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Psychosocial predictors of smoking behavior change
Sot. Sci. & Med. 1972, Vol. 6, pp. 137-144. Pergamon
Press, Printed in Great Britain.
PSYCHOSOCIAL PREDICTORS OF SMOKING BEHAVIOR CHANGE RICHARD National
Clearinghouse
A. EISINGER
for Smoking and Health, United States Public Health Service
Abstract-A prospective analysis was undertaken in an attempt to discover possible predictors of smoking behavior change. Smokers interviewed in 1966 were interviewed again in 1968. In the two year interim approximately 15 per cent of those interviewed had quit and 20 per cent had reduced smoking consumption. Smoking behavior change was examined as a function of selected demographic, behavioral and attitudinal variables. Univariate and multivariate analyses of the data were performed. A multiple discriminant analysis employing four variables was successful in predicting smoking behavior change. Practical implications of some of the findings were discussed. SINCE the release in 1964 of the Surgeon General’s report on smoking and health, a large number of psychological treatises on the subject of cigarette smoking have been reported [l]. The emphasis of these reports (psychological, physiological, sociological) as well as the approach (survey, experiment, theoretical discourse) has differed from study to study. In general, however, these discussions have concentrated upon the adoption and retention of the smoking habit in terms of psychological, physiological, and sociological concomitants. Only a few have been concerned with the cessation of cigarette smoking. Because of the scientific aversion to retrospective analyses, and/or because of the longitudinal requirement involved in studies of smoking cessation, information relating to the cessation process and associated variables is exiguous. The existing literature relating to the cessation of smoking, although incomplete, has both valuable applied and theoretical implications. The information obtained from these studies could; (1) materially aid professional health specialists who are attempting, through promotional techniques, to dissuade smokers from continuing the habit, (2) abet the smoker who desires to terminate the habit, but who seeks information or assistance to achieve this goal, (3) verify or contradict existing theories and speculation regarding the dynamics of behavior change. The existing literature substantiates a relationship between smoking cessation and a number of demographic variables. Recent studies have shown that quitters are usually older than non-quitters [2], males are more successful than females in giving up smoking [3], and highly educated smokers are not better able to stop smoking than less well educated smokers [4]. Smoking behavior practices have also been shown to relate to smoking cessation. The more cigarettes smoked per day the less likely is a smoker able to give up the habit, and smokers who previously attempted to quit and failed have been found to be ultimately more successful in quitting than smokers attempting to quit for the first time. A comprehensive account of demographic and behavioral characteristics as well as a number of attitudinal responses related to smoking cessation can be found in Guilford’s [5] report. The purpose of the present study is to verify some of the relationships between demographic variables, attitudinal variables and smoking behavior change, to help clarify the inconclusive and contradictory data concerning some of these relationships, and to investigate relationships between smoking cessation and psychosocial variables heretofore 137
138
RICHARD
A. EISINGER
untreated. Moreover, the study will attempt to examine the smoker’s social environment and his attitudes toward smoking as possible predictors of smoking cessation. Finally, two theories, one specifically concerned with smoking cessation and the other relating to type of smoking gratification will be considered for both their predictive and explicative value for smoking cessation. A major objection to much of the empirical literature related to smoking is directed at methods of statistical analysis. Since most of these studies have been of a survey nature, analyses of obtained results have typically been confined to the generation of contingency tables. As Straits [6] has noted, through the utilization of contingency analyses one encounters the danger of explaining the same variance more than once since the size of survey samples rarely permits working with more than two or three variables at a time. By employing a multivariate statistical technique, as will be done in this study, and supplementing this with contingency analyses, data can be treated in a more efficient and flexible fashion, eliminating many of the pitfalls which would occur if either of the techniques were utilized singularly. METHOD
In 1966 one national and two community surveys of smoking attitudes and behavior were conducted for the United States Public Health Service. Area probability techniques and stratification by type of population and geographic area were employed in selecting the national sample. Random procedures were also employed in selecting the samples from two geographically distinct urban communities: San Diego, California, and Onondaga County (Syracuse), New York. Subjects
Following the “National Smoking Test”, a network television program aired in January 1968 by the Columbia Broadcasting System, a sample of respondents interviewed in 1966 was telephoned and questioned about their exposure to the television program and their current smoking habits. The sample was drawn through stratification by sex, education, and number of cigarettes smoked per day in 1966. Of the sample selected for the telephone interview 69.7 per cent of those in Syracuse, 89-9 per cent of those in San Diego and 93.5 per cent of the national group were reached. Of the 433 respondents ultimately interviewed, 278 were classified as “current” cigarette smokers in 1966. The remaining respondents, classified as “former” or “never” cigarette smokers in 1966, were excluded from this analysis. Only four respondents of the 278 could not be classified into one of the four smoking behavior change categories in 1968 (“quit”, “reduced”, “no change”, “increased”). Procedure
The purpose of the interview was not only to ascertain what sort of person was watching the program, but also to determine in what way, if any, the respondents had altered their cigarette smoking behavior since 1966. Of particular interest was the behavior change in the San Diego and Syracuse samples since U.S. Public Health Service community laboratories had been in operation in those cities for more than 2 years. Interviewers began each phone conversation by saying: “Good.. . . . . . , . . . . . ., I am.. . . . . . . . . . . .
