Attrition in a MultiComponent Smoking Cessation Study for Females

TOBACCO INDUCED DISEASES Vol. 3, No. 2:59-71 (2006) © PTID Society

Attrition in a Multi-Component SmokingCessation Study for Females

Robert F. Leeman1, Zandra N. Quiles2, Laurence A. Molinelli3,Donna Medaglia Terwal3, Beth L. Nordstrom4, Arthur J. Garvey3,

Taru Kinnunen3

1Department of Psychiatry, Yale University School of Medicine, New Haven, CT; 2Lehman College, City University of New York, New York, NY; 3Tobacco DependenceTreatment and Research, Harvard School of Dental Medicine, Boston, MA; 4 Ingenix

Pharmaceutical Services, Newton, MA

ABSTRACT: Limiting attrition (i.e., participant dropout before the conclusion ofa study) is a major challenge faced by researchers when implementing clinicaltrials. Data from a smoking cessation trial for females (N = 246) were analyzed inorder to identify baseline smoking-related, demographic and psychologicalcharacteristics affecting likelihood of early (i.e., before the quit attempt) and late(i.e., after the quit attempt) dropout. There were a number of significantdemographic predictors of attrition. Participants with at least one child living athome were at increased risk of both early and late dropout. Non-Whites were atincreased risk of early dropout, while not having a college degree put one atincreased risk of late dropout. Age was found to be a protective factor in that theolder a participant was, the less likely she was to drop out in the early stages ofthe trial. With respect to psychological variables, weight concerns increased riskof attrition, as did the experience of guilt. In terms of smoking-related variables,mean cigarettes per day was not a significant predictor of attrition, althoughlength of longest prior quit attempt was a significant predictor of early dropoutwhen age was removed from the regression.

INTRODUCTION

Participant attrition (i.e., participantdropout before the conclusion of a study)is a threat to the validity of researchfindings in that attrition introducessampling bias. Attrition also hurts thecost-effectiveness of research becauselimited staff time and financial resourcesare likely to be invested in “dropouts,”who typically yield little to no useabledata [1]. Recognizing the importance ofattrition, researchers have begun tosuggest that analyses should beconducted with completion of treatment

as an outcome variable in addition toabstinence [2 ]. Given the manycontrasting and equivocal findings in thesmall literature on this topic, limitedprogress has been made up to this pointin identifying the characteristicsassociated with attrition.

In the attempt to explain risingattrition rates and the relatively lowpercentage of successful quit attempts insmoking cessation trials, researchershave put forth the notion that remainingsmokers in the population are primarilyheavily addicted, long-term users [3, 4],who are resistant to the treatments

60 Leeman R, Quilles ZN, Molinelli LA, Terwal DM, Nordstrom BL, Garvey AJ, Kinnunen T

presently available [5, 6]. Femaleslikely comprise a high percentage of thisheavily addicted, long-term populationof smokers. While there is debate in theliterature as to whether or not womenhave had greater difficulty with smokingcessation during the past several years[7-13], there is clear evidence thatgender differences in smokingprevalence declined during the secondhalf of the 20th century with morewomen than men taking up smoking[14]. Accordingly, a precipitous drop insex mortality ratios for lung cancer couldalso be observed during the latter half ofthe 20th century, a decline from a 6.7 to 1male/female ratio in 1960 to 2.3 to 1 in1990 [14].

Several smoking-related variableshave been analyzed for their effects onattrition. Among a sample of femalesmokers [15] and smokers with a historyof depression [3], a high number ofcigarettes smoked per day (CPD) hasbeen found to be associated with missedstudy meetings and attrition. However,in a small study involving Hispanicsmokers (N = 93), Nevid et al. [16]found null results with respect to CPD.Length of prior quit attempts andconfidence that one will succeed havealso been found to influence attrition.Borrelli et al. [2] found that femalesmokers with prior quit attempts of alonger duration were less likely to dropout and both Munoz, Marin, Posner andPerez-Stable [17] and Nevid et al. [16]concluded, perhaps counter intuitively,that Hispanic smokers with higherconfidence in the success of their quitattempt at baseline were more likely todrop out.

