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Anger and everyday risk-taking decisions in children and adolescents
Personality and Individual Differences 90 (2016) 342–346
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Anger and everyday risk-taking decisions in children and adolescents Elisa Gambetti ⁎, Fiorella Giusberti Department of Psychology, University of Bologna, Italy
a r t i c l e
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Article history: Received 30 July 2015 Received in revised form 18 November 2015 Accepted 21 November 2015 Available online 28 November 2015 Keywords: Anger Hostility Aggression Decision-making Adolescence Childhood Risk
a b s t r a c t The current research examined the relationship between cognitive, affective and behavioral components of anger and risk decision-making in childhood and adolescence. 88 children and 101 adolescents completed hypothetical choice scenarios and the Multidimensional School Anger Inventory–Revised. Results showed that: 1) hostility, anger experience and destructive expression of anger were positively related to risky decisions in everyday-life situations; 2) only the behavioral component of anger was predictive of risk-taking; 3) hostility and anger experience indirectly affected, through the destructive expression of anger, risky decisions in childhood; 4) the effect of hostility on risk was both direct and indirect, while the effect of anger experience was only indirect on the adolescence sample. Theoretical and practical implications of these findings were discussed. © 2015 Elsevier Ltd. All rights reserved.
1. Introduction In the developmental literature, risk decision-making is defined as making decisions that is associated with some probability of undesirable results (Boyer, 2006). A number of studies have found that childhood and adolescence are both characterized by experimentations, greater preference for risky over certain decisions and appreciation of risk (e.g., Eftekari, Turner, & Larimer, 2004; Reyna, 1996). In particular, there is evidence that school-age children often make risky decisions, especially when they are playing away from home and not directly supervised by adults (e.g., Petrass, Blitvich, & Finch, 2009; Saluja et al., 2004), and that adolescents frequently engage in several risky behaviors, such as cigarette smoking, having unprotect sex or initiating interpersonal aggression (e.g., Rai et al., 2003). According to most theoretical accounts, all risk decisions involve a trade-off between short-term gains and potential long-term costs (e.g., Baumeister & Scher, 1998). For example, cigarette smoking may appeal to an individual because of its immediate benefit, such as relief from stress or sharing an enjoyable moment with friends, despite long-term health hazards. From this perspective, individual characteristics that influence the weighing of costs and benefits, or bias the ability to accurately evaluate the trade-off, should contribute to an overall disposition toward risk-taking. Several works showed that there are significant individual differences in making risky decisions in young people: risk-taking and related decisionmaking processes may reflect underlying dispositional qualities that ⁎ Corresponding author at: Department of Psychology, University of Bologna, V.le Berti Pichat, 5, 40127 Bologna, Italy E-mail address: [email protected] (E. Gambetti).
http://dx.doi.org/10.1016/j.paid.2015.11.049 0191-8869/© 2015 Elsevier Ltd. All rights reserved.
vary across individuals (e.g. Chassin & DeLucia, 1996; Hoffrage, Weber, Hertwing, & Chase, 2003). For this reason, it is important to identify which individual characteristics make children and adolescents more vulnerable to making risky decisions in several everyday situations. Actually, evidence suggests that mortality and morbidity during childhood and adolescence are highly associated with risky decisions (e.g., Cobb, 1998; Rice & Dolgin, 2008) and that economic and personal costs of risky behaviors are increasing (Savadori & Rumiati, 2005). 1.1. Individual differences in risk-taking Numerous studies showed that individual differences in cognitive, emotional, psychobiological and social domains could influence and explain several risk-taking behaviors during development (for a review see Boyer, 2006). Regarding the cognitive and emotional aspects, studies analyzed how specific factors, such as cognitive appraisals and personality traits, influence decision-making in potentially risky situations. For example, children who judge their personal vulnerability for injury, the potential severity of injury or danger in a situation as low engages in greater risk-taking (Morrongiello & Matheis, 2004). Moreover, young people who are high in impulsivity and in sensation seeking or low in inhibitory control (i.e., capacity to resist off limits but interesting hazards) engage in more risk behaviors, such as drug abuse or peer aggressions (e.g., Morrongiello, Corbett, McCourt, & Johnston, 2006; Stanford, Greve, Bourdeaux, Mathias, & Brumbelow, 1996). Other works identified depression (Jessor, Van Den Bos, Vanderryn, Costa, & Turbin, 1995), low self-regard (Dryfoos, 1990), negative emotionality, avoidant strategies of coping (Cooper, Wood, Orcutt, & Albino, 2003) and extraversion (i.e., high activity level, sociability and dominance)
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(Schwebel & Plumert, 1999) positively associated with youth's risktaking decisions. On the other hand, agreeableness (i.e., kindness, likeability and trustworthiness) and conscientiousness (i.e., organization and reliability) were found negatively related with youth's deviant and unhealthy behaviors (Markey, Markey, Ericksen, & Tinsley, 2003). In summary, the literature showed that cognitive (e.g., self- and otherrepresentations), affective (e.g., negative emotionality) and behavioral (e.g., impulsivity, inhibitory control and sensation seeking) differences seem to predict risk-taking in adolescents, whereas there are few studies that explore this issue during childhood. 1.2. Anger and risk-taking One of the individual differences that can affect risk-taking during childhood and adolescence is the tendency to feel anger in different circumstances and situations. For a complete definition of anger, the whole range of anger-related events that occur congruently with the individual's subjective label of anger has to be considered (Eckhardt, Norlander, & Deffenbacher, 2004). Current models define anger as a multidimensional construct consisting of affective, cognitive and behavioral variables (e.g., Kassinove, Roth, Owens, & Fuller, 2002; Wilkowski & Robinson, 2008). In particular, the affective component of anger consists of angry feelings that, according to the dimensional approach of affect (e.g., Posner, Russell, & Peterson, 2005), are characterized by a negative valence and an intensity that could “vary from mild irritation or annoyance to intense fury and rage” (Spielberger, 1996) This component is an internal and stable feeling state, naming trait anger, that is typically associated with an increased motivation to hurt others (Wilkowski & Robinson, 2008). The cognitive component of anger consists of hostile beliefs, such as cynicism and lack of confidence in others. These beliefs produce “attributional biases that make it more likely that the behavior of others will be interpreted as antagonistic or threatening” (Barefoot, 1992). Although it is clear that hostile beliefs are the core cognitive components of anger, there is a long history of debate regarding the question about whether these beliefs are necessary or not for anger elicitation: appraisal and attribution theorists have emphasized hostile interpretations as the main determinant of anger (e.g., Lazarus, 1991; Smith & Kirby, 2004), whereas Cognitive Neo-Associationistic theorists have argued that memory accessibility to hostile thoughts may be sufficient (e.g., Berkowitz & Harmon-Jones, 2004). Finally, aggression is certainty the principal aspect of the behavioral component of anger. Verbal aggression and other forms of antagonistic behavior are frequent phenomena in everyday-life situations. Physical aggression emerges in several forms of anger manifestations, such as breaking objects, slamming doors or hitting someone. These kinds of behaviors are the typical expression of anger that is a characteristic of people who express their anger outwardly (Spielberger, 1996) or in a reactive way (e.g., Blair, 2004). Developmental research showed that the tendency to express angry feelings in a destructive manner is a stable behavioral dimension that emerges early in life (e.g., Putnam & Stifter, 2005). Moreover, research on adults showed that both trait anger and hostile beliefs predict this personality trait (Bettencourt, Talley, Benjamin, & Valentine, 2006). According to Lerner and Tiedens (2006), anger has an infusive influence on decision-making under risk. Research found that angry adults tend to act recklessly (Ahn, 2010) because anger is associated with optimistic beliefs about experiencing future life events and promotes cognitive response decision-making biases that increase the tolerance for risk (e.g., Lerner & Keltner, 2001; Gambetti & Giusberti, 2009). There is also considerable evidence that during adolescence anger increases vulnerability to risky behaviors and predicts numerous risky decisions, such as violence, smoking and substance abuse (e.g., Siqueira, Diab, Bodian, & Rolnitzky, 2000; Vaccaro & Wills, 1998). For these reasons, individual differences in the tendency to feel and express anger may represent very important factors in risk decision-making because they
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function as early and chronic schemas for organizing and interpreting events (Gasper & Clore, 1998; Lerner & Keltner, 2000). 1.3. The present study Given this theoretical framework, anger seems to play an important role in risk-taking during the development, but few studies explored this issue directly. To address this gap, the current study extends prior research investigating the link between anger and risk decisionmaking by examining relations among specific components of anger and risk-taking decisions. In particular, we hypothesized that habitual anger experience (affective component), hostile beliefs (cognitive component) and easiness to engage in acts of destructive expression of anger (behavioral component) would predict risky behavior in children and adolescents and they could interact with each other in influencing risk-taking. Assessing possible interactions among experience of anger, hostile beliefs and destructive expression of anger in risk decision-making may be a worthy addiction to the developmental literature making a bridge between different lines of research: studies on emotions and personality in judgments and decisions (e.g., Cooper et al., 2003) and studies that highlight the importance of cognitive assessments on risk-taking (e.g., Morrongiello & Matheis, 2004). Furthermore, in contrast to much previous research that considered unintentional injury in children (e.g., Morrongiello, Stewart, Pope, Pogrebtsova, & Boulay, 2015) or deviant and unhealthy behaviors in adolescents (e.g., Markey et al., 2003), this study examined risk decision-making in everyday hypothetical scenarios representative of a wide range of situations frequently faced by young people in their everyday lives. 2. Method 2.1. Samples Following approval of the research ethics review board and the head-master, permission forms were sent home to parents of schoolage children and adolescents to obtain consent for their sons to participate in this study. Participants also provided informed consent at school prior to participation. Participants were recruited from two elementary schools and three classes of middle school. Samples comprised 88 children (M = 9.47 years, SD = 0.61, range 8–11, 43% males) and 101 adolescents who ranged in ages from 12 to 16 (M = 13.63, SD = 1.56, 44% males). All participants were fluent in Italian, normally developing (as reported by teachers) and in regular classrooms. Osborne and Costello (2004) suggested that there is no specific criterion for determining sample size in behavioral studies. They showed that one-sixth of the studies used 2:1 subject-to-item ratio and about 20% studies used less than 5:1 subject-to-item ratio. Sample sizes of 88 and 101 were approximately 2:1 subject-to-item ratio which was considered suitable for conducting analyses. 2.2. Instruments 2.2.1. Multidimensional School Anger Inventory–Revised (MSAI–R; Boman, Curtis, Furlong, & Smith, 2006) The 36-item MSAI–R was developed to measure the psychological/ affective, cognitive, and behavioral components of anger with items specifically referring to the school environment (Boman et al., 2006; Furlong, Smith, & Bates, 2002). This instrument is composed of three scales: Anger Experience (e.g., You ask to go to the bathroom and the teacher says, “no”), Hostility (e.g., Rules at school are stupid), and Destructive Expression (e.g., When I'm angry, I'll take it out on whoever is around). All scales use four response categories (from 1 = never to 4 = always). Reliability with Australian children ranged from 0.79 to 0.66 (Boman et al., 2006). The MSAI–R was presented in Italian; this version was a translation of the original questionnaire, with exactly alike
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item numbering. The goodness of translation was verified by a backtranslation from Italian to English, conducted by a native English speaker unfamiliar with the English version of the MSAI–R. The Anger Experience, Hostility, and Destructive Expression scales have good Cronbach's alphas for children (i.e., 0.84, 0.85 and 0.77, respectively), such as for adolescents (i.e., 0.80, 0.70, and 0.70 respectively). 2.2.2. Risk tasks These tasks assessed children and adolescents intentions to take risks, respectively in twelve and thirteen different everyday-life situations, derived by pilot surveys showing good validity (i.e., significant differences across risky and safe choices and no significant differences between effort rates of the risky and the safe options) and test–retest reliability (Gambetti & Giusberti, 2008, 2009). These scenarios have two choices: one of these was identified as “safe” and one “risky”, randomly designated as choice A or choice B. In order to obtain a more sensitive measure of risk behavior, participants were asked to indicate their choice conviction on a 10-point Likert scale ranging from definitely A to definitely B. The dependent variable used for the assessment of risk decision-making was the total score of the children's choice conviction. The complete lists of the scenarios are available from the first author. The internal consistency was adequate (α = .82 for both samples). 2.3. Procedure Each participant was seen individually at school for one 20-min session. They completed the risk task and the MSAI–R. Given the potential for order effects, the task and the questionnaire were randomly administrated for each participant and each scenario of the task was presented one at a time in random order. At the conclusion of each session, participants were asked to provide their actual levels of attention to tasks and understanding of tasks on 4-point Likert scales, with higher number indicating better scores (e.g., 1 = poor and 4 = very good). 3. Results
Table 1 Descriptive statistics and partial correlations, controlling for age and gender.
