motivational factors predicts quit attempts

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doi: 10.1093/ntr/ntq050 The Author 2010. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco.

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Introduction

Both psychological theory and public preconceptions hold thatmotivation to quit smoking is a critical actor or quit success.Balmord and Borland (2008) ound that most smokers believethat wanting to quit is both a necessary and a sucient condi-tion or successul cessation. All theories o health behaviorchange, most notably the class o expectancy-value theories,have a role or motivation, although in most cases it is implicitas the concept o motivation is not directly addressed, beingsubstituted by constructs, such as attitudes to the behavior, nor-mative pressures (Fishbein & Ajzen, 1975); susceptibility andseverity o harm (Rosenstock, Strecher, & Becker, 1988); andvulnerability (Rogers, 1983) or cons o the behavior to change(Velicer, DiClemente, Prochaska, & Brandenburg, 1985). Wests(2006) PRIME theory integrates many o these concepts andconcludes that the proximal determinants o behavior aremotives and outcome expectancies.

The term motivation is used here as a catch-all term. It in-cludes expressed desire or wanting, concerns about the risks onot acting, and behavioral reactions that imply motivation. Allthese have an emotional aspect (hot cognitions), as well as beliesabout the long-term value o acting or reasons or acting (calcu-lated or cold cognitions). The empirical evidence supporting acentral role or motivation in smoking cessation is mixed.Although there is strong evidence that it is predictive o makingquit attempts, this does not seem to translate into prediction omaintenanceor its converse, relapse (e.g., Borland, Owen, Hill, &Schoeld, 1991; Hyland et al., 2006; Segan, Borland, & Greenwood,2002; West, McEwan, Bolling, & Owen, 2001; Zhou et al., 2009).None o the above studies ound evidence that motivational ac-tors (including positive expectancies) predicted quit maintenanceamong those who tried, and some ound signicant negativeassociations (e.g., Borland et al.; Hyland et al.). Indeed, the only

Abstract

Aim: To explore whether measures o motivation to quitsmoking have dierent predictive relationships with makingquit attempts and the maintenance o those attempts.

Methods: Data are rom three wave-to-wave transitions o theInternational Tobacco Control Four (ITC-4) country project.Smokers responses at one wave were used to predict the like-lihood o making an attempt and among those trying the likeli-hood o maintaining an attempt or at least a month at the next

wave. For both outcomes, hierarchical logistic regressions wereused to explore the predictive capacity o seven measures o mo-tivation to quit smoking, controlling or a range o other knownor possible predictors.

Results: Bivariate analyses indicate that measures o moti-vation to quit are predictive o making quit attempts, butthey predict relapse among those making attempts. Multi-variate analyses identiied wanting to quit and requency oprematurely butting out cigarettes as the main positivepredictors o making attempts, but this was reduced byintention and recency o last attempt. For maintenance,premature butting out was the main motivation variablepredicting relapse and was essentially unaected by othermeasures.

Discussion: The ndings show that it is wrong to suggest thatall one needs to quit is to be motivated to do so. The reality isthat one needs to be motivated to prompt action to stopsmoking, but this is not suicient in and o itsel to ensurethat cessation is maintained. These ndings call attention to theimportance o understanding the dierential roles that prequitand postquit experiences play in smoking cessation and o pro-viding help to smokers to stay o cigarettes.

Original Investigation

Motivational actors predict quit attemptsbut not maintenance o smokingcessation: Findings rom the InternationalTobacco Control Four country projectRon Borland, Ph.D.,1 Hua-Hie Yong, Ph.D.,1 James Balmford, Ph.D.,1 Jae Cooper, B.A.,1 K. Michael Cummings, Ph.D.,2Richard J. OConnor, Ph.D.,2 Ann McNeill, Ph.D.,3 Mark P. Zanna, Ph.D.,4 & Geoffrey T. Fong, Ph.D.4

1 VicHealth Centre for Tobacco Control, The Cancer Council Victoria, Victoria, Australia2 Department of Health Behavior, Roswell Park Cancer Institute, Buffalo, NY3 Division of Epidemiology and Public Health, University of Nottingham, Nottingham, UK4 Department of Psychology, University of Waterloo, Waterloo, Canada

Corresponding Author: Ron Borland, Ph.D., VicHealth Centre for Tobacco Control, The Cancer Council Victoria, 1 RathdowneStreet, Carlton, Victoria 3053, Australia. Telephone: 61-3-9635 5185; Fax: 61-3-9635 5440. E-mail: ron.borland@cancervic.org.au

Received November 4, 2009; accepted March 9, 2010

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positive prediction we could nd was in a study oMarlatt, Curry,and Gordon (1988) and then only among those quit or morethan 2 years. This research indicates that the very motives drivingthe making o quit attempts may be at best irrelevant to mainte-nance and at worst associated with relapse.

