self-efficacy, health locus of control, and smoking cessation

m Addictive Behaviors. Vol. 19. No. I. DD. I-I?. 19~4

j Pergamon

Copyright 0 1994 Elsevie; Science Lrd Printed in the USA. All rights reserved

0306-4603194 $6.00 + .00

SELF-EFFICACY, HEALTH LOCUS OF CONTROL, AND SMOKING CESSATION

KAREN STUART Office of ‘Psychiatric Services, Health Department of Victoria, Australia

RON BORLAND Centre for Behavioural Research in Cancer, Carlton South. Victoria. Australia

NANCY McMURRAY Department of Psychology. University of Melbourne

Abstract - This article examines the predictive value of measures of health locus of control and self-efficacy as predictors of outcomes of a widely disseminated, group-facilitated smoking cessation program. Outcomes studied were cessation for at least I day by the end of the program, end of program smoking status (abstinence), and smoking status at 6 months follow-up. Subjects were 257 participants in the smoking cessation program. of whom 207 made attempts to quit and 126 who were not smoking at the end of the treatment. Both pretreatment self-efficacy and health locus of control variables emerged as significant predictors of making an attempt and end of treatment abstinence, Only posttreatment self- efficacy predicted maintenance at 6 months. The results indicate the high self-efficacy is inversely related to making attempts to quit, but positively related to the success of attempts. The role of Health Locus of Control is complex and needs further investigation.

Smoking cessation treatments continue to be plagued by high relapse rates (Brandon, Tiffany, Obremski, & Baker, 1990). One approach to reducing relapse has been to consider cessation as a series of stages (Prochaska & Di Clemente, 1983; Prochaska, Di Clemente, & Norcross, 1992). Predictors of outcome have been found to be heterogeneous across the stages of the change process (Rosen & Shipley, 1983; Prochaska, Di Clemente, Velicer, Ginpil, & Norcross, 1985; Prochaska, Velicer, Di Clemente, & Fava, 1988).

The present study examined the possible relationships between both self-efficacy for smoking cessation and Health Locus of Control on three smoking cessation outcomes following attendance at a widely disseminated group smoking cessation program of demonstrated efficacy (Clarke, Hill, Murphy, & Borland, in press). The three outcomes of interest were making a quit attempt, being abstinent the end of treatment, and abstinence at 6 months follow-up (maintenance). These outcomes relate respectively to the following stages or stage transitions of Prochaska et al. (1992): (a) preparation to action, (b) stability of action, and (c) action to maintenance.

Health Locus of Control (HLC) is multidimensional (Levenson, 1974; Wallston, Wallston, & De Vellis, 1978) with independent beliefs that health outcomes are contingent upon (a) personal behavior (Internal HLC), (b) other powerful people (Powerful Others HLC), and (c) forces such as fate or chance (Chance HLC).

This paper is based on a MA in Clinical Psychology at University of Melbourne of the first author supervised by the second and third authors. Financial assistance from the Anti-Cancer Council of Victoria is gratefully acknowledged, as is the help of the Victorian Smoking & Health Program who coordinate the smoking cessation courses, and allowed us access to those courses.

Requests for reprints should be sent to Ron Borland. Centre for Behavioural Research in Cancer. I Rathdowne Street, Carlton South, Victoria 3053, Australia.

2 K. STUART et aI

Little has been published on the prediction of making a quit attempt using self- efficacy and HLC. One would expect that those who had high self-efficacy and Internal HLC beliefs would be more likely to make an attempt because they believe it is up to them to change their behavior and believe they have the ability to do so. Likewise, one would expect those who had high Powerful Others HLC would be more likely to make an attempt during a cessation treatment because they believe it is up to course facilitators (powerful others) to change their behavior and they have access to such people during treatment. There are no published studies using HLC as predictors of making a quit attempt. Recently. Borland. Owen, Hill. and Schofield (1991) found that self-efficacy (assessed by a single-item measure) had no bivariate relationship with making an attempt. However. multivariate analysis revealed a relationship that was opposite to that expected: low self-efficacy scores predicted making an attempt. Clarification of the relationship between self-efficacy and attempting cessation is required, given this unexpected finding.