Children (1) Anger experience (2) Hostility (3) Destructive expression N M SD SEM Adolescents (1) Anger experience (2) Hostility (3) Destructive expression N M SD SEM
1
2
– .43⁎⁎ .51⁎⁎ 88 41.53 7.10 .76
– .66⁎⁎ 88 10.10 4.67 .50
– .15⁎ .34⁎⁎ 101 36.39 4.86 .48
3
– .07 101 13.64 4.00 .40
Risk-taking
– 88 15.54 5.51 .59
– 101 15.83 3.86 .38
.33⁎⁎ .30⁎⁎ .45⁎⁎ 88 68.43 25.33 2.48 .26⁎⁎ .38⁎⁎ .41⁎⁎ 101 67.77 18.31 1.82
⁎ p b .05 (2-tailed). ⁎⁎ p b .001 (2-tailed).
3.4. Regression analyses predicting risk-taking from anger components In order to evaluate the anger components that explain and predict risk-taking, two hierarchical linear regression analyses were performed separately by each sample we studied. All predicting variables were centered (the actual score minus the mean score) to avoid the problem of multicollinearity in the regression. The covariates were entered in step 1 (age and gender), then the predictors (i.e., Anger Experience, Hostility and Destructive Expression) were entered in step 2. Table 2 reported the standardized beta coefficient and changed in R-squares for children and adolescents, respectively. Results revealed that, for children, after adjusting for age destructive expression of anger was only associated with risk measure. In adolescent sample, results showed that after adjusting for age both destructive expression of anger and hostility predicted risky decisions.
3.1. Preliminary analyses 3.5. Path analyses Descriptive analysis of ratings of children's attention during the tasks revealed high ratings (M = 3.9; SD = 0.56 for children; M = 3.8; SD = 0.4 for adolescents). Thus, there was no evidence to indicate that differential attention or understanding to the tasks contributed to our findings. 3.2. Descriptive analysis The means and standard deviations of all the measures are reported in Table 1. In order to assess the influence of gender on risk, we performed t-test. Results showed that males take more risks (M = 54.83, SD = 9.34 for children; M = 72.68, SD = 20.79 for adolescents) than females (M = 46.59, SD = 9.06, t87 = 4.51, p b .001 for children; M = 63.98, SD = 15.25, t100 = 2.42, p b .05 for adolescents). Moreover, age and risk-taking were positively correlated both in childhood (r = .32, p b .001) and in adolescence (r = .22, p b .05). 3.3. Correlations between risk-taking and anger components We examined partial correlations, controlling for age and gender, among MSAI–R scales (i.e., Anger Experience, Hostility and Destructive Expression) and risk-taking. The significance of these values permits a first approximation to the covariance of these measures that can be seen in Table 1. Anger Experience, Hostility and Destructive Expression were positively related to risk-taking in children and adolescents.
Finally, two path analyses, one for each sample, were conducted to determine whether there were indirect effects of cognitive and affective components of anger, through behavioral component of anger, on risktaking in children and whether the direct effects of hostility or the indirect effects through destructive expression of anger were stronger in adolescents (see Kassinove et al., 2002). Anger experience and hostility were considered exogenous variables and destructive expression and risk were endogenous variables. The model from children (see Fig. 1) did not differ significantly from a fully saturated model (χ22102 = 3.82,
Table 2 Hierarchical regression predicting risk-taking from MSAI–R scales in children and adolescents.
Age (in years) Gender Anger experience Hostility Destructive expression of anger ΔR2 ⁎ p b 0.05 (2-tailed). ⁎⁎ p b 0.01 (2-tailed). ⁎⁎⁎ p b .001 (2-tailed).