There are several possible mechanisms or the nding thatmotivation is unrelated to quit maintenance. First, motivationmay have a threshold-related eect, and i there is enough

motivation to generate an attempt (i.e., it is above the threshold;West, 2006), then additional motivation makes no dierence tothe outcome o the attempt (i.e., no predictive relation or mo-tivational variables). Second, another view holds that i smokersrely too much on motivation to see them though a quit attempt,then they might neglect other eective coping strategies, andthis could lead to a negative association o motivation withmaintenance. Consistent with this, many smokers believe thatwanting to quit is both necessary and sucient to be successul(Balmord & Borland, 2008). Third, it is possible that thosehighly motivated to quit may represent a group o highly ad-dicted smokers who would have already quit i they could. Thishypothesis would predict a negative relationship with mainte-nance that would disappear when measures o dependence (e.g.,

diculty in quitting) were controlled or. It would also predictthat the eect would only appear where the smokers were pre-dominantly dependent and in those who had tried beore andrelapsed rapidly. Finally, expressed motivation beore com-mencing a dicult task may be independent o the level o mo-tivation experienced while trying to maintain the new behaviorpattern (e.g., not smoking). Motivation to maintain change mayneed to be assessed quite dierently and perhaps only aterbeginning to act. It might also vary considerably over time.Rothman (2000) argued that attempts to change behavior arereasonably understood by expectancy-value theories but thatmaintenance o change is more determined by the experienceso the new behavioral pattern. Higher expectancies prequit canactually be counter-productive postquit, as unmet expectationscan result in disappointment and dissatisaction with the newbehavior, leading to relapse, potentially accounting or theobserved negative relationship.

The aim o this study is to explore the nature o dierencesin the predictive relation between variables that are designed toassess aspects o positive motivation to quit and the initiation oa quit attempt as compared with its maintenance. We also ex-plored these in relation to other potential predictors as ound byHyland et al. (2006). We have studied a broad range o motiva-tional measures so as to assess whether the above-mentionedndings are limited to some aspects o motivation.

Methods

DesignThis is a prospective cohort study where variables measured atone wave o the cohort are used to predict smoking cessationoutcomes (quit attempts or maintenance) at the next wave.We report three replications.

Sample and data collectionData come rom our waves (36) o the International TobaccoControl Four (ITC-4) country project, a quasiexperimental

Table 1. Sample characteristics or respon-dents in the three wave-to-wave transitions

Waves 34,n = 5,369

Waves 45,n = 4,843

Waves 56,n = 4,988

Age (years):M(SD) 46.4 (13.7) 47.3 (13.5) 48.5 (13.3)% Female 57.1 57.7 57.5Cigarettes per day:M(SD) 16.9 (10.4) 17.2 (10.2) 17.3 (10.0)% Recruited each wave

Wave 1 56.4 43.2 30.8Wave 2 12.9 9.4 6.5Wave 3 30.8 20.9 14.3Wave 4 NA 26.5 16.3Wave 5 NA NA 32.2

% CountryCanada 25.1 25.6 25.0USA 21.7 23.5 22.7UK 25.7 24.9 25.3Australia 27.5 26.0 27.1

% Made a quit attemptby ollowing wave

41.1 38.3 37.3

% Quit >1 month(maintenance) amongthose who trieda

24.6 25.7 25.3

Notes. NA = not applicable.aExcludes respondents quit or less than a month at ollow-up (n = 83

at Wave 4; n = 88 at Wave 5; and n = 81 at Wave 6).

longitudinal survey o smokers and subsequent to recruitmentas either smokers or recent quitters. The ITC-4 country surveyis an annual survey conducted via computer-assisted telephoneinterview in Canada, UK, USA, and Australia. Using a stratiedrandom-digit dialing procedure, households are contacted andscreened or adult smokers (18 years and older) with the nextbirthday who would agree to participate in the study. Respon-dents were considered smokers at recruitment i they reportedsmoking at least 100 cigarettes in their lietime and smoking at

least once in the past 30 days. A detailed description o the ITCstudy conceptual ramework (Fong et al., 2006) and methodol-ogy (Thompson et al., 2006) can be ound elsewhere.

Data were included rom ITC-4 cohort members who pro-vided predictor data in at least one o the three predictor waves(35) and outcome data in the next wave (46). We have not useddata rom Waves 1 and 2 as some o the questions were only in-cluded rom Wave 3 onward (most notably the explicit measureo wanting to quit). Characteristics o the samples used or each othe three wave-to-wave transitions are provided in Table 1.

Predictor measures

Motivation to quit variables (seven variables)1. Wanting to quit, a measure o explicit motivation measured

by How much do you want to quit smoking?: not at all(1),a little, somewhat, and a lot(4).

2. Frequency o stubbing out a cigarette (a microbehavioral in-dicator o motivation): In the last month, have you stubbedout a cigarette beore you nished it because you thoughtabout the harm o smoking?: never(1), once, a few times, orlots of times (4).