High pretreatment self-efficacy is both theoretically and empirically related to end- of-treatment abstinence (Russell, Armstrong, & Patel, 1976; Di Clemente, Pro- chaska, & Gibertini, 19X5), but little is known about HLC beliefs. It would be expected that those with high Internal HLC and Powerful Others HLC beliefs would maintain cessation until the end of the program because they have the personal resources or support from those who they believe are responsible for their health (i.e., course facilitators). However, Rosen and Shipley (1983) found that Internal HLC did not predict initial control of reduction in smoking.

Of the stages of cessation considered here. most published research has focused upon the maintenance stage. In reviewing this research, it is important to make the distinction between variables measured before treatment and variables measured at the end of treatment as self-efficacy should and does strengthen over treatment (Condiotte & Lichtenstein, 1981; McIntyre, Lichtenstein, & Mermelstein, l983), while HLC should remain stable (Lau, 1981).

Pretreatment self-efficacy has not been shown to be predictive of posttreatment maintenance (Walker & Franzini, 1985: Nicki. Remington, & MacDonald, 1984). The relationship between end-of-treatment self-efficacy and posttreatment maintenance is inconclusive. End-of-treatment self-efficacy has been positively related to I- to 3-month maintenance (Condiotte & Lichtenstein, 1981; McIntyre et al.. 1983; Nicki et al., 1984), but some inconsistent results have been obtained regarding longer-term (5 months or more) maintenance, with Di Clemente (1981) finding an effect at 5 months, while Nicki et al. (1984) found no effects for either 5 months or I2 months maintenance, and McIntyre et al. (1983) found no effects for 6- and 12-month maintenance.

Results from research regarding HLC and posttreatment maintenance are also inconsistent. Shipley (1981) found that those with high pretreatment Internal HLC were more often abstinent over a 6-month period, but no relation for either Powerful Others or Chance HLC. Walker and Franzini (1985) found HLC beliefs measured during treatment unrelated to six months maintenance. By contrast, Horwitz, Hindi- Alexander and Wagner (198.5) found recidivism at 1 year was predicted by high pretreatment Powerful Others HLC, although not by the other two HLC scales.

There has been little research conducted to study the interrelationship between HLC and self-efficacy within the field of smoking abstinence. Wojcik (1988) appears to be the only researcher to study both, using them to predict 3-month smoking status for two samples (self-quitters and program quitters). He found that self-

Predicting smoking cessation 3

efficacy was the strongest predictor of self-treated abstainers, while Powerful Others HLC beliefs was the strongest predictor for the program treated relapsers. Unfortu- nately, Wojcik did not state when the variables were measured.

METHOD

Subjects There were 385 subjects, 174 males and 211 females, who enrolled in Fresh Start

smoking cessation programs conducted by a variety of community agencies in Victo- ria, Australia (Clarke et al., in press). All programs were conducted by trained facilitators who are trained and licensed by the Victorian Smoking and Health Pro- gram (the agency coordinating smoking control activities in the State). Sixty-three percent of the sample were recruited from programs conducted at workplaces (Workplace programs), while the rest were recruited from programs conducted at community centres (Community programs). The average age of the subjects was 36 (SD = 10.8), and approximately half had white collar and/or professional occupations.

Design The study was concerned with three binary outcomes:

I. Making an attempt (attempters vs. continued smokers): attempters were defined as those who stopped smoking for at least 1 day by the end of the course, while continued smokers had not stopped for a day by the end of the course.

2. End-of-treatment (abstainers vs. early relapsers): of those who attempted to quit (as defined above), those who were consuming no tobacco at the end of the course were defined as abstainers and those who were consuming any tobacco each day were defined as early relapsers.

3. Six-month follow-ups (maintainers vs. late relapsers): of the abstainers at end-of-treatment, those who were not smoking at follow-up were defined as maintainers, and those who were smoking as late relapsers.

