Self-Efficacy: A Predictor for Smoking Cessation Contemplatorsin Kuwaiti Adults

Hanan E. Badr and Philip M. Moody

The failure of most of the smoking cessation programs might be due to negligence ofincluding self-efficacy as an imperative factor in changing many adverse behaviorssuch as smoking. This study investigates the role of self-efficacy as a predictor forsmoking cessation contemplators and precontemplators in adult male Kuwaitismoker employees. A sample of 657 Kuwaiti male smokers represented the target pop-ulation. Factor analysis with varimax rotation to the self-efficacy 16-items scale re-vealed four essential factors—mood changes, relaxation, stress, and self-image—forsmoking urge in the studied population. Contemplators had significant higher meanself-efficacy total scores and Factor IV (self-image) subtotal scores thanprecontemplators. Stepwise multivariate logistic binary regression analysis illus-trated that self-efficacy is the first predictor for contemplating smoking cessation fol-lowed by monthly income. Self-efficacy as a cognitive determinant should be consid-ered to mediate improvement in the smoking cessation programs.

Key words: self-efficacy, smoking, contemplators

Many people are still smoking regardless of theknowledge that tobacco smoking is potentially lethaland is considered the single, primary cause of prevent-able, premature death worldwide. Moreover, many ofthe smoking cessation programs fail and a large per-centage of smokers are not even motivated to discon-tinue smoking (Dijkstra & De Vries, 2000).Self-efficacy (SE) may play an imperative, influenc-ing, and effective role in the success of such programs.

SE, a construct derived from social learning theory(SLT), refers to an individual’s conviction that he orshe is capable of executing a course of action to pro-duce a given outcome (Bandura & Adams, 1977). SLTsuggests that there is an interaction among behavioral,personal, and environmental factors. Such factorsthrough the process of reciprocal determination mayimpact an individual’s self-confidence that he or shecan resist an adverse behavior or habit, for example,smoking.

Among employed individuals, it is not clear whatparticular SLT constructs interact with SE beliefs to re-

sist smoking. Employees who work long hours are atincreased risk of smoking (Resnick et al., 1997;Stanton, Oei, & Siva, 1994). One third of young smok-ers reported that they first started smoking regularly atwork (Borland, Chapman, Owen, & Hill, 1990).

Prochaska, DiClemente, and Norcross (1992) notedthat, in attempting to lower the percentage of smokersin the population, intervention programs must aim toencourage precontemplators in the process of quitting.In the framework of the stages of changes model(precontemplation, contemplation, action, and mainte-nance stages), a stage-matched intervention wouldhave to be developed to target smokers and to motivatethem to transfer to the following stage, the contempla-tion stage.

The outcome expectancies refer to the perception ofthe possible consequences of one’s action; perceivedSE pertains to personal action control or agency(Schwarzer & Fuchs, 1995).

The unwillingness of the precontemplators to quitsmoking can be explained due to the interaction amongthe three cognitive variables: the pros of smoking, thecons of smoking, and temptation. Thus, it might be ex-pected that smokers with these different psychologicalprofilesandsubtypesneeddifferent sortsof informationand interference to be inspired in the process of quittingsmoking (Prochaska & Prochaska 1999; Velicer,Hughes, Fava, Prochaska, & DiClemente, 1995).

This study investigated the role of SE as a predictorfor smoking cessation contemplators and precontem-plators in adult male Kuwaiti smoker employees.

International Journal of Behavioral Medicine2005, Vol. 12, No. 4, 273–277

Copyright © 2005 byLawrence Erlbaum Associates, Inc.

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Hanan E. Badr, Department of Community Medicine and Behav-ioral Sciences, Faculty of Medicine, Kuwait University; Philip M.Moody, Department of Community Medicine and Behavioral Sci-ences, Faculty of Medicine, Kuwait University.

This research was funded by a grant from the Research Adminis-tration, Kuwait University (Project No. MC040).

Correspondence concerning this article should be addressed toHanan E. Badr, Department of Community Medicine and BehavioralSciences, Faculty of Medicine, Kuwait University, P.O. Box 24923,Safat 13110, Kuwait. E-mail: hanan@hsc.edu.kw

Method

Study Design and Sampling Procedure

This cross-sectional data were collected as part of amultistage stratified cluster survey designed to assessthe prevalence of cigarette smoking in Kuwait. Thefirst stratification was according to ministries; six min-istries were systematically selected.