Children results
Adolescents results
Step 1
Step 2
Step 1
Step 2
.383⁎⁎⁎ .186⁎
.343⁎⁎⁎ .081 .166 −.010 .353⁎⁎ .180⁎⁎⁎
.207⁎ .224⁎
.246⁎⁎ .145 .103 .307⁎⁎⁎ .332⁎⁎⁎ .239⁎⁎⁎
.167⁎⁎⁎
.078⁎⁎
E. Gambetti, F. Giusberti / Personality and Individual Differences 90 (2016) 342–346
Fig. 1. Path analysis on children sample. **p b .001 (2-tailed).
p = .14), such as the model from adolescents (see Fig. 2) (χ22.99 = 4.19, p = .12). The standardized regression weights for the indirect effects of anger experience and hostility through destructive expression of anger on risky decisions were 0.21 and 0.31 in children, .33 and .34 in adolescents, respectively. In children, the direct effect of anger experience and hostility was non-significant; in adolescents, there was a significant direct effect of hostility on risky decisions (.27), while the direct effect of anger experience was non-significant. 4. Discussion We used a number of everyday-life situations to explore risk decision-making and to identify the specific anger components that could predict these decisions in children and adolescents. The principal hypothesis, that is anger components were all predictive of later risktaking decisions, was partially supported. On the one hand, the findings showed that affective, cognitive and behavioral components of anger are all related to risk-taking decisions in children and adolescents. These findings are consistent with past research indicating that anger is an important factor in risk decision-making. In particular, prior works on adults has reported that the tendency to experience anger is related to optimistic beliefs about experiencing future life events and optimistic perceptions of risk (Lerner & Keltner, 2000). Moreover, previous studies highlighted that anger makes people indiscriminately optimistic about their own changes of success (Fischhoff, Gonzalez, Lerner, & Small, 2005) and careless in their thought (Tiedens, 2001). In this sense, also our study suggests that anger promotes decision-making biases that increase one's tolerance for risk. On the other hand, results showed that only the behavioral component of anger (i.e., destructive expression) was predictive of risky
Fig. 2. Path analysis on adolescent sample. *p b .05, **p b .01, ***p b .001 (2-tailed).
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decisions in children and adolescents. Moreover, the effects of the affective (i.e., angry feelings) and the cognitive (i.e., hostility) components of anger on risky decisions were mediate by the behavioral component of anger in children sample. On the other hand, the effect of hostility was both direct and indirect through destructive expression of anger, while the effect of angry feelings was only indirect in the adolescence sample. These findings highlight the importance of the behavioral component of anger in risk decision-making in both childhood and adolescence. All of this appears to be coherent with the relationship between outwardly expressed anger and a wide range of risky types of behaviors, such as competitive and attack responses (Kassinove et al., 2002), as well as substance use (Eftekari et al., 2004). A possible explanation could be that individuals with high levels of destructive expressed anger may have low impulse control. Our results converge with other theories of self-control (e.g., Mischel & Ayduk, 2004) and cognitive control (e.g., Kerns et al., 2004) in emphasizing the nature such process in the anger domain (Wilkowski & Robinson, 2008). The fact that hostility directly predicts risky decisions in adolescence and indirectly in childhood suggests the immediacy with which the cognitive component of anger may produce risky decisions in youth. However, hostility seems to be not so closely linked to risk decision-making in childhood. The absence of a direct relationship between hostility and children's risky decisions may be due to the fact that impulsivity, and in this sense destructive expressed anger, has an important role first of all in childhood. Age increasing, it seems to become important the cognitive component of anger in risk decision-making, which assumed a central role in adolescence, jointly the behavioral component of anger. In the developmental literature there are several models that seek to explain risk decision-making in childhood and adolescence considering four research perspectives (i.e., cognitive, emotional, psychobiological and social) (for a review see Boyer, 2006). However, researchers have quite recently begun considering the potential role of emotions in risk-taking (e.g., Cauffman & Steinberg, 2000; Morrongiello et al., 2015). The current study refers to this developmental perspective, highlighting the importance of examining relations among individual differences in the tendency to feel a specific emotion, also considering the underlying cognitive and behavioral processes, and risk decisionmaking in childhood and adolescence. In this sense, it is important to consider the role of emotional regulation and the possibility that particularly impulsive or anger prone individuals make risky decisions. Anger has a number of adaptive functions such as providing an internal signal that goals are blocked or thwarted (Berkowitz & Harmon-Jones, 2004) or communicating to others that their actions are viewed as an encroachment on freedom or resources (Rothenberg, 1971). Nevertheless, for a subset of individuals, anger may become a habitual, and often dysfunctional, way of reaction to frustrations. Although our findings extend the knowledge of the determinants of risk-taking decisions in children and adolescents, there are some limitations to this work and questions that remain to be considered in future research. First, the correlation between anger and risk-taking could be spurious through a linkage with other causal factors. For example, a person who is low on the ability to inhibit or self-regulate would also be likely to feel and express anger and take risks. Thus, further studies are required to evaluate the role of other variables, such as impulsivity and inhibition, on risk-taking. Second, we cannot assert with certainty that what children and adolescents proposed to do would necessary be what they would actually do. The use of hypothetical, rather than real, decisions may be a relevant factor in the observed pattern of effects. Nevertheless, many studies suggest and confirm that reports of personal intentions greatly correspond with subsequent actual risktaking (e.g., Hockey, Maule, Clough, & Bdzola, 2000; Morrongiello & Dawber, 2004). Despite these limitations, the current research has potential implications for both theories of decision-making and educational programs. As our findings suggest, anger may shape individual choices. These data fit
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with a growing body of evidence suggesting that individual differences in affective experiences influence risk decision-making (e.g., Maner et al., 2007). The current study suggests the utility of a motivationbased approach to decision-making and is consistent with other theories positing emotion-specific influences on choices and decisions (e.g., Lerner & Keltner, 2000). These findings have also practical implications for teachers and educators interested in identifying children and adolescent most at risk for taking potentially risky decisions. Our results suggest that school educational programs, usually focused on anticipatory guidance strategies (e.g. instructing children about the importance of avoiding risky behaviors), may be enhanced by knowledge of personality traits. References Ahn, H. (2010). Modeling and analysis of affective influences on human experience, prediction, decision making, and behavior. (Ph.D. diss.) Massachusetts Institute of Technology. Barefoot, J. (1992). 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Anger and everyday risk-taking decisions in children and adolescents Elisa Gambetti ⁎, Fiorella Giusberti Department of Psychology, University of Bologna, Italy
a r t i c l e
i n f o
Article history: Received 30 July 2015 Received in revised form 18 November 2015 Accepted 21 November 2015 Available online 28 November 2015 Keywords: Anger Hostility Aggression Decision-making Adolescence Childhood Risk
a b s t r a c t The current research examined the relationship between cognitive, affective and behavioral components of anger and risk decision-making in childhood and adolescence. 88 children and 101 adolescents completed hypothetical choice scenarios and the Multidimensional School Anger Inventory–Revised. Results showed that: 1) hostility, anger experience and destructive expression of anger were positively related to risky decisions in everyday-life situations; 2) only the behavioral component of anger was predictive of risk-taking; 3) hostility and anger experience indirectly affected, through the destructive expression of anger, risky decisions in childhood; 4) the effect of hostility on risk was both direct and indirect, while the effect of anger experience was only indirect on the adolescence sample. Theoretical and practical implications of these findings were discussed. © 2015 Elsevier Ltd. All rights reserved.
