matching

clients to treatment) may provide practitioners with a useful tool toguide treatment recommendations.

Moreover, knowledge of characteristics that increase responsivenessto treatment (e.g., wanting to quit for the health of one's child) can beused to tailor existing interventions to enhance treatment effectiveness.If these values or motives can be influenced by the treatment, quitattempts may be more likely to be successful. Possibly, techniquesfrom values-based treatments (e.g., Acceptance and CommitmentTherapy) may be useful in increasing efficacy of available cessationtreatments (Bricker et al., 2010). In addition, knowledge of characteris-tics that motivate parents to quit and that increase success in quittingcan be used to promote the use of cessation support among smokingparents in public or clinical settings.

Finally, quitline counselling seems effective regardless of intentionto quit and SES. As the smoking prevalence is high among disadvan-taged groups and quit attempts are less likely to be successful amongsmokers with lower SES and a lower motivation to quit, interventionsthat work among these groups are strongly needed (Hiscock et al.,2012). Thus, quitline counsellingmay help reduce the social inequalitiesassociated with tobacco use and cessation treatment outcome.

This study may provide directions for future research. First, futureresearch may use more rigorous research designs (e.g., experimentaldesigns) to examine whether tailoring available interventions toaddress smokers in their role as parents can improve reach andeffectiveness of existing cessation treatments. Also, future studies mayidentify and examine the role of additional child-related characteristicsthat may be relevant in enhancing parental smoking cessation(e.g., severity of respiratory symptoms). Moreover, the effectiveness ofclient-treatmentmatching strategies will need to be examined in futureresearch. Matching criteria may include socio-demographic factors,severity of dependence, and intrapersonal characteristics. Once reliableand consistent treatment moderators have been identified, a client-treatment matching protocol may be developed, which could then bevalidated for clinical care (for an example, see Melnick et al., 2001).

Conclusions

In conclusion, the present study provides evidence that a numberof pre-treatment characteristics (e.g., educational level, motivationto quit) influence responsiveness to treatment, which should beconsidered in treatment selections. Smoking parents represent ahigh priority population segment among adult smokers. The findingsare the first to show that smoking parents who have a child with achronic respiratory illness or who report that they want to quit forthe health of their child are particularly likely to benefit from cessa-tion support.

131K. Schuck et al. / Preventive Medicine 69 (2014) 126–131

Funding

This work was supported by ZonMW the Netherlands Organizationfor Health Care Research and Development (grant number: 50-50110-96-639).

Conflict of interest statement

The authors declare that there are no conflicts of interest.

References

Brandon, T.H., Simmons, V.N., Meade, C.D., Quinn, G.P., Lopez Khoury, E.N., Sutton, S.K., etal., 2012. Self-help booklets for preventing postpartum smoking relapse: a random-ized trial. Am. J. Public Health 102, 2109–2115.

Bricker, J.B., Leroux, B.G., Peterson Jr., A.V., Kealey, K.A., Sarason, I.G., Andersen, M.R., et al.,2003. Nine-year prospective relationship between parental smoking cessation andchildren's daily smoking. Addiction 98, 585–593.

Bricker, J.B., Mann, S.L., Marek, P.M., Liu, J., Peterson, A.V., 2010. Telephone-delivered Ac-ceptance and Commitment Therapy for adult smoking cessation: a feasibility study.Nicotine Tob. Res. 12, 454–458.

De Leon, G., Melnick, G., Cleland, C.M., 2010. Matching to sufficient treatment: some char-acteristics of undertreated (mismatched) clients. J. Addict. Dis. 29, 59–67.

DiFranza, J.R., Aligne, C.A., Weitzman, M., 2004. Prenatal and postnatal environmental to-bacco smoke exposure and children's health. Pediatrics 113 (4 Suppl.), 1007–1015.

Fagerstrom, K., Furberg, H., 2008. A comparison of the Fagerstrom Test for Nicotine De-pendence and smoking prevalence across countries. Addiction 103, 841–845.

Ferguson, J., Bauld, L., Chesterman, J., Judge, K., 2005. The English smoking treatment ser-vices: one-year outcomes. Addiction 100 (Suppl. 2), 59–69.

Ferguson, J., Docherty, G., Bauld, L., Lewis, S., Lorgelly, P., Boyd, K.A., McEwen, A., Coleman, T.,2012. Effect of offering different levels of support and free nicotine replacement therapyvia an English national telephone quitline: randomised controlled trial. BMJ 344, e1696.http://dx.doi.org/10.1136/bmj.e1696.