. of (Chilton Research Services) (the InterAgency Council on Smoking and Health) (the San Diego Inter-Agency Council). We are talking
PsychosocialPredictors of Smoking Behavior Change
139
to a cross section of people throughout (the country) (Onondaga County) (San Diego) about television viewing,and you were selectedas part of this cross section.” All respondents were then questioned about their television viewing on the night of the “National Smoking Test” broadcast, as well as about their current cigarette consumption. As already noted, each respondent was subjected to an extensive and exhaustive personal interview concerning his smoking attitudes and behavior, conducted in his own home in 1966. Interviewers were supplied with an interview schedule* from which they read a question and its response alternatives to the interviewee and into which they recorded his response. The duration of the interview was between 1 and IQ hours as current smokers were asked more questions than forme; or never smokers. Responses to selected items from the 1966 interview schedule were examined in terms of their predictive value of subsequent success in stopping smoking. Items examined were selected on the basis of their demonstrability in prior studies to differentiate quitters from non-quitters as well as their intrinsic interest and relationship with the problem of smoking behavior change. RESULTS Respondents surveyed in San Diego had greater success in quitting smoking (22.6%) than respondents in the national survey (9.9 %, t = 2.49, p < 0.02) or the Onondaga County survey (9.3 %, t = 2.50, p < O-02). It is likely that this greater success rate is attributable in part to an intensive anti-smoking program sponsored by the U.S. Public Health Service in that city. Of the 274 respondents from the three surveys for whom smoking behavior change was ascertainable, 40 terminated (14*4’/J, 56 reduced (20-l %), 137 did not change (49.3 %) and 41 increased (14.7 %) their smoking consumption. Analyses of relevant variables revealed that respondents in the three surveys were similar in terms of age, sex and education and as a consequence were combined for all further analyses. Of the thirty variables examined, eight (p < 0~001) were found to significantly discriminate between quitters, reducers, no changers and increasers at the O-05 level using chi square analyses. These variables were: sex, number of cigarettes smoked per day, presence of children under 16 years of age in the respondent’s household, respondent’s acquaintance with someone whose health had been adversely affected by smoking, perceived difficulty of stopping smoking, agreement with the statement “research will find a cure long before most of today’s smokers will get any of the diseases smoking is supposed to cause”, score on Tomkins’ addictive typology, and score on Tomkins’ habitual typology. An elaboration of these differences is presented in the following section. Non-significant variables included age, education, smoking status of respondent’s spouse, perceived effects of smoking upon health, advice from physicians to quit smoking, and perceived vulnerability to smoking related diseases. As noted earlier, two models of smoking behavior were examined in terms of their predictive power for smoking behavior change. The first, a model denoting prerequisites for smoking behavior change developed by Horn and Waingrow [7] was not supported by analyses in this study. The second model, developed by Tomkins [S] is an attempt by the author to differentiate types of smokers based upon his theory of the management of affect. Through a scale described by Ikard et al. [9] respondents were scored as high, moderate or low on each of six smoking typologies. As already noted, two of these typologies significantly differentiated quitters, reducers,, no changers and increasers. *The Horn-Waingrow smoking behavior and attitude interview schedule, developed by Daniel Horn and Selwyn Waingrow,National Clearinghousefor Smokingand Health, United States Public Health Service.
140
A. EISNGER
RI-
The expressed purpose of this exposition is to delineate the significance of selected independent variables as predictors of smoking behavior change. Univariate tests will not suffice in this regard since intercorrelations and interactions between independent variables are not taken into account through these methods. The size of the sample and the type of data to be analyzed limit the choice of multivariate approaches which could be employed here. The most efficient multivariate technique which could be applied to the data appears to be a multiple discriminant approach which could permit the analysis of polytomic variables as predictors of smoking behavior change. The discriminant analysis approach employed here is one which achieves optimal discrimination by computing a maximum likelihood function for each respondent in each group (quit, reduced, no change, increased.) In addition, an overall measure of dispersion (Mahalanobis D2) of the four groups according to their configuration on an N variable dimension is calculated. Straits [lo] has noted that in the discriminant model the independent variables must be normally distributed with equal covariance matrices for each group. Although one rarely encounters normal multivariate distributions in the behavioral sciences, the practice has been to employ a discriminant function if prediction is satisfactory. The first multiple discriminant analysis was undertaken by selecting fourteen variables which had been shown to relate to the discontinuation of smoking or to differentiate resTABLE1 COMPARIWNOF ACTUALSMOKINGBEHAVIOR WITHBEHAVIOR PREDICTEDBY THEFOURDISCRIMINANT ANALYSES Actual behavior
Quit
Predicted behavior Reduced No change
Increased
P
Wx2)
df
106.23
36
< GO1
Quit Reduced No change Increased
Based on the 14 variable discriminant 054 0.14 0.06 0.16 0.54 0.20 0.17 0.21 0.39 0.17 0.17 0.23
Quit Reduced No change Increased
Based on the 7 variable discriminant analysis 0.54 0.14 0.06 0.26 0.10 060 0.16 0.14 0.23 0.24 0.33 0.20 0.20 0.12 0.17 0.51
84.87
21
< 031
Quit Reduced No change Increased
Based on the 4 variable discriminant analysis 0.54 0.14 0.06 0.26 0.16 060 0.14 0.10 0.21 0.24 0.28 0.27 0.20 0.23 0.08 0.49
70.59
12
< GO1
Quit Reduced No change Increased
Based on the 3 variable discriminant 0.46 0.17 0.09 0.08 064 0.12 0.19 0.23 0.28 0.23 0.23 0.03
62.37
9
< .OOl
N
Note-Values to 1.00.
(35)
(50)
in cells represent proportion
analysis 0.26 0.10 0.23 0.43
analysis
(123) of respondents
028 0.16 0.30 0.51 (35)
classified into each category.
