Social cognitive determinants of drinking in young adults

Addictive Behaviors 26 (2001) 689 – 706

Social cognitive determinants of drinking in young adults: Beyond the alcohol expectancies paradigm Arie Dijkstra*, Laura Sweeney, Winnie Gebhardt Clinical & Health Psychology Section, Leiden University, Leiden, The Netherlands

Abstract In prior investigations of the psychology of drinking behavior, drinkers’ positive expectancies regarding the effects of alcohol have been studied extensively. From a social cognitive point of view, however, several additional psychological factors also deserve attention, namely negative expectancies, social influence, and self-efficacy expectations. In a representative sample of 161 university students, this study examined to what extent inclusion of these additional social cognitive factors enhanced the predictive power of the predominant alcohol-expectancies model of drinking behavior, and to what extent all four social cognitive factors were related to the uptake and cessation of drinking behavior. The three additional social cognitive factors contributed 17% to the explained variance in drinking behavior, in addition to the 18% accounted for by positive expectancies. The constructs with the greatest predictive strength all pertained to the social effects and social context of drinking. The most important predictors of drinking behavior were found to differ for male versus female students, and for students living with their parents versus those living on their own. The data on drinking acquisition and cessation suggest that in this sample little change in drinking behavior could be expected. The social cognitive factors were strongly related to acquisition stages but only weakly to cessation stages. Recommendations for interventions aimed at lowering alcohol intake are given. D 2001 Elsevier Science Ltd. All rights reserved. Keywords: Social cognitive theory; Alcohol expectancies; Stages of change

1. Introduction In prior research into the psychological determinants of alcohol consumption, positive expectancies have been studied extensively (for reviews see Goldman, Brown, Christiansen, * Corresponding author. Leiden University, Wassenaarseweg 52, P.O. Box 9555, 2300 RB, Leiden, Netherlands. Tel.: +31-71-5274036. E-mail address: [email protected] (A. Dijkstra). 0306-4603/01/$ – see front matter D 2001 Elsevier Science Ltd. All rights reserved. PII: S 0 3 0 6 - 4 6 0 3 ( 0 0 ) 0 0 1 5 3 - 2

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& Smith, 1991; Leigh, 1989; Leigh & Stacy, 1991). Positive expectancies refer to the drinker’s perceptions of the positive outcomes of drinking, and have been shown to be causally related to alcohol consumption in both adults and adolescents (Christiansen, Smith, Roehling, & Goldman, 1989; Darkes & Goldman, 1993; Dunn & Goldman, 1998; Smith, Goldman, Greenbaum, & Christiansen, 1995). Although this line of research has yielded an impressive amount of data on the mediating role of positive expectancies in drinking behavior, some recent studies have attempted to apply more comprehensive psychological models to alcohol consumption. For example, Ajzen’s (1988) theory of planned behavior has been used in some studies to identify additional psychological determinants of drinking behavior (Marcoux & Shope, 1997; Schlegel, D’Avernas, Zanna, DeCourville, & Manske, 1992). Unfortunately, the predictors operationalized in these studies (viz., attitude, subjective norm, and perceived behavioral control) do not provide a basis for valid comparisons with existing findings in the alcohol expectancy literature. In the present study, Bandura’s (1986, 1997) social cognitive theory was used to map the psychology of drinking. This theory distinguishes several sources of behavior in general that appear to offer a useful basis for understanding drinking behavior. Moreover, in view of the nature of the constructs identified in the model, it provides a basis for assessing whether additional social cognitive constructs would enhance the predictive power of the traditional positive expectancies approach to drinking behavior. One of the key sources of behavior distinguished in Bandura’s (1986) social cognitive theory is expectancies of outcome. Besides positive expectancies with regard to the desired effects of drinking, which form the focus of attention in the alcohol expectancy literature, expectancies with regard to negative effects may be important determinants of drinking behavior (e.g., Shafer & Leigh, 1996; Wiers, Hoogeveen, Sergeant, & Gunning, 1997). Whereas positive expectancies refer to motives to drink, negative expectancies refer to motives not to drink, or not to drink more. Lee, Greely, and Oei (1999) found that drinking was related not only to positive expectancies, but also to negative expectancies regarding the effects of drinking (e.g., negative affective changes and loss of control; see also Grube, Ames, & Delaney, 1994). On the other hand, Earleywine (1995) found that positive but not negative expectancies were related to intentions to drink and drinking behavior. These inconsistent findings might be attributable to differences in the conceptualization of negative expectancies. For example, Leigh (1989) distinguished between expectancies regarding short-term, direct effects (e.g., decreased psychomotor coordination) and longer-term negative effects of drinking (e.g., liver cirrhosis). A second important factor contributing to behavior in general (Bandura, 1986), and drinking behavior in particular, is social influence (Christiansen et al., 1989). Several operationalizations of social influence have been linked to alcohol consumption in prior research. Expectations concerning the positive social effects of drinking, which are typically taken into account in the alcohol expectancies framework (e.g., Smith et al., 1995), form one way of conceptualizing social influence. A second social influence construct has been used in research on the modeling influences of the social environment on alcohol consumption (Curran, Stice, & Chassin, 1997). In this context, modeling refers to a fundamental process of learning about the effects and the controllability of alcohol consumption by observing and communicating with others. A third type of social influence is emphasized in the theory of