Glasgow, R.E., Vogt, T.M., Boles, S.M., 1999. Evaluating the public health impact of healthpromotion interventions: the RE-AIM framework. Am. J. Public Health 89,1322–1327.

Gwaltney, C.J., Metrik, J., Kahler, C.W., Shiffman, S., 2009. Self-efficacy and smoking cessa-tion: a meta-analysis. Psychol. Addict. Behav. 23 (1), 56–66.

Halterman, J.S., Borrelli, B., Conn, K.M., Tremblay, P., Blaakman, S., 2010. Motivation to quitsmoking among parents of urban children with asthma. Patient Educ. Couns. 79,152–155.

Halterman, J.S., Szilagyi, P.G., Yoos, H.L., Conn, K.M., Kaczorowski, J.M., Holzhauer, R.J., et al.,2004. Benefits of a school-based asthma treatment program in the absence of second-hand smoke exposure: results of a randomized clinical trial. Arch. Pediatr. Adolesc.Med.158, 460–467.

Haug, S., Meyer, C., Ulbricht, S., Schorr, G., Ruge, J., Rumpf, H.J., et al., 2010. Predictors andmoderators of outcome in different brief interventions for smoking cessation in gen-eral medical practice. Patient Educ. Couns. 78, 57–64.

Hiscock, R., Bauld, L., Amos, A., Fidler, J.A., Munafò, M., 2012. Socioeconomic status andsmoking: a review. Ann. N. Y. Acad. Sci. 1248, 107–123. http://dx.doi.org/10.1111/j.1749-6632.2011.06202.x.

Hitchman, S.C., Fong, G.T., Zanna, M.P., Hyland, A., Bansal-Travers, M., 2011. Support andcorrelates of support for banning smoking in cars with children: findings from theITC Four Country Survey. Eur. J. Public Health 21, 360–365.

Hymowitz, N., Cummings, K.M., Hyland, A., Lynn,W.R., Pechacek, T.F., Hartwell, T.D., 1997.Predictors of smoking cessation in a cohort of adult smokers followed for five years.Tob. Control. 6 (Suppl. 2), S57–S62.

Kraemer, H.C., Wilson, G.T., Fairburn, C.G., Agras, W.S., 2002. Mediators and moderators oftreatment effects in randomized clinical trials. Arch. Gen. Psychiatry 59, 877–883.

Lancaster, T., Stead, L.F., 2005. Self-help interventions for smoking cessation. Cochrane Da-tabase Syst. Rev. (3), CD001118.

Leonardi-Bee, J., Jere, M.L., Britton, J., 2011. Exposure to parental and sibling smoking andthe risk of smoking uptake in childhood and adolescence: a systematic review andmeta-analysis. Thorax 66, 847–855.

Melnick, G., De Leon, G., Thomas, G., Kressel, D., 2001. A client-treatment matching proto-col for therapeutic communities: first report. J. Subst. Abuse Treat. 21 (3), 119–128.

Miller, Rollnick, 2002. Motivational Interviewing: Preparing People for Change, 2nd ed.Guilford Press, New York.

Otten, R., Engels, R.C., van de Ven, M.O., Bricker, J.B., 2007. Parental smoking and adoles-cent smoking stages: the role of parents' current and former smoking, and familystructure. J. Behav. Med. 30, 143–154.

Otten, R., Engels, R.C., van den Eijnden, R.J., 2005. Parental smoking and smoking behaviorin asthmatic and nonasthmatic adolescents. J. Asthma 42, 349–355.

Rose, J.S., Chassin, L., Presson, C.C., Sherman, S.J., 1996. Prospective predictors of quit at-tempts and smoking cessation in young adults. Health Psychol. 15, 261–268.

Rosen, L.J., Noach, M.B., Winickoff, J.P., Hovell, M.F., 2012. Parental smoking cessation toprotect young children: a systematic review and meta-analysis. Pediatrics 129,141–152.

Schnoll, R.A., Martinez, E., Tatum, K.L., Glass, M., Bernath, A., Ferris, D., et al., 2011. In-creased self-efficacy to quit and perceived control overwithdrawal symptoms predictsmoking cessation following nicotine dependence treatment. Addict. Behav. 36,144–147.

Schuck, K., Bricker, J.B., Otten, R., Kleinjan, M., Engels, R.C.M.E., 2014. Effectiveness of pro-active quitline counseling in smoking parents recruited through primary schools: re-sults of a randomized controlled trial. Addiction 109, 830–841. http://dx.doi.org/10.1111/add.12485.