In terms of demographic predictors,there is indirect evidence suggesting thatparticipant race may influence attrition.Nevid et al. [16] reported a tendency on

the part of minorities to terminateoutpatient community-based treatmentservices sooner than Whites. Inaddition, there is an oft-reported findingthat members of minority groups tend tobe distrusting of medical research,perhaps due to the mistreatmentminorities have received in past medicalresearch [18 ]. Other demographicvariables that may increase likelihood ofattrition include lower education level[2, 3], (although Nevid et al. [16] foundnull results) and a lower Body MassIndex (BMI) [2, 19]. Given that femalesmokers are likely to have competingfamily responsibilities that may interferewith their commitment to cessationtreatment [20], having children currentlyliving at home may increase likelihoodof attrition. There are also findings thatpoint to a relationship between age andattrition. Fortmann and Killen [8] foundthat enrolled participants in their studytended to be older than qualified non-participants, suggesting that olderindividuals may be more committed tocessation and accordingly, less likely todrop out of studies. However, Curtin etal. [3] and Nevid et al. [16] reported nosignificant relationships betweenattrition and age.

A psychological variable that wouldseem likely to influence attrition isconcern about weight gain since womenfrequently report weight control as areason for smoking [21, 22]. Borrelli etal. [2] found no significant relationshipsbetween weight concerns and attritionthough. In light of the abstinenceviolation effect [23]—the occurrence ofa “slip” during a cessation attempt,which the participant attributes tointernal, stable and global factors (e.g.,personal weakness) —a prediction couldbe made that tendencies toward guiltwould be relevant to attrition.

Attrition in a Multi-Component Smoking Cessation Study for Females 61

According to this scenario, a temporaryslip during a quit attempt would beaccompanied by intense feelings of guilt.Those who are more prone to guilt mayexperience particularly strong feelingsshould such a slip occur. Due to thesefeelings, “high guilt” participants maydecide to drop out rather than magnifytheir guilt by admitting to researchersthat they have smoked.

Data from a clinical trial evaluatingexercise as an adjunctive treatment fornicotine gum among female smokerswere analyzed in order to determinewhich participant characteristics wereassociated with attrition. An analysissuch as this may help to clarify whichsmokers may be at heightened risk forattrition and potentially which attributesshould be addressed by researchers inorder to keep more participants in trialsand make their samples morerepresentative of the smokingpopulation.

METHOD

ParticipantsParticipants were recruited from the

greater Boston, MA area using acombination of radio, newspaper andtelevision advertising. In theseadvertisements, female smokers wereinvited to participate in a quit smokingstudy in which they would receive freenicotine gum and additional treatmentshould they qualify.

The main exclusion criteria werecurrent involvement in exercise at leastonce per week, an average consumptionrate of fewer than five cigarettes per day,active and severe psychiatric illness, ahistory of a serious vascular or cardiaccondition, bleeding peptic ulcers andinsulin-dependent diabetes mellitus.Par t i c ipan ts wi th condi t ionscontraindicated with nicotine gum use

such as temporomandibular jointdisorder, bleeding peptic ulcers,pregnancy or lactation were excluded aswell. Information regarding exclusioncriteria was obtained from a preliminarytelephone screen and a baseline clinicaldiagnostic exercise test/medical screen.

ProceduresThis clinical trial was approved by

the Office for Research SubjectProtection at Harvard Medical Schooland the Human Research Committee atBrigham and Women’s Hospital. Allparticipants were provided with nicotinegum treatment and brief behavioralcounseling and were randomized intoone of three conditions each lasting atotal of 19 weeks (three weeks pre-quitand 16 weeks post-quit). The first wasan exercise condition consisting of 40minute supervised sessions including afive-minute warm-up routine, 30minutes of aerobic exercise (i.e., walkingor running on a treadmill), followed by afive-minute cool down. Participants inthis condition were also stronglyencouraged to take part in home-basedexercise sessions and several suggestions(e.g., walking) were offered. The secondwas an equal-contact control conditionconsisting of health and wellnesslectures. These sessions were of equalduration as the supervised exercisesessions. These wellness sessionsincluded no tangible cessation helpbeyond the brief behavioral counselingthat all participants received. The thirdwas a standard care control conditioninvolving no additional treatmentbeyond the nicotine gum and briefbehavioral counseling. No significantdifferences based on conditionassignment were found for any variablesassessed at baseline.