The second level of stratification was according tothe number of departments within each ministry; threedepartments were chosen from each ministry, withprobability proportional to the number of employees ineach department.

In the last stage, all the employees in the chosen de-partments were grouped in equal clusters, with eightclusters chosen randomly for inclusion in the study.The details of the sampling procedure are reportedelsewhere (Moody, Memon, Sugathan, El-Gerges, &Al-Bustan, 1999).

All the male Kuwaiti smoker employees compriseda total of 657 (a subsample of the national 4,000 partic-ipants included in the original sample) and representedthe target population of this study. The women who dowork and smoke were too few to be included in thissample.

Study Instrument

An anonymous self-administered questionnaire wascompleted by the studied sample. Socioeconomic dataincluded age, marital status, monthly income, and levelof education. SE to avoid cigarette smoking was evalu-ated using 16-item scale measuring how likely the par-ticipant is able to resist the urge to smoke in differentsituations. Respondents were asked to indicate theirlevel of confidence that they could avoid smoking inthese specific high-risk emotional and social situa-tions. Each statement has a 4-point Likert scale rangingfrom 1 (most of the time) to 4 (not at all) with totalscore ranging from 16 to 64 with the higher score re-flecting higher SE to avoid smoking.

By criterion, smokers who are planning to quitsmoking in the following 6 months are called contem-plators and smokers who are not are called pre-contemplators. The contemplation to quit cigarettesmoking was assessed, and whether the smoker had at-tempted quitting smoking during the 12 months pre-ceding the survey and the number of the attempts if anywas evaluated.

Data Collection and Analysis

Data entry and analysis were done using the Statisti-cal Package for Social Sciences (SPSS) version 12.Student t test, chi-square test, correlation coefficient,and stepwise binary logistic regression were calculated

to estimate the relation between the studied variables ata level of significance of p < .05 and 95% confidenceinterval (CI).

The SE data were subjected to factor analysis usingprincipal component analysis with varimax rotation(oblique method) that produced four factors explainingthe main domains for the urge of smoking. Reliabilitycoefficients between the items within each factor werecomputed.

Results

More than half of the studied male smokers werecontemplators (61.3%). Participants with the highestlevel of education were significantly (p < .05) morecommon in the contemplators than in theprecontemplators (22.1% and 15.7%, respectively);the reverse was found for the lowest level of education(18.1% and 22.1%, respectively) as illustrated in Table1. The table also shows that contemplators have a sig-nificantly higher monthly income than precon-templators (10.7 vs. 6.3, p < .05). No significant differ-ence was observed between the two groups regardingyears of smoking or daily consumption of cigarettes.

Factor analysis with varimax rotation of the 16items of SE produced four factors that explained68.2% of the total variance. These were identified as“mood changes,” “relaxation,” “stress,” and “self-im-age.” Loadings higher than 0.5 were selected for eachfactor. Reliability coefficients were calculated and re-vealed high internal consistency of the items makingup each factor (0.7–0.9). Table 2 illustrates the detailsof the analysis.

Table 3 presents the significant positive correlationcoefficients among individual total scores for the fourfactors. The correlations corresponded to moderate tostrong relations (r = 0.33–0.75, p < .01).

The study revealed that contemplators had signifi-cantly higher mean total SE scores than precon-templators (35.3 and 33.2, respectively, p < .05).Among the four factors yielded, only self-image (Fac-tor IV) subtotal scores were also significantly higher incontemplators (7.9 and 7.2, respectively, p = .001) asillustrated in Table 4. Further analysis of self-imagesubtotal scores revealed higher mean scores amongthose with relapses than those who did not try quittingat all (7.8 and 7.3, p < .05). It also showed a significantrelation with level of education (df = 3, F = 4.551, p <.01).

Stepwise multivariate logistic binary regressionanalysis examined the relation between contemplationto quit smoking as dependent variable (contemplators= 0 and precontemplators = 1) and the differentsociodemographic factors, history of smoking, and SEtotal scores as independent variables. There were63.6% correct classifications. The significant factors in

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the final model are shown in Table 5. SE was the firstpredictor for smoking cessation contemplation; the βwas negative, indicating that participants who have lowSE have an odds ratio of 1.8 to be precontemplatorscompared to the high SE individuals (p < .01). The ef-fect of monthly income as the second predictor de-creased that of level of education (although it was sig-nificant in bivariate analysis). Those with low monthlyincome have an odds ratio of 2.5 to be precon-

templators for smoking cessation than the highmonthly income group (p < .05).