Row values total
PsychosocialPredictors of Smoking Behavior Change
141
pondents in terms of the four smoking categories through x2 analyses. The selected variables were: (1) number of cigarettes smoked per day in 1966, (2) concern about effect of smoking upon health, (3) perceived possibility of being a smoker in 5 years, (4) perceived difficulty of quitting, (5) agreement or disagreement with the statement “Research will find a cure . . .” (6) number of previous attempts to quit, (7) health of an acquaintance was adversely affected by smoking, (8) others tried to influence respondent to alter his smoking behavior, (9) children present in household, (10) sex, (11) age, (12) education, (13) habitual typology and (14) psychologically addictive typology. Results of this and other discriminant analyses are presented in Table 1. A second analysis was undertaken employing seven variables which were found to be significant through x2 analyses. The third analysis undertaken employed variables with a high x2/df ratio. Four variables were selected for this analysis: # 1, #4, # 5, and #7. The fourth analysis was undertaken by eliminating the variable with the lowest x’/dfratio; perceived difficulty of quitting. In the absence of an adequate stepwise multiple discriminant program (which if available would not necessarily yield the most efficient set of predictors), it appears from Table 1 that the foui variable discriminant analysis is the most efficient and parsimonius in correctly predicting smoking behavior change. No attempt will be made to defend the choice of variables employed in these analyses. However, the evidence demonstrating that four variables have such substantial power in predicting smoking behavior change is extremely significant. Although it was originally intended to extensively evaluate data relating to exposure to the “National Smoking Test”, the small sample prohibited such an analysis. Of the 238 current smokers in 1968 thirty-five (15-O per cent) viewed the program. Evidently, smokers are little different from the general population in their willingness or desirability to expose themselves to dissonant information. DISCUSSION Of those respondents surveyed slightly over 14 per cent had quit smoking between 19661968. Horn [I I] revealed that 7 per cent of the smokers questioned in a U.S. Public Health Service survey had quit between 1964-1966. The increase in rate of quitting may in part be attributable to expanded efforts by the U.S. Public Health Service, American Cancer Society and others to inform the public of the health hazards of smoking. The U.S. Public Health Service now estimates that more than one million people quit smoking each year. The results of this survey provide only moderate support for existing evidence relating demographic variables to smoking behavior change. Males were found to have been more likely to quit and reduce smoking consumption than females. The relationship between smoking behavior change and age and education was, however, not significant. Results also demonstrate that as the number of cigarettes smoked per day increased, rate of quitting decreased. On the other hand, respondents smoking more than 25 cigarettes per day had a higher rate of reducing than respondents smoking between 15-24 cigarettes per day. Respondents classified as “light” smokers (O-14 cigarettes per day) had little opportunity to be classified as reducers and, in fact, none were found to have reduced smoking consump tion between 1966-1968. It seems reasonable to assume that lighter smokers were less dependent upon cigarettes and could contend with the smoking threat by quitting whereas heavier smokers may have found it easier to reduce their smoking consumption to reduce the dissonance associated with maintaining the habit. S.S.M. 6/1--r
142
b.XARD
A,
&SINGER
Respondents reporting children present in their household had a high (43.6 per cent) rate of quitting or reducing smoking consumption. Although many adults seem little concerned about their own smoking behavior they seem quite solicitous about the prospects of their children adopting the habit. Consequently, many parents may wish to present themselves as a proper model to their children by stopping or reducing their cigarette consumption. Respondents who perceived stopping smoking to be easy were more successful in quitting than respondents who perceived stopping smoking to be difficult. Respondents who preferred to quit demonstrated a higher rate of quitting than respondents who preferred to reduce or who preferred no change in their smoking consumption. As one might expect, a person will be more successful in quitting if he is desirous of quitting. However, respondents who do not possess this outlook toward quitting demonstrate a higher rate of reducing cigarette consumption. Perhaps, contrary to what some may have assumed, respondents who choose to reduce their smoking consumption are not compromising due to a failure to quit smoking, but may either be (1) attempting to reduce smoking consumption as an end in itself, or (2) reducing as a step in a series of successive approximations which will ultimately culminate in total elimination of cigarette consumption. Reducers, in other words, may find the “cold turkey” approach of quitting unpalatable and may be utilizing a temporary reduction of cigarette consumption as a confidence boost in preparation for further attempts at reduction of cigarette consumption. Respondents in agreement with the statement that research will find cures for diseases long before most of today’s smokers contract them had a much lower rate of quitting (6.8 per cent) than respondents who disagreed with the statement (18-O per cent). Perhaps future public information efforts should be directed at eliminating this rationalization from the cigarette smoker’s repertoire. Perhaps the most effective predictor of smoking behavior change discovered was the respondent’s acquaintance with someone whose health had been adversely affected by smoking. Of those respondents reporting an acquaintance whose health had been affected by smoking 27.1 per cent quit smoking whereas only 9.7 per cent of those respondents reporting no such acquaintance quit smoking. This finding was not unexpected. A study by DeWolfe and Governale [12] revealed that nurses who were exposed to a high fear condition (assignment to a tuberculosis ward) were much more susceptible to persuasive communications regarding preventive tuberculosis practices than a control group of comparable nurses who were not exposed to tuberculosis patients. From this study and some of his own research Janis [ 131 concluded : ‘6. . . direct confrontation with the threat seems to be extraordinarily effective in breaking through the defensive facade that normally enables a person to maintain an unwarranted but highly cherished attitude of complacency. Once people become convinced of their personal vulnerability to a potential source of danger, then resistance to authoritative recommendations seems to be strikingly diminished.”