Those randomized into the exerciseand equal contact control wellnessconditions were asked to attend twiceweekly sessions for five weeks followedby weekly sessions for the remaining 14weeks. Participants in the standard carecondition were provided eight sessionsover the course of the 19-week study.All but one of these sessions took placefollowing the quit date. All sessionswere held in the late afternoon/earlyevening and session locations were inclose proximity to public transportation.Participants were given a payment of$50 upon completion of the study.

Measures and AnalysesA number of smoking-related items

were included in the baselinequestionnaire, including mean cigarettessmoked per day (CPD), duration oflongest prior quit attempt, number ofyears as a smoker and nicotinedependence, which was measured usingthe revised Fagerstrom Test for NicotineDependence (FTND) [24].

The following demographiccharacteristics were analyzed: race,highest level of education, body massindex (BMI), age and number ofchildren currently living at home.

In terms of psychological variables,confidence in the quit attempt wasassessed with a single item rated on afive-point scale from “very slightly ornot at all” to “extremely.” Concernabout postcessation weight gain wasassessed using a scale developed byBorrelli and Mermelstein [25], made upof six items measured on five-pointLikert scales (e.g., “How likely is it thatyou would go back to smoking afterquitting if you gained too muchweight?”) (an alpha of .87 was providedby the authors). Depression wasassessed with the Center for

Epidemiological Studies DepressionScale [26]. The guilt scale wascomprised of five items from thePersonal Feelings Questionnaire-2Revised Scale [27] assessing a series offeelings and behaviors (e.g., “I feltintensely guilty”) for which participantswere to rate their frequency ofoccurrence during the past week on afour-point scale (alpha = .71 from thepresent study).

Participants who met the followingthree qualifications were included inanalyses: 1. passed both the preliminarytelephone screen and the baselineclinical diagnostic exercise test/medicalscreen; 2. were able to be contactedregarding their treatment grouprandomization and 3. provided completebaseline data. Similar to the approachused by Curtin et al. [3], participantswere divided among three participationlevels: 1) early dropouts, who droppedout before making a quit attempt; 2) latedropouts, who made a quit attempt butdid not complete treatment and 3)treatment completers. Minimal criteriafor treatment completion wereattendance at one of the final twoassessments (week 12 or 16) andabsence from no more than two of thenine assessments conducted during the19 weeks of the trial.

Correlation coefficients were used toassess relationships among all predictorvariables and to identify highlycorrelated variables (i.e., over 0.50) forthe purposes of prevent ingmulticolinearity in the main analysis.All variables were entered into apreliminary multinomial logisticregression. In cases of highly correlatedpairs, the weaker predictor was excludedfrom the main analysis. T-tests wereplanned to assess whether participantswho differ with respect to the


d i c h o t o m o u s d e m o g r a p h i cclassifications also differ with respect toany continuous predictor variables thatsignificantly predicted attrition (e.g.,racial differences in guilt scores).

Multinomial logistic regression wasthe main method of statistical analysis,using participation level as the outcomemeasure with treatment completer as thereference group. Treatment groupassignment was also included as apredictor variable because of thepossibility that assignment to either thestandard care control or equal contactcontrol conditions would be associatedwith a greater likelihood of attrition.The lack of definitive findings in theattrition literature did not justifyhierarchical entry of variables into theregression, thus all predictor variableswere entered simultaneously.

Race was dichotomized intoWhite/Non-white, education intograduated/did not graduate from collegeand number of children at home intohave none/have at least one. A logtransformation was conducted in order tocorrect a large positive skew in thedistribution of the length of longest priorquit attempt variable. For all continuousvariables, a value three standarddeviations above the mean wascalculated and scores higher than thisvalue were rounded down to this cutoffpoint to prevent undue influence on thepart of outliers.

RESULTS

Description of SampleSix prospective participants were

excluded at the exercise test/medicalscreening because their resting EKG’srevealed cardiac abnormalities. Anotherindividual who passed the screening wasexcluded because it was determined thatshe was physically incapable of regular

exercise. Of the 267 participants whopassed inclusion criteria, baseline datacould not be obtained from 13 of them,four passed the stress test and providedbaseline data but could not be contactedafterward regarding their grouprandomization and four others submittedbaseline questionnaires with missingdata on at least one key variable, leavinga sample of 246 for analysis in thepresent study.