This design necessarily resulted in fewer subjects for each successive analysis (structural dropouts).

Definition and measures of variables The measures administered at the end of the first treatment session included: sex,

age, tobacco consumption (in units, one unit being a cigarette, cigar, or pipe), number of previous quit attempts (5 ordered categories), longest time spent abstinent (9 categories). number of years smoked (9 categories), and behavioral expectations variables. The latter assessed the expectation (“likelihood”) to stop smoking (a) for at least I day by the end of treatment, and (b) permanently. Subjects were asked to respond to these two questions using linear analogue scales, where 100 represented “certain” and 0 represented “definitely won’t.”

Self-efficacy was measured using 14 items from the Confidence Questionnaire developed by Condiotte and Lichtenstein (1981), the two with the highest factor loadings for each of the seven clusters found by Condiotte and Lichtenstein (1981). Principal components analysis was conducted on the 14-item pretreatment self-efficacy scale. Results revealed no evidence of the seven clusters obtained by Condiotte and Lichtenstein (1981), or of the three factors identified by Velicer, Di Clemente,

-l K. STUART et al

Rossi, and Prochaska (1990), and as the 14 items loaded on a general factor, the self- efficacy scale was used as a single measure. This is consistent with Baer. Holt, and Lichtenstein’s (1986) suggestion that the original scale is better scored as a unitary scale.

The health locus of control was assessed with the three Multidimensional Health Locus of Control Scales of Wallston, Wallston. and De Vellis (1978), using 5-point Likert scales.

At the end of treatment, tobacco consumption, self-efficacy and health locus of control were measured again and subjects were asked whether they had stopped smoking for at least I day since the course began and about current tobacco consumption. In addition. subjects’ attendance was obtained from the course facilitators’ records.

At h-month follow-up, subjects were asked if they were currently smoking. Those who were smoking were asked if they had stopped for a day or more since the end of the course, and if so, how long had they remained abstinent. Those who were currently smoking were asked how many slip-ups and relapses they had since their abstinence attempts during the treatment. Slip-ups were defined to subjects as smoking on 1 day but stopping within 14 h. and relapse was defined as smoking on 2 or more consecutive days and then abstaining.

Ttmttttcttt - ’ ‘Fwsh Strrrt” stnokitlg ccsscrtirtti pr0grrttn.s

The Fresh Start program is a widely disseminated program used in both community settings and workplaces throughout Victoria, Australia. The program involves eight group sessions within a 4-week period (i.e.. twice weekly). It is based on a cognitive behavioral model of change and is similar to other smoking cessation programs. It consists of education about why people smoke. the negative effects of smoking both long term and short term, and the benefits of quitting. It includes information about common withdrawal symptoms, side effects of abstaining, and techniques to monitor and cope with withdrawal symptoms for recovering in the event of slip-ups. Participants are taught relaxation, stress management. and techniques for changing thinking patterns. The program also involves homework exer- cises such as keeping consumption diaries. identifying high-risk settings. and developing strategies to cope in these settings without smoking. The programs conducted in the workplace and community do not significantly differ in format or information provided. However, the session length in the workplace courses was sometimes shorter.

Both pretreatment and end-of-treatment questions were added to standard Anti- Cancer Council of Victoria (ACCV) evaluation questionnaire booklets, and subjects were asked to complete the pretreatment and end-of-treatment questionnaires as part of ongoing evaluation studies. Both questionnaires were designed to be completed and returned within the treatment sessions. The 6-month follow-up questions were unique to this study.

To minimise nonstructural drop-out rates, all subjects who did not return the posttreatment questionnaires within the sessions were sent a copy of the questionnaires and a note requesting that they complete them. The 6-month follow-up proce- dure was first by mail, and then by phone for those who did not return the reminder copy of questions. All those who were contacted by phone agreed to respond.


All analyses were carried out using the UNIX version of SPSSX. Subject characteristics of drop-outs were compared with those still in the study using t tests or analysis of variance as appropriate. Variables with skewed distributions were re- coded to better approximate normality.