l
The crucial point to be emphasized here is that smokers will be more likely to alter their attitudes and behavior towards smoking if they are directly confronted with the threat (e.g., familiarity with someone whose health had been affected by smoking, participation in a role-playing session, etc.) than if they are passively exposed to the same fear arousing information through indirect methods such as television programs or much publicized U.S. Public Health Service warnings. Tomkins’ smoking “types” differentiate smokers on the basis of utility of the cigarette
Psychosocial Predictors of Smoking Behavior Change
143
in the management of affect. Six non-independent “types” exist: the pleasurable relaxation smoker, the stimulation smoker, the handling smoker (all smoke to enhance positive affect), the tension reduction smoker (smokes to reduce negative affect), the habitual smoker (smokes with no affect) and the psychologically addicted smoker (smokes to enhance positive and reduce negative affect). All smokers can be rated on the six types
through a scale devised by Ikard et al., noted earlier. Score on Tomkins’ habitual “type” did not differentiate respondents in terms of rate of quitting. However, it was demonstrated that respondents with a high habitual score had a higher rate of reducing (39-O per cent) cigarette consumption than respondents with a moderate score who in turn demonstrated a higher rate of reducing (27.9 per cent) than respondents ‘with a low score (14-l per cent). This differentiation is most likely due to the high correlation between habitual score and number of cigarettes smoked per day [14]. The identical relationship was found between reducing cigarette consumption and score on Tomkins’ psychologically addictive type. Again, a high correlation has been noted between addictive score and number of cigarettes smoked per day. As a result of their subjacent degree of psychological and physiological dependency upon cigarettes, respondents with a low addictive score demonstrated a higher rate of quitting (18.9 per cent) than respondents with either a moderate (10.6 per cent) or higher (11.2 per cent) addictive score. As was noted earlier, a multiple discriminant analysis was employed in an effort to distinguish predictors of smoking behavior change. Univariate tests were explained to be insufficient for this purpose because of their failure to take into consideration intercorrelations between independent variables. The multiple discriminant approach was chosen in the place of the more commonly employed multiple regression analysis because it retained information lost in a regression analysis by the assumption that the four groups may be positioned on a unidimensional scale. The results of the discriminant analysis demonstrated that the probability of correctly classifying a quitter was as high (O-54)whether twelve, seven or four variables were employed. In what may be the only other discriminant analysis of smoking behavior change utilizing the likelihood function approach, Straits [15] obtained probabilities of O-62 and 0.56 of correctly classifying quitters employing eleven and seven variables respectively (not identical to those employed in the present study). SUMMARY A prospective analysis was undertaken in an attempt to discover possible predictors of smoking behavior change. Respondents subjected to a lengthy interview in 1966 were reinterviewed in 1968 at which time their smoking behavior status was assessed. Respondents were classified as either “quit”, “reduced”, “no change”, or “increased”. Smoking behavior change was examined as a function of responses to the 1966 interview. Males were found to be more likely to quit or reduce cigarette consumption than females. Respondents with children present in their household were more likely to have quit or reduced smoking than respondents reporting no children in their household. As the number of cigarettes smoked per day increased, respondents were less likely to have quit but more likely to have reduced smoking consumption. Eight behavioral and attitudinal variables were demonstrated through univariate analyses to differentiate respondents in terms of smoking behavior change typology: number of cigarettes smoked per day, perceived difficulty of quitting, agreement or disagreement with the statement “Research will find a cure for the diseases smoking is supposed to cause long before any of today’s smokers get them”, acquaintance with someone whose health had adversely been affected by smoking, presence of children in the respondent’s household, sex, score on Tomkins’ psychologically addictive type, and score on Ton&ins’ habitual smoking type. A number of additional variables successfully discriminated “quitters” from “non-quitters”. A multiple discriminant model generating maximum likelihood functions was employed to study the relationship between smoking behavior change and selected psychological and sociological factors demon-
144
RICHARDA. EMNGER
strated through univariate analyses to be related to smoking behavior alteration. Four discriminant analyses were undertaken, employing fourteen, seven four and three variables respectively. The four variable analysis utilizing the tist four variables noted above was successful in predicting respondents who quit and reduced smoking consumption. Practical implications of some of the findings were discussed. REFERENCES 1. 2. ::
2: 7. 8. 9.
10. 11. 12. 13.
:::
IKARD, F., Smoking Bibliography: Selected References, unpublished manuscript, U.S. Public Health Service, National Clearinghouse for Smoking and Health, 1967. HAMMOND,E. C., and PERCY, CONSTANCE, Ex-smokers, N. Y. State J. Med., F&,1958. GUILFORD,JOANFactors related to successful abstinance from smoking, unpublished report, 1966. Sm, B., Sociological and psychological correlates of adoption and discontinuation of cigarette smoking, unpubllished manuscript, 1965. GUILFORD,op. cit. STR~, B., The discontinuation of cigarette smoking: a multiple discriminant analysis, paper presented at the American Sociological Association meeting, 1966. HORN. D.. and WAMOROW. S.. Some dimensions of a model for smoking behavior Change. Am. J. Publ. &th-., 56, 1966. ’ . TOMKINS,S., A psychological model for smoking behavior, Am. J. Pub!. Hlth., suppl. 56, 1966. IKARD. F.. G~EZN. DOROTHY.and HORN. D. The develonment of a scale to differentiate between tvnes of smoking as related to the management of affect, paper presented at the Eastern Psychological Association meeting, 1968. S-rxArrs, 1966, op. cit. HORN, D., Factors affecting the cessation of cigarette smoking: a prospective study, paper presented at the Eastern Psychological Association meeting, 1968. DEWOLFE. A., and GOVERNALE,CATHERINE,Fear and attitude change, J. Ab. Sot. Psych., 69, 1964 JANB, I., Effects of fear arousal on attitude change: recent developments in theory and experimental research, in Berkowitz, L. (ed.), Advances in Experimental Social Psychology, Academic Press, New York. U.S. Public Health Service survey, unpublished data, 1966. Snu\rrs, 1966, op. cit.
