Examining the effectiveness of a community-based self-help program to increase women's readiness for...

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American Journal of Community Psycgology [ajcp] PP128-301309 April 17, 2001 13:57 Style file version Nov. 19th, 1999

American Journal of Community Psychology, Vol. 29, No. 3, 2001

Examining the Effectiveness of aCommunity-Based Self-Help Program to IncreaseWomen’s Readiness for Smoking Cessation1

Lindsey R. Turner,2 Osvaldo F. Morera, Timothy P. Johnson,Kathleen S. Crittenden, Sally Freels, Jennifer Parsons,Brian Flay, and Richard B. WarneckeUniversity of Illinois at Chicago, Chicago, Illinois

This study investigated the effectiveness of two components of a smoking ces-sation intervention: a reading manual and a series of televised programs. Fe-male smokers in the Chicago metropolitan area with a high school educationor less were interviewed at 4 different times: baseline, immediate postinter-vention, and 6 and 12 months. We examined the effects of several baselinemeasures (race, age, number of cigarettes smoked, and stage of readiness tochange) and exposure to the intervention components on subsequent stage ofchange. Race, baseline smoking rate, baseline stage, and exposure to both inter-vention components had direct effects on stage at immediate postintervention,with both intervention components increasing readiness to quit. Furthermore,exposure to the manual interacted with baseline stage, such that the manualbenefited women at earlier stages more than women at later stages. Effects ofboth components were sustained at 6 months, and the effects of the manualwere sustained at 12 months.

KEY WORDS: smoking cessation; intervention; stage of change; women.

Cigarette smoking is an important current public health problem, and posesone of the leading preventable causes of premature morbidity and mortality

1This research was supported by grant CA42760 and training grant #CA57699-06 from theNational Cancer Institute. We thank Richard Campbell and three anonymous reviewers forhelpful comments.

2To whom correspondence should be addressed at Health Research and Policy Centers, Uni-versity of Illinois at Chicago, 850 W. Jackson, Suite 400, Chicago, Illinois 60607; e-mail:[email protected].

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0091-0562/01/0600-0465$19.50/0 C© 2001 Plenum Publishing Corporation

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466 Turner, Morera, Johnson, Crittenden, Freels, Parsons, Flay, and Warnecke

(U.S. Department of Health and Human Services [USDHHS], 1990a). Be-cause of the many health dangers of smoking, the National Cancer Insti-tute set a goal of reducing smoking prevalence to 15% by the year 2000(Greenwald & Sondik, 1986). However, despite evidence that the num-ber of adult smokers has declined substantially in past years, estimatesindicate that approximately 25% of American adults continue to smokecigarettes (Pierce, Fiore, Novotny, Hatzandrieu, & Davis, 1989a). Rates ofsmoking have decreased more slowly among women than among men, es-pecially among women with high school education or less (Pierce et al.,1989a; USDHHS, 1989). Furthermore, many of those who have alreadyquit are more affluent and well-educated smokers (Pierce et al., 1989a;USDHHS, 1989), leaving a group of smokers who are less likely to have ac-cess to cessation services offered through traditional avenues such as medicalsettings.

In contrast to a clinic approach, which involves time-intensive multi-session cessation packages often inaccessible to much of the population,community-based public health intervention programs provide a broaderreaching intervention strategy. A majority of smokers are interested in self-directed, efficient approaches (Glynn, Boyd, & Gruman, 1990), which appearto have been effective for many smokers (Fiore et al., 1990). Many smokersreport that they are interested in quitting on their own, and in fact, it ap-pears that most of the smokers who successfully quit have done so withoutthe assistance of any formal services (Fiore et al., 1990). Compared with in-tensive clinical intervention, community-based public health interventionstend to have lower overall quit rates; however, they are able to reach largenumber of smokers at relatively minimal cost, resulting in population quitrates comparable to that of clinical approaches (Curry, 1993; Lichtenstein& Glasgow, 1992). These programs also have the advantage of being ableto reach smokers who might be unlikely to seek services in a clinic setting,such as those not ready to commit the time and effort necessary for a moreintensive cessation program.

In recent years, a number of cessation interventions have been spon-sored by the National Cancer Institute’s Smoking, Tobacco, and CancerProgram (STCP), with many of these utilizing a minimal intervention strat-egy. One of the more common minimal treatment approaches is the use ofreading manuals or booklets that provide information designed to assist inthe cessation process. Reviews indicate that these types of programs can bequite effective (Curry, 1993), particularly when paired with other self-helpmethods, such as telephone counseling (Orleans et al., 1991; Zhu et al., 1996),personalized feedback (Prochaska, DiClemente, Velicer, & Rossi, 1993), andtelevised cessation programs (Gruder, Warnecke, Jason, Flay, & Peterson,

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Effectiveness of a Smoking Cessation Intervention 467

1990; Jason, Tait, Goodman, Buckenberger, & Gruder, 1988). The use of areading manual in conjunction with a televised intervention has been foundto result in increases in quit rates beyond those who receive only a televisedcomponent (Jason et al., 1988).

A number of demographic variables appear to differentially affect pro-gram success. For example, differences in smoking cessation have been as-sociated with race (Warnecke et al., 1991), age (Kviz, Clark, Crittenden,Warnecke, & Freels, 1995), and initial smoking rate (Cohen et al., 1989).However, few studies have examined whether such variables affect partici-pation in cessation interventions, and the effectiveness of that participation.A recent study of women with low incomes found that lower self-efficacy andhigher intention to quit smoking were associated with increased rates of par-ticipation in a cessation intervention (Pohl, Martinelli, & Antonakos, 1998).Reviews of self-help cessation approaches have called for the examinationof such interactions between participant characteristics and the success ofcessation interventions (Curry, 1993). The goal of this study was to examinethe effectiveness of a minimal self-help intervention for smoking cessationamong women and to further examine how differences in several importantbaseline variables influenced those effects.

In many evaluations of cessation programs, outcome has been opera-tionalized by a dichotomy of either abstinence or smoking. More recently,however, smoking cessation has come to be viewed as a process, with multiplestages of readiness for cessation. One of the most influential developmentsin understanding smoking cessation has been the development and applica-tion of Prochaska and DiClemente’s transtheoretical model (Prochaska &DiClemente, 1983; Prochaska, DiClemente, & Norcross, 1992). This stage-based model proposes that behavior change occurs as an individual pro-gresses through a series of identifiable stages of readiness for behavioralchange. Also included in the model are a number of processes of change(Prochaska, Velicer, DiClemente, & Fava, 1988), which differ in importanceand effectiveness at each of the various stages of change (Perz, DiClemente,& Carbonari, 1996). Individual characteristics such as self-efficacy for cessa-tion and perceived costs and benefits of cessation, labeled decisional balance(Velicer, DiClemente, Prochaska, & Brandenburg, 1985), also differ betweenthe stages.