MANOVA was used to analyse univariate relationships between predictor variables and outcomes in one set of analyses even though the outcomes were binary, as it was easier to perform list-wise deletion of cases with missing data on variables to be used in the discriminant analyses. In an effort to minimise listwise exclusion of subjects due to missing data on one or more predictor variable, successive stepwise discriminant analyses were conducted initially including all predictor variables, then successively including only the variables which were significant, until all variables entered remained significant for the increased sample size. Patterns were analysed using both function coefficients and the correlation of each variable with the function. This allows exploration of redundancy between variables and is useful for interpreting effects which are not apparent in the bivariate analyses.

RESULTS

Subjects’ characteristics Subjects smoked an average of 2.5 (SD = 11.4) units (cigarette and/or cigar and/or

pipe) per day for an average of 18 years (SD = 9.8). They had made a median of 2 to 3 previous attempts to quit and stayed stopped for 4 to 5 weeks (median) on their longest previous attempt. Consumption was significantly greater for males (27 c/f 24 units a day; t = 2.48, &= 358, p < .05) and among community program subjects than for workplace subjects respectively (27 c/f 24 units a day, t = 2.56, df = 361, p < .05). Community subjects had significantly higher expectations that they would quit for at least 1 day (t = 3.50, df= 342, p < .Ol), had significantly lower expectations to quit permanently (t = 1.98, & = 334, p < .05), and had more previous quit attempts (t = 2.26, df = 366, p < .05) than subjects from workplace centres. Given these subjects’ characteristics, source of recruitment was included in the discriminant analyses.

Reduction in sample sizes Table 1 outlines sample sizes obtained, and sample sizes used for the final discrimi-

nant analyses, for each outcome (grouping) variable. Apart from the expected reduction due to the design of the study, sample sizes were further reduced because of drop-outs and missing data.

The 128 subjects who dropped out between pre- and end-of-treatment did not significantly differ on any of the predictor variables. The 30 subjects who dropped out between end-of-treatment and 6-month follow-up were found to have significantly longer periods of previous abstention than those who remained in the study (t = 2.11, df = 122, p < .05). Although 6-month follow-up data were collected from 96 subjects, one subject obtained an end-of-treatment self-efficacy score that was four standard deviations below the mean, so the data for this individual was dropped from the analyses.

Predictors of attempting to quit Univariate analyses revealed that compared with nonattempters, attempters had

significantly stronger pretreatment expectations that they would (a) stop smoking for

K. STUART et al

Table I. Sample sizes obtained (and sample sizes used in discriminant analyses) for each outcome variable

End-of-treatment outcomes Six-month follow-up

Making an attempt Abstinence Maintenance II = 2.57 01 = 217)* II = 207 (II = 180) II = 95 (II = 87)

Nonattempters n = 50 (n = 42)

vs. Attempters + Early relapser\

II = 207 (II = 175) n = 81 tn = 70) vs.

Abstainet-s * Late relapsers n = IX 01 = I IO) II = 39 01 = 35)

v,. Maintainer\

,I = 56 (II = 52)

‘~Sample \ize\ used in final multivariate anal! \e\

at least one day by the end of the course [f(229) = 3.49, p < .OOl]. and (b) quit permanently this attempt [t(225) = 3.20, p < ,011, and had attended more sessions of the course [t(254) = 2.30, p < .OS]. Initially. 14 variables were included in the stepwise discriminant analysis.

After conducting a series of analyses, seven variables remained significant using 217 subjects’ data. The seven variables that contributed to the final discriminant analysis, their associated standardized canonical function coefficients, and their correlations with the discriminant function, are presented in Table 2.

Consideration of the standardized function coefficients and correlations with the function indicate that attempters are more likely to be male. and be from workplace programs. Prior to treatment, attempters had higher expectations that they were going to quit both for at least I day and permanently from this attempt. had less strong Internal HLC beliefs, and smoked less per day, than continued smokers. Although self-efficacy was uncorrelated with the discriminant function. it entered the discriminant function after the expectation variables with low self-efficacy being associated with making an attempt.