1. Introduction In the developmental literature, risk decision-making is defined as making decisions that is associated with some probability of undesirable results (Boyer, 2006). A number of studies have found that childhood and adolescence are both characterized by experimentations, greater preference for risky over certain decisions and appreciation of risk (e.g., Eftekari, Turner, & Larimer, 2004; Reyna, 1996). In particular, there is evidence that school-age children often make risky decisions, especially when they are playing away from home and not directly supervised by adults (e.g., Petrass, Blitvich, & Finch, 2009; Saluja et al., 2004), and that adolescents frequently engage in several risky behaviors, such as cigarette smoking, having unprotect sex or initiating interpersonal aggression (e.g., Rai et al., 2003). According to most theoretical accounts, all risk decisions involve a trade-off between short-term gains and potential long-term costs (e.g., Baumeister & Scher, 1998). For example, cigarette smoking may appeal to an individual because of its immediate benefit, such as relief from stress or sharing an enjoyable moment with friends, despite long-term health hazards. From this perspective, individual characteristics that influence the weighing of costs and benefits, or bias the ability to accurately evaluate the trade-off, should contribute to an overall disposition toward risk-taking. Several works showed that there are significant individual differences in making risky decisions in young people: risk-taking and related decisionmaking processes may reflect underlying dispositional qualities that ⁎ Corresponding author at: Department of Psychology, University of Bologna, V.le Berti Pichat, 5, 40127 Bologna, Italy E-mail address: [email protected] (E. Gambetti).
http://dx.doi.org/10.1016/j.paid.2015.11.049 0191-8869/© 2015 Elsevier Ltd. All rights reserved.
vary across individuals (e.g. Chassin & DeLucia, 1996; Hoffrage, Weber, Hertwing, & Chase, 2003). For this reason, it is important to identify which individual characteristics make children and adolescents more vulnerable to making risky decisions in several everyday situations. Actually, evidence suggests that mortality and morbidity during childhood and adolescence are highly associated with risky decisions (e.g., Cobb, 1998; Rice & Dolgin, 2008) and that economic and personal costs of risky behaviors are increasing (Savadori & Rumiati, 2005). 1.1. Individual differences in risk-taking Numerous studies showed that individual differences in cognitive, emotional, psychobiological and social domains could influence and explain several risk-taking behaviors during development (for a review see Boyer, 2006). Regarding the cognitive and emotional aspects, studies analyzed how specific factors, such as cognitive appraisals and personality traits, influence decision-making in potentially risky situations. For example, children who judge their personal vulnerability for injury, the potential severity of injury or danger in a situation as low engages in greater risk-taking (Morrongiello & Matheis, 2004). Moreover, young people who are high in impulsivity and in sensation seeking or low in inhibitory control (i.e., capacity to resist off limits but interesting hazards) engage in more risk behaviors, such as drug abuse or peer aggressions (e.g., Morrongiello, Corbett, McCourt, & Johnston, 2006; Stanford, Greve, Bourdeaux, Mathias, & Brumbelow, 1996). Other works identified depression (Jessor, Van Den Bos, Vanderryn, Costa, & Turbin, 1995), low self-regard (Dryfoos, 1990), negative emotionality, avoidant strategies of coping (Cooper, Wood, Orcutt, & Albino, 2003) and extraversion (i.e., high activity level, sociability and dominance)
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(Schwebel & Plumert, 1999) positively associated with youth's risktaking decisions. On the other hand, agreeableness (i.e., kindness, likeability and trustworthiness) and conscientiousness (i.e., organization and reliability) were found negatively related with youth's deviant and unhealthy behaviors (Markey, Markey, Ericksen, & Tinsley, 2003). In summary, the literature showed that cognitive (e.g., self- and otherrepresentations), affective (e.g., negative emotionality) and behavioral (e.g., impulsivity, inhibitory control and sensation seeking) differences seem to predict risk-taking in adolescents, whereas there are few studies that explore this issue during childhood. 1.2. Anger and risk-taking One of the individual differences that can affect risk-taking during childhood and adolescence is the tendency to feel anger in different circumstances and situations. For a complete definition of anger, the whole range of anger-related events that occur congruently with the individual's subjective label of anger has to be considered (Eckhardt, Norlander, & Deffenbacher, 2004). Current models define anger as a multidimensional construct consisting of affective, cognitive and behavioral variables (e.g., Kassinove, Roth, Owens, & Fuller, 2002; Wilkowski & Robinson, 2008). In particular, the affective component of anger consists of angry feelings that, according to the dimensional approach of affect (e.g., Posner, Russell, & Peterson, 2005), are characterized by a negative valence and an intensity that could “vary from mild irritation or annoyance to intense fury and rage” (Spielberger, 1996) This component is an internal and stable feeling state, naming trait anger, that is typically associated with an increased motivation to hurt others (Wilkowski & Robinson, 2008). The cognitive component of anger consists of hostile beliefs, such as cynicism and lack of confidence in others. These beliefs produce “attributional biases that make it more likely that the behavior of others will be interpreted as antagonistic or threatening” (Barefoot, 1992). Although it is clear that hostile beliefs are the core cognitive components of anger, there is a long history of debate regarding the question about whether these beliefs are necessary or not for anger elicitation: appraisal and attribution theorists have emphasized hostile interpretations as the main determinant of anger (e.g., Lazarus, 1991; Smith & Kirby, 2004), whereas Cognitive Neo-Associationistic theorists have argued that memory accessibility to hostile thoughts may be sufficient (e.g., Berkowitz & Harmon-Jones, 2004). Finally, aggression is certainty the principal aspect of the behavioral component of anger. Verbal aggression and other forms of antagonistic behavior are frequent phenomena in everyday-life situations. Physical aggression emerges in several forms of anger manifestations, such as breaking objects, slamming doors or hitting someone. These kinds of behaviors are the typical expression of anger that is a characteristic of people who express their anger outwardly (Spielberger, 1996) or in a reactive way (e.g., Blair, 2004). Developmental research showed that the tendency to express angry feelings in a