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planned behavior (Ajzen, 1988), where subjective norms regarding the behavior in question form a key construct. Subjective norms refer to the perceived opinion of others about one’s drinking behavior. Kilty (1987), Schlegel et al. (1992), and Trafimov (1996) found that subjective norms predicted respondents’ intentions to drink alcohol. A third factor governing behavior in general (Bandura, 1986, 1997), and drinking behavior in particular (Marlatt & Gordon, 1985), is self-efficacy expectations. Selfefficacy refers to judgments of one’s personal ability to accomplish a certain task (Bandura, 1986, 1997). People high in self-efficacy persist even in the face of obstacles. With regard to drinking behavior, self-efficacy expectations refer to self-perceptions of one’s ability not to give in to urges or social pressures to drink (Marlatt & Gordon, 1985). Aas, Klepp, Laberg, and Aaro (1995) and Skutle (1999) did indeed find that selfefficacy expectations were negatively related to drinking behavior. Moreover, there appear to be distinct domains of self-efficacy expectations. For example, self-efficacy with regard to not giving in to social pressures to drink can be distinguished from self-efficacy expectations with regard to not giving in to the urge to drink away negative emotions (Marlatt & Gordon, 1985). In sum, Bandura’s (1986, 1997) social cognitive theory identifies four types of social cognitive factors that appear to be important determinants of drinking behavior: positive outcome expectancies, negative outcome expectancies, social influence, and self-efficacy expectations. As already noted, positive outcome expectancies have received considerable attention in prior research on drinking behavior. On the other hand, considerably less research attention has been given to the remaining three social cognitive factors. The present study was undertaken to test a comprehensive psychological model of drinking behavior incorporating all four types of social cognitive factors. Besides examining the social cognitive determinants of drinking, the present study also aimed to shed light on the processes that give rise to changes in drinking behavior over time. The stages of change model (Prochaska, DiClemente, & Norcross, 1992) define five stages that individuals pass through in the process of intentionally changing their behavior. First, in the precontemplation stage people do not plan to change their present behavior. Second, in the contemplation stage people plan to change their behavior within the next 6 months. Third, in the preparation stage people plan to change their behavior within 1 month. Fourth, in the action stage people have already changed their behavior, but the change spans a period of less than 6 months. Fifth, in the maintenance stage people have changed their behavior, and have maintained this change for 6 months or longer. Recently, Prochaska et al.’s (1992) model has been expanded to include both stages of acquisition and stages of cessation of a target behavior (Migneault, Pallonen, & Velicer, 1997). In an investigation of stages with regard to ‘‘usually drinking three or more drinks on a day you drink’’ in a sample of adolescents (aged 15 to 18), Migneault et al. (1997) distinguished five acquisition stages and five cessation stages. The five acquisition stages described the process of transition from not consuming three or more drinks per occasion and not planning to do so within the next 6 months (acquisition precontemplation), to consuming three or more drinks per occasion already for more than 6 months (acquisition maintenance). Conversely, cessation stages described the process of transition from consuming three or more drinks per occasion and not planning to change this behavior

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within the next 6 months (cessation precontemplation), to having quit consuming three or more drinks per occasion for a period of 6 months or longer (cessation maintenance). Migneault et al.’s cross-sectional data indicated that adolescents who were consuming three or more drinks per occasion perceived more benefits and fewer disadvantages of drinking alcohol than those who did not drink that amount. Furthermore, adolescents who used to drink three or more beverages per occasion in the past, but had since stopped doing so, perceived fewer benefits and more disadvantages of drinking than those who presently drank that amount. No data are available, however, on patterns of change in self-efficacy and social influence through the stages of acquisition and cessation of drinking behavior. The present study assessed drinking behavior and its determinants by means of a questionnaire distributed to a sample of university students. The first goal of the study was to examine whether expectations with regard to the negative outcomes of drinking, social influence, and self-efficacy expectations would contribute substantially to the explained variance in alcohol consumption, over and above the variance explained by positive alcohol expectancies. The second goal was to assess the relative strength of these four social cognitive factors as predictors of alcohol consumption. The study’s third goal was to investigate the stages of change model, that is, to assess to what extent acquisition and cessation stages provided a meaningful description of drinking behavior in the student sample, and to compare students in different stages of change in terms of the four social cognitive factors. Both the social cognitive factors and the stages of acquisition and cessation were operationalized in terms of a single criterion behavior, namely regularly consuming four or more drinks per occasion. This criterion was selected in view of a recognized definition of binge drinking in young adults, which specifies distinct criteria for male drinkers (five or more glasses in a row) and female drinkers (four or more glasses in a row; Wechsler, Dowdall, Davenport, & Rimm, 1995). Because application of this sexspecific criterion would have unduly complicated the data collection process, the more conservative criterion of four drinks per occasion was used for all respondents. Also, epidemiological and other research has linked this consumption of four or more alcoholic drinks per occasion to negative health outcomes (e.g., Garretsen, Bongers, Oers, & Van de Goor, 1999). Some of the university students in the sample were living on their own, while others lived with their parents. We expected that the relative influence of the social cognitive factors on drinking behavior might be sensitive to this difference in living environment. Therefore, the social cognitive determinants of drinking for students in these two living environments were examined separately and compared. Furthermore, because males and females are exposed to different socialization influences, we expected that the relative influence of the social cognitive factors on drinking behavior might also be sensitive to gender. For example, Brown, Goldman, Inn, and Anderson (1980) found that women expected more positive social experiences as a result of alcohol consumption, whereas men were more apt to expect arousal and potentially aggressive behavior. Thus, the fourth goal of this study was to assess and compare the social cognitive determinants of drinking in subgroups defined on the basis of gender and living environment.