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3. A measure o concern about the nancial cost o smokingwas ormed rom the mean o two questions: In the lastmonth, how much did you think about the money you spendon smoking?: never(1) to very often (5) and In the past6 months has the price o cigarettes led you to think aboutquitting?: not at all(1) to very much (3).

4. A measure o strength o health concerns (modiied romHyland et al., 2006) was derived rom the mean o ouritems: (a) How worried are you, i at all, that smoking

will (a) damage your health in the uture?; . . . (b) lower your quality o lie in the uture?, both measured on a4-point scale rom not at all worried (1) to very worried(4); (c) In the past 6 months has concern or your per-sonal health led you to think about quitting? measuredrom not at all(1) to very much (3); and (d) In the lastmonth, how much did you think about the harm yoursmoking might be doing to you?: never(1) to very often(5). Cronbach alpha coeicient or this composite mea-sure ranged rom .81 to .83 across the three predictorwaves.

5. Health outcome expectancy was measured by How muchdo you think you would benet rom health and other gainsi you were to quit permanently in the next 6 months?, romnot at all(1) to extremely(5).

6. Liestyle outcome expectancy (only asked rom Wave 4, so isonly included in two o the three replications) was assessedby: I you were to quit smoking, would your ability to enjoylie be: improved a lot (5), improved a little, stay the same,made a little worse, or made much worse (1)?.

7. Overall attitude to smoking: What is your overall opiniono smoking?: coded rom 1 (very positive) to 5 (very nega-tive). This can be thought o as an indicator o the balancebetween wanting to smoke and quit. It is included in this seto variables because it was ound to a strong predictor omaking a quit attempt in Hyland et al. (2006).

Demographic variablesDemographic variables included age (1824, 2439, 4054, and55+ years), gender, country o residence (Canada, USA, UK, orAustralia), and socioeconomic status as indicated by reportedhousehold income and highest level o education (see Hylandet al. 2006, or a ull description o how education and incomewere derived).

Tobacco dependence variablesDependence was assessed using the Heaviness o Smoking Index(HSI; range 06). The HSI was created as the sum o two cate-gorical measures: number o cigarettes smoked per day (coded:0: 010 cigarettes/day (CPD), 1: 1120 CPD, 2: 2130 CPD, and3: 31+ CPD) and time to irst cigarette (coded: 0: 61 min ormore, 1: 3160 min, 2: 630 min, and 3: 5 min or less). The HSIwas then recoded into three categories o dependence: low: 01,moderate: 23, and high: 46. Baseline smoking requency wasalso included (daily and less than daily). An additional indicatoro dependence was length o the longest attempt ever (never,less than 1 week, 1 week to 1 month, 1 month to 6 months, andmore than 6 months).

We also assessed use o quit smoking medications on thelast quit attempt (yes and no) and use o cessation services(Clinics, Quitlines, etc) in the last year, whether or not speci-cally related to the last quit attempt.

Variables with a motivational component (not puremeasures o motivation to quit: called motivationrelated here; our variables)

A binary measure o whether the respondent had made a quitO

attempt in the previous year (i.e., beore the predictor wave)with having done so indicating increased past motivation.Sel-ecacy, assessed by, I you decided to give up smokingO

completely in the next 6 months, how sure are you that youwould succeed?, with the options: not at all sure (1), slightly

sure, moderately sure, very sure, and extremely sure (5). Sel-ecacy estimates can include an assessment o perceivedmotivation to put in eort as well as capacity to do so.Intention to quit assessed on a 4-point scale:O planning in thenext month (4),planning beyond 1 month but within 6 months ,

planning beyond 6 months , and not planning to quit(1). Inten-tion to quit is typically seen as a consequence o motivation.Motivation to smoke. Based on the average o smokersO

responses to the ollowing two statements: You enjoy smok-ing too much to give it up and Smoking is an importantpart o your lie, both coded rom 1 (strongly disagree) to 5(strongly agree).

Outcome measuresThe two outcome measures assessed at ollow-up were whetheror not respondents reported making a quit attempt in the inter-val between waves and among those who tried whether they hadachieved at least 1-month abstinence at the ollow-up (mainte-nance). Those quit or less than 1 month were excluded. We alsoredid the analyses using a 6-month sustained abstinence cri-terion, thus restricting the analyses to those who made theirattempts at least 6 months prior to the ollow-up assessment.

AnalysesInitially, we explored whether the predictor variables could betreated as continuous or whether there were nonlinearities thatwould demand treating them as sets o ordinal categories. In allcases, the two models gave equivalent results, so we report thesimpler analyses treating each as quasilinear.