Based on the results of several studies defining these stages and ex-amining characteristics of smokers in each stage (Dijkstra, De Vries, &Bakker, 1996; Prochaska et al., 1992; Prochaska et al., 1994), the stagescan be characterized as follows. In the precontemplation stage, smokersare not thinking of quitting within the next 6 months. They tend to lacka desire to change, perceive more costs than benefits associated with

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quitting smoking, and have low self-efficacy for cessation. In the contem-plation stage, smokers are thinking of quitting within the next 6 months.They also have low self-efficacy but anticipate more advantages to quittingthan do smokers in precontemplation. The preparation stage involves plan-ning to quit smoking within the next month and planning for that attempt.Individuals in this stage are similar to contemplators in terms of self-efficacy,but they have begun to make behavioral changes such as cutting down orhaving attempted cessation in the past year. The action stage involves ac-tually quitting, and includes the 6-month period following cessation, beforea person reaches the final stage of maintenance. The maintenance stage in-volves actually staying quit, and making a long-term adjustment to being anonsmoker.

These stages have been further elaborated to provide finer distinc-tions within the precontemplation stage. Cluster analytic studies have iden-tified separate groups of smokers within precontemplation, with some whoare stuck or “immotive” and others who are progressing, albeit slowly, to-ward cessation (Velicer, Hughes, Fava, Prochaska, & DiClemente, 1995).This distinction between immotives and precontemplators has been sup-ported by subsequent research (Dijkstra, Bakker, & De Vries, 1997; Dijkstra,Roijackers, & De Vries, 1998). Other elaborations of the precontemplationstage have identified three groups of smokers, who differ on levels of moti-vation, confidence, and action (Crittenden, Manfredi, Lacey, Warnecke, &Parsons, 1994).

The ultimate goal of many interventions is cessation of smoking, andoutcomes are often measured in these terms. Recently, however, the stagesof readiness for change have been used as an outcome measure in sev-eral studies (i.e., DiClemente et al., 1991). By using stage of change asa dependent measure and comparing an individual’s readiness to changebefore and after the intervention, one is able to detect increases in readi-ness although cessation may not have occurred. Those who would typi-cally be considered abstinent from smoking are classified within the actionor maintenance stages, whereas the previous stages provide a more finelygrained classification of those who would typically be considered nonab-stinent. Thus, the stages of change encompass more standard measures ofcessation, while providing an approach that identifies intermediate stepsalong the path from smoking to cessation. This allows evaluations of out-come to detect smaller changes, and allows subsequent interventions to bemore precisely targeted (Velicer, Prochaska, Fava, Laforge, & Rossi, 1999).Furthermore, psychometric evaluations of this measure reveal that it is sta-ble and valid, and appropriate for use as an outcome measure (Crittendenet al., 1994; Crittenden, Manfredi, Warnecke, Cho, & Parsons, 1998; Moreraet al., 1998).

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An additional advantage of the stages of change model is that it pro-vides a framework for targeting interventions to smokers in different stagesof readiness for cessation. For example, smokers in early stages of changeperceive many costs associated with cessation, and therefore, an interven-tion that counters this belief by emphasizing the benefits of cessation maybe effective. Studies comparing tailored stage-matched interventions havefound that different types of written materials are differentially effectiveamong contemplators versus preparers (Dijkstra, De Vries, Roijakers, &van Breukelen, 1998). Additionally, interventions designed specifically forpeople who are ready to change their behavior are less effective for thosein earlier stages who are not yet ready to change their behavior (Prochaska,1991). In other words, readiness to change at baseline differentially affectsthe success of an intervention.

As applied to cessation interventions, it can be expected that baselinestage moderates the relationship between exposure to intervention materialsand smoking cessation. Moderator variables are independent variables thatinteract with other independent variables to enhance the predictability ofan outcome measure, beyond the main effects of each independent variable.In the literature on smoking, several variables have been shown to moder-ate the relationship between social influences and smoking tendencies. Forexample, self-efficacy moderates the relationship between social influenceand smoking tendencies (Stacy, Sussman, Dent, Burton, & Flay, 1992), andfamily intactness moderates the relationship between parental smoking andadolescent smoking (Wohlford, 1970).

In the area of smoking cessation interventions, a number of variablesmay have differential effects on the success of interventions; however, fewstudies have specifically examined these moderator effects. In this study,our goal was to determine whether several baseline demographic variablesmoderated the effectiveness of the intervention, specifically, the ability ofthe intervention to promote increased readiness to quit smoking. Based onprevious research and theory, we developed four hypothesized moderatorrelationships. First, previous studies have found that increased exposure toa smoking intervention program led to greater levels of smoking cessation(Warnecke, Langenberg, Wong, Flay, & Cook, 1992), and that televised inter-vention components were utilized more by older smokers than by youngersmokers (Warnecke et al., 1991). Therefore, we hypothesized that televisedmaterials are more effective for older smokers than for younger smokers. Inother words, age moderates the relationship between exposure to interven-tion and smoking cessation.

In addition to the hypothesized Age×Television Exposure interaction,earlier research indicates that other demographic variables may moderatethe relationship between exposure to intervention materials and smoking

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cessation. Warnecke et al. (1991) found that more segments of a televisedintervention were recalled by African American women than by women ofother racial groups; thus, we expected that race would moderate the effec-tiveness of the televised component of the intervention.

Although previous work suggests age and race as moderators of theeffectiveness of the televised component of the intervention, different mod-erators are suggested for the reading manual component. Heavy smokerstend to be more likely to participate in cessation interventions (Glasgow,Klesges, Klesges, & Somes, 1988; Wagner et al., 1990), and to recall moreportions of a cessation manual (Warnecke et al., 1991). Therefore, the use ofa manual may be more effective for heavy smokers than for light smokers.However, evidence from a number of other studies suggests that light smok-ers are actually more likely to quit than are heavy smokers (Cohen et al.,1989; Ockene, Hymowitz, Sexton, & Broste, 1982). Thus, we did not have aspecific hypothesis regarding the direction of a possible interaction betweensmoking rate and effectiveness of the manual.