destructive manner is a stable behavioral dimension that emerges early in life (e.g., Putnam & Stifter, 2005). Moreover, research on adults showed that both trait anger and hostile beliefs predict this personality trait (Bettencourt, Talley, Benjamin, & Valentine, 2006). According to Lerner and Tiedens (2006), anger has an infusive influence on decision-making under risk. Research found that angry adults tend to act recklessly (Ahn, 2010) because anger is associated with optimistic beliefs about experiencing future life events and promotes cognitive response decision-making biases that increase the tolerance for risk (e.g., Lerner & Keltner, 2001; Gambetti & Giusberti, 2009). There is also considerable evidence that during adolescence anger increases vulnerability to risky behaviors and predicts numerous risky decisions, such as violence, smoking and substance abuse (e.g., Siqueira, Diab, Bodian, & Rolnitzky, 2000; Vaccaro & Wills, 1998). For these reasons, individual differences in the tendency to feel and express anger may represent very important factors in risk decision-making because they
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function as early and chronic schemas for organizing and interpreting events (Gasper & Clore, 1998; Lerner & Keltner, 2000). 1.3. The present study Given this theoretical framework, anger seems to play an important role in risk-taking during the development, but few studies explored this issue directly. To address this gap, the current study extends prior research investigating the link between anger and risk decisionmaking by examining relations among specific components of anger and risk-taking decisions. In particular, we hypothesized that habitual anger experience (affective component), hostile beliefs (cognitive component) and easiness to engage in acts of destructive expression of anger (behavioral component) would predict risky behavior in children and adolescents and they could interact with each other in influencing risk-taking. Assessing possible interactions among experience of anger, hostile beliefs and destructive expression of anger in risk decision-making may be a worthy addiction to the developmental literature making a bridge between different lines of research: studies on emotions and personality in judgments and decisions (e.g., Cooper et al., 2003) and studies that highlight the importance of cognitive assessments on risk-taking (e.g., Morrongiello & Matheis, 2004). Furthermore, in contrast to much previous research that considered unintentional injury in children (e.g., Morrongiello, Stewart, Pope, Pogrebtsova, & Boulay, 2015) or deviant and unhealthy behaviors in adolescents (e.g., Markey et al., 2003), this study examined risk decision-making in everyday hypothetical scenarios representative of a wide range of situations frequently faced by young people in their everyday lives. 2. Method 2.1. Samples Following approval of the research ethics review board and the head-master, permission forms were sent home to parents of schoolage children and adolescents to obtain consent for their sons to participate in this study. Participants also provided informed consent at school prior to participation. Participants were recruited from two elementary schools and three classes of middle school. Samples comprised 88 children (M = 9.47 years, SD = 0.61, range 8–11, 43% males) and 101 adolescents who ranged in ages from 12 to 16 (M = 13.63, SD = 1.56, 44% males). All participants were fluent in Italian, normally developing (as reported by teachers) and in regular classrooms. Osborne and Costello (2004) suggested that there is no specific criterion for determining sample size in behavioral studies. They showed that one-sixth of the studies used 2:1 subject-to-item ratio and about 20% studies used less than 5:1 subject-to-item ratio. Sample sizes of 88 and 101 were approximately 2:1 subject-to-item ratio which was considered suitable for conducting analyses. 2.2. Instruments 2.2.1. Multidimensional School Anger Inventory–Revised (MSAI–R; Boman, Curtis, Furlong, & Smith, 2006) The 36-item MSAI–R was developed to measure the psychological/ affective, cognitive, and behavioral components of anger with items specifically referring to the school environment (Boman et al., 2006; Furlong, Smith, & Bates, 2002). This instrument is composed of three scales: Anger Experience (e.g., You ask to go to the bathroom and the teacher says, “no”), Hostility (e.g., Rules at school are stupid), and Destructive Expression (e.g., When I'm angry, I'll take it out on whoever is around). All scales use four response categories (from 1 = never to 4 = always). Reliability with Australian children ranged from 0.79 to 0.66 (Boman et al., 2006). The MSAI–R was presented in Italian; this version was a translation of the original questionnaire, with exactly alike
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item numbering. The goodness of translation was verified by a backtranslation from Italian to English, conducted by a native English speaker unfamiliar with the English version of the MSAI–R. The Anger Experience, Hostility, and Destructive Expression scales have good Cronbach's alphas for children (i.e., 0.84, 0.85 and 0.77, respectively), such as for adolescents (i.e., 0.80, 0.70, and 0.70 respectively). 2.2.2. Risk tasks These tasks assessed children and adolescents intentions to take risks, respectively in twelve and thirteen different everyday-life situations, derived by pilot surveys showing good validity (i.e., significant differences across risky and safe choices and no significant differences between effort rates of the risky and the safe options) and test–retest reliability (Gambetti & Giusberti, 2008, 2009). These scenarios have two choices: one of these was identified as “safe” and one “risky”, randomly designated as choice A or choice B. In order to obtain a more sensitive measure of risk behavior, participants were asked to indicate their choice conviction on a 10-point Likert scale ranging from definitely A to definitely B. The dependent variable used for the assessment of risk decision-making was the total score of the children's choice conviction. The complete lists of the scenarios are available from the first author. The internal consistency was adequate (α = .82 for both samples). 2.3. Procedure Each participant was seen individually at school for one 20-min session. They completed the risk task and the MSAI–R. Given the potential for order effects, the task and the questionnaire were randomly administrated for each participant and each scenario of the task was presented one at a time in random order. At the conclusion of each session, participants were asked to provide their actual levels of attention to tasks and understanding of tasks on 4-point Likert scales, with higher number indicating better scores (e.g., 1 = poor and 4 = very good). 3. Results
Table 1 Descriptive statistics and partial correlations, controlling for age and gender.