Hierarchical multivariate logistic regression was used to ex-amine the association between each predictor variable separatelyand the two outcomes o making quit attempts and maintenanceamong those who tried. At the rst step, each motivational pre-dictor was entered along with the demographic variables. Theset o motivational predictor variables were entered together onthe second step. A third and ourth step controlled or the mixedmotivation-related set (sel-ecacy, intention, motivation tosmoke, and recency o last attempt) and the dependence-relatedset (HSI, daily/non-daily smoking, and length o longest previ-ous quit attempt), respectively. These last two steps were alsoconducted in reverse order. In addition, where the signicanceo the ocal motivational predictors changed markedly, we con-ducted additional analyses to identiy the variable or variablesthat produced the eects. Signicance was set atp < .05. Analyseswere perormed using SPSS version 14.0.

Results

Summary statistics or each motivational predictor are presentedin Table 2. Average levels on all predictors were similar across

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motivation-related variables attenuated the size o the eects

o want to quit and requency o prematurely butting out

(Column 3), mainly due to eects o intention to quit and

recency o last quit attempt. The addition o the dependence

measures at the nal step had no real eect (Column 4). All

eects were in the expected direction. The dependence mea-

sures were negatively related to making a quit attempt as ex-

pected (Hyland et al., 2006), and among the motivation-related

measures, having made a quit attempt the year beore, having

less motivation to smoke, and having an intention to quit soon-er were all positively associated with making a quit attempt.

We now turn to predictors o short-term quit maintenance

among those who made attempts. Table 5 (Column 1) shows

that ater controlling or demographics, ve o the motivation-

to-quit variables were signicantly inversely associated with re-

porting being quit or at least a month at ollow-up in at least

two o the three wave-to-wave transitions. That is, higher moti-

vation was predictive o relapse. When all motivation-to-quit

variables were added together (Column 2), want to quit and the

nancial cost measure both remained signicant in two waves.

These two may be interrelated as each was responsible or the

other becoming nonsignicant in the waves when both did notpredict. The addition o the motivation-related measures

(Column 3) resulted in want to quit becoming nonsignicant,

with intention to quit and the recency o last quit attempt re-

sponsible, as was ound or predicting quit attempts. The mea-

sures o dependence were responsible or nancial cost becoming

nonsignicant, as shown in Column 4 (all had equal impact). O

the variables not in the core motivational set, those indepen-

dently predictive o short-term quit maintenance in the nal

model were recency o last attempt (no quit attempt in the last

year; two waves), higher sel-ecacy (one), lower HSI (all

three), having a longest attempt o 6 months or more (two), and

being a nondaily smoker (one wave).

Additional analyses were run to examine the associationbetween each predictor variable and maintenance ater control-

ling or the use o stop-smoking medications (including Nico-

tine Replacement Therapy) to quit and the use o cessation

waves. Table 3 shows the interitem correlation matrix amongthe seven core motivation-to-quit variables and the additional

motivation-related variables (showing ranges across the threereplications). Correlations above the diagonal are or the sub-sample who made quit attempts and are restricted to the sevenocal measures. Those below the diagonal are or the entiresample. As expected, the seven measures were all positivelycorrelated and had expected associations with the othermotivation-related measures.

All motivation-to-quit variables were signicantly associatedwith making a quit attempt in all three wave-to-wave transitionsater controlling or demographic actors (Table 4, Column 1).In analyses not reported here, we tested or by-country interac-tions with the motivation-to-quit variables and outcomes butound none. When all the motivation-to-quit variables were

added together (Column 2), Want to quit and requency o pre-maturely butting out were the only two predictors that remainedsigniicant in all three replications. Want to quit was mainlyresponsible or the other measures dropping out. Adding the

Table 2. Mean (SD) scores on motivationand selected other predictors or eachwave-to-wave transition

Variable (range) Waves 34 Waves 45 Waves 56

Wanting to quit (14) 3.00 (1.14) 2.99 (1.15) 3.00 (1.14)Frequency o stubbing out (14) 1.69 (1.07) 1.70 (1.09) 1.68 (1.07)Concern about fnancial cost (15) 2.88 (0.93) 2.86 (0.92) 2.82 (0.92)Health concerns (14) 2.71 (0.85) 2.71 (0.84) 2.57 (0.96)Health outcome expectancy (15) 3.67 (1.18) 3.61 (1.18) 3.64 (1.20)Liestyle outcome expectancy

(15)NA 3.84 (1.04) 3.85 (1.04)

Overall attitude to smoking (15) 3.55 (0.90) 3.55 (0.90) 3.55 (0.92)Motivation to smoke (15) 3.17 (0.95) 3.19 (0.95) 3.24 (0.97)Intention to quit (14) 2.87 (0.95) 2.85 (0.96) 2.84 (0.97)Sel-efcacy (15) 2.43 (1.25) 2.45 (1.24) 2.42 (1.24)

Notes. NA = not applicable.