The variables not in the discriminant function were age, number of sessions attended, Powerful Others and Chance HLC, number of years smoked, previous quit

Table 2. Standardized canonical discriminant functmn coefficients and canonical correlations with the function for discriminating

between attempters and nonattempters

Pretreatment variables Function Correlations

coefficients with function

Behavioral expectation to (a) Quit for 1 day

tb) Quit this time Amount smoked per day Self-efficacy Internal HLC Sex Source of recruitment

Predicting smoking cessation

Table 3. Standardized canonical discriminant function coefficients and correlations with the function of discriminating between

end-of-treatment abstainers and early relapsers

Pretreatment variables Function Correlations


Expectation to quit for I day 0.63 0.73 Self-efficacy 0.51 0.66 Powerful Others HLC -0.27 -0.32 Chance HLC 0.47 0.26

attempts, and length of longest previous attempt. Using the discriminant function, 66% of the subjects were correctly classified, and this did not vary markedly between predicting attempters (66%) and nonattempters (69%).

Predictors of end-of-treatment abstinence Univariate analyses revealed that prior to treatment, abstainers had significantly

higher expectations that they would stop for 1 day by the end of the course [t(l85) = 3.30, p < .Ol], were more likely to think they would quit permanently [t( 183) = 2.19, p < .05], and had higher self-efficacy [t(181) = 3.01, p < .Ol] than early relapsers.

Successive discriminant analyses were conducted on the same 14 variables as for predicting making an attempt, to discriminate between abstainers and early relapsers until 4 variables remained significant using 180 subjects’ data. The standardized canonical function coefficients, and correlations with the function for each significant variable are presented in Table 3.

The results indicate that prior to treatment, abstainers had higher expectations that they would quit for at least 1 day, higher self-efficacy, lower Powerful Others HLC, and higher Chance HLC than early relapsers. Using this function and 179 subjects’ data, 58% of the cases were correctly classified, 57% correctly classified as early relapsers, and 60% correctly classified as abstainers.

Changes in self-efjcacy and HLC beliefs over treatments Subjects’ self-efficacy significantly increased over the course [F( 1,213) = 63.01,

p < .OOOl], and a significant interaction effect occurred between the three groups [F(1,213) = 41.95, p < .OOOl]. Planned comparisons indicated that abstainers’ self- efficacy increased more over treatment than relapsers’ self-efficacy. and both increased more than those who continued to smoke.

Subjects’ Powerful Others HLC beliefs significantly increased over treatment [F(1,211) = 4.95, p < .05], but no interaction effect was observed between outcomes. Subjects’ lnternal and Chance HLC beliefs did not change over treatment [Internal HLC: F(1,212) = 0.70 ns, Chance HLC: F(1,211) = 0.27 ns]. and no interaction effects occurred [Internal HLC: F(1,212) = 1.39 ns; Chance HLC: F(1,211) = 0.78 ns].

Predictors of &month posttreatment maintenrrnce Twenty-seven percent (n = 26) of the 95 subjects completed the 6-month follow-up

questionnaire by phone because they did not return it by post. Subjects who were contacted by phone were found to be less likely to be maintainers [X?(l) = 6.21, p < .05]. They also had shorter past periods of not smoking prior to treatment (t = 3.26,

K. STUAKT et al

Table 4. Standardized canonical dixriminant function coefticients and correlations with the function for discriminating between

maintainers and late relapsers 6 month\ after- treatment

Variable Function Correlation\


End-of-treatment Self-efficacy

Length of previous abstention

No. of previous attempts Age Method of follow-up

&= 93, p < .Ol), and stronger end-of-treatment Internal HLC beliefs (t = 2.10. &= 86, I) < .OS), than subjects who responded by mail. Therefore. method of follow-up (mail vs. phone) was included in the discriminant analysis as a potential discriminating variable.