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2. Method A sample of psychology students at Leiden University was recruited during seminar-type course meetings in groups of 10 to 12 students. Because all first-year psychology students are randomly assigned to such a seminar group, and attendance is mandatory, the sample may be viewed as representative of first-year psychology students at this university. At the end of the seminar meeting, self-report questionnaires were distributed to all seminar participants. By means of standardized verbal instructions, the students were asked to fill out the questionnaire immediately, without consulting others. All 161 students approached in this way completed the questionnaire. 2.1. Questionnaire 2.1.1. Drinking behavior Drinking behavior was measured in such a way that quantity-frequency indexes could be calculated (Wiers et al., 1997). Participants were asked to indicate, with respect to the past 30 days, the frequency and number of alcoholic beverages they had consumed on weekdays (Monday, Tuesday, Wednesday, and Thursday) as well as on weekend days (Friday, Saturday, and Sunday). Frequency was operationalized as the number of days per week on which the respondent had drunk alcohol. Quantity was assessed in terms of the number of alcoholic beverages participants typically drank on days when alcohol was consumed, with responses given in terms of the following eight categories: 0–3; 4–5; 6–10; 11–20; 21–30; 31–40; 41–50; 51 or more. These categories were coded from 1 to 8, respectively. For both periods, weekdays and weekends, frequency and number of alcoholic beverages were multiplied and then summed to form a quantity-frequency index. 2.1.2. Socio-demographic characteristics Gender, age, and living environment (with parents or on one’s own) were assessed. 2.1.3. Positive and negative expectations Four scales measuring expected positive and negative outcomes of drinking were constructed based on existing measures of alcohol expectancies (see review by Leigh, 1989) as well as prior research into smoking behavior (e.g., Dijkstra, De Vries, & Roijackers, 1998). All items measuring outcome expectations were worded as conditional statements ‘‘If . . ., then . . .’’ Answers were given on a scale from 1 (I do not agree at all) to 5 (I agree completely). Scale scores were formed by averaging over item scores. Expectations of positive outcomes of drinking four or more beverages in a row were assessed with two scales: Expectations of social benefits (e.g., feeling more attractive; five items; a [Cronbach’s alpha] = .81), and expectations of cognitive–emotional effects (e.g., relaxation; five items; a = .81). Negative expectations of drinking four or more beverages in a row were also assessed with two scales: Expectations of negative physical effects of drinking (e.g., detrimental effects on the nervous system; four items; a = .90), and expectations of self-evaluative outcomes (e.g., feeling dissatisfied with oneself; four items; a = .81).

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2.1.4. Social influence Two scales assessed social influence. Social norm was measured based on the operationalization of subjective norm in the theory of planned behavior (Ajzen, 1988; Conner & Norman, 1996): Participants indicated how their parents, their friends, other students, and their roommates viewed drinking four or more glasses per occasion, by selecting a response between 1 (certainly too much) and 5 (certainly not too much). These four items were averaged to form a social norm scale (a = .91), with higher scores reflecting a more tolerant social norm. The second social influence scale was based on Curran et al.’s (1997) operationalization of social modeling. Participants were asked to estimate what proportion of their parents, their friends, other students, and their roommates typically drank four or more glasses per occasion. For the latter three items, participants selected one of five responses: 0 (no one), 1 (less than half), 2 (half), 3 (more than half), or 4 (all). For the item concerning parents, there were three response categories: 0 (none), 2 (one of them), or 4 (both). Because the items composing this scale refer not to a single psychological construct, but rather to distinct sources of environmental information, the scale was treated as an aggregated index of modeling influences. The item scores were summed to form a scale score. Higher scores reflected greater modeling influence to drink four or more beverages per occasion. 2.1.5. Self-efficacy expectations Two distinct types of self-efficacy expectations were measured using scales with demonstrated predictive validity in studies of smoking behavior (e.g., Dijkstra et al., 1998): Selfefficacy to resist the urge to drink four or more alcoholic beverages in particular social situations (e.g., being out with friends; four items; a = .89), and self-efficacy to cope with the urge to drink four or more alcoholic beverages in negative emotional states (e.g., feeling tense; three items; a = .91). Participants were asked: ‘‘Imagine you have decided to drink no more than 3 alcoholic beverages. How sure are you that you would be able to do so [. . .]?’’ At the end of each item a social or emotional situation was specified. The items could be scored from 1 (I am very sure I would be able to) to 5 (I am not sure at all that I would be able to). The two scales were formed by averaging the item scores. Higher scores reflected higher confidence to resist the urge to drink in certain situations. 2.1.6. Stages of change Stages of acquisition and cessation were assessed using a decision tree algorithm adapted from Migneault et al. (1997). There were two possible responses to each question: yes or no. The sequence of questions answered by a given respondent could follow one of several flow paths. Depending on the participant’s response to a given question, he or she was guided by arrows printed in the questionnaire to the subsequent question. The first question (posed to all respondents) was: ‘‘Over the past thirty days, did you regularly drink four or more alcoholic beverages on occasions when you drank?’’ For participants whose response was no, the next question was: ‘‘Have you ever drunk four or more alcoholic beverages per occasion regularly, for a thirty-day period?’’ Participants who indicated that they had never regularly consumed four or more drinks for a 30-day a period were considered to be in one of the early acquisition stages. Participants who had previously drunk this much regularly

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over a 30-day period were considered to be in one of the late cessation stages. Participants in the early acquisition stages were then asked whether they were planning to begin regularly drinking four or more alcohol beverages per occasion in the next month (yes = acquisition-preparation), or in the next 6 months (no = acquisition-precontemplation; yes = acquisition-contemplation). Participants in the late cessation stages were asked whether it was longer than 6 months ago that they regularly drank four or more alcoholic beverages per occasion (no = cessation-action; yes = cessation-maintenance). Participants who had responded yes to the very first question (viz., ‘‘During the past thirty days, have you regularly drunk four of more alcoholic beverages per occasion’’) were subsequently asked whether they had been doing this for a period longer than 6 months (no = acquisitionaction; yes = acquisition-maintenance) and whether they were planning to stop drinking this much in the next month (yes = cessation-preparation), or in the next 6 months (no = cessation-precontemplation; yes = cessation-contemplation). Thus, the algorithm classified people into one of five acquisition stages or one of five cessation stages. As in Migneault et al.’s study, participants classified into the acquisition-action or acquisition-maintenance stage could also be classified into the cessation-precontemplation, cessation-contemplation, or cessation-preparation stage. 2.2. Statistical analyses To assess whether the univariate relations among the eight social cognitive measures and drinking behavior were in expected and interpretable directions, Pearson correlations were computed. To test whether the additional social cognitive constructs (negative expectations, social influence, and self-efficacy) contributed substantially to the explained variance in drinking behavior, over and above the variance accounted for by positive expectations, a hierarchical linear regression analysis was conducted. In the first block, three covariates were entered: gender, age, and living environment (with parents or not). In the second block, the two scales measuring positive (social and cognitive–emotional) expectations were entered. In the third block, six measures corresponding to the three additional social cognitive factors were entered: negative self-evaluative expectations, negative physical expectations, social norm, modeling, social self-efficacy, and emotional self-efficacy. To evaluate the relative contribution of the eight social cognitive measures to the explanation of drinking behavior, these measures were entered simultaneously in an additional stepwise regression analysis, after entry of the three covariates. To test gender differences and differences related to living environment, this stepwise analyses was also conducted separately for males and females, and for students living with their parents and students living on their own. To analyze the data with regard to the stages of change construct, two separate sets of ANOVAs were conducted: One set compared participants in the five acquisition stages on the eight social cognitive measures and on drinking behavior, and the second set compared participants in the five cessation stages on the same group of dependent variables. Students who had never consumed more than four drinks per occasion and students who drank more than four per occasion regularly during the past 30 days were