Press, Printed in Great Britain.
PSYCHOSOCIAL PREDICTORS OF SMOKING BEHAVIOR CHANGE RICHARD National
Clearinghouse
A. EISINGER
for Smoking and Health, United States Public Health Service
Abstract-A prospective analysis was undertaken in an attempt to discover possible predictors of smoking behavior change. Smokers interviewed in 1966 were interviewed again in 1968. In the two year interim approximately 15 per cent of those interviewed had quit and 20 per cent had reduced smoking consumption. Smoking behavior change was examined as a function of selected demographic, behavioral and attitudinal variables. Univariate and multivariate analyses of the data were performed. A multiple discriminant analysis employing four variables was successful in predicting smoking behavior change. Practical implications of some of the findings were discussed. SINCE the release in 1964 of the Surgeon General’s report on smoking and health, a large number of psychological treatises on the subject of cigarette smoking have been reported [l]. The emphasis of these reports (psychological, physiological, sociological) as well as the approach (survey, experiment, theoretical discourse) has differed from study to study. In general, however, these discussions have concentrated upon the adoption and retention of the smoking habit in terms of psychological, physiological, and sociological concomitants. Only a few have been concerned with the cessation of cigarette smoking. Because of the scientific aversion to retrospective analyses, and/or because of the longitudinal requirement involved in studies of smoking cessation, information relating to the cessation process and associated variables is exiguous. The existing literature relating to the cessation of smoking, although incomplete, has both valuable applied and theoretical implications. The information obtained from these studies could; (1) materially aid professional health specialists who are attempting, through promotional techniques, to dissuade smokers from continuing the habit, (2) abet the smoker who desires to terminate the habit, but who seeks information or assistance to achieve this goal, (3) verify or contradict existing theories and speculation regarding the dynamics of behavior change. The existing literature substantiates a relationship between smoking cessation and a number of demographic variables. Recent studies have shown that quitters are usually older than non-quitters [2], males are more successful than females in giving up smoking [3], and highly educated smokers are not better able to stop smoking than less well educated smokers [4]. Smoking behavior practices have also been shown to relate to smoking cessation. The more cigarettes smoked per day the less likely is a smoker able to give up the habit, and smokers who previously attempted to quit and failed have been found to be ultimately more successful in quitting than smokers attempting to quit for the first time. A comprehensive account of demographic and behavioral characteristics as well as a number of attitudinal responses related to smoking cessation can be found in Guilford’s [5] report. The purpose of the present study is to verify some of the relationships between demographic variables, attitudinal variables and smoking behavior change, to help clarify the inconclusive and contradictory data concerning some of these relationships, and to investigate relationships between smoking cessation and psychosocial variables heretofore 137
138
RICHARD
A. EISINGER
untreated. Moreover, the study will attempt to examine the smoker’s social environment and his attitudes toward smoking as possible predictors of smoking cessation. Finally, two theories, one specifically concerned with smoking cessation and the other relating to type of smoking gratification will be considered for both their predictive and explicative value for smoking cessation. A major objection to much of the empirical literature related to smoking is directed at methods of statistical analysis. Since most of these studies have been of a survey nature, analyses of obtained results have typically been confined to the generation of contingency tables. As Straits [6] has noted, through the utilization of contingency analyses one encounters the danger of explaining the same variance more than once since the size of survey samples rarely permits working with more than two or three variables at a time. By employing a multivariate statistical technique, as will be done in this study, and supplementing this with contingency analyses, data can be treated in a more efficient and flexible fashion, eliminating many of the pitfalls which would occur if either of the techniques were utilized singularly. METHOD
In 1966 one national and two community surveys of smoking attitudes and behavior were conducted for the United States Public Health Service. Area probability techniques and stratification by type of population and geographic area were employed in selecting the national sample. Random procedures were also employed in selecting the samples from two geographically distinct urban communities: San Diego, California, and Onondaga County (Syracuse), New York. Subjects
Following the “National Smoking Test”, a network television program aired in January 1968 by the Columbia Broadcasting System, a sample of respondents interviewed in 1966 was telephoned and questioned about their exposure to the television program and their current smoking habits. The sample was drawn through stratification by sex, education, and number of cigarettes smoked per day in 1966. Of the sample selected for the telephone interview 69.7 per cent of those in Syracuse, 89-9 per cent of those in San Diego and 93.5 per cent of the national group were reached. Of the 433 respondents ultimately interviewed, 278 were classified as “current” cigarette smokers in 1966. The remaining respondents, classified as “former” or “never” cigarette smokers in 1966, were excluded from this analysis. Only four respondents of the 278 could not be classified into one of the four smoking behavior change categories in 1968 (“quit”, “reduced”, “no change”, “increased”). Procedure
The purpose of the interview was not only to ascertain what sort of person was watching the program, but also to determine in what way, if any, the respondents had altered their cigarette smoking behavior since 1966. Of particular interest was the behavior change in the San Diego and Syracuse samples since U.S. Public Health Service community laboratories had been in operation in those cities for more than 2 years. Interviewers began each phone conversation by saying: “Good.. . . . . . , . . . . . ., I am.. . . . . . . . . . . .
