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Individual differences in trait urgency moderate the role of the affect heuristic in adolescent binge drinking
Personality and Individual Differences 47 (2009) 829–834
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Personality and Individual Differences journal homepage: www.elsevier.com/locate/paid
Individual differences in trait urgency moderate the role of the affect heuristic in adolescent binge drinking Wendy J. Phillips *, Donald W. Hine, Anthony D.G. Marks School of Behavioural, Cognitive and Social Sciences, University of New England, Armidale, NSW 2351, Australia
a r t i c l e
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Article history: Received 27 January 2009 Received in revised form 29 May 2009 Accepted 26 June 2009 Available online 31 July 2009 Keywords: Adolescents Alcohol Binge drinking Addictive behaviours Affect heuristic Dual process Urgency Impulsivity
a b s t r a c t This study investigated the roles of the affect heuristic and outcome beliefs in explaining the relationship between negative urgency and adolescent binge drinking behaviour. The sample consisted of 391 Australian high school students, who were selected to be low or high on urgency. We hypothesised that highly urgent adolescents would be more likely than adolescents low in urgency to utilise the affect heuristic (i.e., to rely upon affective input) when making alcohol-related decisions. Multiple-group path analysis supported this prediction. Adolescents high in urgency exhibited greater use of the affect heuristic by displaying a direct path from affective associations to binge drinking; whereas adolescents low in urgency exhibited greater reliance upon rational processing by displaying an indirect path via outcome beliefs. Ó 2009 Elsevier Ltd. All rights reserved.
1. Introduction Binge drinking represents a dangerous adolescent pastime. Between 20% and 30% of teenagers in Australia, Canada, the United Kingdom, and the United States, regularly consume large amounts of alcohol over short periods of time (World Health Organization, 2004). Strategies to prevent or curb alcohol use typically include components that address known risk factors. Therefore greater awareness of these factors can lead to more effective strategies. To this end, a utilitarian etiological picture may be revealed by integrating contributions from independent fields of psychological research. Contributions from cognitive psychologists have primarily involved consequentialist decision making theories of alcohol consumption, such as expectancy theory (Mitchell & Biglan, 1971), conflict theory of decisional balance (Prochaska et al., 1994), and the theory of reasoned action (Ajzen, 2000). From this broad theoretical perspective, beliefs about the consequences of alcohol use are posited as the main determinants of drinking behaviour. This approach suggests that the decision to drink alcohol involves a rational process of weighing the anticipated positive and negative consequences of alcohol use, and performing a mental cost-benefit analysis. Several similar cognitive constructs have been developed * Corresponding author. Tel.: +61 2 6773 3606; fax: +61 2 6773 3820. E-mail address: [email protected] (W.J. Phillips). 0191-8869/$ - see front matter Ó 2009 Elsevier Ltd. All rights reserved. doi:10.1016/j.paid.2009.06.028
to assess this proposition, including outcome expectancies (Brown, Goldman, Inn, & Anderson, 1980), the pros and cons of drinking (Migneault, Pallonen, & Velicer, 1997), and behavioural beliefs (Fishbein & Ajzen, 1975). Ensuing research has consistently supported the consequentialist perspective. For example, self-reported beliefs about the consequences of drinking have predicted alcohol consumption, binge drinking and drinking problems in cross-sectional and longitudinal studies of adolescents and undergraduates (e.g., Christiansen & Goldman, 1983; Sher, Wood, Wood, & Ruskin, 1996). A preponderance of positive beliefs about the consequences of alcohol use may be viewed as a proximal risk factor for alcohol consumption. Conversely, personality traits have been investigated as ultimate risk factors. In particular, a relationship between impulsivity and alcohol use is well supported (see Baer, 2002). Until recently, clarification of this relationship was impeded by multiple definitions of ‘‘impulsivity” in the psychological literature. However, Whiteside and Lynam’s (2001) identification of distinct impulsivity-related traits has facilitated recent investigations into the impulsivity–risk relationship. The impulsivity-related trait of negative urgency reflects individual differences in the tendency to act rashly, quickly, and without planning, while experiencing negative emotion (Cyders & Smith, 2008). Urgency has been associated with problem levels of involvement in several risky behaviours (see Cyders & Smith, 2008). In relation to alcohol use, individuals who self-report as high in
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urgency have been found to consume more alcohol, develop more drinking problems, and engage in more heavy drinking than less urgent individuals (Fischer, Anderson, & Smith, 2004; Smith et al., 2007). Recent research has focussed on determining proximal mechanisms by which biologically based impulsivity traits influence drinking behaviour. For example, it has been proposed that individuals with high levels of trait disinhibition possess a rewardseeking style which predisposes them to develop and act upon positive alcohol outcome expectancies (Smith & Anderson, 2001). Supporting this position, positive expectancies have been found to moderate and to mediate the relationship between disinhibition and alcohol use (e.g., McCarthy, Kroll, & Smith, 2001). Using similar reasoning, Fischer and colleagues (2004, 2008) suggested that individuals with high levels of negative urgency may acquire the expectation that alcohol will relieve feelings of distress. However initial investigations have failed to observe an interaction between urgency and tension reduction expectancies in the prediction of alcohol use or drinking problems (Fischer et al., 2004; Fischer & Smith, 2008). The absence of a significant interaction between urgency and expectancies suggests that another factor may activate the relationship between urgency and alcohol use. Expectancy models of drinking focus on rational determinants of decision making and behaviour (i.e., outcome beliefs), and generally view affect as an evaluative component of a belief. However separate research has demonstrated that affect can also independently influence decision making by acting as informational input (see Loewenstein, Weber, Hsee, & Welch, 2001). In this capacity, affect refers to a ‘‘quality of goodness or badness (1) experienced as a feeling state (with or without consciousness) and (2) demarcating a positive or negative quality of a stimulus” that derives from prior exposure to the same or similar stimulus (Slovic, Peters, Finucane, & MacGregor, 2005, p. S35). According to Slovic and colleagues (2002), an individual’s affective responses to a stimulus leads to particular affective associations becoming attached to the stimulus image in the individual’s mind, where the image is stored with both affective and rational components. Thus, images stored in memory are tagged with affect, forming a type of ‘‘affect pool” containing all positive and negative affective associations pertaining to each image. Individuals are thought to consult their affect pool when subsequently confronted with a similar stimulus. In this