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classified into one of the acquisition stages. Students who drank more than four per occasion regularly during the past 30 days and those who had been doing that in the past were classified into one of the cessation stages. As noted above, the algorithm permits some respondents to be classified in both an acquisition stage and a cessation stage. Such double classification was applied to 39 of the respondents in the present study. These participants were included in both sets of ANOVAs. In cases where one or more demographic variable showed a significant relationship with the outcome variable, the demographic variable(s) was introduced into the ANOVA as a covariate. Tukey contrasts were used to assess specific differences between stages. The significance criterion used in all analyses was P < .05.

3. Results 3.1. Pearson correlations The correlations displayed in Table 1 indicate that seven of the eight social cognitive measures were significantly related to drinking behavior. All of these relations were in the expected direction: Participants reported drinking more to the extent that they expected more positive outcomes of consuming four or more drinks in a row, expected fewer negative self-evaluative outcomes, perceived more people in their environment as drinking this much, perceived those people to be more tolerant towards drinking this much, and reported lower confidence to resist the urge to drink this much. Only the expected negative physical consequences of consuming four or more drinks in a row were not related to drinking behavior. Furthermore, the following relations were also in the expected directions: (1) The higher the modeling influences and the more tolerant the social norm, the more positive expectations and the fewer negative self-evaluative expectations Table 1 Correlations involving the eight psychological measures and drinking behavior 1 (1) Positive social expectations (2) Positive cognitive/emotional expectations (3) Negative self-evaluative expectations (4) Negative physical expectations (5) Modeling (6) Social norm (7) Self-efficacy social (8) Self-efficacy emotional (9) Drinking behavior * P < .01. ** P < .05.

2

3

4

5

6

7

8

.04 .08 .02 .00 .13

.50* .24* .12 .40*

.38* .22* .52*

.72* .46*

.32*

.66* .05

.04

.05

.04

.35*

.27* .30* .34* .33* .41*

.21* .27* .38* .40* .38*

.20** .41* .14 .11 .29*

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participants reported; and (2) the more positive expectations participants reported, the lower their confidence to fight the urge to drink more. Finally, significant correlations were observed between the two scales measuring each social cognitive construct: r = .66 for positive expectations; r = .35 for negative expectations; r = .50 for social influence; and r = .72 for self-efficacy. 3.2. Sample characteristics As can be seen in Table 2, 75% of the participants were female, and 52% lived with their parents. The mean age was 19.6 years (S.D. = 1.56). Almost 40% did not drink at all on weekdays, while the majority of the participants (over 50%) drank on 1 or 2 weekdays. On weekends, only 24% of participants did not drink at all. On weekdays, nearly 80% of participants drank less than four beverages per occasion. This figure dropped to 55% in the weekend.

Table 2 Student sample characteristics Variable

Category

Gender (%)

Females Males With parents On their own

75.2 24.8 51.9 48.1 19.6

On 0 days On 1 day On 2 days On 3 days On 4 days 0–3 4–5 6 – 10 11 – 20

39.8 26.7 22.4 5.6 5 78.4 13.4 5.7 2.5

On 0 days On 1 day On 2 days On 3 days 0–3 4–5 6 – 10 11 – 20 21 – 30

24.2 35.4 31.7 8.2 55.1 19.2 19.2 5.8 0.6

Living situation (%) Age (mean in years) Drinking on working daysa Frequency (%)

Number of beverages (%)

Drinking on weekendsb Frequency (%)

Number of beverages (%)

a b

Monday, Tuesday, Wednesday, and Thursday. Friday, Saturday, and Sunday.

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Table 3 Hierarchical regression analysis of drinking behavior, testing the additional explanatory power of the social cognitive measures above that provided by positive expectations Model test Covariates Positive expectations Additional factors

F

P value

Cumulative adjusted R2

7.83 15.22 12.22

< .01 < .001 < .001

.05 .23 .40

Change test F

P value

7.83 18.04 8.23

< .01 < .001 < .001

The variables were entered in three subsequent blocks: covariates (socio-demographic variables), two positive expectations scales, and six additional social cognitive scales.

3.3. Social cognitive predictors of drinking behavior 3.3.1. Model testing: can additional social cognitive constructs enhance the positive alcoholexpectancies model? Table 3 shows the results of the three-step hierarchical linear regression analysis: In the first block, age, gender, and living environment were entered as covariates; in the second block two scales measuring positive outcome expectancies were entered; and in the third block six scales measuring negative outcome expectancies, social influence, and self-efficacy expectations were added to the model. The results indicate firstly that the two scales measuring positive expectations contributed significantly (18%) to the explained variance in drinking behavior above that explained by the covariates. Secondly, as hypothesized, the remaining six social cognitive measures also contributed significantly (an additional 17%) to the explained variance in drinking behavior. The model as a whole explained 40% of the variance in drinking behavior. 3.3.2. Relative strength of the eight social cognitive predictors After controlling for the three covariates, all eight social cognitive measures were added simultaneously in a stepwise regression analysis. As can be seen in Table 4, three of the eight measures emerged as significant predictors of drinking behavior. The strongest predictor identified in this analysis was social norm, which explained 24% of the variance in drinking behavior above that explained by the covariates. Positive social expectations also contributed significantly, adding 6%. Lastly, self-efficacy with regard to resisting the urge to drink more Table 4 Stepwise regression analysis of drinking behavior, examining the relative explanatory strength of the eight social cognitive measures Model test Gender Social norm Positive social expectations Self-efficacy social

F

P value

Cumulative adjusted R2

7.83 30.2 27.52 23.66

< .01 < .001 < .001 < .001

.04 .28 .34 .37

Change test F

P value

7.83 50.05 16.14 8.17

< .01 < .001 < .001 < .01

The socio-demographic variables were entered first, followed by the eight psychological measures in a stepwise regression procedure.