See Figure 1 for the number ofparticipants in each demographicclassification. The 64 Non-Whiteparticipants included Blacks (n = 42),Hispanics (n = 10), Asians/PacificIslanders (n = 2) and “other” (n = 10).The 133 participants who did notgraduate from college included thosewho had some college or technicalschool (n = 106), high school graduates(n = 25) and those who did not graduatefrom high school (n = 2). The majorityof participants (55%) were single andnever married, while 24% wereseparated/divorced/widowed and 21%were married. At the time of the trial,78% of participants were employed fullor part-time. Participants had smokedfor an average of almost 21 years (M =20.71, SD = 10.07) and their averagenicotine dependence score was 4.89 (SD= 2.34), considered a moderate level ofdependence based on population norms[24].

Attrition and DemographicsTwenty-three percent of the sample

completed treatment, 28% dropped outearly and 49% were late dropouts. Therewere no significant differences inlikelihood of attrition based on treatmentgroup assignment.


See Figure 1 for the percentage ofparticipants in each demographicclassification who dropped out andcompleted treatment. Non-whites, those

who had not graduated from college andthose with at least one child living athome were more likely to have droppedo u t o f t h e t r i a l .

Figure 1. Percentage of participants in each demographic classification who dropped out and completed treatment

0%

10%

20%

30%

40%

50%

60%

Early dropout

Late dropout

Treatment completer

Education

White(n = 182)

Non-White(n = 64)

Collegegraduate

(n = 113)

Non-graduate

(n = 133)

Have none(n = 158)

Have at least one(n = 88)

Children at home?Race

Prediction of AttritionThree pairs of predictor variables

were found to be highly correlated, all atp < .001: age with number of years as asmoker (r = 0.92), depression with guilt(r = 0.59) and mean cigarettes smokedper day (CPD) with nicotine dependence(r = 0.64). A preliminary multinomiallogistic regression including all variablesindicated that age, guilt and CPD werestronger predictors of participation level,thus the other three variables wereexcluded from the main analysis.

Univariate descriptives for allcontinuous predictor variables includedin the main regression by participationlevel are included in Table 1. Thevariables entered into this regression

were found to be a good fit for the data,X2 (24, N = 246) = 63.67, p < .001. Onlyone variable, having children living athome, was a significant predictor of bothearly and late dropout. Having at leastone child living at home placedparticipants at higher risk of attrition.Among the predictor variables, non-white race, guilt and weight concernswere predictive of early, but not latedropout, while increasing age was aprotective factor decreasing thelikelihood of early dropout. Not havinggraduated from college was a significantpredictor of late, but not early dropout(Table 2). None of the smoking-relatedvariables included in the main analysissignificantly predicted attrition.


TABLE 1. Means and Standard Deviations for Continuous Predictor Variables by Participation Level----------------------------------------------------------------------------------------------------------------

Participation level

Early Late Treatment Totaldropout dropout completer(n=68) (n=121) (n=57) (N=246)

----------------------------------------------------------------------------------------------------------------Age 36.01 37.80 39.91 37.80

(10.24) (9.52) (9.92) (9.88)Demographicvariables Body Mass Index (BMI) 27.15 26.08 26.10 26.38

(4.33) (5.62) (5.07) (5.17)----------------------------------------------------------------------------------------------------------------

Cigarettes per day (CPD) 17.99 18.39 18.12 18.21(8.34) (8.13) (8.32) (8.20)

Smoking-related Longest prior quit attempt 215 343 612 370variables (in days) (413) (683) (982) (718)

Log transformed version of 1.65 1.89 2.05 1.86 longest prior quit attempt (0.90) (0.86) (1.07) (0.93)

----------------------------------------------------------------------------------------------------------------Confidence in quit attempt 2.34 2.46 2.58 2.46 (0-4 scale) (1.05) (0.89) (0.93) (0.94)

Psychological Guilt (0-15 scale) 2.76 2.27 1.72 2.28variables (2.88) (2.37) (1.93) (2.45)

Weight concern (1-24 range) 13.25 12.01 10.82 12.08(5.82) (5.77) (5.73) (5.81)

----------------------------------------------------------------------------------------------------------------Standard deviations in parentheses


TABLE 2. Summary of Multinomial Logistic Regression Analysis Predicting Attrition (N = 246)----------------------------------------------------------------------------------------------------------------