way, the nature and intensity of an individual’s affective associations may influence responses to decision alternatives. Researchers have identified several ways that affect can influence decision making and behavioural outcomes. Experimental studies have demonstrated that affective reactions are typically faster than cognitive evaluations (LeDoux, 1996; Zajonc, 1980), and can influence decision outcomes with little or no cognitive mediation (see Loewenstein et al., 2001). Neurological evidence has also supported a direct affect–behaviour relationship, by identifying neural projections from the sensory thalamus to the amygdala that are not mediated by cortical processing (LeDoux, 1996). Due to their speed and automaticity, affective responses to a decision task may provide a quick assessment of behavioural options that enables rapid action (Zajonc, 1980). These fast affectbased assessments and actions led Slovic and colleagues (2002), Slovic and colleagues (2005) to coin the phrase ‘‘affect heuristic”; a term that aptly describes an emotionally-driven shortcut that bypasses rational considerations of decision alternatives. Affect has also been hypothesised to influence behaviour indirectly, whereby affective responses to a decision task serve to redirect rational processing toward high-priority concerns (Armony, Servan-Schreiber, Cohen, & LeDoux, 1995). For example, Damasio (1994) proposed that affective reactions to behavioural alternatives determine their
relative desirability, which in turn guides conscious decision making. The affect heuristic is based on dual-process models of decision making which posit that individuals possess two distinct information processing systems: (1) an experiential system that is passive, effortless, fast, and involves affective responses to behavioural options, and (2) a rational system that is deliberate, effortful, largely affect free, and involves traditional cost-benefit analyses (e.g., Epstein, 1994). Like behaviour resulting from the experiential system, negative urgency involves acting quickly, spontaneously and rashly in response to emotions. Thus, individual differences in urgency may influence the degree of reliance upon affective input during decision making leading to alcohol use. The current study attempts to integrate contributions from personality and cognitive researchers by applying the affect heuristic (Slovic et al., 2005). It aims to explain the relationship between negative urgency and binge drinking behaviour in adolescents, by investigating the roles of outcome beliefs (i.e., pros and cons of drinking) and affective associations with alcohol use. We hypothesised that urgency would moderate the predictive effects of affective associations and perceived pros and cons of alcohol use on binge drinking. More specifically, we predicted that a direct relationship between affective associations and binge drinking would be stronger for adolescents high in urgency than for low scorers on this personality dimension. Conversely, we expected that an indirect relationship between affective associations and binge drinking, via pros and cons of alcohol use, would be stronger for adolescents who score low on urgency than for highly urgent adolescents. 2. Method 2.1. Participants Participants were 555 Australian high school students (296 males and 259 females) aged between 14 and 18 years (M = 15.68, SD = 1.19). Of these, 58 cases were deleted due to excessive missing data (>30%) or a failure to respond to the alcohol use measures. These cases appeared to comprise non-drinkers and hostile respondents. To facilitate clear comparisons between low and high urgency respondents, only participants who scored 0.25 SD below the mean and 0.25 SD above the mean of the urgency measure were retained for subsequent analyses, leaving a final sample of 391. All missing data were replaced by values imputed by the expectation maximization algorithm in SPSS 14 (SPSS Inc., 2005). 2.2. Procedure Data were collected by completion of a questionnaire assessing demographics, affective associations with alcohol use, alcohol consumption, alcohol outcome beliefs, and negative urgency. Students were recruited from classes identified by the school principal. After obtaining consent from parents and students, the questionnaires were administered during class time. Participants were instructed not to discuss their responses with classmates, and advised that all responses would remain anonymous. 2.3. Measures 2.3.1. Binge drinking Binge drinking was measured by two estimates of heavy drinking behaviour: maximum alcohol use and binge drinking frequency. Maximum alcohol use represented an estimate of alcohol consumed during heavy drinking episodes. Participants reported
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the largest number of standard alcoholic drinks they have ever consumed within a 24-h period. One standard drink was defined as 10 g of pure alcohol, and examples were provided. Participants also indicated how often they consume that number of drinks within a 24-h period. This was assessed on a 10-point scale ranging from (0) never to (9) every day, which was subsequently converted into days per month (e.g., never = 0, every day = 30). When a point represented a range of frequencies, the midpoint was calculated (e.g., 2–3 times a month became 2.5 days per month; Dawson, 2003). The largest quantity of alcohol consumed within 24-h was multiplied by the frequency of consuming that amount within 24-h to produce an estimate of the number of drinks consumed per month during heavy drinking sessions. Binge drinking frequency was assessed by a single item that asked participants how often they consume 4+ standard drinks (females) or 5+ standard drinks (males) within a 2-h period. Participants responded on the same 10-point scale, which was subsequently converted into days per month. The binge drinking frequency and maximum alcohol use measures were treated as two observed indicators assessing a latent variable labelled binge drinking (a = .89).
2.3.2. Negative urgency Negative urgency was assessed by the UPPS Impulsive Behavior Scale (Whiteside & Lynam, 2001), an inventory that assesses four impulsivity-related constructs: urgency, (lack of) premeditation, (lack of) perseverance, and sensation seeking. The urgency subscale consists of 12 items measuring the degree to which individuals act rashly when experiencing negative affect (e.g., ‘‘I often make matters worse because I act without thinking when I am upset”). Respondents rated how well each statement applies to them on a 4-point scale from (1) agree to (4) disagree. Urgency scores were computed by summing item scores (a = .82). Adolescents who scored less than 0.25 SD below the mean were classified as Low urgency (n = 196, M = 22.01, SD = 3.63) and those who scored more than 0.25 SD above the mean were classified as High urgency (n = 195, M = 35.21, SD = 3.56).
2.3.3. Alcohol outcome beliefs Positive and negative beliefs about the outcomes of alcohol use were assessed by the 16-item Decisional Balance Inventory (DBI; Migneault et al., 1997). Eight statements describing positive drinking outcomes comprise a Pros scale (e.g., ‘‘Drinking gives me courage”) and eight items listing negative outcomes comprise a cons scale (e.g., ‘‘Drinking causes problems with others”). Participants were asked to rate the importance of each outcome when deciding if, or how much, to drink. Response options ranged from (1) not important to (5) extremely important. Composite measures of expected pros and cons were computed by summing scale items (pros a = .90, cons a = .85).