Schuck, K., Otten, R., Engels, R.C.M.E., Kleinjan, M., 2012. The role of environmentalsmoking in smoking-related cognitions and susceptibility to smoking in never-smoking 9–12 year-old children. Addict. Behav. 37, 1400–1405.

Schuck, K., Otten, R., Kleinjan, M., Bricker, J.B., Engels, R.C.M.E., 2011. Effectiveness of pro-active telephone counselling for smoking cessation in parents: study protocol of arandomized controlled trial. BMC Public Health 11, 732.

Schuck, K., Otten, R., Kleinjan, M., Bricker, J.B., Engels, R.C.M.E., 2013. School-based promo-tion of cessation support: reach of proactive mailings and acceptability of treatmentin smoking parents recruited into cessation support through primary schools. BMCPublic Health 13.

Shiffman, S., Brockwell, S.E., Pillitteri, J.L., Gitchell, J.G., 2008. Use of smoking-cessationtreatments in the United States. Am. J. Prev. Med. 34, 102–111.

Smith, B.J., Carson, K.V., Brinn, M.P., Labiszewski, N.A., Peters, M.J., Fitridge, R., Koblar, S.A.,Jannes, J., Veale, A.J., Goldsworthy, S.J., Litt, J., Edwards, D., Esterman, A.J., 2013.Smoking termination opportunity for inpatients (STOP): superiority of a course ofvarenicline tartrate plus counselling over counselling alone for smoking cessation: a12-month randomised controlled trial for inpatients. Thorax 68 (5), 485–486.http://dx.doi.org/10.1136/thoraxjnl-2012-202484.

Spencer, L., Pagell, F., Hallion, M.E., Adams, T.B., 2002. Applying the transtheoretical modelto tobacco cessation and prevention: a review of literature. Am. J. Health Promot. 17,7–71.

Stead, L.F., Hartman-Boyce, J., Perera, R., Lancaster, T., 2013. Telephone counselling forsmoking cessation. Cochrane Database Syst. Rev. (8), CD002850 http://dx.doi.org/10.1002/14651858.CD002850.pub3.

Strecher, V.J., Shiffman, S., West, R., 2006. Moderators and mediators of a web-basedcomputer-tailored smoking cessation program among nicotine patch users. NicotineTob. Res. 8 (Suppl. 1), S95–S101.

Tucker, J.S., Ellickson, P.L., Klein, D.J., 2002. Smoking cessation during the transition fromadolescence to young adulthood. Nicotine Tob. Res. 4, 321–332.

Tzelepis, F., Paul, C.L., Walsh, R.A., Wiggers, J., Duncan, S.L., Knight, J., 2013. Predictors ofabstinence among smokers recruited actively to quitline support. Addiction 108,181–185.

UKATT Research Team, 2008. UK alcohol treatment trial: client–treatment matching ef-fects. Addiction 103, 228–238.

Velicer,W.F., Redding, C.A., Sun, X., Prochaska, J.O., 2007. Demographic variables, smokingvariables, and outcome across five studies. Health Psychol. 26, 278–287.

West, R., Hajek, P., Stead, L., Stapleton, J., 2005. Outcome criteria in smoking cessation tri-als: proposal for a common standard. Addiction 100, 299–303.

Winickoff, J.P., Hillis, V.J., Palfrey, J.S., Perrin, J.M., Rigotti, N.A., 2003a. A smoking cessationintervention for parents of children who are hospitalized for respiratory illness: thestop tobacco outreach program. Pediatrics 111, 140–145.

Winickoff, J.P., McMillen, R.C., Carroll, B.C., Klein, J.D., Rigotti, N.A., Tanski, S.E., et al., 2003b.Addressing parental smoking in pediatrics and family practice: a national survey ofparents. Pediatrics 112, 1146–1151.

Winickoff, J.P., Tanski, S.E., McMillen, R.C., Hipple, B.J., Friebely, J., Healey, E.A., 2006. A na-tional survey of the acceptability of quitlines to help parents quit smoking. Pediatrics117, e695–e700.

Witkiewitz, K., Hartzler, B., Donovan, D., 2010. Matching motivation enhancement treat-ment to client motivation: re-examination of the Project MATCH motivationmatching hypothesis. Addiction 105, 1403–1413.

Wolitzky-Taylor, K.B., Arch, J.J., Rosenfield, D., Craske, M.G., 2012. Moderators and non-specific predictors of treatment outcome for anxiety disorders: a comparison of cog-nitive behavioral therapy to acceptance and commitment therapy. J. Consult. Clin.Psychol. 80, 786–799.