Children (1) Anger experience (2) Hostility (3) Destructive expression N M SD SEM Adolescents (1) Anger experience (2) Hostility (3) Destructive expression N M SD SEM
1
2
– .43⁎⁎ .51⁎⁎ 88 41.53 7.10 .76
– .66⁎⁎ 88 10.10 4.67 .50
– .15⁎ .34⁎⁎ 101 36.39 4.86 .48
3
– .07 101 13.64 4.00 .40
Risk-taking
– 88 15.54 5.51 .59
– 101 15.83 3.86 .38
.33⁎⁎ .30⁎⁎ .45⁎⁎ 88 68.43 25.33 2.48 .26⁎⁎ .38⁎⁎ .41⁎⁎ 101 67.77 18.31 1.82
⁎ p b .05 (2-tailed). ⁎⁎ p b .001 (2-tailed).
3.4. Regression analyses predicting risk-taking from anger components In order to evaluate the anger components that explain and predict risk-taking, two hierarchical linear regression analyses were performed separately by each sample we studied. All predicting variables were centered (the actual score minus the mean score) to avoid the problem of multicollinearity in the regression. The covariates were entered in step 1 (age and gender), then the predictors (i.e., Anger Experience, Hostility and Destructive Expression) were entered in step 2. Table 2 reported the standardized beta coefficient and changed in R-squares for children and adolescents, respectively. Results revealed that, for children, after adjusting for age destructive expression of anger was only associated with risk measure. In adolescent sample, results showed that after adjusting for age both destructive expression of anger and hostility predicted risky decisions.
3.1. Preliminary analyses 3.5. Path analyses Descriptive analysis of ratings of children's attention during the tasks revealed high ratings (M = 3.9; SD = 0.56 for children; M = 3.8; SD = 0.4 for adolescents). Thus, there was no evidence to indicate that differential attention or understanding to the tasks contributed to our findings. 3.2. Descriptive analysis The means and standard deviations of all the measures are reported in Table 1. In order to assess the influence of gender on risk, we performed t-test. Results showed that males take more risks (M = 54.83, SD = 9.34 for children; M = 72.68, SD = 20.79 for adolescents) than females (M = 46.59, SD = 9.06, t87 = 4.51, p b .001 for children; M = 63.98, SD = 15.25, t100 = 2.42, p b .05 for adolescents). Moreover, age and risk-taking were positively correlated both in childhood (r = .32, p b .001) and in adolescence (r = .22, p b .05). 3.3. Correlations between risk-taking and anger components We examined partial correlations, controlling for age and gender, among MSAI–R scales (i.e., Anger Experience, Hostility and Destructive Expression) and risk-taking. The significance of these values permits a first approximation to the covariance of these measures that can be seen in Table 1. Anger Experience, Hostility and Destructive Expression were positively related to risk-taking in children and adolescents.
Finally, two path analyses, one for each sample, were conducted to determine whether there were indirect effects of cognitive and affective components of anger, through behavioral component of anger, on risktaking in children and whether the direct effects of hostility or the indirect effects through destructive expression of anger were stronger in adolescents (see Kassinove et al., 2002). Anger experience and hostility were considered exogenous variables and destructive expression and risk were endogenous variables. The model from children (see Fig. 1) did not differ significantly from a fully saturated model (χ22102 = 3.82,
Table 2 Hierarchical regression predicting risk-taking from MSAI–R scales in children and adolescents.
Age (in years) Gender Anger experience Hostility Destructive expression of anger ΔR2 ⁎ p b 0.05 (2-tailed). ⁎⁎ p b 0.01 (2-tailed). ⁎⁎⁎ p b .001 (2-tailed).