2.3.4. Affective associations The word association approach developed by Peters and Slovic (1996) measured alcohol-related affective associations comprising each participant’s ‘‘affect pool”. Participants were asked to list the first five thoughts or images that came to mind when presented with the phrase ‘‘drinking alcohol”, and to rate the thought/image on a scale ranging from (1) very negative to (5) very positive. The five affective response scores were summed to produce a composite score of affective associations with alcohol use (a = .69). An exploratory factor analysis of the eight pros, eight cons, and five affective items confirmed the independence of the affective associations construct. Three factors were extracted according to Cattell’s (1966) Scree Test. Following an oblimin rotation, the five affective items loaded above 0.54 on the third factor, with no cross-loadings over 0.13. 3. Results 3.1. Descriptives Of the 391 participants in the final sample, 300 (77%) were drinkers. Of these, 75% drank less than weekly and averaged one standard drink per week, and 25% drank at least weekly and averaged 15 standard drinks per week. Urgency was significantly positively associated with maximum alcohol use (r = .15, p < .01) and binge drinking frequency (r = .14, p < .01). Means, standard deviations, and correlations for affective associations, pros, cons, and alcohol consumption for the low and high urgency groups are presented in Table 1. 3.2. Multiple-group path analysis Multiple-group path analysis was conducted using AMOS 7.0 (Arbuckle, 2006) to test the hypothesis that urgency moderates the pathways specified in the hypothesised model depicted in Fig. 1. The model posits relationships between binge drinking and the observed variables of affective associations, perceived pros, and perceived cons. Binge drinking was operationalized as a latent variable with two indicators: maximum alcohol use and binge drinking frequency. The alcohol variables were positively skewed, which can produce biased standard errors and misleading significance tests (Cohen, Cohen, West, & Aiken, 2003). To avoid this possibility, we re-computed all significance tests using standard errors based on 1000 bootstrapped samples (Byrne, 2001). Nested model comparisons computed by AMOS indicated that the unconstrained model fit the data significantly better than the same model with all paths constrained to be equal across the two urgency groups, v2difference (6) = 21.58, p = .001. A significant v2difference value indicates that the path coefficients may differ in the sampled populations. Thus, the path coefficients for low and
Table 1 Correlations, means, and standard deviations across low and high urgency groups. Variable
High urgency 1
1. Pros 2. Cons 3. Affective associations 4. Binge drinking frequency 5. Maximum alcohol use Low urgency
2
3 .33**
M SD
.27** .22** .23** .18* 15.12 6.98
4 .22** .18*
**
.28 .08 .08 22.45 8.71
.12 .07 13.93 4.57
5 .22** .02 .29**
.83** .63 2.59
Note: Correlations for the high and low urgency groups are reported above and below the diagonal, respectively. * p < .05. ** p < .01.
.21** .01 .29** .85** 3.07 11.08
M
SD
20.17 24.12 15.56 1.84 17.41
8.11 8.09 4.50 5.43 62.65
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Pros of Drinking .22** (.22**)
.27*** (.17*) Maximum Alcohol Use e1
.36 (.38)
.82*** (.91***)
.02 (.28***)
Affective Associations
e3
R2 = .08 (.13) Binge Drinking 1.00 NT (.93NT)
e2
Binge Drinking Frequency
-.28*** (-.18*)
e4
-.15* (.01) Cons of Drinking
Fig. 1. Summary of multiple-group path analysis assessing the effects of affective associations, pros, and cons on binge drinking for participants scoring low and high on urgency. Unparenthesized and parenthesized values are standardized coefficients for low and high urgency groups, respectively. All significance tests were based on standard errors computed from 1000 bootstrapped samples. *p < .05, **p < .01, ***p < .001, NT, effect not tested.
Table 2 Fit indices for multiple-group path analysis: unconstrained and constrained models. Model
v2
df
CFI
SRMR
RMSEA
Unconstrained Constrained (structural weights)
1.02 22.60*
4 10
1.00 .98
.01 .08
.00 .06
Note: CFI, comparative fit index; SRMR, standardized root mean square residual; RMSEA, root mean square error of approximation. Based on Kline (2005), good fit is defined as non-significant v2, CFI > .90, RMSEA < .08, and SRMR < .10. For the RMSEA and SRMR, a value of 0 represents perfect fit. * p < .05.
high urgency groups were interpreted separately (Arbuckle & Wothke, 1999). The fit indices associated with the two models are presented in Table 2. Affective associations, pros, and cons explained 13% of the variance in binge drinking for the high urgency group and 8% for low urgency. A summary of the unconstrained group comparison analysis is presented in Fig. 1. As predicted, the direct path from affective associations to binge drinking was stronger for adolescents who scored higher on urgency. That is, affective associations were significantly positively associated with binge drinking for highly urgent adolescents but not for those low in urgency. Conversely, the path between cons and binge drinking was moderate in magnitude and significant for the low urgency group, but was small and non-significant for the high urgency group. The path between pros and binge drinking was significant for both groups but the relationship was stronger for the low urgency group. As shown in Table 3, significance tests of direct and indirect effects indicated that the path from affective associations to binge drinking was fully mediated by outcome beliefs for the low urgency group. That is, the indirect path from affective associations through pros and cons to binge drinking was statistically significant, whereas the direct effect of affective associations on binge drinking, after controlling for pros and cons, was not. In contrast, for those who scored high on urgency, the direct path from affective associations to binge drinking was significant, whereas the indirect effect through pros and cons was not. Thus, in both instances respondents’ affective associations predicted binge drinking, but the respective influential paths differed across groups. 4. Discussion The present study tested predictions derived by combining the affect heuristic (Slovic et al., 2002; Slovic et al., 2005) with cognitive and personality research relating to adolescent alcohol use.