Finally, the manual used in this intervention was specifically designedfor smokers in earlier stages of readiness (for more details, see Burton, 1993).Thus we expected that baseline stage of change would moderate the effec-tiveness of the manual, such that the manual would be more effective at pro-moting increases in stage of change among those initially in the earlier stages.

METHOD

The data for this paper are from a study that was part of an integratedpublic health intervention designed to promote smoking cessation amongfemale smokers with high school education or less. The intervention wasdelivered in collaboration with the Illinois division of the American CancerSociety and as part of the Great American Smoke-Out in the autumn of 1993.

Procedure

There were several phases to this intervention: a motivational compo-nent, a registration component, and the cessation intervention. The motiva-tional component consisted of a series of three televised commercial adver-tisements that each ran for 2 weeks. These advertisements featured womenlike those in the target population and were designed to place smoking cessa-tion into a context specifically relevant to women. Motivational themes weredesigned to interest women in the idea of quitting, emphasized the benefitsof quitting, and promoted women’s confidence in their ability to quit, ratherthan emphasizing the negative health consequences of continued smoking.

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These segments aired at various times on eight local television stations inthe Chicago area.

Beginning 1 week after the motivational component, the overlappingregistration component included promotional spots that aired on the localNBC television affiliate. These promotions invited women to call a toll-freenumber to receive free information about how to quit smoking. Of the total24,926 women who called, 21% were eligible (high school education or less).These women were sent a copy of the It’s Time booklet (Burton, 1993), de-veloped by project investigators to help women progress through the stagesof change. All ineligible callers received a quit kit prepared by the Ameri-can Cancer Society. A random sample of 1,796 known eligible women werecalled and asked to complete a brief baseline telephone survey regardingdemographic information, smoking patterns, and television viewing habits.Interviews were completed with 1,589, for a response rate of 88.47%.

Following the conclusion of the motivation and registration compo-nents, the televised cessation intervention began. This consisted of a seriesof 10 televised segments on the local NBC affiliate, which aired on the earlyevening broadcast and were repeated the next day on the early morningbroadcast. The segments were hosted by a female reporter, and featuredfour women who had quit during the registration period. These segmentswere designed for use in conjunction with the written materials, and fea-tured topics such as reasons why quitting is important and tips for dealingwith cessation related concerns, including weight control, stress manage-ment, and social situations. The Great American Smoke-Out occurred onthe sixth day of the series and was designated as the quit date.

Although the content of the materials and the televised segments en-couraged quitting, this was not the primary aim of the intervention becauseprevious research (Crittenden et al., 1994; Warnecke et al., 1991, 1992) in-dicates that many of the female smokers who participate in these types ofinterventions are in the precontemplation stage and hence are not readyto quit. Therefore, both the manual and the televised programming weredesigned to provide women with information that they could use whatevertheir level of readiness to quit. The booklet was organized around themesgeared to the stages of readiness to quit, which were addressed in colorcoded pages. The themes were introduced with the phrase “It’s time to . . .”and then included “Think About It,” “Get Ready,” “Get Started,” “Do It,”and “Keep At It.” The televised segments featured models whose pictureswere also used in the booklet. Daily themes were also selected to addressproblems these women faced as they went through the process of decid-ing whether to quit and then trying to do it. Because the programming wasorganized around the Great American Smoke-Out, there was a quit datethat smokers could choose to target. However, the programming was not

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organized around a process, more around stories about the models’ effortsto quit smoking.

Population Sampling

During a 3-month period ending 1 week prior to the beginning of theintervention components, a baseline population survey was conducted. Thegoal of this survey was to provide a quasi-control sample from which in-formation about the target population could be gathered. Using randomdigit dialing, a sample of women from the Chicago area was screened. Thosewomen who reported that they were smokers and had high school educa-tion or less were asked to complete a brief telephone survey similar to thatadministered to the women who actively registered for the program (seeMeasures section). Interviews were completed with 1,514 women, for a re-sponse rate of 79.14% of all known and estimated eligible women among theinitial sample attempted to be contacted. Of this group, 471 were contactedfor another study, leaving the remaining 1,043 in the population panel.

Data Collection

Immediate Postintervention Survey

The immediate follow-up telephone surveys were conducted over a3-week period, beginning the week immediately after the televised inter-vention. Surveys were completed with 722 of the 1,043 baseline participantsin the population panel, for a response rate of 69.2%. Of the 1,594 baselineparticipants in the registrant panel, data for 17 were found to be duplicate,where the same phone number represented two different women, or whereone woman completed interviews as a member of both the registrant andthe population panel. After removing the duplicate data in the registrantpanel, surveys were completed with 1,287 of the 1,577 baseline women, fora response rate of 81.6%. The greater retention rate in the registrant panelis understandable given that these women had actively responded to the re-cruitment advertisements and were more likely to be interested in continuingwith the study.

Follow-Up Surveys

Follow-up telephone interviews were conducted at 6, 12, 18, and 24months after the postintervention surveys. Only 6- and 12-month data wereused for this study (long-term results are to be reported in a forthcoming

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paper). All eligible sample was released for the 6-month follow-up, regard-less of whether or not the respondent completed an interview at immediatepost. The total sample size for the 6-month wave was 2,617 (1,043 popu-lation and 1,574 registrants). Interviews were completed with 606 womenfrom the population panel and 1,070 from the registrant panel, correspond-ing to response rates of 58.3% and 68.2%, respectively. The remainder ofthe total sample was unavailable due to refusals (n= 375); inability to lo-cate respondents due to numbers that were no longer working, or despitestandard locating procedures such as contacting friends and family, direc-tory assistance, and credit bureaus (n= 322); and eligible respondents notavailable for interview (n= 244).

For the 12-month follow-up, respondents from both panels who com-pleted either the immediate post or 6-month follow-up interview were eli-gible. The total sample size was 2,159 (792 population and 1,367 registrants)and interviews were completed with 455 women from the population paneland 742 from the registrant panel, for response rates of 57.2% and 54.6%, re-spectively. Of the remaining total sample, 260 were unlocatable, 350 refused,and 350 were not available for interview or had died. Nearly a quarter (24%)of the population panel and 13% of the registrant panel were interviewedonly at baseline and were not available at any postintervention waves. Asthis study focused specifically on the effects of exposure to the intervention,which was assessed at immediate post, those participants who responded toonly the baseline survey but not the immediate post follow-up were excludedfrom the current analyses.

