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Thinking about smoking: A novel approach to describing cognitive style profiles
Personality and Individual Differences 82 (2015) 76–80
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Thinking about smoking: A novel approach to describing cognitive style profiles Lynsey J. Brown a, Malcolm J. Bond b,⇑ a b
General Practice, School of Medicine, Flinders University, GPO Box 2100, Adelaide 5001, Australia Health Professional Education, School of Medicine, Flinders University, GPO Box 2100, Adelaide 5001, Australia
a r t i c l e
i n f o
Article history: Received 1 September 2014 Received in revised form 25 February 2015 Accepted 4 March 2015 Available online 20 March 2015 Keywords: Cluster analysis Median splits Cognition Addiction Smoking
a b s t r a c t Cognitive-Experiential Self-Theory (CEST) emphasizes the dual roles of rational and experiential thinking, with individuals having varying preferences for each style. This study explored the relationship between these constructs, illustrating the value of the derived model in addictive behavior, as illustrated by smoking. Data were extracted from a study of the predictors of men’s health behavior. Participants comprised 212 Australian men (aged 25–65 years) who completed a self-report questionnaire which assessed thinking styles and recorded smoking status. Rational and experiential data were subjected to cluster analysis and median splits to identify logical subgroups based on participants’ dual responses. The four derived clusters were more representative of smoking status than groups defined by median splits. In general, both smokers and ex-smokers preferred experiential thinking and non-smokers preferred rational thinking. There was a strong tendency for smokers to report both low rational and high experiential thinking. The use of cluster analysis advanced the evaluation of the interactive nature of rational and experiential thinking by allowing an empirical test of their potential relationship. The thinking profiles reported represent an advance in the assessment of CEST which may provide a useful model for applications in fields both related to, and beyond, addiction. Ó 2015 Elsevier Ltd. All rights reserved.
1. Introduction Cognitive-Experiential Self-Theory (CEST; Epstein, 1973, 1994, 2003) is a dual processing model of reasoning and decision-making based on cognitive styles known as ‘need for cognition’ (rational thinking) and ‘faith in intuition’ (experiential thinking). Rational thinking refers to an analytical and logical style characterized by the desire to seek, appraise and apply information. It demands high levels of cognitive resources and is considered to be reflective and deliberate (Cacioppo, Petty, Feinstein, & Jarvis, 1996). Experiential thinking is more intuitive, innate and adaptive, relying on past experiences in problem solving, such as those related to the experience of affect, leading to the avoidance of negative, and facilitation of positive, emotions (Cacioppo et al., 1996; Epstein, Pacini, DenesRaj, & Heier, 1996). A key tenet of CEST is that the world is interpreted through the simultaneous operation of these two thinking styles, with the relative dominance of either determined by situational (environmental) and dispositional (individual) factors. The former may include the social, economic, administrative or ⇑ Corresponding author. Tel.: +61 8 7221 8503. E-mail addresses: lynsey.brown@flinders.edu.au (L.J. Brown), malcolm.bond@flinders.edu.au (M.J. Bond). http://dx.doi.org/10.1016/j.paid.2015.03.009 0191-8869/Ó 2015 Elsevier Ltd. All rights reserved.
organizational contexts in which reasoning occurs, while the latter embrace psychosocial characteristics such as attitudes, values, affect, knowledge, and skills (Burns & D’Zurilla, 1999; Kahneman, 2003; Sinclair & Ashkanasy, 2005). Research concerning the relative roles of the two thinking styles has reviewed an eclectic mix of variables. For example, the preference for rational thinking has been associated with aspects of personality and psychological adjustment, mathematical and verbal abilities, academic performance, lower depression and state-trait anxiety, less stress among college students, and lower perceived anthrax poisoning risk and apprehension (Berger, Johnson, & Lee, 2003; Epstein et al., 1996); whereas higher experiential thinking has been associated with less clinical guideline concordant behaviors among doctors with respect to treating acute coronary syndromes, but with a higher observed hand hygiene compliance rate (Sladek, Bond, Huynh, Chew, & Phillips, 2008; Sladek, Bond, & Phillips, 2008). Further, both lower rational thinking and higher experiential thinking have been associated with creativity, a more positive attitude towards organic foods, less positive attitudes toward genetically modified foods, paranormal beliefs and more positive attitudes toward, and use of, complementary and alternative medicines (Lindeman & Aarnio, 2006; Raidl & Lubart, 2000/ 2001; Saher, Lindeman, & Hursti, 2006; Wheeler & Hyland, 2005).