Early Dropout Late DropoutGroup Assignment _ SE OR (95% CI) _ SE OR (95% CI)

Stan. Carea -0.47 0.70 0.63 (0.16–2.48) 0.43 0.52 1.54 (0.56–4.29)

Wellnessa 0.51 0.44 1.66 (0.71–3.90) -0.32 0.39 0.73 (0.34–1.55)

DemographicsAge -0.06* 0.02 0.94 (0.90–0.99) -0.04 0.02 0.96 (0.93–1.00)

BMI 0.00 0.04 1.00 (0.92–1.08) -0.02 0.04 0.98 (0.92–1.06)

Children at home? B 1.22* 0.49 3.39 (1.31–8.78) 1.07* 0.43 2.90 (1.26–6.70)

Education c 0.79 0.44 2.20 (0.94–5.19) 0.88* 0.38 2.41 (1.16–5.02)

Race d 1.41** 0.54 4.10 (1.41–11.87) 0.66 0.50 1.93 (0.73–5.11)

Smoking VariablesCigarettes per day 0.04 0.03 1.04 (0.99–1.10) 0.02 0.03 1.02 (0.97–1.07)

Longest quit attempt -0.33 0.23 0.72 (0.46–1.12) -0.13 0.20 0.88 (0.60–1.30)

Psychological VariablesConfidence in quit attempt -0.23 0.22 0.79 (0.51–1.23) -0.19 0.20 0.83 (0.56 –1.22)

Guilt 0.23* 0.09 1.25 (1.04–1.51) 0.16 0.09 1.17 (0.99 –1.39)

Weight concerns 0.07* 0.04 1.08 (1.00–1.16) 0.03 0.03 1.03 (0.97 –1.10)----------------------------------------------------------------------------------------------------------------a Reference group: assignment to exercise groupb Reference group: have no children living at homec Reference group: graduated from colleged Reference group: White race* p < .05 ** p < .01 *** p < .001


Results of correlation coefficientswere examined in order to clarifyrelationships among continuouspredictor variables. Participant age waspositively correlated with cigarettessmoked per day (r = 0.36, p < .001) andduration of longest prior quit attempt (r= 0.20, p = .001). Guilt was positivelycorrelated with weight concerns (r =0.18, p = .005) and negatively correlatedwith confidence in the quit attempt (r = -0.15, p = .022). No other continuouspredictor variables entered into the mainregression were found to be significantlycorrelated.

Given that age and duration oflongest prior quit attempt weresignificantly and positively correlatedand that only age was found to be asignificant predictor in the mainanalysis, a decision was made on a post-hoc basis to run a follow-up regressionwith age eliminated. If longest prior quitattempt was found to be a significantpredictor of attrition in the absence ofage, this would suggest that age acted asa proxy for this variable in the mainanalysis. With age omitted from theregression, length of longest prior quitattempt significantly predicted early (_ =-0.46, SE = 0.22, OR = 0.63, 95% CI:0.41-0.97) but not late dropout,suggesting that, at least to a degree, ageacted as a proxy for this variable in themain analysis.

A series of t-tests were conducted inorder to determine whether participantswho differed in terms of race, educationand having/not having children alsodiffered with respect to any continuousvariables that significantly predictedattrition in the main regression. Onlyone significant difference was found.Participants with children living at home

(M = 1.68, SD = 2.20) had significantlylower guilt scores than those withoutchildren at home (M = 2.61, SD = 2.52),t (244) = 2.89, p = .004.

DISCUSSION

Attrition in the present clinical trialwas predicted to a considerable extent bydemographic variables. Having at leastone child currently living at home was aparticularly strong predictor of attrition,while Non-White race predicted earlydropout and not having graduated fromcollege predicted late dropout. Thathaving at least one child living at homepredicted attrition above and beyondeducational attainment and race suggeststhat this may have been due to the addedresponsibilities faced by women withchildren [20]. The findings for Non-White race are in accordance with theobservations of Nevid et al [16]and theadded risk faced by those with lowereducational attainment replicatesfindings reported by Borrelli et al. [2]and Curtin et al. [3]. Future research,especially involving open-endedmethods, could help to clarify whywomen with one or more of these threerisk factors are more inclined to drop outbefore completing participation. At thevery least, researchers should be madeaware that participants conforming toone or more of these demographicclassifications are at a much higher riskof attrition and should be sensitive to theprobability that these women faceadditional challenges in their efforts toremain in research studies.