Measures

Background Variables

Demographic information gathered at either baseline or the immediatepost survey included age, race, income, and marital and employment status.At baseline, women were asked a series of questions regarding their televi-sion viewing habits, including average number of hours of television watchedper day and whether they had, in the past 5 days, watched the target newsprogram on which the intervention would air.

Smoking Habits

At baseline, women were asked a series of questions regarding theircurrent and past smoking habits and plans for the future. These includednumber of cigarettes smoked daily and whether that was more, less, or the

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same as the number smoked 1 year ago, whether they had a successful 24-hrquit attempt in the past year, and how much they wanted to quit.

Stage of Change

Stage of change, gathered at all timepoints, was categorized based onthe transtheoretical model, and included precontemplation, contemplation,preparation, and action. We used an elaboration of the precontemplationstage (Crittenden et al., 1994) and divided precontemplators into three fur-ther categories. Stage definitions were derived from five questions regardingthe following; whether they plan to quit (yes/no); whether they are seriouslythinking of quitting (yes/no) or cutting down (yes/no); when they plan toquit; and whether they had an intentional 24-hr quit period in the past year(yes/no). Women who were not planning to quit and not seriously thinkingof either cutting down or quitting were categorized as Precontemplation1, women not planning to quit and not seriously thinking of quitting, butseriously thinking of cutting down were Precontemplation 2; and womenplanning to quit or seriously thinking of quitting, but not within 6 monthswere Precontemplation 3. Women who were seriously thinking of quittingand planning to quit within the next 6 months but either not planning toquit within 1 month or had not intentionally quit within the past year werecategorized as contemplators. Women who were seriously thinking of quit-ting, planned to quit within the next month, and had an intentional 24-hrquit episode within the past year were classified in the preparation stage. Atfollow-up timepoints, those who had quit since the last interview wave andwere still abstinent were considered to be in the action stage; however, atbaseline all participants were in either preparation, contemplation, or oneof three precontemplation stages, since nobody had quit yet.

Exposure to the Intervention

At the immediate postintervention survey, women were asked to answera series of questions regarding their exposure to the television and manualcomponents of the intervention. Nine questions asked women whether theyhad or had not seen specific portions of the televised intervention, and 16question asked whether they had or had not skimmed through or read spe-cific parts of the manual. Additionally, women were asked several questionsregarding whether the television series and the manual encouraged them tothink about cessation, whether they attempted cessation, and how helpfulthe intervention was in their cessation attempt.

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Analyses

We first examined the baseline demographic characteristics, smokingpatterns, and television viewing habits of the women in the registrant paneland the population panel, and their exposure to the intervention. We thenexamined the ability of baseline characteristics to predict selection into theregistrant panel and exposure to the intervention components. Before test-ing the moderator hypotheses, we used multiple regression to examine theability of all variables to directly predict stage of change at immediate postintervention.

Consistent with previous approaches to examining moderator variables(Baron & Kenny, 1986; Jaccard, Turrisi, & Wan, 1990; McClelland & Judd,1990), we used multiple regression to assess these interactions. To initiallytest whether any of the hypothesized interactions were significant, we con-ducted a series of regression analyses in which each of the four hypothe-sized interactions was examined separately. As recommended by Cohen andCohen (1983, p. 311), a hierarchical procedure was followed, with the base-line demographic variables and the intervention exposure variables enteredin a first step, followed in a second step by a product term created by mul-tiplying the predictor variable by the moderator variable. The change in R2

was examined to determine whether the interaction accounted for a signifi-cant amount of variance in the criterion variable, above that accounted fordirectly by the moderator and the predictor variable.

We then examined long-term effects of the intervention, by regressing6-month and 12-month stage of change on the baseline variables. Finally, toexamine the possibility of attrition bias at later follow-up waves, we repli-cated the moderator analyses with imputed data.

RESULTS

Our primary interest was in examining the effects of the intervention;therefore, we limited the sample to those women who responded to thesurvey at immediate post and provided data regarding whether or not theywere exposed to the intervention. This resulted in a sample size of 1,287 forthe registration panel and 722 for the population panel. The ages of womenin this study ranged from 18 to 82, with a mean of 45.2 (SD= 14.8). By design,all women who were eligible to participate had no more than a high schooleducation. The breakdown of reported racial group was as follows: 70.9%White, 22.5% African American, 2.7% Latina, 1.3% Native American, and2.4% other. Nearly half (49.9%) were married; 15.2% were single; and 34.8%were separated, divorced, or widowed. Although the sample was selected for

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low levels of education, and many (44%) were unemployed, income levelswere still relatively high, with 35.4% of women reporting yearly householdincomes of above $40,000.

TV Habits

At baseline, women in this sample reported substantial levels of ex-posure to television programming and high levels of exposure to the newsprogram on which the intervention was to be broadcast. Women reportedviewing an average of 2.2 (SD = 2.4) hr of television daily on weekdaysbefore 5:30 p.m. and an average of 3.3 (SD = 2.1) hr daily on weekdaysafter 5:30 p.m. A majority (81%) reported having watched the target newsbroadcast, on the NBC affiliate between 4:30 and 5:30, during the past fiveweekdays, with a mean of 2.9 (SD = 1.9) days.

Smoking Characteristics

At baseline, the women in our sample smoked an average of 20.8cigarettes (SD= 13.3) per day. Reported daily smoking rate tended to clusteraround increments of 5 and 10 (i.e., 10, 15, 20 cigarettes per day). Therefore,we collapsed the scale to group smokers as follows: less than five cigarettesper day (5.8%), 6–15 per day (30.4%), 16–25 per day (41.2%), 26–35 per day(8.3%), 36–45 per day (8.3%), and more than 46 per day (2.9%). Approxi-mately half (52.4%) reported that they were now smoking less than last year,22.9% reported that they were smoking more, and 24.3% reported that theywere smoking the same amount. Many (54.1%) had made an intentional24-hr quit attempt in the past year. A majority (73.8%) reported that theywanted to quit smoking “very much.”

Exposure to the Interventions

Data regarding exposure to the interventions were gathered at immedi-ate post and examined separately for women in the registrant and populationpanels, because of the expectation that women in the population panel wereless likely to have been exposed to the intervention.