Specifically we investigated whether individual differences in negative urgency would moderate the predictive effects of affective associations and alcohol outcome beliefs, to produce different decision making pathways to binge drinking behaviour. As predicted, urgency moderated the effects of affective associations and outcome beliefs on binge drinking. Affective associations were significant direct predictors of binge drinking for high urgency respondents but not for low urgency respondents. In contrast, beliefs about the pros and cons of drinking were stronger predictors of binge drinking for low urgency respondents than for high urgency respondents. For low urgency adolescents, the association between affective associations and binge drinking was fully mediated by pros and cons. That is, low urgency respondents who reported more positive affective associations with drinking alcohol endorsed more pros and fewer cons of drinking, which in turn were associated with greater binge drinking. In contrast, high urgency adolescents’ beliefs about the pros of alcohol use only partially mediated the predictive effect of affective associations on binge drinking. These results are consistent with the view that adolescents with low versus high trait urgency differ in their use of the affect heuristic and rational analysis when making drinking decisions. The affect heuristic may play a more important role in guiding the binge drinking behaviour of high urgency adolescents, whereas a rational assessment of expected positive and negative outcomes may be more influential in guiding the binge drinking of low urgency adolescents. Integrating the affect heuristic with personality research has important theoretical and practical utility. Our study provides preliminary evidence that individuals with different levels of the personality trait negative urgency may make drinking decisions in fundamentally different ways. This knowledge can inform the development of more effective health education programs and interventions. Intervention and prevention strategies are often based on the premise that modifying drinking behaviour involves changing outcome beliefs or developing rational thinking skills (e.g., Darkes & Goldman, 1993). However these approaches have achieved only limited success (Carey, Scott-Sheldon, Carey, & DeMartini, 2007; Skiba, Monroe, & Wodarski, 2004), which suggests they may be ineffective for large segments of the population. Our finding that expected pros and cons explained unique variance in binge drinking for adolescents characterized by low levels of urgency, suggests that these adolescents may be guided by outcome beliefs and may benefit from interventions that target rational processes. However highly urgent adolescents in our sample reported relatively greater reliance upon affective input
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W.J. Phillips et al. / Personality and Individual Differences 47 (2009) 829–834 Table 3 Effects decomposition for the urgency path model of adolescent binge drinking. Moderators
Endogenous variables Pros of drinking
Low urgency Affective associations Direct effects Indirect effects Total effects Pros of drinking Direct effects Indirect effects Total effects Cons of drinking Direct effects Indirect effects Total effects High urgency Affective associations Direct effects Indirect effects Total effects Pros of drinking Direct effects Indirect effects Total effects Cons of drinking Direct effects Indirect effects Total effects
Cons of drinking
Unst.
SE
St.
Unst.
.34** – .34**
.10 – .10
.22** – .22**
–
– –
– –
– –
– –
– –
.39** – .39**
Binge drinking SE
St.
.13 – .13
–
– –
– –
– –
– –
.13 – .13
.22** – .22**
–
– – –
– – –
– – –
– – –
– – –
– – –
.54**
.28**
Unst.
SE
St.
.01 .06** .07
.08 .03 .07
.02 .10** .12
– –
.10** – .10**
.05 – .05
.27** – .27**
– –
– –
.05* – .05*
.03 – .03
.15* – .15*
.13 – .13
–
.31** .04 .35**
.13 .04 .12
.28** .04 .31**
– – –
– – –
– – –
.11 – .11
.06 – .06
.17 – .17
– – –
– – –
– – –
.01 – .01
.06 – .06
.01 – .01
.54**
.32* .32*
.28**
.18* .18*
Note: All significance tests for direct, indirect, and total effects are based on 1000 bootstrapped samples. Unst., unstandardized effects; SE, standard errors; St., standardized effects. * p < .05. ** p < .01.
when making alcohol-related decisions, suggesting that the relevance of purely rational strategies for these individuals may be limited. This is a particularly poignant revelation, given that problematic alcohol consumption is typically positively associated with urgency. That is, current strategies that target rational thinking may be least adequate for those most at risk. High urgency adolescents appear to be guided by affective input; therefore interventions for these individuals should target affect. Alternatively, high urgency adolescents may benefit from a combination of interventions. According to dual-process theory, the observed decision making pathways of low and high urgency adolescents may reflect tendencies to rely upon different information systems. Low urgency adolescents may favour the analytical rational system, whereas high urgency adolescents may prefer the heuristic experiential system. Apart from analysing options, another important function of the rational system involves overriding inappropriate heuristic responses and replacing them with reasoned alternatives. Stanovich and West (2008) proposed that this process entails identifying when heuristic responses should be replaced, as well as knowing how to substitute analytical responses. Consequently, high urgency adolescents may respond to interventions that boost awareness of their affective states and heuristic responses, prior to developing rational thinking skills. When interpreting these results, it is important to remember that this study was based on a community sample of Australian adolescents and these findings may not generalise to other samples and settings. For example, greater use of the affect heuristic may be observed in ‘‘high risk” samples. Other potential limitations of the study include its relatively small sample size for the analysis, positively skewed alcohol use variables, marginal internal consistency of the affective associations measure, and the use of self-report methodology. Retrospective self-reported estimates of binge drinking are subject to recall bias and provide only an indirect measure
of drinking behaviour. Future studies could elicit more accurate estimates by using alternative methodology, such as a diary to record binge drinking over time. Furthermore, interpretation of these results should be tempered by problems inherent in the correlational nature of the analyses. Although path analysis can assess the plausibility of hypothetical causal processes, strong causal inferences are not appropriate when the technique is used with cross-sectional correlational data, given the possibility of third-variable explanations and ambiguity about the true direction of effects. Reassessing this model using a longitudinal design that measures variables at different times, or an experimental design that manipulates participants’ affective associations, would provide a stronger framework for identifying causal effects (Kline, 2005). Our findings are consistent with the view that both affective associations and outcome beliefs guide adolescents’ binge drinking behaviour, and that the relative involvement of affective and rational input may be influenced by urgency. As Wiers and Stacy (2006) note, a focus on affective processes does not discount the relevance of rational decision making to understanding addictive behaviours. Rather, it underlines the need for such affective processes to be understood if addictive behaviours are to be successfully treated. Overall, these results suggest that the affect heuristic offers a worthwhile vantage point for further etiological explorations into the enigmatic arena of adolescent drinking behaviour. References Ajzen, I. (2000). Theory of reasoned action. In A. E. Kazdin (Ed.). Encyclopedia of psychology (Vol. 8, pp. 61–63). Washington, DC, US: American Psychological Association. Arbuckle, J. L. (2006). AMOS 7.0.0. Chicago: Smallwaters. Arbuckle, J. L., & Wothke, W. (1999). AMOS 4.0 user’s guide. Chicago: Smallwaters.