Table 3. Correlations between variables motivating quit attempts (range over the threewave-to-wave transitions; above diagonal or the frst seven variables only: those makingquit attempts; and below diagonal: total sample)

1 2 3 4 5 6 7

Want to quit .21.27 .27.32 .53.56 .40.42 .32.36 .29.33Premature butting out .29.32 .16.18 .29.37 .16.19 .12.18 .13.20Financial cost .37.39 .21.21 .36.39 .25.28 .20.22 .13.15Health concern .63.64 .35.39 .42.42 .48.51 .40.41 .41.42Health outcome expectancy .47.49 .21.24 .31.33 .53.55 .44.44 .25.31Liestyle outcome expectancy .43.43 .18.21 .26.27 .45.46 .47.48 .24.24Overall attitude to smoking .37.39 .18.22 .20.21 .44.46 .31.34 .28.29 Intention to quit .63.64 .28.32 .27.28 .49.51 .36.37 .33.35 .30.31Motive to smoke .31 to .29 .22 to .17 .09 to .07 .20 to .19 .19 to .17 .20 to .18 .20 to .19Sel-efcacy .03.06 .05.09 .04 to .01 .03 to .01 .01.03 .04.04 .020.4Tried in the last year .36 to .34 .24 to .22 .17 to .16 .29 to .27 .19 to .18 .19 to .19 .17 to .16Heaviness o Smoking Index .43 to .35 .14 to .12 .08.10 .03.00 .02.02 .00.05 .03.02Longest attempt .22.23 .08.13 .08.10 .16.17 .10.11 .09.10 .10.12

Notes. Bold text indicates statistically signifcant atp < .05.

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services. These were added to the nal step with the dependence-related variables. Neither variable altered the association betweenmaintenance and any o the predictors appreciably. Reporteduse o stop-smoking medications was independently associatedwith maintaining a quit attempt in both Waves 45 (OR [oddsratio] 1.38, p = .005) and in waves 56 (OR = 1.49, p = .001).However, reported use o other orms o cessation help was not.

We explored the possibility that the time elapsed betweenmeasuring the predictor variables and making a quit attempt

was a potential moderator o the association between motiva-tion and maintenance. For instance, it is plausible that morehighly motivated people might attempt to quit sooner therebyhaving more time to relapse than those who were less motivated.The outcome variable was dened as any attempt that lastedat least 1 month, regardless o smoking status at ollow-up, be-ginning in the 6 months ollowing assessment o the predictorvariables (possible only rom Wave 4 onwards). We essentiallyound the same patterns as above. In the Wave 45 transition(n = 565), none o the core motivational variables were signi-cantly associated with maintenance. In the Wave 56 transition(n = 543), reported wanting to quit was negatively associated

with maintenance ater controlling or all variables (OR = 0.64,p = .025). Liestyle outcome expectancy ater quitting was nega-tively associated, remaining signiicant ater controlling ordemographic variables only (OR = 0.77,p = .041).

Still restricted to the 6 months ollowing measurement, weincreased the outcome variable to 6-month sustained abstinenceand ound essentially the same results. In the Wave 45 analy-ses, want to quit was signicantly predictive when controllingor demographics and all motivation-to-quit variables (OR = 0.78,

p = .35) and borderline with the addition o the dependencevariables (OR = 0.78,p = .052). In the Wave 56 analyses, onlywant to quit (OR = 0.79, p = .020) and concerns over the -nancial cost (OR = 0.78,p = .018) were predictive, and onlyater controlling or demographics, the eects were becomingnonsignicant when other variables were added.

DiscussionThe ndings rom this study conrm that actors that motivatesmokers to make a quit attempt are very dierent rom those

Table 4. Predictors o quit attempts

Core predictorvariable

Other variables included at each step

Step 1. Demographic setStep 2. Plus other motivationto quit variables

Step 3. Plus motivation-related set Step 4. Plus dependence set

Wanting to quitWaves 34 1.83 (1.721.94) 1.61 (1.491.73) 1.23 (1.131.35) 1.22 (1.111.33)Waves 45 1.92 (1.82.05) 1.62 (1.501.76) 1.24 (1.121.37) 1.25 (1.131.38)Waves 56 1.99 (1.862.12) 1.73 (1.601.88) 1.33 (1.211.47) 1.31 (1.191.45)Frequency o butting outWaves 34 1.43 (1.351.50) 1.21 (1.141.28) 1.10 (1.041.18) 1.08 (1.021.16)Waves 45 1.49 (1.411.57) 1.24 (1.171.32) 1.14 (1.061.21) 1.12 (1.051.20)Waves 56 1.35 (1.281.43) 1.12 (1.061.19) 1.04 (0.971.11) 1.03 (0.961.10)Financial costWaves 34 1.32 (1.241.41) 0.96 (0.891.04) 0.98 (0.901.06) 0.99 (0.921.08)Waves 45 1.42 (1.331.52) 1.03 (0.951.11) 1.03 (0.941.12) 1.07 (0.981.16)Waves 56 1.35 (1.261.45) 0.97 (0.901.06) 0.96 (0.891.05) 0.98 (0.901.06)Health concernWaves 34 1.82 (1.691.96) 1.05 (0.951.17) 0.98 (0.881.09) 0.98 (0.881.10)Waves 45 1.98 (1.832.15) 1.10 (0.981.11) 1.04 (0.921.18) 1.03 (0.911.16)Waves 56 1.99 (1.832.16) 1.17 (1.041.31) 1.11 (0.981.25) 1.10 (0.971.24)