Manual Exposure

In the registrant panel, approximately one fourth of the women (27.2%)reported no exposure to the manual. Of these women, 261 (74.6%) reported

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not receiving a manual, although as members of the registrant panel theywere sent one. A number of possible explanations may account for this incon-sistency, including problems with mail delivery, the manual being receivedand discarded by another household member, or the participant simply notremembering having received the manual. This rate of participant recallof receiving materials is fairly consistent with that of studies that utilizemailings. Approximately another fourth (28.7%) reported exposure to all16 parts of the manual, and the remainder of the women were distributedfairly evenly across the intermediate range of exposure, with roughly 3% ofwomen at each of the 1–15 levels of exposure.

Among the 1,026 registrants who reported getting the manual, many ap-peared to regard it favorably, with 49.1% indicating that it encouraged themto think about quitting “very much” and 30.3% reporting that it encouragedthem “somewhat.” A majority (64.5%) reported that the manual led to a quitattempt; however, only 10.5% of women reported that the manual helpedthem to actually quit.

As expected among the population panel, an overwhelming majorityof women (97.2%) reported no exposure to the manual. However, a fewwomen (2.8%) did report some amount of exposure to the manual. Thisfinding is surprising given that the manual was only sent to eligible womenin the registrant panel, and may represent response error.

Because of the nonnormal distribution of manual exposure, and ourprimary interest in examining whether any exposure at all was effective,this variable was consolidated into a dichotomous variable, with those whoreported no exposure scoring “0” and those who reported any amount ofexposure scoring “1.” Exposure to the manual was coded identically for boththe registrant and population panels.

Television Exposure

Registrants reported less exposure to the television series, with 58%reporting having seen none of the segments. The remainder of women werefairly evenly distributed across the remaining categories, with roughly 4%of women at each of the 1–9 levels of exposure. Among the 537 registrantswho reported seeing any part of the television program, many appeared tofeel that it was helpful, with 43.5% and 33%, respectively, indicating that itencouraged them “very much” or “somewhat” to think about quitting. Aswith the manual, a majority (68.4%) indicated that it led to a quit attempt,and again only 10% reported that it helped them to actually quit.

Among the population panel, most women (84.9%) reported no televi-sion exposure; however, some women did report having seen the segments.

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The higher level of television exposure than manual exposure in the pop-ulation panel is understandable, given that the television segments wereavailable for all to see.

As with manual exposure, television exposure was dichotomized forboth the registrant and population panels, with “0” indicating no exposureand “1” indicating exposure to any components.

Registrant Versus Population Panel Differences

Women in the registrant and population panels were expected to differon several characteristics, most notably readiness for smoking cessation, asthe registrants had actively sought to participate in the program and would beexpected to be in later stages of change. Indeed, registrants were more likelythan those in the population panel to be in later stages of change, χ2(4) =523.3, p< .001. Among registrants, 32.4% were prepared for action, 49.3%were contemplative, and 17.9% were in the highest precontemplative stage,with only a few women (0.5%) in the two lowest precontemplative stages.Among the population panel, however, only 10.3% were prepared for ac-tion, 31.6% were contemplative, 26.8% were in the highest precontemplativestage, and 26.1% and 5.2%, respectively, were in the two lower stages.

Women in the registrant panel also differed significantly from thosein the population panel on several important demographic variables. Womenin the registrant panel were significantly older (M = 46.3, SD = 14.5) thanwomen in the population panel (M = 43.1, SD = 15.1), t(1990) = 4.6,p < .001. A larger proportion of women among the registrants (47.8%)were unemployed than that among the population panel (37.4%), χ2(2) =28.8, p < .001, and more of the registrants were African American (27.3%)than were the population panel (15.7%), χ2(4) = 40.0, p < .001. Becauseof these significant differences, and the possibility that the panels differedon other variables not measured, all subsequent analyses included a term tocontrol for panel membership.

Selection Analyses

Because of the univariate demographic differences between panels,these variables were next entered into a multivariate logistic regressionto examine their simultaneous ability to predict panel membership (seeTable I). Additionally, because many of the women in the registrant panelhad not been exposed to the intervention, selection of manual and televi-sion exposure were modeled with two additional logistic regressions (seeTable II).

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Table I. Logistic Regression to Predict Panel Membership by Baseline Variables

Predictor variable B (SE) Wald χ2 Odds ratio 95% C.I.

Baseline stage of change 1.34 (.09) 233.31*** 3.81 (3.21, 4.52)Baseline smoking rate 0.46 (.07) 43.78*** 1.58 (1.38, 1.81)Age 0.02 (.01) 8.26** 1.02 (1.01, 1.03)Race (1 =White) −0.42 (.18) 5.69* 0.65 (0.46, 0.93)Employment (1 = employed) −0.23 (.16) 2.01 0.80 (0.58, 1.09)Marital status (1 = married) 0.11 (.16) 0.49 1.12 (0.82, 1.52)Income −0.14 (.09) 2.53 0.87 (0.73, 1.03)

Overall model 478.51***

Note: N = 2,009; panel membership coded as 1 = registrant.*p < .05. **p < .01. ***p < .001.

Results indicated that those who registered for the intervention weremore likely to be older, women of color, heavy smokers, and at later stagesthan those who did not register. Furthermore, those who actually reportedany exposure to the television were likely to be older, unemployed, and inlater stages of change, and those who reported any exposure to the manualwere likely to be heavy smokers and in later stages of change. This is consis-tent with previous results (Warnecke et al., 1992), indicating that the manualwas used more by heavy smokers than by light smokers.

Prediction of Stage of Change

To test the effects of the intervention on stage of change at follow-up,we performed a hierarchical multiple regression in which stage of change atimmediate post was regressed on intervention exposure and baseline char-acteristics. In addition, a product term was entered in a separate step toexamine the combined effects of manual and television exposure. This termwas created by multiplying the manual and television exposure variables.The final step of the regression is presented in Table III, and indicates thatbaseline stage of change was the strongest predictor, followed by manual andtelevision exposure, which both contributed significantly to the predictionof stage of change at immediate post intervention. Consistent with otherstudies, smoking rate was a significant negative predictor of stage of change.We also found that women of color were more likely to be in higher stagesof change at immediate post. The inclusion of a combined exposure termwas not significant (β=−.06, ns) and did not significantly increase the abil-ity to predict stage of change above that achieved with the other variables(R2 change = .00, F(1, 1926) = 2.7, ns), and therefore, this variable was notincluded in subsequent analyses.