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Personality and Individual Differences journal homepage: www.elsevier.com/locate/paid
Individual differences in trait urgency moderate the role of the affect heuristic in adolescent binge drinking Wendy J. Phillips *, Donald W. Hine, Anthony D.G. Marks School of Behavioural, Cognitive and Social Sciences, University of New England, Armidale, NSW 2351, Australia
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Article history: Received 27 January 2009 Received in revised form 29 May 2009 Accepted 26 June 2009 Available online 31 July 2009 Keywords: Adolescents Alcohol Binge drinking Addictive behaviours Affect heuristic Dual process Urgency Impulsivity
a b s t r a c t This study investigated the roles of the affect heuristic and outcome beliefs in explaining the relationship between negative urgency and adolescent binge drinking behaviour. The sample consisted of 391 Australian high school students, who were selected to be low or high on urgency. We hypothesised that highly urgent adolescents would be more likely than adolescents low in urgency to utilise the affect heuristic (i.e., to rely upon affective input) when making alcohol-related decisions. Multiple-group path analysis supported this prediction. Adolescents high in urgency exhibited greater use of the affect heuristic by displaying a direct path from affective associations to binge drinking; whereas adolescents low in urgency exhibited greater reliance upon rational processing by displaying an indirect path via outcome beliefs. Ó 2009 Elsevier Ltd. All rights reserved.
1. Introduction Binge drinking represents a dangerous adolescent pastime. Between 20% and 30% of teenagers in Australia, Canada, the United Kingdom, and the United States, regularly consume large amounts of alcohol over short periods of time (World Health Organization, 2004). Strategies to prevent or curb alcohol use typically include components that address known risk factors. Therefore greater awareness of these factors can lead to more effective strategies. To this end, a utilitarian etiological picture may be revealed by integrating contributions from independent fields of psychological research. Contributions from cognitive psychologists have primarily involved consequentialist decision making theories of alcohol consumption, such as expectancy theory (Mitchell & Biglan, 1971), conflict theory of decisional balance (Prochaska et al., 1994), and the theory of reasoned action (Ajzen, 2000). From this broad theoretical perspective, beliefs about the consequences of alcohol use are posited as the main determinants of drinking behaviour. This approach suggests that the decision to drink alcohol involves a rational process of weighing the anticipated positive and negative consequences of alcohol use, and performing a mental cost-benefit analysis. Several similar cognitive constructs have been developed * Corresponding author. Tel.: +61 2 6773 3606; fax: +61 2 6773 3820. E-mail address: [email protected] (W.J. Phillips). 0191-8869/$ - see front matter Ó 2009 Elsevier Ltd. All rights reserved. doi:10.1016/j.paid.2009.06.028
to assess this proposition, including outcome expectancies (Brown, Goldman, Inn, & Anderson, 1980), the pros and cons of drinking (Migneault, Pallonen, & Velicer, 1997), and behavioural beliefs (Fishbein & Ajzen, 1975). Ensuing research has consistently supported the consequentialist perspective. For example, self-reported beliefs about the consequences of drinking have predicted alcohol consumption, binge drinking and drinking problems in cross-sectional and longitudinal studies of adolescents and undergraduates (e.g., Christiansen & Goldman, 1983; Sher, Wood, Wood, & Ruskin, 1996). A preponderance of positive beliefs about the consequences of alcohol use may be viewed as a proximal risk factor for alcohol consumption. Conversely, personality traits have been investigated as ultimate risk factors. In particular, a relationship between impulsivity and alcohol use is well supported (see Baer, 2002). Until recently, clarification of this relationship was impeded by multiple definitions of ‘‘impulsivity” in the psychological literature. However, Whiteside and Lynam’s (2001) identification of distinct impulsivity-related traits has facilitated recent investigations into the impulsivity–risk relationship. The impulsivity-related trait of negative urgency reflects individual differences in the tendency to act rashly, quickly, and without planning, while experiencing negative emotion (Cyders & Smith, 2008). Urgency has been associated with problem levels of involvement in several risky behaviours (see Cyders & Smith, 2008). In relation to alcohol use, individuals who self-report as high in
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urgency have been found to consume more alcohol, develop more drinking problems, and engage in more heavy drinking than less urgent individuals (Fischer, Anderson, & Smith, 2004; Smith et al., 2007). Recent research has focussed on determining proximal mechanisms by which biologically based impulsivity traits influence drinking behaviour. For example, it has been proposed that individuals with high levels of trait disinhibition possess a rewardseeking style which predisposes them to develop and act upon positive alcohol outcome expectancies (Smith & Anderson, 2001). Supporting this position, positive expectancies have been found to moderate and to mediate the relationship between disinhibition and alcohol use (e.g., McCarthy, Kroll, & Smith, 2001). Using similar reasoning, Fischer and colleagues (2004, 2008) suggested that individuals with high levels of negative urgency may acquire the expectation that alcohol will relieve feelings of distress. However initial investigations have failed to observe an interaction between urgency and tension reduction expectancies in the prediction of alcohol use or drinking problems (Fischer et al., 2004; Fischer & Smith, 2008). The absence of a significant interaction between urgency and expectancies suggests that another factor may activate the relationship between urgency and alcohol use. Expectancy models of drinking focus on rational determinants of decision making and behaviour (i.e., outcome beliefs), and generally view affect as an evaluative component of a belief. However separate research has demonstrated that affect can also independently influence decision making by acting as informational input (see Loewenstein, Weber, Hsee, & Welch, 2001). In this capacity, affect refers to a ‘‘quality of goodness or badness (1) experienced as a feeling state (with or without consciousness) and (2) demarcating a positive or negative quality of a stimulus” that derives from prior exposure to the same or similar stimulus (Slovic, Peters, Finucane, & MacGregor, 2005, p. S35). According to Slovic and colleagues (2002), an individual’s affective responses to a stimulus leads to particular affective associations becoming attached to the stimulus image in the individual’s mind, where the image is stored with both affective and rational components. Thus, images stored in memory are tagged with affect, forming a type of ‘‘affect pool” containing all positive and negative affective associations pertaining to each image. Individuals are thought to consult their affect pool when subsequently confronted with a similar stimulus. In this way, the nature and intensity of an individual’s affective associations may influence responses to decision alternatives. Researchers