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Table 5 Results of regression analyses with drinking behavior as dependent variable, stratified by gender and living environment Cumulative adjusted R2

P value, t test

.27 .21 .23 .18

.25 .32 .36 .38

< .01 < .05 < .05 < .05

< .01 < .001

.53 .31

.25 .33

< .001 < .05

4.22 14.30 14.69 12.99

< .05 < .001 < .001 < .001

.14 .31 .26 .23

.04 .25 .35 .38

n.s. < .01 < .05 < .05

5.44 18.34 20.10

< .05 < .001 < .001

.21 .39 .38

.06 .33 .45

< .05 < .001 < .001

F

P value

Females (n = 121) Social norm Self-efficacy social Modeling Positive social expectations

37.15 26.85 21.50 17.89

< .001 < .001 < .001 < .001

Males (n = 40) Positive social expectations Negative self-evaluative expectations

13.87 19.64

Living with parents (n = 83) Gender Self-efficacy social Social norm Modeling Not living with parents (n = 77) Gender Social norm Positive physiological expectations

Beta

in social situations added another 3% to the explained variance. Together the variables explained 37% of the variance in drinking behavior. Table 5 displays the stratified results obtained when the stepwise regression analysis was repeated for subgroups defined by gender and living environment. In the analysis of female respondents, social norm, self-efficacy in social situations, modeling, and positive social expectations emerged as significant predictors, explaining respectively 25%, 7%, 4%, and 2% of the variance in drinking behavior. In the case of male respondents, positive social expectations and negative self-evaluation expectations were found to be significant predictors, explaining respectively 25% and 8% of the variance in drinking behavior. For participants living with their parents, drinking behavior was significantly associated with gender, self-efficacy in social situations, social norm, and modeling, which explained respectively 4%, 21%, 10%, and 3% of the variance. In the case of participants living on their own, drinking behavior was significantly associated with gender, social norm, and positive physiological expectations, which explained respectively 6%, 27%, and 12% of the variance. 3.4. Stages of acquisition and cessation of drinking behavior Stage data for 10 respondents were missing. Of the remaining 151 participants, 118 could be classified into one of the stages of acquisition of the behavior ‘‘drinking more than four alcoholic beverages per occasion,’’ and 71 could be classified into one of the cessation stages.

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3.4.1. Social cognitive differences between stages of drinking acquisition Of the participants who had never drunk at the specified criterion, all (n = 79) had no intention of starting to drink this amount in the next 6 months and could therefore be classified in the acquisition-precontemplation stage; in other words, the acquisitioncontemplation or acquisition-preparation stages were not represented in our sample. Of the 39 participants who drank more than four alcoholic beverages per occasion, eight had been doing this for less than 6 months (acquisition-action) and 31 for more than 6 months (acquisition-maintenance). Table 6 depicts the mean scores for each acquisition stage on the eight social cognitive measures. ANOVAs revealed significant differences between the stages for all but one of these measures: Negative physical expectations of drinking showed no significant differences. Tukey contrasts revealed that on the seven other measures, acquisition-precontemplators scored significantly differently from those in the acquisition-maintenance stage: The latter

Table 6 Means of the social cognitive measures, drinking frequency, and drinking quantity for participants in the acquisition and cessation stages Acquisition stages Pc (n = 79) Positive social expectations Positive cognitive expectations Negative selfevaluative Negative physical Modeling Social norm Self-efficacy social Self-efficacy emotional Drinking behavior Number of days % drinking < 4 drinks during weekdays % Drinking < 4 drinks during weekends a

Cessation stages

Act (n = 8)

Mt (n = 31)

Pc (n = 39)

Act (n = 21)

Mt (n = 11)

a

2.13

2.70

2.84

P < .01.

2.56

2.33

1.81

2.59a

2.75

3.21

P < .05

2.90

2.92b

1.96

2.67a

2.63

2.06

P < .05

1.88

1.90

1.55

4.15 6.86a 2.94a,e 4.55a 4.67a

3.69 8.75 3.72 4.28d 4.63

4.15 10.26 4.08 3.28 3.96

n.s. P < .001 P < .001 P < .001 P < .001

3.78 9.08a 3.75c 3.10ce 3.78

3.91 7.73 3.28 3.70 3.85

3.41 3.81 2.57 3.82 4.15

n.s. P < .05 P < .10 P < .10 n.s.

3.81 38.7

P < .001 P < .001*

3.77 38.5

2.48 85.8

1.27 90.9

P < .001 P < .01*

P < .001*

5.1

33.4

80

P < .001*

1.60 97.3

3.63 37.5

84.2

25

0

Pc differs significantly from Mt. Act differs borderline significantly from Mt. c Pc differs borderline significantly from Mt. d Act differs significantly from Mt. e Pc differs borderline significantly from Act. * Significance level from chi-square analysis. b

Significant

Significant n.s. P < .10 n.s.