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Tabl

eII

.L

ogis

tic

Reg

ress

ion

toP

redi

ctE

xpos

ure

toIn

terv

enti

ons

byB

asel

ine

Var

iabl

es

TV

expo

sure

Man

uale

xpos

ure

Pre

dict

orva

riab

leB

(SE

)W

aldχ

2O

dds

rati

o95

%C

.I.

B(S

E)

Wal

dχ

2O

dds

rati

o95

%C

.I.

Bas

elin

est

age

ofch

ange

0.42

(.06

)45

.12*

**1.

52(1

.35,

1.72

)0.

89(.

07)

153.

61**

*2.

42(2

.11,

2.79

)B

asel

ine

smok

ing

rate

0.06

(.05

)1.

441.

06(0

.96,

1.17

)0.

22(.

05)

17.5

5***

1.24

(1.1

2,1.

37)

Age

0.02

(.00

)16

.61*

**1.

02(1

.01,

1.03

)0.

00(.

00)

0.95

1.00

(1.0

0,1.

01)

Rac

e(1=

Whi

te)

0.00

(.16

)0.

000.

99(0

.73,

1.35

)−0

.29

(.15

)3.

520.

75(0

.56,

1.01

)E

mpl

oym

ent(

1=

empl

oyed

)−0

.52

(.14

)14

.89*

**0.

59(0

.45,

0.77

)−0

.12

(.14

)0.

760.

89(0

.68,

1.16

)M

arit

alst

atus

(1=

mar

ried

)0.

20(.

14)

1.95

1.29

(0.9

2,1.

60)

0.08

(.14

)0.

381.

09(0

.83,

1.42

)In

com

e0.

09(.

08)

1.32

1.01

(0.9

4,1.

27)

0.00

(.08

)0.

001.

00(0

.86,

1.16

)

Ove

rall

mod

el10

0.37

***

243.

36**

*

Not

e:N=

2,00

9;ex

posu

reco

ded

as1=

yes,

0=

no.

*p<

.05.

**p<

.01.

***p<

.001

.

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Table III. Multiple Regression Analysis to Predict Stage of Change atImmediate Postintervention

Variable B (SE) β

Baseline stage of change 0.50 (.02) .49***Baseline smoking rate −0.06 (.02) −.06**Age 0.00 (.00) −.02Race (1 =White) −0.11 (.05) −.04*Panel (1 = registrant) −0.04 (.07) .02Manual exposure 0.30 (.07) .13***TV exposure 0.25 (.08) .10**Manual × television exposure −0.17 (.10) −.06

Note: R2 = .33. p < .001.*p < .05. **p < .01. ***p < .001.

Moderator Effects

As described in the beginning of the paper, we hypothesized that fourkey background variables would moderate the effects of the intervention.These variables were race, age, daily number of cigarettes smoked at base-line, and stage of change at baseline. Three of the hypothesized interactionterms had nonsignificant regression coefficients (ps> .05), and their additionto the model did not result in a significant increase in the amount of varianceexplained above the “main effects” model. These were the following interac-tion terms: Television×Age, R2 change = .00, F (1, 1926) = .04, ns, Televi-sion × Race, R2 change = .00, F (1, 1926) = .12, ns, and Manual× SmokingRate, R2 change = .00, F (1, 1926) = .22, ns. Only the Baseline Stage ofChange ×Manual Exposure interaction had a significant regression coeffi-cient (β = −.31, p < .01) and resulted in a significant but modest increase,R2 change = .01, F (1, 1926) = 11.11, p < .01.

To further assess this significant interaction, we examined the relation-ship between exposure to the manual and follow-up stage of change at dif-ferent levels of the moderator variable, baseline stage of change. To do so,we conducted another regression analysis, with all variables entered as be-fore except baseline stage of change, which was broken into three categories:precontemplation (including all subtypes), contemplation, and preparation.These were treated as two dummy coded variables, with precontemplationas the contrast. To examine the interaction between baseline stage andmanual exposure, we included three conditional exposure terms that in-dicated manual exposure given baseline stage of change. For example, thefirst conditional exposure term indicated manual exposure among those whowere precontemplative at baseline; those exposed to the manual received ascore of “1,” all others scored “0.” Results of this regression are reported inTable IV.

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Table IV. Multiple Regression Analyses of Stage of Change at Immediate Postintervention,Examining Interaction Between Baseline Stage of Change and Manual Exposure

Variable B (SE) β

Baseline stage (1 = contemplation) 0.91 (.07) .39***Baseline stage (1 = preparation) 1.25 (.10) .46***Baseline smoking rate −0.06 (.02) −.07**Age 0.00 (.00) −.03Race (1 =White) −0.14 (.05) −.06**Panel (1 = registrant) 0.21 (.07) .09**Television exposure 0.16 (.05) .07**Manual exposure given precontemplation 0.68 (.11) .17***Manual exposure given contemplation 0.13 (.08) .05Manual exposure given preparation 0.15 (.10) .05

Note: R2 = .26. p < .001.*p < .05. **p < .01. ***p < .001.

One possible explanation for the decreased effects of manual exposureat later stages of change is that women who start at later stages of changemay slide back to earlier stages such as precontemplation. This backslidingmay negate the apparent effects of the intervention in these later stages.Therefore, we computed crosstabulations to examine the direction of changein stage from baseline to immediate post, for women who were versus werenot exposed to the manual. These were broken down by baseline stage ofchange (see Table V). Indeed, women in later stages did appear to makemore negative change than did those in earlier stages. Although a majority ofwomen starting in precontemplation and exposed to the manual progressedto higher stages of change (63.3%), most women in contemplation stayed

Table V. Differences in Stage of Change From Baseline to Immediate Postintervention,Crosstabulated by Manual Exposure and Baseline Stage

Negative No Positivechange change change

Baseline precontemplation (all 3 substages)a

Not exposed to manual (n = 467) 26 (5.6%) 235 (50.3%) 206 (44.1%)Exposed to manual (n = 169) 7 (4.1%) 55 (32.5%) 107 (63.3%)

Baseline contemplationb


Baseline preparationc


aχ2(2) = 18.38, p < .001.bχ2(2) = 15.24, p < .001.cχ2(2) = 11.01, p < .001.

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the same (60.8%) and most women in preparation dropped to a lower stageof change (56.6%). However, at all baseline stages, those exposed to themanual demonstrated more positive change and less negative change thanthose not exposed. For example, 70.6% of those not exposed to the manualdropped back to later stages, whereas only 56.6% of those exposed to themanual dropped back. Thus, it appears that the intervention is effective notonly in promoting forward movement through the stages of change, but alsoin preventing some of the negative changes that occurs among preparers.