Smoking Background

The study showed that 260 of the contemplators(64.5%) tried to quit cigarette smoking (one to fivetimes) in the previous year of the study but relapsed(Table 1). Self-image (Factor IV) subtotal score was

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Table 1. Sociodemographic Background and Smoking History of the Participants

Variables Contemplatorsa Precontemplatorsb p

Age (M ± SD) 33.2 ± 7.8 32.6 ± 8.2 .382Level of education (%)

Intermediate and below 18.1 22.1Secondary 23.8 18.1 .025Diploma 36 44.1Graduate and above 22.1 15.7

Marital status (%)Single 23.3 28.3 .09Ever married 76.7 71.7

Monthly income (%)< 500 KD (low) 35.7 44.5500–1,000 KD (moderate) 53.6 49.2 .031> 1,000 KD (high) 10.7 6.3

Number of years of smoking (M ± SD) 14.6 ± 7.9 14.8 ± 8.2 .758Daily cigarette consumption (M ± SD) 25.3 ± 15 25.5 ± 16.8 .847Number of attempted quitting during the last year (%)

Once 24.3 02–5 times 35 0 NA> 5 times 5.2 0Did not try 35.5 100

Note. N = 657. NA = not applicable.an = 403. bn = 254.

Table 2. Factor Analysis of Self-Efficacy Scale Using Principal Component Analysis and Varimax Rotation

Self-Efficacy Items Mood Changes Relaxation Stress Self-Image

Factor I: Mood changes (22.4%a, alpha = 0.89b)3. When you feel nervous 0.84 0.26 0.23 —4. When you feel depressed 0.87 0.21 0.18 —5. When you feel bored 0.78 0.26 0.17 0.18

11. When you have finished a meal 0.51 0.41 0.48 –0.2110. When you feel uncomfortable 0.55 0.21 0.52 0.24

Factor II: Relaxation (17.3%a, alpha = 0.83b)1. When you are waiting for someone or something 0.44 0.52 0.25 0.162. When you want to take a break from work or some other activity 0.42 0.61 0.26 —8. When someone offers you a cigarette 0.23 0.73 0.13 0.259. When you are drinking coffee or tea 0.42 0.58 0.44 –0.17

12. When you are talking with someone 0.13 0.61 0.27 0.4Factor III: Stress (15.5%a, alpha = 0.77b)

13. When you have disagreement with other staff 0.44 0.11 0.68 0.246. When you do desk work — 0.25 0.71 0.41

15. When you work with colleagues who smoke 0.31 0.38 0.65 —Factor IV: Self-image (13%a, alpha = 0.66b)

7. When you want to reward yourself for something you have done 0.22 0.49 0.13 0.5714. When you want something in your mouth — 0.23 0.25 0.6916. When you want to feel more attractive — — — 0.79

Note. Loadings > 0.50 are bolded.aPercent of explained variance. bReliability coefficients.

the only factor that showed a significant relation withrelapses as pointed out previously.

Another finding was that only Factor III (stress)subtotal scores had a significant negative correlationwith number of years of smoking and the daily con-sumption of cigarettes (r = –0.1, p < .05 for each). Thismeans that the longer the duration of smoking and themore excessive and the more severe the daily cigaretteconsumption is, the worse the SE subtotal score ofstress is. The other three factors or SE total scores hadno significant association with history of smoking.

Discussion

The findings of this study revealed that moodchanges, relaxation, stress, and self-image are the fouressential factors for smoking urge in the studied popu-lation. These findings are to a great extent in concor-

dance with the factors yielded in Karanci’s (1992)study. This supports the universality of situations thatadvocate use of tobacco among smokers.

The study pointed out that SE is a crucial con-founder of smoking cessation contemplation, becauseserious smokers contemplating quitting displayed sig-nificantly higher scores than precontemplators, and itwas the first predictor in the final logistic regressionmodel. In addition, the finding that self-image (FactorIV) was the only factor that differed significantly be-tween contemplators and precontemplators, and be-tween those with relapses and those who did not try toquit, indicates that poor self-image is the most difficultfactor to resist in the studied sample. A tailored inter-vention program is required to change the disbeliefs inthis cluster of smokers. This might mirror the weight ofself-image in this affluent community especiallyamong the highly educated participants in the study.