. of (Chilton Research Services) (the InterAgency Council on Smoking and Health) (the San Diego Inter-Agency Council). We are talking
PsychosocialPredictors of Smoking Behavior Change
139
to a cross section of people throughout (the country) (Onondaga County) (San Diego) about television viewing,and you were selectedas part of this cross section.” All respondents were then questioned about their television viewing on the night of the “National Smoking Test” broadcast, as well as about their current cigarette consumption. As already noted, each respondent was subjected to an extensive and exhaustive personal interview concerning his smoking attitudes and behavior, conducted in his own home in 1966. Interviewers were supplied with an interview schedule* from which they read a question and its response alternatives to the interviewee and into which they recorded his response. The duration of the interview was between 1 and IQ hours as current smokers were asked more questions than forme; or never smokers. Responses to selected items from the 1966 interview schedule were examined in terms of their predictive value of subsequent success in stopping smoking. Items examined were selected on the basis of their demonstrability in prior studies to differentiate quitters from non-quitters as well as their intrinsic interest and relationship with the problem of smoking behavior change. RESULTS Respondents surveyed in San Diego had greater success in quitting smoking (22.6%) than respondents in the national survey (9.9 %, t = 2.49, p < 0.02) or the Onondaga County survey (9.3 %, t = 2.50, p < O-02). It is likely that this greater success rate is attributable in part to an intensive anti-smoking program sponsored by the U.S. Public Health Service in that city. Of the 274 respondents from the three surveys for whom smoking behavior change was ascertainable, 40 terminated (14*4’/J, 56 reduced (20-l %), 137 did not change (49.3 %) and 41 increased (14.7 %) their smoking consumption. Analyses of relevant variables revealed that respondents in the three surveys were similar in terms of age, sex and education and as a consequence were combined for all further analyses. Of the thirty variables examined, eight (p < 0~001) were found to significantly discriminate between quitters, reducers, no changers and increasers at the O-05 level using chi square analyses. These variables were: sex, number of cigarettes smoked per day, presence of children under 16 years of age in the respondent’s household, respondent’s acquaintance with someone whose health had been adversely affected by smoking, perceived difficulty of stopping smoking, agreement with the statement “research will find a cure long before most of today’s smokers will get any of the diseases smoking is supposed to cause”, score on Tomkins’ addictive typology, and score on Tomkins’ habitual typology. An elaboration of these differences is presented in the following section. Non-significant variables included age, education, smoking status of respondent’s spouse, perceived effects of smoking upon health, advice from physicians to quit smoking, and perceived vulnerability to smoking related diseases. As noted earlier, two models of smoking behavior were examined in terms of their predictive power for smoking behavior change. The first, a model denoting prerequisites for smoking behavior change developed by Horn and Waingrow [7] was not supported by analyses in this study. The second model, developed by Tomkins [S] is an attempt by the author to differentiate types of smokers based upon his theory of the management of affect. Through a scale described by Ikard et al. [9] respondents were scored as high, moderate or low on each of six smoking typologies. As already noted, two of these typologies significantly differentiated quitters, reducers,, no changers and increasers. *The Horn-Waingrow smoking behavior and attitude interview schedule, developed by Daniel Horn and Selwyn Waingrow,National Clearinghousefor Smokingand Health, United States Public Health Service.
140
A. EISNGER
RI-
The expressed purpose of this exposition is to delineate the significance of selected independent variables as predictors of smoking behavior change. Univariate tests will not suffice in this regard since intercorrelations and interactions between independent variables are not taken into account through these methods. The size of the sample and the type of data to be analyzed limit the choice of multivariate approaches which could be employed here. The most efficient multivariate technique which could be applied to the data appears to be a multiple discriminant approach which could permit the analysis of polytomic variables as predictors of smoking behavior change. The discriminant analysis approach employed here is one which achieves optimal discrimination by computing a maximum likelihood function for each respondent in each group (quit, reduced, no change, increased.) In addition, an overall measure of dispersion (Mahalanobis D2) of the four groups according to their configuration on an N variable dimension is calculated. Straits [lo] has noted that in the discriminant model the independent variables must be normally distributed with equal covariance matrices for each group. Although one rarely encounters normal multivariate distributions in the behavioral sciences, the practice has been to employ a discriminant function if prediction is satisfactory. The first multiple discriminant analysis was undertaken by selecting fourteen variables which had been shown to relate to the discontinuation of smoking or to differentiate resTABLE1 COMPARIWNOF ACTUALSMOKINGBEHAVIOR WITHBEHAVIOR PREDICTEDBY THEFOURDISCRIMINANT ANALYSES Actual behavior
Quit
Predicted behavior Reduced No change
Increased
P
Wx2)
df
106.23
36
< GO1
Quit Reduced No change Increased
Based on the 14 variable discriminant 054 0.14 0.06 0.16 0.54 0.20 0.17 0.21 0.39 0.17 0.17 0.23
Quit Reduced No change Increased
Based on the 7 variable discriminant analysis 0.54 0.14 0.06 0.26 0.10 060 0.16 0.14 0.23 0.24 0.33 0.20 0.20 0.12 0.17 0.51
84.87
21
< 031
Quit Reduced No change Increased
Based on the 4 variable discriminant analysis 0.54 0.14 0.06 0.26 0.16 060 0.14 0.10 0.21 0.24 0.28 0.27 0.20 0.23 0.08 0.49
70.59
12
< GO1
Quit Reduced No change Increased
Based on the 3 variable discriminant 0.46 0.17 0.09 0.08 064 0.12 0.19 0.23 0.28 0.23 0.23 0.03
62.37
9
< .OOl
N
Note-Values to 1.00.
(35)
(50)
in cells represent proportion
analysis 0.26 0.10 0.23 0.43
analysis
(123) of respondents
028 0.16 0.30 0.51 (35)
classified into each category.