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perceived more positive outcomes of drinking, experienced lower negative self-evaluation, perceived more social influence, and had lower self-efficacy than did the precontemplators. The stage criterion was drinking four or more drinks on a regular basis during the last 30 days. Table 6 shows that participants in the acquisition-precontemplation stage drank on significantly fewer days per week than did participants in acquisition-action or acquisitionmaintenance. Furthermore, over 97% of the acquisition-precontemplators did not consume four or more drinks on weekdays and over 84% did not consume four or more drinks on weekend days. 3.4.2. Social cognitive differences between stages of drinking cessation Of the 39 participants who regularly drank more than four drinks per occasion over the past month, 38 were not planning to change their drinking behavior in the coming 6 months, and could therefore be classified as cessation-precontemplators; none of these participants were planning to quit drinking this much in the coming 6 months, but not in the coming month (cessation-precontemplation); and one participant was planning to quit consuming four drinks per occasion within the next month (cessation-preparation). Because the latter individual was still engaged in the criterion behavior, he or she was classified for the purposes of the ANOVAs together with the other drinkers of more than four per occasion. Of the 32 participants who had regularly consumed more than four drinks per occasion in the past, 21 had quit drinking more than four beverages per occasion less than 6 months ago (cessationaction) and 11 had quit doing this more than 6 months ago (cessation-maintenance). Table 6 depicts the mean scores for each stage on the eight social cognitive measures. ANOVAs revealed significant ( P < .05) differences between the cessation stages on only two of the social cognitive measures: modeling and self-efficacy to cope with social pressures to drink. Statistical trends ( P < .10) were observed on two measures: Expectation of positive cognitive/emotional outcomes was lower in participants in maintenance and they perceived a less tolerant social norm. Regarding drinking behavior, participants in cessation-action and cessation-maintenance stages reported drinking on fewer days than did those in cessation-precontemplation. Furthermore, of the participants in cessation-action and cessation-maintenance, respectively 86% and 90% did not drink more than four consumptions per occasion on weekdays. On weekends, however, only 20% of participants in cessation-maintenance consumed more than four drinks, compared to almost 70% of participants in cessation-action.

4. Discussion The present study was aimed at mapping the social cognitive factors underlying alcohol consumption. More specifically, this study examined the predictive strength of a comprehensive psychological model of drinking behavior. In line with Bandura’s (1986, 1997) social cognitive theory, this model incorporated four clusters of cognitive factors: positive and negative outcome expectancies, social influence, and self-efficacy expectations. Prior research on drinking behavior has focused primarily on just one of these social cognitive factors: positive expectancies. The first goal of this study was to examine whether the other

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three social cognitive factors might offer enhanced insight into drinking behavior, over and above that offered by the traditional alcohol expectancies approach. First of all, positive expectancies were found to explain 18% of the variance in drinking behavior, which is similar to the percentages reported by Leigh (1989) (10%–19%) and Goldman et al. (1991) (22%). Addition of measures of the three other social cognitive factors nearly doubled the predictive strength of the model, adding 17% to the explained variance in drinking behavior. In a review of applications of the theory of planned behavior to health behaviors, Godin and Kok (1996) showed that attitude, subjective norm, and perceived behavioral control on average yielded 34% explained variance. Thus, the 35% explained variance in drinking behavior observed in the present study is comparable to the standards of established models in applied psychology, and represents a clear improvement over psychological models of drinking behavior that recognize only positive expectancies. The second goal of this study was to assess the relative strength of the eight cognitive factors as predictors of drinking behavior. In stepwise regression analyses in which variables representing all four social cognitive factors were considered simultaneously, social norm emerged as the strongest predictor, explaining 24% of the variance in drinking behavior. After social norm, positive expectancies regarding social outcomes added 6%. This suggests that positive expectancies may not be the most important factors contributing to drinking behavior. Nevertheless, it could be argued that positive social expectancies and social norms both refer (respectively directly and indirectly) to perceived positive outcomes of drinking. In this sense, measures of positive social expectancies and social norm may tap the same underlying phenomenon (viz., expected social rewards). On the other hand, perceptions of social norms differ from positive social expectancies in that they refer not only to anticipated social rewards, but also to anticipated social punishments. The third factor found to contribute (another 3%) to the explained variance in drinking behavior was self-efficacy regarding one’s ability to cope with social pressures to drink. It is striking that, in the present student population, the three strongest predictors identified in the stepwise analysis were all related to perceived social effects of drinking: The opinions of others, anticipated social rewards or punishments associated with these social norms, expected social outcomes of drinking, and the ability to counter social pressures to drink. A third goal of this study was to assess whether the relative importance of the social cognitive factors differed for male versus female respondents, and for students living with their parents versus those living on their own. In the case of female students, all variance in drinking behavior was explained by factors related to the social context of drinking, with social norm explaining the first 25%. In male students, 25% of the variance was explained by positive social expectancies, while direct negative self-evaluative expectancies added 8%. Thus, besides the anticipation of positive social effects, drinking by male students seemed related to anticipated departure from personal standards. These findings seem partly consistent with research by Brown et al. (1980), who found that women expected more positive social consequences of drinking alcohol, whereas men were more likely to expect arousal and potentially aggressive behavior. In students who lived with their parents, the first 25% of variance in drinking behavior was explained by self-efficacy to cope with social pressures to drink, whereas in students living on their own the first 33% was explained by social norms. Thus, in students who no longer lived

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with their parents, drinking was strongly related to the opinions of others, whereas drinking by students living with their parents was more strongly related to the ability to counter social pressures to drink. In interpreting this difference it is important to consider that the social norm measure used in this study consisted of three items measuring peer opinions and only one measuring parental opinions. It therefore stands to reason that students living on their own, who are likely to be surrounded by peers both day and night, would be particularly vulnerable to such social norms; students living with their parents, on the other hand, may experience relative protection from general peer norms. Therefore, drinking behavior in the latter group may be less governed by social rewards and punishments and more by a personal choice and ability to control drinking. Our fourth goal was to study acquisition and cessation stages in relation to the criterion ‘‘regularly drinking four or more alcoholic beverages on occasions when you drink,’’ and the relation between the social cognitive factors and these stages of change. First of all, students in the contemplation and preparation stages were conspicuous by their absence in the case of both acquisition and cessation: Students who had never regularly drunk four or more alcoholic beverages per occasion were not planning to do so in the future, and students who regularly drank four or more alcoholic beverages per occasion were not planning to drink less in the future. Using a larger sample, Migneault et al. (1997) also found that only 1.2% of their adolescent sample could be classified into the acquisition-contemplation stage, and only 0.8% in the acquisition-preparation stage. Because intentions are usually powerful predictors of behavior, one might expect relatively little future change in drinking behavior in such a sample. On the other hand, it may be that asking people whether they are deliberately planning to engage in an unhealthy behavior does not constitute a valid assessment of the individual’s psychological inclination to do so. With regard to the cessation stages, Migneault et al. did find 6.2% of their participants to be in contemplation and 5.6% in preparation. The absence of respondents in these two cessation stages in the present study might be related to more stable drinking patterns in the present, somewhat older sample, which consisted of young adult university students rather than adolescents. With regard to cognitive differences between the acquisition stages, the present findings replicate those of Migneault et al. (1997) in that precontemplators scored significantly lower than maintainers on reasons to drink and significantly higher on self-evaluative reasons not to drink. Furthermore, the results with regard to tolerance from the social environment (social norms) towards consuming four or more drinks per occasion were similar to those of Hill, Boudreau, Amyot, De´ry, and Godin (1997) with regard to smoking acquisition: Respondents who had not (yet) engaged in the criterion behavior viewed their environment as significantly less tolerant than those who are already engaged in the criterion behavior. The present results were also consistent with those of Hill et al. with regard to self-efficacy: Those who had not (yet) engaged in the criterion behavior were significantly more confident that they would be able to cope with stimuli conductive to the unhealthy criterion behavior than those who are already engaged in the criterion behavior. With regard to the cessation stages, only two clear differences emerged on the social cognitive measures: students in precontemplation reported more people in their environment who consumed four or more drinks per occasion than students in maintenance, and their selfefficacy to cope with social pressures was lower. Thus, in contrast with the findings of