Health outcome expectancyWaves 34 1.43 (1.351.50) 1.10 (1.031.18) 1.09 (1.021.16) 1.10 (1.031.18)Waves 45 1.41 (1.331.49) 1.04 (0.971.12) 1.04 (0.961.12) 1.05 (0.981.14)Waves 56 1.39 (1.321.46) 1.00 (0.931.07) 1.01 (0.941.08) 1.01 (0.941.09)Liestyle outcome expectancyWaves 34 NA NA NA NAWaves 45 1.45 (1.361.54) 1.07 (0.991.15) 1.03 (0.951.11) 1.04 (0.961.12)Waves 56 1.43 (1.341.52) 1.06 (0.991.14) 1.02 (0.941.10) 1.03 (0.951.11)Overall attitude to smokingWaves 34 1.43 (1.341.53) 1.07 (1.001.16) 1.05 (0.971.13) 1.05 (0.971.13)Waves 45 1.45 (1.351.56) 1.06 (0.971.15) 1.03 (0.951.11) 1.03 (0.941.12)Waves 56 1.46 (1.361.56) 1.08 (0.991.16) 1.04 (0.961.13) 1.05 (0.971.14)

Notes. NA = not applicable.

Figures are odds ratios, and 95% CIs are in parentheses. Bold text indicates statistically signifcant atp < .05. Step 1 involves seven separateanalyses or each wave, while Steps 24 are single analyses per wave. Waves 34 (n = 5,064 valid + 305 missing), Waves 45 (n = 4,585 valid + 258missing), and Waves 56 (n = 4,633 + 355 missing).

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involved in maintaining abstinence. Thus, to suggest that all oneneeds to quit is to be motivated to do so is wrong. The reality isthat one needs to be motivated to prompt action to stop smok-ing, but this is not sucient in and o itsel to ensure that onewill stop smoking or any length o time. This is not an isolatednding, being consistent with other studies (e.g., Hyland et al.,2006; Zhou et al., 2009) where positive eects or predictingattempts reversed (e.g., Borland et al., 1991; Hyland et al.) ortrended (e.g., West et al., 2001; Zhou et al.) toward the motiva-tional measures predicting relapse. Indeed, the ndings are verysimilar to those o Hyland et al. on earlier waves o this study,although the reverse eect o motivational variables on mainte-nance was clearer or the variables in common.

Beore going on to try to understand these results, it isimportant to consider limitations o the study. Single-itemmeasures were used or several constructs; however, given thatwe ound the expected positive eects or quit attempts, lack ovalidity o the measures cannot be used to explain the reversal oeects or maintenance. Motivation is changeable, and a posi-tive relationship between motivation and maintenance mighthave been ound i the ollow-up period was shorter. We tested

or this to some degree by shortening the period in which quitattempts were included to the 6 months ater the predictor waveand ound similar trends, albeit with some sense that the par-ticular motivational variables may have changed. This is only apartial control as it involves memory or a period o 6 months ormore beore the outcomes were measured. This should be less aproblem or maintenance than or making attempts, but i itmisses a proportion o less memorable attempts (which wouldinclude those longer ago and thus closest to the predictors), itcould distort the ndings.

The inding that measures o motivation predicted quitattempts largely independent o expressed intention to quit iscurious. It may be because the motivational variables include amore stable motivational component than the intentionmeasure. Our intention to quit smoking measure asked i therespondent was planning to stop smoking in the next month,6 months, beyond that, or not at all. We assessed the predictive-ness o quit intention across periods o around 1 year. It is plau-sible that more o the eects would be mediated throughintention, at least or making attempts, i the period being askedabout was more consistent with the intention question. We can

Table 5. Predictors o quit maintenance

Core predictor variable

Other variables included at each step

Demographic setPlus other motivation toquit variables Plus motivation-related set Plus dependence set