have identified several ways that affect can influence decision making and behavioural outcomes. Experimental studies have demonstrated that affective reactions are typically faster than cognitive evaluations (LeDoux, 1996; Zajonc, 1980), and can influence decision outcomes with little or no cognitive mediation (see Loewenstein et al., 2001). Neurological evidence has also supported a direct affect–behaviour relationship, by identifying neural projections from the sensory thalamus to the amygdala that are not mediated by cortical processing (LeDoux, 1996). Due to their speed and automaticity, affective responses to a decision task may provide a quick assessment of behavioural options that enables rapid action (Zajonc, 1980). These fast affectbased assessments and actions led Slovic and colleagues (2002), Slovic and colleagues (2005) to coin the phrase ‘‘affect heuristic”; a term that aptly describes an emotionally-driven shortcut that bypasses rational considerations of decision alternatives. Affect has also been hypothesised to influence behaviour indirectly, whereby affective responses to a decision task serve to redirect rational processing toward high-priority concerns (Armony, Servan-Schreiber, Cohen, & LeDoux, 1995). For example, Damasio (1994) proposed that affective reactions to behavioural alternatives determine their
relative desirability, which in turn guides conscious decision making. The affect heuristic is based on dual-process models of decision making which posit that individuals possess two distinct information processing systems: (1) an experiential system that is passive, effortless, fast, and involves affective responses to behavioural options, and (2) a rational system that is deliberate, effortful, largely affect free, and involves traditional cost-benefit analyses (e.g., Epstein, 1994). Like behaviour resulting from the experiential system, negative urgency involves acting quickly, spontaneously and rashly in response to emotions. Thus, individual differences in urgency may influence the degree of reliance upon affective input during decision making leading to alcohol use. The current study attempts to integrate contributions from personality and cognitive researchers by applying the affect heuristic (Slovic et al., 2005). It aims to explain the relationship between negative urgency and binge drinking behaviour in adolescents, by investigating the roles of outcome beliefs (i.e., pros and cons of drinking) and affective associations with alcohol use. We hypothesised that urgency would moderate the predictive effects of affective associations and perceived pros and cons of alcohol use on binge drinking. More specifically, we predicted that a direct relationship between affective associations and binge drinking would be stronger for adolescents high in urgency than for low scorers on this personality dimension. Conversely, we expected that an indirect relationship between affective associations and binge drinking, via pros and cons of alcohol use, would be stronger for adolescents who score low on urgency than for highly urgent adolescents. 2. Method 2.1. Participants Participants were 555 Australian high school students (296 males and 259 females) aged between 14 and 18 years (M = 15.68, SD = 1.19). Of these, 58 cases were deleted due to excessive missing data (>30%) or a failure to respond to the alcohol use measures. These cases appeared to comprise non-drinkers and hostile respondents. To facilitate clear comparisons between low and high urgency respondents, only participants who scored 0.25 SD below the mean and 0.25 SD above the mean of the urgency measure were retained for subsequent analyses, leaving a final sample of 391. All missing data were replaced by values imputed by the expectation maximization algorithm in SPSS 14 (SPSS Inc., 2005). 2.2. Procedure Data were collected by completion of a questionnaire assessing demographics, affective associations with alcohol use, alcohol consumption, alcohol outcome beliefs, and negative urgency. Students were recruited from classes identified by the school principal. After obtaining consent from parents and students, the questionnaires were administered during class time. Participants were instructed not to discuss their responses with classmates, and advised that all responses would remain anonymous. 2.3. Measures 2.3.1. Binge drinking Binge drinking was measured by two estimates of heavy drinking behaviour: maximum alcohol use and binge drinking frequency. Maximum alcohol use represented an estimate of alcohol consumed during heavy drinking episodes. Participants reported
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the largest number of standard alcoholic drinks they have ever consumed within a 24-h period. One standard drink was defined as 10 g of pure alcohol, and examples were provided. Participants also indicated how often they consume that number of drinks within a 24-h period. This was assessed on a 10-point scale ranging from (0) never to (9) every day, which was subsequently converted into days per month (e.g., never = 0, every day = 30). When a point represented a range of frequencies, the midpoint was calculated (e.g., 2–3 times a month became 2.5 days per month; Dawson, 2003). The largest quantity of alcohol consumed within 24-h was multiplied by the frequency of consuming that amount within 24-h to produce an estimate of the number of drinks consumed per month during heavy drinking sessions. Binge drinking frequency was assessed by a single item that asked participants how often they consume 4+ standard drinks (females) or 5+ standard drinks (males) within a 2-h period. Participants responded on the same 10-point scale, which was subsequently converted into days per month. The binge drinking frequency and maximum alcohol use measures were treated as two observed indicators assessing a latent variable labelled binge drinking (a = .89).
2.3.2. Negative urgency Negative urgency was assessed by the UPPS Impulsive Behavior Scale (Whiteside & Lynam, 2001), an inventory that assesses four impulsivity-related constructs: urgency, (lack of) premeditation, (lack of) perseverance, and sensation seeking. The urgency subscale consists of 12 items measuring the degree to which individuals act rashly when experiencing negative affect (e.g., ‘‘I often make matters worse because I act without thinking when I am upset”). Respondents rated how well each statement applies to them on a 4-point scale from (1) agree to (4) disagree. Urgency scores were computed by summing item scores (a = .82). Adolescents who scored less than 0.25 SD below the mean were classified as Low urgency (n = 196, M = 22.01, SD = 3.63) and those who scored more than 0.25 SD above the mean were classified as High urgency (n = 195, M = 35.21, SD = 3.56).
2.3.3. Alcohol outcome beliefs Positive and negative beliefs about the outcomes of alcohol use were assessed by the 16-item Decisional Balance Inventory (DBI; Migneault et al., 1997). Eight statements describing positive drinking outcomes comprise a Pros scale (e.g., ‘‘Drinking gives me courage”) and eight items listing negative outcomes comprise a cons scale (e.g., ‘‘Drinking causes problems with others”). Participants were asked to rate the importance of each outcome when deciding if, or how much, to drink. Response options ranged from (1) not important to (5) extremely important. Composite measures of expected pros and cons were computed by summing scale items (pros a = .90, cons a = .85).