Children results
Adolescents results
Step 1
Step 2
Step 1
Step 2
.383⁎⁎⁎ .186⁎
.343⁎⁎⁎ .081 .166 −.010 .353⁎⁎ .180⁎⁎⁎
.207⁎ .224⁎
.246⁎⁎ .145 .103 .307⁎⁎⁎ .332⁎⁎⁎ .239⁎⁎⁎
.167⁎⁎⁎
.078⁎⁎
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Fig. 1. Path analysis on children sample. **p b .001 (2-tailed).
p = .14), such as the model from adolescents (see Fig. 2) (χ22.99 = 4.19, p = .12). The standardized regression weights for the indirect effects of anger experience and hostility through destructive expression of anger on risky decisions were 0.21 and 0.31 in children, .33 and .34 in adolescents, respectively. In children, the direct effect of anger experience and hostility was non-significant; in adolescents, there was a significant direct effect of hostility on risky decisions (.27), while the direct effect of anger experience was non-significant. 4. Discussion We used a number of everyday-life situations to explore risk decision-making and to identify the specific anger components that could predict these decisions in children and adolescents. The principal hypothesis, that is anger components were all predictive of later risktaking decisions, was partially supported. On the one hand, the findings showed that affective, cognitive and behavioral components of anger are all related to risk-taking decisions in children and adolescents. These findings are consistent with past research indicating that anger is an important factor in risk decision-making. In particular, prior works on adults has reported that the tendency to experience anger is related to optimistic beliefs about experiencing future life events and optimistic perceptions of risk (Lerner & Keltner, 2000). Moreover, previous studies highlighted that anger makes people indiscriminately optimistic about their own changes of success (Fischhoff, Gonzalez, Lerner, & Small, 2005) and careless in their thought (Tiedens, 2001). In this sense, also our study suggests that anger promotes decision-making biases that increase one's tolerance for risk. On the other hand, results showed that only the behavioral component of anger (i.e., destructive expression) was predictive of risky
Fig. 2. Path analysis on adolescent sample. *p b .05, **p b .01, ***p b .001 (2-tailed).
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decisions in children and adolescents. Moreover, the effects of the affective (i.e., angry feelings) and the cognitive (i.e., hostility) components of anger on risky decisions were mediate by the behavioral component of anger in children sample. On the other hand, the effect of hostility was both direct and indirect through destructive expression of anger, while the effect of angry feelings was only indirect in the adolescence sample. These findings highlight the importance of the behavioral component of anger in risk decision-making in both childhood and adolescence. All of this appears to be coherent with the relationship between outwardly expressed anger and a wide range of risky types of behaviors, such as competitive and attack responses (Kassinove et al., 2002), as well as substance use (Eftekari et al., 2004). A possible explanation could be that individuals with high levels of destructive expressed anger may have low impulse control. Our results converge with other theories of self-control (e.g., Mischel & Ayduk, 2004) and cognitive control (e.g., Kerns et al., 2004) in emphasizing the nature such process in the anger domain (Wilkowski & Robinson, 2008). The fact that hostility directly predicts risky decisions in adolescence and indirectly in childhood suggests the immediacy with which the cognitive component of anger may produce risky decisions in youth. However, hostility seems to be not so closely linked to risk decision-making in childhood. The absence of a direct relationship between hostility and children's risky decisions may be due to the fact that impulsivity, and in this sense destructive expressed anger, has an important role first of all in childhood. Age increasing, it seems to become important the cognitive component of anger in risk decision-making, which assumed a central role in adolescence, jointly the behavioral component of anger. In the developmental literature there are several models that seek to explain risk decision-making in childhood and adolescence considering four research perspectives (i.e., cognitive, emotional, psychobiological and social) (for a review see Boyer, 2006). However, researchers have quite recently begun considering the potential role of emotions in risk-taking (e.g., Cauffman & Steinberg, 2000; Morrongiello et al., 2015). The current study refers to this developmental perspective, highlighting the importance of examining relations among individual differences in the tendency to feel a specific emotion, also considering the underlying cognitive and behavioral processes, and risk decisionmaking in childhood and adolescence. In this sense, it is important to consider the role of emotional regulation and the possibility that particularly impulsive or anger prone individuals make risky decisions. Anger has a number of adaptive functions such as providing an internal signal that goals are blocked or thwarted (Berkowitz & Harmon-Jones, 2004) or communicating to others that their actions are viewed as an encroachment on freedom or resources (Rothenberg, 1971). Nevertheless, for a subset of individuals, anger may become a habitual, and often dysfunctional, way of reaction to frustrations. Although our findings extend the knowledge of the determinants of risk-taking decisions in children and adolescents, there are some limitations to this work and questions that remain to be considered in future research. First, the correlation between anger and risk-taking could be spurious through a linkage with other causal factors. For example, a person who is low on the ability to inhibit or self-regulate would also be likely to feel and express anger and take risks. Thus, further studies are required to evaluate the role of other variables, such as impulsivity and inhibition, on risk-taking. Second, we cannot assert with certainty that what children and adolescents proposed to do would necessary be what they would actually do. The use of hypothetical, rather than real, decisions may be a relevant factor in the observed pattern of effects. Nevertheless, many studies suggest and confirm that reports of personal intentions greatly correspond with subsequent actual risktaking (e.g., Hockey, Maule, Clough, & Bdzola, 2000; Morrongiello & Dawber, 2004). Despite these limitations, the current research has potential implications for both theories of decision-making and educational programs. As our findings suggest, anger may shape individual choices. These data fit
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with a growing body of evidence suggesting that individual differences in affective experiences influence risk decision-making (e.g., Maner et al., 2007). The current study suggests the utility of a motivationbased approach to decision-making and is consistent with other theories positing emotion-specific influences on choices and decisions (e.g., Lerner & Keltner, 2000). These findings have also practical implications for teachers and educators interested in identifying children and adolescent most at risk for taking potentially risky decisions. Our results suggest that school educational programs, usually focused on anticipatory guidance strategies (e.g. instructing children about the importance of avoiding risky behaviors), may be enhanced by knowledge of personality traits. References Ahn, H. (2010). Modeling and analysis of affective influences on human experience, prediction, decision making, and behavior. (Ph.D. diss.) Massachusetts Institute of Technology. Barefoot, J. (1992). 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