Want to quitWaves 34 0.89 (0.780.99) 0.95 (0.831.09) 0.96 (0.821.13) 1.00 (0.851.17)Waves 45 0.81 (0.720.91) 0.83 (0.710.96) 0.90 (0.751.08) 0.90 (0.751.08)Waves 56 0.77 (0.680.87) 0.86 (0.740.99) 0.95 (0.801.14) 0.96 (0.801.15)Freq o butting outWaves 34 0.91 (0.830.99) 0.94 (0.851.03) 0.93 (0.841.02) 0.90 (0.811.00)Waves 45 0.88 (0.800.97) 0.90 (0.821.00) 0.90 (0.811.01) 0.89 (0.800.99)Waves 56 0.83 (0.740.92) 0.87 (0.780.97) 0.89 (0.790.99) 0.85 (0.760.96)Financial costWaves 34 0.81 (0.720.91) 0.83 (0.730.94) 0.84 (0.740.96) 0.89 (0.781.01)Waves 45 0.82 (0.720.93) 0.85 (0.740.98) 0.87 (0.750.99) 0.91 (0.791.05)Waves 56 0.89 (0.781.02) 1.01 (0.881.17) 1.04 (0.901.20) 1.12 (0.961.30)Health concernWaves 34 0.87 (0.770.99) 1.04 (0.861.25) 1.04 (0.861.26) 1.04 (0.861.26)Waves 45 0.89 (0.771.03) 1.17 (0.951.44) 1.22 (0.991.51) 1.20 (0.971.49)Waves 56 0.72 (0.620.83) 0.82 (0.661.00) 0.86 (0.701.07) 0.85 (0.681.05)

Health outcome expectancyWaves 34 0.92 (0.831.01) 0.98 (0.871.10) 0.97 (0.861.09) 0.99 (0.881.12)Waves 45 0.95 (0.851.05) 1.06 (0.931.21) 1.05 (0.921.20) 1.08 (0.941.23)Waves 56 0.88 (0.790.97) 1.00 (0.881.14) 0.99 (0.871.12) 0.99 (0.861.13)Liestyle outcome expectancyWaves 34 NA NA NA NAWaves 45 0.89 (0.790.99) 0.93 (0.821.06) 0.92 (0.811.05) 0.92 (0.811.05)Waves 56 0.90 (0.800.99) 1.00 (0.881.14) 1.02 (0.891.16) 1.06 (0.921.22)Overall attitude to smokingWaves 34 0.95 (0.841.06) 1.00 (0.881.14) 1.00 (0.881.14) 1.01 (0.881.16)Waves 45 0.90 (0.791.02) 0.94 (0.821.08) 0.93 (0.801.07) 0.95 (0.821.10)Waves 56 0.91 (0.811.04) 1.04 (0.901.19) 1.02 (0.891.18) 1.02 (0.881.18)

Notes. NA = not applicable.

Figures are odds ratios, and 95% CIs are in parentheses. Bold text indicates statistically signifcant atp < .05. Step 1 involves seven separateanalyses or each wave, while Steps 24 are single analyses per wave. Waves 34 (n = 1,994 valid + 127 missing), Waves 45 (n = 1,662 valid + 103missing), and Waves 56 (n = 1638 valid + 141 missing).

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Motivational actors and smoking cessation

think o no mechanisms by which any likely biases in sel-report(largely dierential memory) might explain this nding.

Similarly, we think it unlikely that the dierent eects ormotivation are due to a need o smokers to espouse positivethoughts about the value o quitting regardless o doubts. Where-as the more cognitive measures o motivation, such as outcomeexpectancies, had their eects through expressed wanting, themeasure least likely to be subject to expectancy eects (prema-

turely butting out cigarettes) was most predictive o relapse.Whatever the explanation or the ndings, it needs to applyequally to hot and cold motivational processes, as very similareects were ound or expressed wanting as or expectancies.

None o the proposed mechanisms or explaining the dier-ence in predictive power o the motivational variables receivedstrong support. The hypothesis that motivation beyond thatwhich generates a quit attempt is potentially threatening ormaintenance because it may be relied on to the exclusion oeective treatments was not supported. The eects were notmediated or moderated by use o help (medication), so we haveno evidence or the second mechanism that motivation is beingused as a substitute or more eective strategies. It is possible

that the measures o motivation we used are unrelated to thecapacity o the individual to generate competing thoughts attimes when cravings to smoke threaten relapse, that is, that gen-eral motivation has no additional benet beyond some thresh-old level (which might be indexed by enough to try). Postquitting,it may be the strength o the motivational orce at the momentwhen a craving occurs that is critical, something consistent withWests PRIME model. I so, it suggests that we need to be devel-oping new measures o motivation that are specic to relapseprevention rather than assuming the adequacy o general mea-sures that can be assessed independently o the behavioral state.Such measures will need to be reerenced to, or take intoaccount, the actual experiences o being quit and how thesemight change and/or might be amenable to interventions (in-

cluding pharmacotherapies and skills development). They mightbe like Kahler et al. (2007) measure o commitment to quit or odetermination to quit (Segan et al., 2002). However, thesekinds o measures can really only be assessed once the indi-vidual has made a commitment to quit or has actually stopped.