Long-Term Effects

We were also interested in examining possible long-term effects of theintervention, and conducted further regression analyses to predict stage ofchange at 6- and 12-month postintervention. This series of regression anal-yses was similar to those used for predicting stage of change at immediatepost. The baseline demographics of age, race, and smoking rate, in additionto baseline stage of change, were all entered with exposure to the televi-sion and exposure to the manual. In the second stage, various interactionswere examined, each in a separate run. As with the previous analyses, acombined term for manual and television exposure was not significant anddid not significantly increase the amount of variance explained in stageat 6- and 12-month, postintervention and was therefore excluded. Again,only the Baseline Stage × Manual Exposure interaction was significant,at both 6- and 12-month postintervention. These were followed up as be-fore, with manual exposure examined at each of the three stages of change(see Table VI). Findings were similar to those at immediate post; however,

Table VI. Multiple Regression Analyses of Stage of Change at 6- and 12-Month Follow-Up,Examining Interaction Between Baseline Stage of Change and Manual Exposure

6 months 12 months

Variable B (SE) β B (SE) β

Baseline stage (1 = contemplation) 1.00 (.11) .36*** 0.96 (.12) .34***Baseline stage (1 = preparation) 1.26 (.15) .39*** 1.14 (.17) .34***Baseline smoking rate −0.09 (.03) −.08** −0.13 (.03) −.12***Age 0.00 (.00) .02 0.00 (.00) −.01Race (1 =White) −0.19 (.08) −.06* −0.33 (.09) −.10***Panel (1 = registrant) 0.19 (.10) .07 0.15 (.12) .05Television exposure 0.26 (.08) .09*** −0.09 (.09) .03Manual exposure given precontemplation 0.50 (.16) .10** 0.66 (.18) .13***Manual exposure given contemplation −0.12 (.12) −.04 −0.12 (.14) −.04Manual exposure given preparation −0.04 (.15) −.01 0.14 (.18) .04

Note: For both 6 months and 12 months R2 = .17, p < .001.*p < .05. **p < .01. ***p < .001.

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panel status became nonsignificant at both 6- and 12-month postinterven-tion and television exposure had also dropped to nonsignificance by the12-month follow-up.

To control for the possibility of attrition affecting the results at follow-up points, we recomputed these regression analyses with imputed data atimmediate post and 6- and 12-month postintervention. For those individualsmissing stage of change data at any or all follow-up points, the value fromthe previous measurement point was used. That is, for those women missingstage of change data at immediate post, the baseline stage of change valuewas imputed. For missing stage of change data at 6 months, the immediatepost values were imputed, and the 6-month values were imputed for missing12-month data. This assumed no movement either up or down the stages;for example, those women who were contemplative at baseline were alsoassumed to be contemplative at follow-up.3

At immediate post, 30 women were missing stage of change data, 523women were missing stage of change data at 6 months, and 896 womenwere missing stage of change data at 12 months. Results were nearly iden-tical to those just reported. Television exposure was significant at imme-diate post and 6 months, but not at 12 months. Of the four hypothesizedinteractions, only Baseline Stage ×Manual Exposure was significant at im-mediate post and 6 months; however, this was no longer significant at 12months. The pattern of the interaction was identical to that found with-out imputed data; the relationship between manual exposure and follow-up stage of change was strongest for those who were precontemplative atbaseline.

To examine whether a systematic pattern appeared among the missingdata, those women missing data at any follow-up point were compared withthose with a complete data set. A logistic regression revealed that womenmissing data were significantly more likely to be younger, unmarried, andwith lower incomes than women who remained in the study for all follow-up

3In studies with a dichotomous outcome (smoking vs. abstinent), it is appropriate to considerthose who do not respond to be smoking—all participants begin as smokers and, unless demon-strated otherwise, are likely to be smoking at follow-up. With a graded approach such as thestages of change, all stages below maintenance reflect status as a smoker. Although it wouldbe expected that nonrespondents would be unlikely to have quit, it is not necessarily truethat they would decrease in readiness to change. An approach such as classifying all nonre-spondents as precontemplative assumes complete relapse to the earliest stage of change, andmay not necessarily be accurate. For example, a woman who has been at the contemplationstage for the first three timepoints may be more likely to remain contemplative at the fourthtimepoint than to have relapsed to the earliest precontemplative stage. Our method of dataimputation assumes no change over time for those women who are missing data at follow-upwaves. Although this is not as conservative as assuming complete backsliding to the earlieststage, it is reasonably conservative in that it assumes no change, and this is likely to weakenthe ability to detect any positive effects of the intervention.

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Table VII. Logistic Regression to Compare Participants Missing Follow-Up Data to ThoseNot Missing Follow-Up Data

Variable B (SE) Wald χ2

Baseline stage of change −0.06 (.06) 0.91Baseline smoking rate 0.03 (.05) 0.33Panel (1 = registrant) 0.22 (.18) 1.59Age −0.01 (.00) 5.73*Race (1 =White) −0.09 (.14) 0.38Employment (1 = employed) 0.00 (.13) 0.00Marital status (1 = married) −0.33 (.13) 7.13**Income −0.16 (.07) 5.21*Television exposure −0.19 (.13) 2.04Manual exposure −0.09 (.16) 0.32

Overall model 30.36***

Note: Outcome coded as 1 = missing data, 0 = no missing data. −2 Log Likelihood = 1743.*p < .05. **p < .01. ***p < .001.

points (see Table VII). Panel membership, baseline stage of change, smok-ing rate, and exposure to the intervention components were unrelated tocontinued participation in follow-up data collection.

DISCUSSION

In this study, we were interested in assessing the effectiveness of thecomponents of a smoking intervention program that targeted female smok-ers, and whether baseline characteristics of those participants might mod-erate the effectiveness of the intervention. Through a series of regressionanalyses, we found that although baseline smoking rate and race had directeffects on the prediction of smoking outcome, they did not interact signif-icantly with exposure to the components of the intervention. Furthermore,age had neither a direct effect on smoking outcome, nor did it interact withtelevision exposure. These results suggest that although older women andwomen of color were more likely to be in later stages of change at the imme-diate post measurement point, this was not due to increased effectivenessof the manual for these groups. The lack of interactions suggest that thetelevised component of our intervention was equally effective for femalesmokers of various age and race, and the manual was equally effective forsmokers at various baseline rates of cigarette consumption. We expectedthese interactions based on previous work that used abstinence as an out-come, rather than stage of change. Furthermore, our study was unique in itsfocus on a sample of women with high school education or less, whereas otherstudies have included more heterogenenous samples. The decreased demo-graphic variability among our sample may have also decreased the likelihood

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of detecting differences in these variables. Despite the lack of age, race, andsmoking rate as moderators among this specific group of women, we believethat it is important for future outcome evaluations to remain mindful of thepossibility of differential effectiveness of interventions based on initial par-ticipant characteristics. We also believe that interventions can be maximallyuseful and effective when program planners consider the characteristics andneeds of a particular group.