2.3.4. Affective associations The word association approach developed by Peters and Slovic (1996) measured alcohol-related affective associations comprising each participant’s ‘‘affect pool”. Participants were asked to list the first five thoughts or images that came to mind when presented with the phrase ‘‘drinking alcohol”, and to rate the thought/image on a scale ranging from (1) very negative to (5) very positive. The five affective response scores were summed to produce a composite score of affective associations with alcohol use (a = .69). An exploratory factor analysis of the eight pros, eight cons, and five affective items confirmed the independence of the affective associations construct. Three factors were extracted according to Cattell’s (1966) Scree Test. Following an oblimin rotation, the five affective items loaded above 0.54 on the third factor, with no cross-loadings over 0.13. 3. Results 3.1. Descriptives Of the 391 participants in the final sample, 300 (77%) were drinkers. Of these, 75% drank less than weekly and averaged one standard drink per week, and 25% drank at least weekly and averaged 15 standard drinks per week. Urgency was significantly positively associated with maximum alcohol use (r = .15, p < .01) and binge drinking frequency (r = .14, p < .01). Means, standard deviations, and correlations for affective associations, pros, cons, and alcohol consumption for the low and high urgency groups are presented in Table 1. 3.2. Multiple-group path analysis Multiple-group path analysis was conducted using AMOS 7.0 (Arbuckle, 2006) to test the hypothesis that urgency moderates the pathways specified in the hypothesised model depicted in Fig. 1. The model posits relationships between binge drinking and the observed variables of affective associations, perceived pros, and perceived cons. Binge drinking was operationalized as a latent variable with two indicators: maximum alcohol use and binge drinking frequency. The alcohol variables were positively skewed, which can produce biased standard errors and misleading significance tests (Cohen, Cohen, West, & Aiken, 2003). To avoid this possibility, we re-computed all significance tests using standard errors based on 1000 bootstrapped samples (Byrne, 2001). Nested model comparisons computed by AMOS indicated that the unconstrained model fit the data significantly better than the same model with all paths constrained to be equal across the two urgency groups, v2difference (6) = 21.58, p = .001. A significant v2difference value indicates that the path coefficients may differ in the sampled populations. Thus, the path coefficients for low and
Table 1 Correlations, means, and standard deviations across low and high urgency groups. Variable
High urgency 1
1. Pros 2. Cons 3. Affective associations 4. Binge drinking frequency 5. Maximum alcohol use Low urgency
2
3 .33**
M SD
.27** .22** .23** .18* 15.12 6.98
4 .22** .18*
**
.28 .08 .08 22.45 8.71
.12 .07 13.93 4.57
5 .22** .02 .29**
.83** .63 2.59
Note: Correlations for the high and low urgency groups are reported above and below the diagonal, respectively. * p < .05. ** p < .01.
.21** .01 .29** .85** 3.07 11.08
M
SD
20.17 24.12 15.56 1.84 17.41
8.11 8.09 4.50 5.43 62.65
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Pros of Drinking .22** (.22**)
.27*** (.17*) Maximum Alcohol Use e1
.36 (.38)
.82*** (.91***)
.02 (.28***)
Affective Associations
e3
R2 = .08 (.13) Binge Drinking 1.00 NT (.93NT)
e2
Binge Drinking Frequency
-.28*** (-.18*)
e4
-.15* (.01) Cons of Drinking
Fig. 1. Summary of multiple-group path analysis assessing the effects of affective associations, pros, and cons on binge drinking for participants scoring low and high on urgency. Unparenthesized and parenthesized values are standardized coefficients for low and high urgency groups, respectively. All significance tests were based on standard errors computed from 1000 bootstrapped samples. *p < .05, **p < .01, ***p < .001, NT, effect not tested.
Table 2 Fit indices for multiple-group path analysis: unconstrained and constrained models. Model
v2
df
CFI
SRMR
RMSEA
Unconstrained Constrained (structural weights)
1.02 22.60*
4 10
1.00 .98
.01 .08
.00 .06
Note: CFI, comparative fit index; SRMR, standardized root mean square residual; RMSEA, root mean square error of approximation. Based on Kline (2005), good fit is defined as non-significant v2, CFI > .90, RMSEA < .08, and SRMR < .10. For the RMSEA and SRMR, a value of 0 represents perfect fit. * p < .05.
high urgency groups were interpreted separately (Arbuckle & Wothke, 1999). The fit indices associated with the two models are presented in Table 2. Affective associations, pros, and cons explained 13% of the variance in binge drinking for the high urgency group and 8% for low urgency. A summary of the unconstrained group comparison analysis is presented in Fig. 1. As predicted, the direct path from affective associations to binge drinking was stronger for adolescents who scored higher on urgency. That is, affective associations were significantly positively associated with binge drinking for highly urgent adolescents but not for those low in urgency. Conversely, the path between cons and binge drinking was moderate in magnitude and significant for the low urgency group, but was small and non-significant for the high urgency group. The path between pros and binge drinking was significant for both groups but the relationship was stronger for the low urgency group. As shown in Table 3, significance tests of direct and indirect effects indicated that the path from affective associations to binge drinking was fully mediated by outcome beliefs for the low urgency group. That is, the indirect path from affective associations through pros and cons to binge drinking was statistically significant, whereas the direct effect of affective associations on binge drinking, after controlling for pros and cons, was not. In contrast, for those who scored high on urgency, the direct path from affective associations to binge drinking was significant, whereas the indirect effect through pros and cons was not. Thus, in both instances respondents’ affective associations predicted binge drinking, but the respective influential paths differed across groups. 4. Discussion The present study tested predictions derived by combining the affect heuristic (Slovic et al., 2002; Slovic et al., 2005) with cognitive and personality research relating to adolescent alcohol use.