On the other hand, for relapses, the other three fac-tors along with SE total scores did not turn out to besignificant factors distinguishing them from those whodid not try quitting. This may indicate the presence ofdifferent cognitive subtypes within the same stage ofcontemplation. Hierarchies of tempting situations cor-respond to hierarchies of SE: The more a critical situa-tion induces craving, the greater the perceived efficacyneeded to prevent relapse (Velicer, DiClemente, Rossi,& Prochaska, 1990).

This finding is consistent with the study by Stuart,Borland, and McMurray (1994) that concluded that SEis a significant predictor of making an attempt to quitsmoking. The same study revealed that high SE is in-versely related to making attempts to quit but posi-tively related to the success of attempts. Adult studieshave found that SE expectations are predictive ofsmoking cessation (Mudde, Kok, & Strecher, 1995).Therefore, those with greater conviction to resistsmoking are more likely to succeed at quitting.

DiClemente et al. (1991) emphasized that publichealth messages have to be addressed to smokers whoare at various stages of motivation. Precontemplators,those who do not think about quitting, require a dissim-ilar message than contemplators who struggle with thepros and cons of quitting. Moreover, those who are pre-pared for action necessitate different kinds of supportthan those who have stopped smoking and confront re-lapse crisis. Smoking cessation precontemplators per-ceive fewer advantages of quitting than contemplators(De Vries et al., 1998).

Socioeconomic status reflected partly by monthlyincome was another confounder for smoking cessationcontemplation. Low income is accompanied with moredifficulties and life hardships that will end up withmore stressful situations, which increases the urge tosmoke. Educational level was a significant factor in thebivariate analysis but was diluted by the strong effectof income in the final multivariate model. Social SE

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Table 3. Correlation Coefficient Among Self-EfficacyFactor Subtotal Scores

I II IIIIV

(Self-Image)

Factor I: Mood changes — 0.75* 0.68* 0.33*Factor II: Relaxation — 0.71* 0.5*Factor III: Stress — 0.49*

*p < .01.

Table 4. Smoking Cessation Contemplation andSelf-Efficacy Total Scores and Factors Subtotal Scores (M ±SD)

SE Scores Contemplatorsa Precontemplatorsb p

SE total score 35.3 ± 10.6 33.2 ± 13 .03Factor I

(Mood changes)10.4 ± 4.6 9.7 ± 4.5 .07

Factor II(Relaxation)

10.4 ± 3.6 10.0 ± 3.5 .21

Factor III(Stress)

7.6 ± 2.6 6.4 ± 2.9 .11

Factor IV(Self-image)

7.9 ± 2.5 7.2 ± 2.8 .001

Note. SE = self-efficacy.an = 403. bn = 254.

Table 5. Significant Factors Associated with StepwiseLogistic Binary Regression Analysis for Predictors ofContemplating Smoking Cessation

Variables Adjusted OR CI p

Self-Efficacy total score 1.76 1.83–3.96 .003Monthly income

LowModerate 2.45 1.13–5.32 .023High (reference group) 1.69 0.87–3.29 .124

Note. OR = odds ratio; CI = confidence interval.

proved to have the strongest association with smoking.Smoking prevention programmers should consider andinclude SE beliefs and the individual intentions tosmoke in the future plans (Holm, Kremers, & De Vries,2003).

Another important finding that SE subtotal stressfactor score is the only factor that is negatively relatedto the duration of smoking and the daily consumptionof cigarettes. This might be due to the existence of highnicotine dependence in these smokers that is difficultto resist in stressing situations. This matches withSchwarzer and Fuchs’s (1995) study, which found thatSE beliefs to resist temptation to smoke predict reduc-tion in the number of cigarettes smoked (r = –.62).Shadel, Shiffman, Niaura, Nichter, and Abrams (2000)found that smokers who have higher levels of nicotinedependence typically smoke in several situations ascompared with smokers who have lower levels of nico-tine dependence. Shadel, Niaura, Goldstein, andAbrams (2001) established that smokers who have amore pronounced nicotine dependency demonstratedincreases in SE to not smoke and coped more effec-tively using cognitive avoidance when provided with aspecific coping instruction.

Moreover, the target population was employeeswho are exposed to new peers, work stressors, and en-vironmental influences that interact with personal fac-tors to increase risk of heavy and regular smoking(Fagan et al., 2003).

The results of this study can be helpful for the ac-complishment of male smoking cessation programs. Itis important for the health education programmers anddecision makers to distinguish between contemplatorsand precontemplators according to the transtheoreticalmodel of change. Moreover, the specific configurationof individual communities should not be neglected inplanning successful antitobacco messages.