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Migneault et al. (1997), positive and negative expectancies did not discriminate between cessation stages in the present study. This difference may be attributable to the fact that Migneault et al.’s respondents were younger and the groups they compared were larger than those in the present study. Even within the present study, the discriminative power of the social cognitive measures in the present study did appear to be stronger in the acquisition stages (N = 118) than in the cessation stages (N = 71). Another possibility is that the cut-off point of four or more drinks may be more relevant in the acquisition process than in the cessation process. That is, the meaning of four or more drinks in students who never drank that much may differ from the meaning of this number of drinks in students who have experienced the outcomes and controllability of drinking four or more themselves. This study had some limitations. The first limitation is the homogeneous sample of participants. All participants studied at the university and almost 87% were between 8 and 2 years of age. Thus, the generalizability of these findings to other educational and age groups cannot be assumed. A second limitation is the cross-sectional nature of this study, which specifically constrains conclusions with regard to causality. Although social cognitive theory casts the four clusters of predictors examined in this study as causes of behavior, the theory explicitly states that these constructs can also be effects of behavior. That is, experiencing positive or negative effects of drinking shapes positive and negative expectancies, and experiencing of high or low control over drinking shapes self-efficacy expectations. Furthermore, modeling influences and perceptions of social norms can result from selective exposure. That is, people who drink may select others with similar behavior to drink with, thereby shaping their social environment and the social influences to which they are exposed. Thus, the social cognitive constructs assessed in the present study could be effects rather than causes of drinking behavior. However, there is convincing empirical evidence that these four social cognitive constructs can indeed be causal factors in behaviors such as drinking and smoking. In prospective studies, decreases in positive expectancies have predicted decreases in drinking (Darkes & Goldman, 1993), negative expectancies have predicted smoking cessation (Dijkstra et al., 1998), modeling influences have predicted smoking uptake (De Vries et al., 1994) and drinking uptake (Engels, 1998), social norms have predicted drinking (Schlegel et al., 1992) and smoking uptake (De Vries et al., 1994), and self-efficacy expectations have predicted smoking cessation (Mudde, Kok, & Strecher, 1995). Thus, although the present data cannot reveal how strong the causal relation is between these social cognitive constructs and drinking behavior, it is plausible that a considerable percentage of the explained variance observed in this study reflect the causal effects of these constructs on drinking behavior. In the development of health education interventions aimed at decreasing alcohol intake, the social cognitive sources of drinking behavior need to be addressed. The present data suggest several tentative recommendations for intervention development. Firstly, social norms should be targeted as an important determinant of drinking. Perceptions of the opinions of others are based on interpretations of the behavior and verbal responses of others (Sherif, 1936). In group sessions, interpretations of such behavior and verbal responses could be steered so as to reveal less tolerant norms by counselors trained to guide and reinterpret individual responses within the group. Secondly, interventions can be used to counter positive expectancies associated with drinking. Darkes and Goldman (1993)

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succeeded in lowering positive expectancies in students by teaching them that the effects they anticipated from drinking were not due to alcohol, but to their expectancies regarding the effects of alcohol. They had students judge whether a fellow student had or had not drunk an alcoholic beverage. The accuracy of students’ judgments failed to exceed chance levels, setting the stage for a lively discussion of the role of expectancies in drinking behavior. This ‘‘expectancy challenge’’ treatment led to significant decreases both in alcohol expectancies and in alcohol intake. Thirdly, interventions should teach skills to counter pressures to drink (Petraitis, Flay, & Miller, 1995). In role playing exercises, subjects can practice behavioral responses and form implementation intentions that will guide their behavioral responses in actual encounters with social pressures to drink. In conclusion, the psychological model investigated in the present study recognizes negative expectancies, social influence, and self-efficacy expectations, in addition to positive expectancies, as useful constructs for mapping the psychology of drinking. Prospective and experimental studies will be needed to determine to what extent these social cognitive factors are indeed causes rather than effects of drinking behavior. Intervention studies will also be needed to demonstrate that these social cognitive factors can be changed for the better, and that such changes do in fact lead to decreased drinking behavior.