Specifically we investigated whether individual differences in negative urgency would moderate the predictive effects of affective associations and alcohol outcome beliefs, to produce different decision making pathways to binge drinking behaviour. As predicted, urgency moderated the effects of affective associations and outcome beliefs on binge drinking. Affective associations were significant direct predictors of binge drinking for high urgency respondents but not for low urgency respondents. In contrast, beliefs about the pros and cons of drinking were stronger predictors of binge drinking for low urgency respondents than for high urgency respondents. For low urgency adolescents, the association between affective associations and binge drinking was fully mediated by pros and cons. That is, low urgency respondents who reported more positive affective associations with drinking alcohol endorsed more pros and fewer cons of drinking, which in turn were associated with greater binge drinking. In contrast, high urgency adolescents’ beliefs about the pros of alcohol use only partially mediated the predictive effect of affective associations on binge drinking. These results are consistent with the view that adolescents with low versus high trait urgency differ in their use of the affect heuristic and rational analysis when making drinking decisions. The affect heuristic may play a more important role in guiding the binge drinking behaviour of high urgency adolescents, whereas a rational assessment of expected positive and negative outcomes may be more influential in guiding the binge drinking of low urgency adolescents. Integrating the affect heuristic with personality research has important theoretical and practical utility. Our study provides preliminary evidence that individuals with different levels of the personality trait negative urgency may make drinking decisions in fundamentally different ways. This knowledge can inform the development of more effective health education programs and interventions. Intervention and prevention strategies are often based on the premise that modifying drinking behaviour involves changing outcome beliefs or developing rational thinking skills (e.g., Darkes & Goldman, 1993). However these approaches have achieved only limited success (Carey, Scott-Sheldon, Carey, & DeMartini, 2007; Skiba, Monroe, & Wodarski, 2004), which suggests they may be ineffective for large segments of the population. Our finding that expected pros and cons explained unique variance in binge drinking for adolescents characterized by low levels of urgency, suggests that these adolescents may be guided by outcome beliefs and may benefit from interventions that target rational processes. However highly urgent adolescents in our sample reported relatively greater reliance upon affective input
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W.J. Phillips et al. / Personality and Individual Differences 47 (2009) 829–834 Table 3 Effects decomposition for the urgency path model of adolescent binge drinking. Moderators
Endogenous variables Pros of drinking
Low urgency Affective associations Direct effects Indirect effects Total effects Pros of drinking Direct effects Indirect effects Total effects Cons of drinking Direct effects Indirect effects Total effects High urgency Affective associations Direct effects Indirect effects Total effects Pros of drinking Direct effects Indirect effects Total effects Cons of drinking Direct effects Indirect effects Total effects
Cons of drinking
Unst.
SE
St.
Unst.
.34** – .34**
.10 – .10
.22** – .22**
–
– –
– –
– –
– –
– –
.39** – .39**
Binge drinking SE
St.
.13 – .13
–
– –
– –
– –
– –
.13 – .13
.22** – .22**
–
– – –
– – –
– – –
– – –
– – –
– – –
.54**
.28**
Unst.
SE
St.
.01 .06** .07
.08 .03 .07
.02 .10** .12
– –
.10** – .10**
.05 – .05
.27** – .27**
– –
– –
.05* – .05*
.03 – .03
.15* – .15*
.13 – .13
–
.31** .04 .35**
.13 .04 .12
.28** .04 .31**
– – –
– – –
– – –
.11 – .11
.06 – .06
.17 – .17
– – –
– – –
– – –
.01 – .01
.06 – .06
.01 – .01
.54**
.32* .32*
.28**
.18* .18*
Note: All significance tests for direct, indirect, and total effects are based on 1000 bootstrapped samples. Unst., unstandardized effects; SE, standard errors; St., standardized effects. * p < .05. ** p < .01.
when making alcohol-related decisions, suggesting that the relevance of purely rational strategies for these individuals may be limited. This is a particularly poignant revelation, given that problematic alcohol consumption is typically positively associated with urgency. That is, current strategies that target rational thinking may be least adequate for those most at risk. High urgency adolescents appear to be guided by affective input; therefore interventions for these individuals should target affect. Alternatively, high urgency adolescents may benefit from a combination of interventions. According to dual-process theory, the observed decision making pathways of low and high urgency adolescents may reflect tendencies to rely upon different information systems. Low urgency adolescents may favour the analytical rational system, whereas high urgency adolescents may prefer the heuristic experiential system. Apart from analysing options, another important function of the rational system involves overriding inappropriate heuristic responses and replacing them with reasoned alternatives. Stanovich and West (2008) proposed that this process entails identifying when heuristic responses should be replaced, as well as knowing how to substitute analytical responses. Consequently, high urgency adolescents may respond to interventions that boost awareness of their affective states and heuristic responses, prior to developing rational thinking skills. When interpreting these results, it is important to remember that this study was based on a community sample of Australian adolescents and these findings may not generalise to other samples and settings. For example, greater use of the affect heuristic may be observed in ‘‘high risk” samples. Other potential limitations of the study include its relatively small sample size for the analysis, positively skewed alcohol use variables, marginal internal consistency of the affective associations measure, and the use of self-report methodology. Retrospective self-reported estimates of binge drinking are subject to recall bias and provide only an indirect measure
of drinking behaviour. Future studies could elicit more accurate estimates by using alternative methodology, such as a diary to record binge drinking over time. Furthermore, interpretation of these results should be tempered by problems inherent in the correlational nature of the analyses. Although path analysis can assess the plausibility of hypothetical causal processes, strong causal inferences are not appropriate when the technique is used with cross-sectional correlational data, given the possibility of third-variable explanations and ambiguity about the true direction of effects. Reassessing this model using a longitudinal design that measures variables at different times, or an experimental design that manipulates participants’ affective associations, would provide a stronger framework for identifying causal effects (Kline, 2005). Our findings are consistent with the view that both affective associations and outcome beliefs guide adolescents’ binge drinking behaviour, and that the relative involvement of affective and rational input may be influenced by urgency. As Wiers and Stacy (2006) note, a focus on affective processes does not discount the relevance of rational decision making to understanding addictive behaviours. Rather, it underlines the need for such affective processes to be understood if addictive behaviours are to be successfully treated. Overall, these results suggest that the affect heuristic offers a worthwhile vantage point for further etiological explorations into the enigmatic arena of adolescent drinking behaviour. References Ajzen, I. (2000). Theory of reasoned action. In A. E. Kazdin (Ed.). Encyclopedia of psychology (Vol. 8, pp. 61–63). Washington, DC, US: American Psychological Association. Arbuckle, J. L. (2006). AMOS 7.0.0. Chicago: Smallwaters. Arbuckle, J. L., & Wothke, W. (1999). AMOS 4.0 user’s guide. Chicago: Smallwaters.
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