Of the 95 subjects followed up at 6 months, Sh (59%) had maintained cessation, but I4 had had slip-ups and 6 subjects had had intervening periods of relapse. Sepa- rate analyses conducted treating these last six subjects as late relapsers, produced essentially the same results as those presented below.

Apart from method of follow-up, the only significant bivariate difference between maintainers and late relapsers was that maintainers had survived longer on previous quit attempts.

Successive stepwise discriminant analyses were conducted on I9 variables (the I4 used in the previous analyses, end-of-treatment self-efficacy and HLC scales, plus method of follow-up) to discriminate between maintainers and late relapsers until 5 variables remained significant using 87 subjects’ data. The standardized canonical function coefficients, and correlations with the function for each significant variable are presented in Table 4. Maintainers tended to be younger, have higher posttreatment self-efficacy, had abstained for longer periods of time during their longest previous attempt, had fewer previous quit attempts, and were more likely to respond to the follow-up questions by mail than late relapsers. Using the discriminant function and 87 cases, 69% of subjects were correctly classified, 67% correctly classified as maintainers, and 71% correctly classified as late relapsers.

II I S C U S S I 0 N

The present study found that self-efficacy and HLC beliefs were predictors of aspects of the process of smoking cessation, but generally only in multivariate

analyses. Self-efficacy was related to the three stages of cessation studied, but its role varied

across stages. In addition, self-efficacy was found to increase over the course of treatment, among those who made attempts, but not among nonattempters.

Contrary to the expected theoretical relationship (Bandura, l986), low pretreatment self-efficacy was related to making an attempt, but only in multivariate analyses. Although the negative relationship was unexpected, it is consistent with the findings of Borland et al. (1991). In both the present study and Borland et al.‘s. measures of expectations were included among the predictor variables and self-


efficacy became significant only after the effects of the expectation variables were removed. As expectation variables are proposed to be combinations of self-efficacy and motivation (Sutton, 1989), once the effects of expectations are removed, it may unmask a tendency for some smokers with low self-efficacy to make quit attempts, perhaps without strong motivation to succeed (see also Borland et al., 1991).

The result that pretreatment self-efficacy predicted early abstinence in both unin- variate and multivariate analyses is consistent with Bandura’s (1986) theory and previous research (Russell et al., 1976; Di Clemente et al., 1985). However, pretreatment self-efficacy was not related to maintenance 6 months after treatment, support- ing previous findings (Walker & Franzini, 1985; Nicki et al., 1984). This provides further evidence that pretreatment self-efficacy is not useful in understanding maintenance some months beyond the end of treatment, even when considered with other variables known to be associated with maintenance.

The present study also found no bivariate relationship between end-of-treatment self-efficacy and maintenance which is consistent with previous research (McIntyre et al., 1983; Nicki et al., 1984). However, when a multivariate approach was adopted, maintainers were found to have higher self-efficacy than late relapsers. This multivariate result is consistent with the only previous study that adopted a multivariate approach (Di Clemente, 1981). The findings suggests that end-of-treatment self- efficacy is important in understanding maintenance, but that its relationship may be masked by effects of other variables.

Taken together, results regarding self-efficacy provide support for Harris’ (1985) argument regarding the inadequacy of using univariate results to select variables for multivariate analyses. The results also clearly indicate that self-efficacy is not limited to prediction of self-quitting as Wojcik (1988) inferred but is also useful in predicting program quitters.

HLC was found to be significant in understanding making an attempt and end-of- treatment abstinence but relationships were only revealed using multivariate analyses. No relationships were found between any pretreatment or end-of-treatment HLC beliefs and maintenance. Powerful Others HLC was found to change over the course of treatment, and this change only occurred among early relapsers.

In the multivariate analyses attempters had lower Internal HLC than nonattempters after considering expectation variables, self-efficacy, and tobacco consumption. It may be that an additional subgroup of smokers attempted to quit for other reasons but believed that they were unlikely to control the outcome of an attempt. Alterna- tively, it may be that the subgroup generally do not believe that they control their health but do control making a quit attempt.