Third, the possibility that those with high motivation are,on average, a group predisposed to relapse due to actors such ashigher nicotine dependence and lower sel-ecacy was onlypartially supported. We tested this by controlling or past quit-ting history, behavioral dependence, and sel-ecacy but oundthat these actors, particularly dependence, had little eect onthe associations with the motivation variables. Herd, Borland,and Hyland (2009) ound that requency o strong urges to

smoke postquitting was a predictor o relapse ater controllingor time quit and prequit measures o dependence (which werenot predictive), so some elements o dependence, other than theconventional behavioral measures used here, may be important.Even i dependence did ully account or the reversal o eects,it is hard to see it masking a true positive association betweenthe motivational variables we measured and maintenance.However, high motivation to cease a behavior that one is none-theless continuing to engage in can be seen as evidence o highinternal confict. The only motivational measure to remain asignicant negative predictor o maintenance ater controllingor all other variables, requency o butting out, may be a good

measure o such internal confict. Those who requently stubout a cigarette beore nishing it may be highly conficted by thecompeting desire to quit and to smoke, which would make itmore dicult to remain quit once an attempt is made.

The ourth potential mechanism or the reversal o eect,related to the rst, was that dierent motivational actors areimportant ater quitting to those that are assessed beorehand.On a general level, the making o quit attempts seems to be

strongly associated with the desire to escape the potential harmso smoking, while the predictors o maintenance may be relatedto the experienced benets o a nonsmoking liestyle and howthese relate to uture expected benets. However, the mecha-nism or this eect proposed byRothman (2000) was not sup-ported. Rothmans theory would predict that the outcomeexpectancy variables would become the main negative predic-tors o maintenance, especially those or outcomes that had not(yet) been realized. However, the strongest negative predictorwas requency o butting out rather than a cognitive measure ooutcome expectancy. Further, it is not clear how such a modelwould explain repeated ailures to stay quit. It seems unlikelythat smokers would repeat the same pattern o unmet expecta-tions on subsequent quit attempts; rather, each attempt would

begin with more accurate expectations.

One consequence o the nding that the motivational vari-ables do not share a common relationship with both attemptsand maintenance is that the study o quitting, including theevaluation o smoking cessation interventions, should look atthe contribution o the interventions or making quit attemptsseparately to their contribution to supporting maintenance.Some interventions might contribute to both attempting andmaintenance, but others may only contribute to one. In somecases, it is also important to look at the combined or net eectas the reason why smokers who are highly motivated to quit willeventually succeed at marginally greater rates is because tryingmore oten compensates or their reduced chance o success on

any given attempt. There may need to be shits in strategy oncethe person has quit as some actors that helped stimulate theattempt may reduce the l ikelihood o long-term maintenance.

The other major implication o the ndings is that it providesa clear demonstration that the ability to remain o cigarettes isnot something that is strongly under volitional control. Themajority o smokers are genuinely dependent on cigarettes andnot able to easily rerain rom smoking (Giovino, Henningeld,Tomar, Escobedo, & Slade, 1995; PhilipMorrisUSA, 2009). Thus,the notion that all a smoker must do to stop smoking is want to ismisleading, wanting to does not seem to acilitate maintenance.This means that there may need to be renewed ocus on treat-ments that help smokers address their biological dependence to

nicotine. Normal volitional actors seem to be sucient to mo-tivate attempts, and these need to be supported and enhanced,but unless we are prepared to accept low quit rates, there is a needto develop more eective interventions to help smokers remainsmoke ree (Cummings, Fong, & Borland, 2009). Motivation is acomplex set o belies and inclinations that we dont know enoughabout, especially postquitting. The ndings o this study suggest aneed to shit ocus once people try to enact a new liestyle choiceto ocus on maximizing the immediate benets they obtain romit, or maintaining the promise that these benets will occur intime, rather than continuing to ocus on the things that motivatedthe change in the rst place. Gain-ramed communications might

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be more important once a person has actually quit than whenthey are only contemplating trying (Toll et al., 2007). Strong dis-ease-related messages are potent motivators o making quit at-tempts (National Cancer Institute, 2008) but may play little rolein maintenance.

Funding

This research was unded by grants rom the National CancerInstitute o the United States (R01 CA 100362), the Roswell

Park Transdisciplinary Tobacco Use Research Center (P50CA111236), Robert Wood Johnson Foundation (045734),Canadian Institutes o Health Research (57897 and 79551),National Health and Medical Research Council o Australia(265903 and 450110), Cancer Research UK (C312/A3726), andCanadian Tobacco Control Research Initiative (014578), withadditional support rom the Centre or Behavioural Researchand Program Evaluation, National Cancer Institute o Canada/

Canadian Cancer Society. None o the sponsors played anydirect role in the design and conduct o the study; the collection,management, analysis, and interpretation o the data; or thepreparation, review, and approval o the manuscript.

Declaration o Interests

None declared.

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