Increased age was a protective factorin that the older an individual was, theless likely they were to drop out beforemaking a quit attempt. This finding is in


accordance with Fortmann and Killen’s[8] observation that enrolled participantstended to be older than qualified non-participants. It is important to note thatage was a significant predictor of earlydropout even with length of longest priorquit attempt included in the regression,meaning that the protective quality ofage was due to more than just thetendency for older participants to havehad longer prior quit attempts. Areplication of the effect of age onattrition and an explanation of thisfinding would be valuable avenues forfuture research.

Feelings of guilt predicted anincreased likelihood of attrition. Aspeculative link can be made betweenthese findings and the abstinenceviolation effect [23]. Those who reportgenerally higher levels of guilt atbaseline may have particular difficultydealing with actual or anticipated “slips”during cessation treatment and choose todrop out as a result. Further research isneeded to better understand relationshipsamong guilt, the abstinence violationeffect and likelihood of attrition.

That weight concerns predicted earlydropout is in accordance with findingsthat many women who smoke, in part,do so in the attempt to maintain theirweight [21, 22]. Concerns about actualor anticipated weight gain apparentlycontributed to a decision to drop out forsome women in the present trial. Thisfinding diverges from that of Borrelliand colleagues [2], who found no effectof weight concerns on attrition.

The attrition rate for the present trialwas higher than rates typically reportedin the literature. The high rate ofattrition could have been due to anumber of factors. Our treatmentprotocol required attendance at a total of24 sessions at our site in Downtown

Boston for those randomized to theexercise or equal contact controlconditions, in addition to at-homeexercise for the exercise group anddirections to use a dozen or more piecesof nicotine gum per day. Thecommitment required was likely seen asdaunting for all but those participantswho were highly motivated to quit.Those for whom the treatment was notefficacious tended to be reticent toremain in the study and attend sessionsregularly. High attrition rates are notunheard of in this literature, though. In arecent 13-week trial for women featuringgum plus cognitive-behavioral groupcounseling, approximately one-third ofparticipants were reported to havedropped out by the fifth week of thetrial, when smoking cessation was tohave been completed (Ginsberg et al.,1997). Attrition rates of over 50% arealso not unusual in clinical trials testingtreatments for alcohol and opiatedependence [29, 30]. It has been arguedthat a high percentage of the smokingpopulation is highly addicted and hasbeen smoking for many years [29, 30].Irvin and colleagues [5, 6] proposed thatcessation will be increasingly difficultfor this population of smokers. Whilethe sample in the present trial can beclassified as moderately nicotinedependent on average, they smokedalmost a pack of cigarettes per day andhad smoked for an average of overtwenty years. Given the long smokingcareers and heavy use of cigarettesamong those in the present sample, thehigh rate of attrition in this trial was notentirely surprising.

Attrition is a serious problem forboth researchers and participants inclinical trials. As a result, researchersare beginning to report analysesconcerning attrition, but further work is


needed if this problem is to be properlyaddressed, especially since researchfindings to this point have beenequivocal. While all researchers shouldconsider conducting and reportingattrition analyses, results from large,representative community sampleswould be particularly useful, given thatthe majority of published attritionfindings have come from trials involvingspecialized samples [e.g., 2, 3, 16] .Smokers dropping out of clinical trialsare likely those who are most in need ofassistance in quitting. Attrition thereforedecreases the likelihood of successfulquitting and increases the probabilitythat smokers will eventually facemorbidity and mortality. For thesereasons, learning more about participantswho drop out can only help to enhancecessation programs and as a result,benefit smokers, researchers and publichealth as a whole.

ACKNOWLEDGMENTS

Support was provided by NIH/NIDAgrant DA-12503 to Taru Kinnunen. Theauthors would like to thankGlaxoSmithKline (formerly SmithKlineBeecham) for supplying the nicotinegum used in the study. The authorswould like to thank Dr. L. HowardHartley, M.D. from the Brigham andWomen’s Hospital, Boston, for hisvaluable contribution in the testingprocedures of the study participants.

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Attrition in a MultiComponent Smoking Cessation Study for Females

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