Row values total
PsychosocialPredictors of Smoking Behavior Change
141
pondents in terms of the four smoking categories through x2 analyses. The selected variables were: (1) number of cigarettes smoked per day in 1966, (2) concern about effect of smoking upon health, (3) perceived possibility of being a smoker in 5 years, (4) perceived difficulty of quitting, (5) agreement or disagreement with the statement “Research will find a cure . . .” (6) number of previous attempts to quit, (7) health of an acquaintance was adversely affected by smoking, (8) others tried to influence respondent to alter his smoking behavior, (9) children present in household, (10) sex, (11) age, (12) education, (13) habitual typology and (14) psychologically addictive typology. Results of this and other discriminant analyses are presented in Table 1. A second analysis was undertaken employing seven variables which were found to be significant through x2 analyses. The third analysis undertaken employed variables with a high x2/df ratio. Four variables were selected for this analysis: # 1, #4, # 5, and #7. The fourth analysis was undertaken by eliminating the variable with the lowest x’/dfratio; perceived difficulty of quitting. In the absence of an adequate stepwise multiple discriminant program (which if available would not necessarily yield the most efficient set of predictors), it appears from Table 1 that the foui variable discriminant analysis is the most efficient and parsimonius in correctly predicting smoking behavior change. No attempt will be made to defend the choice of variables employed in these analyses. However, the evidence demonstrating that four variables have such substantial power in predicting smoking behavior change is extremely significant. Although it was originally intended to extensively evaluate data relating to exposure to the “National Smoking Test”, the small sample prohibited such an analysis. Of the 238 current smokers in 1968 thirty-five (15-O per cent) viewed the program. Evidently, smokers are little different from the general population in their willingness or desirability to expose themselves to dissonant information. DISCUSSION Of those respondents surveyed slightly over 14 per cent had quit smoking between 19661968. Horn [I I] revealed that 7 per cent of the smokers questioned in a U.S. Public Health Service survey had quit between 1964-1966. The increase in rate of quitting may in part be attributable to expanded efforts by the U.S. Public Health Service, American Cancer Society and others to inform the public of the health hazards of smoking. The U.S. Public Health Service now estimates that more than one million people quit smoking each year. The results of this survey provide only moderate support for existing evidence relating demographic variables to smoking behavior change. Males were found to have been more likely to quit and reduce smoking consumption than females. The relationship between smoking behavior change and age and education was, however, not significant. Results also demonstrate that as the number of cigarettes smoked per day increased, rate of quitting decreased. On the other hand, respondents smoking more than 25 cigarettes per day had a higher rate of reducing than respondents smoking between 15-24 cigarettes per day. Respondents classified as “light” smokers (O-14 cigarettes per day) had little opportunity to be classified as reducers and, in fact, none were found to have reduced smoking consump tion between 1966-1968. It seems reasonable to assume that lighter smokers were less dependent upon cigarettes and could contend with the smoking threat by quitting whereas heavier smokers may have found it easier to reduce their smoking consumption to reduce the dissonance associated with maintaining the habit. S.S.M. 6/1--r
142
b.XARD
A,
&SINGER
Respondents reporting children present in their household had a high (43.6 per cent) rate of quitting or reducing smoking consumption. Although many adults seem little concerned about their own smoking behavior they seem quite solicitous about the prospects of their children adopting the habit. Consequently, many parents may wish to present themselves as a proper model to their children by stopping or reducing their cigarette consumption. Respondents who perceived stopping smoking to be easy were more successful in quitting than respondents who perceived stopping smoking to be difficult. Respondents who preferred to quit demonstrated a higher rate of quitting than respondents who preferred to reduce or who preferred no change in their smoking consumption. As one might expect, a person will be more successful in quitting if he is desirous of quitting. However, respondents who do not possess this outlook toward quitting demonstrate a higher rate of reducing cigarette consumption. Perhaps, contrary to what some may have assumed, respondents who choose to reduce their smoking consumption are not compromising due to a failure to quit smoking, but may either be (1) attempting to reduce smoking consumption as an end in itself, or (2) reducing as a step in a series of successive approximations which will ultimately culminate in total elimination of cigarette consumption. Reducers, in other words, may find the “cold turkey” approach of quitting unpalatable and may be utilizing a temporary reduction of cigarette consumption as a confidence boost in preparation for further attempts at reduction of cigarette consumption. Respondents in agreement with the statement that research will find cures for diseases long before most of today’s smokers contract them had a much lower rate of quitting (6.8 per cent) than respondents who disagreed with the statement (18-O per cent). Perhaps future public information efforts should be directed at eliminating this rationalization from the cigarette smoker’s repertoire. Perhaps the most effective predictor of smoking behavior change discovered was the respondent’s acquaintance with someone whose health had been adversely affected by smoking. Of those respondents reporting an acquaintance whose health had been affected by smoking 27.1 per cent quit smoking whereas only 9.7 per cent of those respondents reporting no such acquaintance quit smoking. This finding was not unexpected. A study by DeWolfe and Governale [12] revealed that nurses who were exposed to a high fear condition (assignment to a tuberculosis ward) were much more susceptible to persuasive communications regarding preventive tuberculosis practices than a control group of comparable nurses who were not exposed to tuberculosis patients. From this study and some of his own research Janis [ 131 concluded : ‘6. . . direct confrontation with the threat seems to be extraordinarily effective in breaking through the defensive facade that normally enables a person to maintain an unwarranted but highly cherished attitude of complacency. Once people become convinced of their personal vulnerability to a potential source of danger, then resistance to authoritative recommendations seems to be strikingly diminished.”