References

Bandura, A. J., & Adams, N. E. (1977). Analysis of self-efficacy the-ory of behavior change. Cognitive Therapy and Research, 1,287–308.

Borland, R., Chapman, S., Owen, N., & Hill, D. (1990). Effects ofworkplace smoking bans on cigarette consumption. AmericanJournal of Public Health, 80, 178–180.

De Vries, H., Mudde, A. N., Dijkstra, A., & Willemsen, M. C.(1998). Differential beliefs, perceived social influences, andself-efficacy expectations among smokers in various motiva-tional phases. Preventive Medicine, 27, 681–689.

DiClemente, C. C., Prochaska, J. O., Fairhurst, S. K., Velicer, W. F.,Velasquez, M. M., & Rossi, J. S. (1991). The process of smok-

ing cessation: An analysis of precontemplation, contemplation,and preparation stages of change. Journal of Consulting andClinical Psychology, 59, 295–304.

Dijkstra, A., & De Vries, H. (2000). Clusters of precontemplatingsmokers defined by the perception of the pros, cons, andself-efficacy. Addictive Behaviors, 25, 373–385.

Fagan, P., Eisenberg, M., Frazier, I., Toddard, A. M., Vrunin, J. S., &Orensen, G. (2003). Employed adolescents and beliefs aboutself-efficacy to avoid smoking. Addictive Behaviors, 28,613–626.

Holm, K., Kremers, S. P., & De Vries, H. (2003). Why do Danish ad-olescents take up smoking? European Journal of Public Health,13, 67–74.

Karanci, N. A. (1992). Self-Efficacy-Based smoking situation fac-tors: The effects of contemplating quitting versus. InternationalJournal of the Addictions, 27, 879–886.

Moody, P. M., Memon, A., Sugathan, T., El-Gerges, N., &Al-Bustan, M. (1999). Factors associated with the initiation ofsmoking by Kuwaiti males. Journal of Substance Abuse, 10,375–384.

Mudde, A. N., Kok, G. J., & Strecher, V. J. (1995). Self-efficacy as apredictor for the cessation of smoking: Methodological issuesand implications for smoking cessation programs. Psychologyand Health, 10, 353–367.

Prochaska, J. O., DiClemente, C. C., & Norcross, J. C. (1992). Insearch of how people change, applications to addictive behav-iors. American Psychologist, 47, 1102–1114.

Prochaska, J. O., & Prochaska, J. M. (1999). Why don’t continentsmove? Why don’t people change? Journal of Psychotherapy In-tegration, 9, 83–102.

Resnick, M. D., Bearman, P. S., Blum, R. W., Bauman, K. E., Harris,K. M., Joes, J. et al. (1997). Protecting adolescents from harm.Findings from the national longitudinal study on adolescenthealth. Journal of the American Medical Association, 278,823–832.

Schwarzer, R., & Fuchs, R. (1995). General background(self-efficacy and health behaviours). In M. Conner & P. Nor-man (Eds.), Predicting health behaviour: Research and prac-tice with social cognition models (pp. 1–29). Buckingham,England: Open University Press.

Shadel, W. G., Niaura, R., Goldstein, M. G., & Abrams, D. B.(2001). Cognitive avoidance as a method of coping with a pro-vocative smoking cue: The moderating effect of nicotine de-pendence. Journal of Behavioural Medicine, 24, 169–182.

Shadel, W. G., Shiffman, S., Niaura, R., Nichter, M., & Abrams, D.B. (2000). Current models of nicotine dependence: What isneeded to advance understanding of tobacco etiology amongyouth. Drug and Alcohol Dependence, 59, 9–22.

Stanton, W., Oei, T., & Siva, P. (1994). Socio-demographic charac-teristics of adolescent smokers. International Journal of Addic-tion, 29, 913–925.

Stuart, K., Borland, R., & McMurray, N. (1994). Self-efficacy, healthlocus of control, and smoking cessation. Addictive Behaviors,19, 1–12.

Velicer, W. F., DiClemente, C. C., Rossi, J. S., & Prochaska, J. O.(1990). Relapse situations and self-efficacy: An integrativemodel. Addictive Behaviors, 15, 271–283.

Velicer, W. F., Hughes, S. L., Fava, J. L., Prochaska, J. O., &DiClemente, C. C. (1995). An empirical typology of subjectswithin stage of change. Addictive Behaviors, 20, 299–320.

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