The only significant interaction, that of baseline stage of change withexposure to the manual, indicated that the manual was more effective inincreasing stage of change among women who were initially in the precon-templative stage than among those who were in later stages. Part of thereason for this increase appears to be the greater ability of the manual topromote forward change among those initially in early stages than to preventbacksliding among those initially in later stages.

The nature of this interaction is very important, indicating that compo-nents of an intervention program can be targeted to an individual’s stage ofchange and can work well with those individuals in precontemplative stages.This group is often neglected in smoking research, as its members are, by def-inition, less interested in taking action to stop smoking, which is a necessarycharacteristic for participating in cessation interventions. Recent guidelinesfor cessation program planning have called for tailored programs that alsotarget smokers in early stages of change, increasing motivation for partici-pating in cessation programs and leading toward an ultimate quit attempt(Glynn et al., 1990). Our research has demonstrated that the It’s Time man-ual used in this study can indeed meet that first goal, increasing readiness toquit smoking among those in the precontemplative stages.

Despite fairly high levels of attrition by 12 months following the inter-vention, exposure to the manual continued to be related to stage throughthe 12-month follow-up. However, the direct effects of television exposureceased to be significant by this last measurement point. One possible ex-planation for this finding is that the television programs were briefer andoccurred in a specific time period, whereas women had the opportunity toread and re-read parts of the manual. This would have allowed women toutilize the manual as a reference and to be certain that they understood themessages clearly. In contrast, the television spots were one-time occurrences,with the goal of providing a cue to use the manual. Although there was nota significant interaction between television and manual exposure, it is pos-sible that some of the women who benefitted from having read the manualwere prompted to read the manual because of having viewed one or more ofthe television segments. In this study, the television segments were providedas public service announcements by the local news and, therefore, did notsubstantially increase the cost of the intervention beyond the costs incurred

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from development and dissemination of the manual, and collection of data.It is therefore recommended that both types of intervention be consideredfor further use.

This study’s focus on urban women with a high school education orless provides important information regarding this vulnerable population.Most of the excess in female smoking is among those with low levels ofeducation, and education is one of the best predictors of smoking amongwomen (Pierce et al., 1989a). Smoking rates are expected to decrease mostslowly among those with lower education (Pierce, Fiore, Novotny,Hatzandrieu, & Davis, 1989b). Therefore, if smoking rates are to decrease, itwill be necessary to target groups where smoking is not declining. The needfor interventions serving this population have been emphasized (Glynn et al.,1990; USDHHS, 1990b). However, because of our focus on women with highschool education or less, and particularly those in earlier stages of change,our findings concerning the effectiveness of these reading materials maynot generalize to other self-help intervention programs. Certainly, furtherresearch is needed to determine the generalizability of these findings.

This study is limited in its use of a dichotomy for measuring exposureto the intervention. Because the intervention consisted of multiple televi-sion segments and manual components, a more precise approach could beused to examine whether a dose–response relationship exists between in-creased exposure and better outcomes, and further analyses are underwayto examine these relationships. Nonetheless, even with a simple dichotomousoutcome, we were able to detect a significant effect of the intervention mate-rials, and a significant interaction between baseline stage of change and themanual.

Fairly high attrition was noted in the follow-up waves, and women whodid not respond to the follow-up surveys appeared to differ from those whoremained in the study, with those dropping out being younger, unmarried,and with lower incomes. Perhaps these women are less geographically stablethan older, married women, and therefore are more likely to have movedand been unreachable at follow-up. It is important to note that baseline stageand initial smoking rate did not differ among these groups, and thus, women’sreadiness to change and smoking habits do not appear to affect participationin the follow-up surveys. Furthermore, manual and television exposure didnot differ, indicating that exposure to the intervention components did notresult in different rates of survey dropout than would have occurred withoutexposure to the intervention.

The use of a panel methodology in this study provides several strengths,but also has some limitations. The inclusion of a population panel providesvaluable information about the natural course of smoking habits and cessa-tion patterns in the population that was targeted by this intervention (Freels

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et al., in press). However, because we did not randomly assign women to theintervention, certain selectivity biases may exist. As we found in the selec-tion analyses, women who registered for the intervention were more likelyto be older, women of color, heavy smokers, and in later stages of change.However, this did not necessarily correspond to use of the intervention mate-rials, as the television segments were used more by older, employed womenin later stages of change, whereas the manual components were used moreby heavy smokers in later stages of change.

It is clear that readiness to quit smoking is a crucial variable in determin-ing whether an individual will register for, participate in, and benefit froma cessation intervention. Despite the finding that women in later stages ofchange were more likely to register for and participate in the intervention, itis actually those women in earlier stages that benefited most from their par-ticipation. This emphasizes the importance of targeting these women withproactive recruitment approaches because intervention can be effective forsmokers who report that they are not ready to quit, if they can be motivatedto actually participate in an intervention such as ours.

It has been previously argued that outcome measurement should in-volve a stages of change perspective (Velicer, Prochaska, Rossi, & Snow,1992). Such an approach allows for assessment of changes in readiness toquit, rather than focusing exclusively on actual cessation. This emphasis onincreasing motivation and readiness to quit is an important focus of smokinginterventions. A national advisory panel of the National Cancer Instituterecommended that minimal interventions focus on increasing motivationfor quit attempts, and that these interventions be targeted to stages of ces-sation and particular segments of the population (Glynn et al., 1990). Thisstudy demonstrates that minimal interventions can have significant effects onreadiness for smoking cessation, in particular within a sample of women withhigh school education or less, a population especially in need of assistance.Future smoking cessation research should focus on tailoring interventioncomponents to an individual’s readiness for behavior change. A logical nextstep in research efforts would incorporate tailored interventions throughoutthe entire course of an intervention.

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