There were no univariate relationships between any pretreatment HLC beliefs and abstinence. These findings are inconsistent with Shipley’s (198 1) results, but support findings of Walker and Franzini (1985). In the multivariate analyses, the direction of the relationships were opposite to the anticipated direction: abstainers tended to have strong beliefs that their health was contingent upon chance, and that it was not contingent on powerful others, but there was no effect for Internal HLC. It is difficult to explain why people who believe that chance plays little role in their health (low Chance HLC) were more likely to relapse. The finding of a reverse effect for Powerful Others HLC may be because those who place most reliance on powerful others are more likely to be unprepared for the demands abstinence places on them.

As expected, Powerful Others HLC was found to increase over treatment. By contrast, Horwitz, Hindi-Alexander, and Wagner (1985) found that Powerful Others

HLC did not increase between pretreatment and l-year posttreatment. The two findings are potentially reconcilable. It may be that Powerful Others HLC changes during contact with cessation program facilitators (i.e., powerful others). but following the end of treatment Powerful Others HLC may decrease back to its original pretreatment level. As the increase in Powerful Others HLC occurred irrespective of the outcome of treatment, it is likely that the treatment itself influenced such beliefs rather than outcomes of the treatment.

Consistent with previous research (Sutton, 1989), both behavioral expectation variables were directly related to making a quit attempt and were the strongest contributors to discriminating between attempters and nonattempters. Interestingly, both expectations provided unique contributions in the discriminant analysis even though they were moderately correlated. It was unexpected that a high expectation to quit for at least I day would be better predictive of early abstinence than expectations of long-term maintenance. Subjects may have difficulty developing accurate expectations regarding permanent change, and thus their expectations to quit for 1 day may be more accurate estimates of their capacity to stay stopped in the shot-t term. The failure to find any relationship with expectations of permanent cessation and 6-months maintenance is congruent with this explanation.

As was the case for other variables, smoking history variables had different relationships with the three stages of change studied here. Results based largely on multivariate analyses indicated that attempters were lighter smokers than nonattempters, and maintainers had smoked for fewer years. had longer previous periods of abstention, but had fewer previous quit attempts than late relapsers. These results are consistent with other findings (Hallett & Sutton, 1988: Mothersill. McDowell, & Rosser. 19X8).

Attempters were more likely to be recruited from workplace centres as compared with community centres than nonattempters. This finding suggests that the context of recruitment influences initial action. although it appears to have no impact on other outcomes. The finding that those who needed a reminder telephone call at 6 months follow-up were less likely to be maintainers reinforces the need to do exhaus- tive follow-up if estimates of cessation rates are to be representative.

As differences occurred for both sources of recruitment and method of 6-month data collection, caution must be taken in interpreting and generalizing multivariate results for late maintenance and making an attempt. In addition, as the sample sizes for the early abstinence and late maintenance multivariate analyses were relatively small. the generdlizability of the results cannot be assumed without replication. However, the consistency of the later analyses across an alternative definition of maintenance (total abstinence for the entire follow-up) suggests that the results arc unlikely to be due to any idiosyncrasy of definition. However, the reduced power of the analyses due to smaller sample size means that small contributions from some of the variables found to be nonsignificant in this study cannot be ruled out. It should also be noted that the findings are based on self-report of smoking status. However, as self-report of smoking status is generally accurate (Kozlowski & Heatherton. 1990: Vclicer. Prochaska, Rossi, & Snow. 1992). the results are unlikely to be arti- facts of systematic errors in measurement.

Apart from the theoretical implications, the current results have practical implications for future cessation treatments. Cessation programs could be tailored specifi- cally to the phase the smoker is in. Initial treatment should focus on increasing motivation and influencing expectations in succeeding to quit. Once the person stops

Predicting smoking cessation II

smoking, treatment could focus on altering specific HLC beliefs and increasing confidence in their ability to refrain from smoking. Treatment that is tailored to a particular cessation stage should improve success rates.

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