References Aas, H., Klepp, K. I., Laberg, J. C., & Aaro, A. L. (1995). Predicting adolescents intentions to drink alcohol: alcohol expectancies and self-efficacy. Journal of Studies on Alcohol, 56, 293 – 299. Ajzen, I. (1988). Attitudes, personality and behavior. Milton Keynes: Open Univ. Press. Bandura, A. (1986). Social foundations of thought and action; a social cognitive theory. Englewood Cliffs, NJ: Prentice-Hall. Bandura, A. (1997). The exercise of control. New York: Freeman. Brown, S. A., Goldman, M. S., Inn, A., & Anderson, L. R. (1980). Expectations of reinforcement from alcohol: their domain and relation to drinking patterns. Journal of Consulting and Clinical Psychology, 48, 419 – 426. Christiansen, B. A., Smith, G. T., Roehling, P. V., & Goldman, M. S. (1989). Using alcohol expectancies to predict adolescent drinking behavior after one year. Journal of Consulting and Clinical Psychology, 57, 93 – 99. Conner, M., & Norman, P. (1996). Predicting health behaviour. Buckingham: Open Univ. Press. Curran, P. J., Stice, E., & Chassin, L. (1997). The relation between adolescent alcohol use and peer alcohol use: a longitudinal random coefficients model. Journal of Consulting and Clinical Psychology, 65, 130 – 140. Darkes, J., & Goldman, M. S. (1993). Expectancy challenge and drinking reduction: experimental evidence for a mediational process. Journal of Consulting and Clinical Psychology, 61, 344 – 353. De Vries, H., Backbier, E., Dijkstra, M., Van Breukelen, G., Parcel, G., & Kok, G. (1994). A Dutch social influence smoking prevention approach for vocational school students. Health Education Research, 9, 365 – 374. Dijkstra, A., De Vries, H., & Roijackers, J. (1998). Long-term effectiveness of computer-generated tailored feedback in smoking cessation. Health Education Research, 13, 207 – 214. Dunn, M. E., & Goldman, M. S. (1998). Age and drinking-related differences in the memory organization of alcohol expectancies in 3rd-, 6th-, 9th- and 12th-grade children. Journal of Consulting and Clinical Psychology, 66, 579 – 585. Earleywine, M. (1995). Expectancy accessibility, alcohol expectancies and intentions to consume alcohol. Journal of Applied Social Psychology, 25, 933 – 943. Engels, R. (1998). Forbidden fruits. Social dynamics in smoking and drinking behavior of adolescents. Doctoral dissertation. Maastricht University. Garretsen, H. F. L., Bongers, I. M. B., Oers, J. A. M., & Van De Goor, L. A. M. (1999). The development of

706

A. Dijkstra et al. / Addictive Behaviors 26 (2001) 689–706

alcohol consumption and problem drinking in Rotterdam 1980 – 1994: more problem drinking amongst the young and middle aged. Alcohol and Alcoholism, 34, 733 – 740. Godin, G., & Kok, G. (1996). The theory of planned behavior: a review of its applications to health-related behaviors. American Journal of Health Promotion, 11, 87 – 98. Goldman, M. S., Brown, S. A., Christiansen, B. A., & Smith, G. T. (1991). Alcoholism and memory: broadening the scope of alcohol-expectancy research. Psychological Bulletin, 110, 137 – 146. Grube, J. W., Ames, G. M., & Delaney, W. (1994). Alcohol expectancies and workplace drinking. Journal of Applied Social Psychology, 24, 646 – 660. Hill, A. J., Boudreau, F., Amyot, E., De´ry, D., & Godin, G. (1997). Predicting the stages of smoking acquisition according to the theory of planned behavior. Journal of Adolescent Health, 21, 107 – 115. Kilty, K. M. (1987). Attitudinal and normative variables as predictors of drinking behavior. Journal of Studies on Alcohol, 39, 1178 – 1194. Lee, N. K., Greely, J., & Oei, T. P. (1999). The relationship of positive and negative alcohol expectancies to patterns of consumption of alcohol in social drinkers. Addictive Behaviors, 24, 359 – 369. Leigh, B. C. (1989). In search of the seven dwarves: issues of measurement and meaning in alcohol expectancy research. Psychological Bulletin, 105, 361 – 373. Leigh, B. C., & Stacy, A. W. (1991). On the scope of alcohol expectancy research remaining issues of measurement and meaning. Psychological Bulletin, 110, 147 – 154. Marcoux, B. C., & Shope, J. T. (1997). Application of the theory of planned behavior to adolescent use and misuse of alcohol. Health Education Research, 12, 323 – 331. Marlatt, G. A., & Gordon, J. R. (1985). Relapse prevention: maintenance strategies in the treatment of addictive behaviors. New York, London: Guilford Press. Migneault, J. P., Pallonen, U. E., & Velicer, W. F. (1997). Decisional balance and stage of change for adolescent drinking. Addictive behavior, 22, 339 – 351. Mudde, A. N., Kok, G. J., & Strecher, V. J. (1995). Self-efficacy as a predictor for the cessation of smoking: methodological issues and implications for smoking cessation programs. Psychology and Health, 10, 353 – 367. Petraitis, J., Flay, B. R., & Miller, T. Q. (1995). Reviewing theories of adolescent substance use: organizing pieces in the puzzle. Psychological Bulletin, 1, 67 – 86. Prochaska, J. O., DiClemente, C. C., & Norcross, J. C. (1992). In search of how people change, applications to addictive behaviors. American Psychologist, 47, 1102 – 1114. Schlegel, R. P., D’Avernas, J. R., Zanna, M. P., DeCourville, N. H., & Manske, S. R. (1992). Problem drinking: a problem for the theory of reasoned action? Journal of Applied Social Psychology, 22, 358 – 385. Shafer, J., & Leigh, B. C. (1996). A comparison of factor structures of adolescent and adult alcohol expectancies. Addictive Behaviors, 21, 403 – 408. Sherif, M. (1936). The psychology of social norms. New York: Harper & Row. Skutle, A. (1999). The relationship among self-efficacy expectancies, severity of alcohol abuse and psychological benefits from drinking. Addictive Behaviors, 24, 87 – 98. Smith, G. T., Goldman, M. S., Greenbaum, P. E., & Christiansen, B. A. (1995). Expectancy for social facilitation from drinking: the divergent paths of high-expectancy and low-expectancy adolescents. Journal of Abnormal Psychology, 104, 32 – 40. Trafimov, D. (1996). The importance of attitudes in the prediction of college students’ intentions to drink. Journal of Applied Social Psychology, 26, 2167 – 2188. Wechsler, H., Dowdall, G. W., Davenport, A., & Rimm, E. B. (1995). A gender-specific measure of binge drinking among college students. American Journal of Public Health, 85, 982 – 985. Wiers, R. W., Hoogeveen, K., Sergeant, J. A., & Gunning, W. B. (1997). High- and low-dose alcohol-related expectancies and the differential associations with drinking in male and female adolescent and young adults. Addiction, 92, 871 – 888.