l
The crucial point to be emphasized here is that smokers will be more likely to alter their attitudes and behavior towards smoking if they are directly confronted with the threat (e.g., familiarity with someone whose health had been affected by smoking, participation in a role-playing session, etc.) than if they are passively exposed to the same fear arousing information through indirect methods such as television programs or much publicized U.S. Public Health Service warnings. Tomkins’ smoking “types” differentiate smokers on the basis of utility of the cigarette
Psychosocial Predictors of Smoking Behavior Change
143
in the management of affect. Six non-independent “types” exist: the pleasurable relaxation smoker, the stimulation smoker, the handling smoker (all smoke to enhance positive affect), the tension reduction smoker (smokes to reduce negative affect), the habitual smoker (smokes with no affect) and the psychologically addicted smoker (smokes to enhance positive and reduce negative affect). All smokers can be rated on the six types
through a scale devised by Ikard et al., noted earlier. Score on Tomkins’ habitual “type” did not differentiate respondents in terms of rate of quitting. However, it was demonstrated that respondents with a high habitual score had a higher rate of reducing (39-O per cent) cigarette consumption than respondents with a moderate score who in turn demonstrated a higher rate of reducing (27.9 per cent) than respondents ‘with a low score (14-l per cent). This differentiation is most likely due to the high correlation between habitual score and number of cigarettes smoked per day [14]. The identical relationship was found between reducing cigarette consumption and score on Tomkins’ psychologically addictive type. Again, a high correlation has been noted between addictive score and number of cigarettes smoked per day. As a result of their subjacent degree of psychological and physiological dependency upon cigarettes, respondents with a low addictive score demonstrated a higher rate of quitting (18.9 per cent) than respondents with either a moderate (10.6 per cent) or higher (11.2 per cent) addictive score. As was noted earlier, a multiple discriminant analysis was employed in an effort to distinguish predictors of smoking behavior change. Univariate tests were explained to be insufficient for this purpose because of their failure to take into consideration intercorrelations between independent variables. The multiple discriminant approach was chosen in the place of the more commonly employed multiple regression analysis because it retained information lost in a regression analysis by the assumption that the four groups may be positioned on a unidimensional scale. The results of the discriminant analysis demonstrated that the probability of correctly classifying a quitter was as high (O-54)whether twelve, seven or four variables were employed. In what may be the only other discriminant analysis of smoking behavior change utilizing the likelihood function approach, Straits [15] obtained probabilities of O-62 and 0.56 of correctly classifying quitters employing eleven and seven variables respectively (not identical to those employed in the present study). SUMMARY A prospective analysis was undertaken in an attempt to discover possible predictors of smoking behavior change. Respondents subjected to a lengthy interview in 1966 were reinterviewed in 1968 at which time their smoking behavior status was assessed. Respondents were classified as either “quit”, “reduced”, “no change”, or “increased”. Smoking behavior change was examined as a function of responses to the 1966 interview. Males were found to be more likely to quit or reduce cigarette consumption than females. Respondents with children present in their household were more likely to have quit or reduced smoking than respondents reporting no children in their household. As the number of cigarettes smoked per day increased, respondents were less likely to have quit but more likely to have reduced smoking consumption. Eight behavioral and attitudinal variables were demonstrated through univariate analyses to differentiate respondents in terms of smoking behavior change typology: number of cigarettes smoked per day, perceived difficulty of quitting, agreement or disagreement with the statement “Research will find a cure for the diseases smoking is supposed to cause long before any of today’s smokers get them”, acquaintance with someone whose health had adversely been affected by smoking, presence of children in the respondent’s household, sex, score on Tomkins’ psychologically addictive type, and score on Ton&ins’ habitual smoking type. A number of additional variables successfully discriminated “quitters” from “non-quitters”. A multiple discriminant model generating maximum likelihood functions was employed to study the relationship between smoking behavior change and selected psychological and sociological factors demon-
144
RICHARDA. EMNGER
strated through univariate analyses to be related to smoking behavior alteration. Four discriminant analyses were undertaken, employing fourteen, seven four and three variables respectively. The four variable analysis utilizing the tist four variables noted above was successful in predicting respondents who quit and reduced smoking consumption. Practical implications of some of the findings were discussed. REFERENCES 1. 2. ::
2: 7. 8. 9.
10. 11. 12. 13.
:::
IKARD, F., Smoking Bibliography: Selected References, unpublished manuscript, U.S. Public Health Service, National Clearinghouse for Smoking and Health, 1967. HAMMOND,E. C., and PERCY, CONSTANCE, Ex-smokers, N. Y. State J. Med., F&,1958. GUILFORD,JOANFactors related to successful abstinance from smoking, unpublished report, 1966. Sm, B., Sociological and psychological correlates of adoption and discontinuation of cigarette smoking, unpubllished manuscript, 1965. GUILFORD,op. cit. STR~, B., The discontinuation of cigarette smoking: a multiple discriminant analysis, paper presented at the American Sociological Association meeting, 1966. HORN. D.. and WAMOROW. S.. Some dimensions of a model for smoking behavior Change. Am. J. Publ. &th-., 56, 1966. ’ . TOMKINS,S., A psychological model for smoking behavior, Am. J. Pub!. Hlth., suppl. 56, 1966. IKARD. F.. G~EZN. DOROTHY.and HORN. D. The develonment of a scale to differentiate between tvnes of smoking as related to the management of affect, paper presented at the Eastern Psychological Association meeting, 1968. S-rxArrs, 1966, op. cit. HORN, D., Factors affecting the cessation of cigarette smoking: a prospective study, paper presented at the Eastern Psychological Association meeting, 1968. DEWOLFE. A., and GOVERNALE,CATHERINE,Fear and attitude change, J. Ab. Sot. Psych., 69, 1964 JANB, I., Effects of fear arousal on attitude change: recent developments in theory and experimental research, in Berkowitz, L. (ed.), Advances in Experimental Social Psychology, Academic Press, New York. U.S. Public Health Service survey, unpublished data, 1966. Snu\rrs, 1966, op. cit.