L.J. Brown, M.J. Bond / Personality and Individual Differences 82 (2015) 76–80
Importantly, this growing body of research has consistently supported the assertion that rational and experiential thinking styles are independent, albeit interactive, constructs, rather than the two extremes of a single continuum (Epstein, 2003; Handley, Newstead, & Wright, 2000; Newstead, Handley, Harley, Wright, & Farrelly, 2004). That is, CEST assumes that both styles are used, with individuals having a varying degree of preference for each. Indeed, behavior is assumed to be the product of the two styles, which interact both simultaneously and sequentially (Epstein, 2003). The experiential style can influence the rational by making quick cognitions that are incorrect or biased (impulsive thoughts or behavior). Yet it also offers the rational style access to novel information (e.g., creative ideas). Conversely, the rational style is able to moderate the experiential system and also be taught to understand potential biases inherent in the experiential system (e.g., understanding that impulsive behavior may be counterproductive and thus resisting it). However, through repetition, rational style activities may become proceduralized (habitualized), with their control then shifted to the experiential style. Notwithstanding these hypothesized mechanisms of interaction between rational and experiential styles, as stated earlier, they are viewed as independent constructs. Therefore, analysis can either literally treat them as such, as illustrated by de Stadelhofen, Rossier, Rigozzi, Zimmerman, and Berthoud (2004) and Marks, O’Neill, and Hine (2008), for example, or accommodate possible associations between them. The most common such strategy is to apply median splits to classify participants as high or low on rational and experiential thinking, respectively (Edmond & Marmurek, 2010; Pacini & Epstein, 1999; Shiloh, Salton, & Sharabi, 2002). While this procedure allows for four thinking style ‘profiles’, cut-points are relatively arbitrary, and do not allow scores close to the median to be meaningfully interpreted. The empirical alternative presented in the current paper is the application of 2-step cluster analysis to rational and experiential scores. The goal was to identify unique subgroups of participants, characterized by low within group variance and high between group variance, that might provide a better representation of thinking style profiles than traditional median splits. To that end, the desired outcome was a novel measurement strategy leading to a more informed interpretation of the components of CEST. To evaluate the obtained clusters, their utility in describing the thinking style profiles of smokers, ex-smokers and non-smokers was examined. This enquiry is particularly relevant given the contemporary focus on implicit cognition as a key enabler of addictions and addictive behaviors (Fazio & Olson, 2003; Robinson & Berridge, 2001; Strack & Deutsch, 2004; Wiers & de Jong, 2006; Wiers & Stacy, 2006). While explicit cognitions refer to conscious, deliberate mental processes, implicit cognitions are influences on behavior such as knowledge, perception or memory that occur without conscious awareness (Stacy & Wiers, 2006). In short, implicit cognitive processing is hypothesized to increase the salience of addiction-related cues which in turn facilitate addictive behaviors. For the smoker, cravings are proposed to be initiated by automatic unconscious triggers, followed by associated cognitions concerning methods to regain the positive feeling associated with smoking (Bernheim & Rangel, 2004; Glautier, 2004). Despite the acknowledged overlap between implicit cognitions and experiential thinking, and explicit cognitions and rational thinking (Evans, 2008; Rooke, Hine, & Thorsteinsson, 2008), few studies have directly applied CEST. That is, limited research has tested whether addicted, as opposed to non-addicted, individuals have a greater preference for experiential thinking and/or a lesser preference for rational thinking. There is, for example, little data pertaining to smoking, although two studies are illustrative. de Stadelhofen et al. (2004) noted that smokers reported significantly higher experiential thinking than non-smokers. There was
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also a trend toward non-smokers reporting higher levels of rational thinking. Further, Marks et al. (2008) reported that experiential thinking (but not rational thinking) was a significant predictor of smoking, in conjunction with automatic affective evaluations of smoking. Smoking status (current smokers, ex-smokers and nonsmokers) was used as the exemplar to demonstrate the derived cognitive style profiles in the current research. Ex-smokers have not previously been considered, yet given that CEST is a model of reasoning, and may therefore be used as a framework to understand decision-making, the fact that these individuals have implemented change (smoking cessation) is of particular interest, with their cognitive style potentially differing from other participants. In summary, smoking status comparisons were used as an initial commentary on the validity of the obtained clusters.
2. Materials and methods 2.1. Participants and procedure The data reported were extracted from a study of predictors of men’s health behaviors (Brown & Bond, 2008). Based on the stereotypical belief that men are reluctant to engage in appropriate health behaviour (Australian Bureau of Statistics [ABS], 2006; Courtenay, 2000a, 2000b), this previous research explored the potential influence of health status, masculinity, social support, and somatic awareness on help-seeking and health promotion behaviours. Neither smoking status nor thinking styles were reported. Approval for the study was provided by the authors’ institutional Research Ethics Committee. Data were available from 212 Australian men aged between 25 and 65 years, all of whom had sufficient command of English to complete a self-report questionnaire. Volunteers were recruited from community groups based on sport, special interests, leisure and occupation. They were sourced during meetings of such groups to which the researchers were invited. Consenting attendees were provided with information about the study, the questionnaire and a reply-paid envelope for its confidential return. The mean age of the sample was 45.5 years (SD = 10.8). Most participants (83.6%) were married and employed full-time (89.9%). While 45.3% had been educated to tertiary level, a further 32.7% held a trade certificate. 2.2. Measures 2.2.1. Thinking styles The 24-item version of the Rational-Experiential Inventory (REI; Pacini & Epstein, 1999) was used. Two scales, defined as Rational (e.g., ‘I enjoy intellectual challenges’) and Experiential thinking (e.g., ‘I believe in trusting my hunches’) are measured using 12 items each. Respondents use a 5-point scale (definitely false to definitely true), with total scores ranging from 12 to 60 for each thinking style. Higher Rational scores suggest a tendency to enjoy cognitive activities such as critical thinking, while higher Experiential scores relate to a preference for intuitive activities. Internal reliability coefficients (a) with the current sample were .85 for Rational thinking and .83 for Experiential thinking. The obtained correlation between the scales (r = .09, p > .05) supports the claim that they operationalize two independent information processing systems (Epstein, 1994). 2.2.2. Smoking status Embedded in an assessment of common health behaviors was a single item that sought smoking status (smoke currently, smoked but have ceased, have never smoked).
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L.J. Brown, M.J. Bond / Personality and Individual Differences 82 (2015) 76–80 Table 2 Cognitive style scores by smoking status.
3. Results 3.1. Determination of cluster membership
Rational
Continuous Rational and Experiential responses were subjected to a 2-step cluster analysis. The optimal statistical outcome was a three cluster solution, providing a cohesion and separation index (goodness-of-fit) of 0.5 (the upper end of ‘fair’; Mooi & Sarstedt, 2011). These clusters were determined to be high Rational/high Experiential, high Rational/low Experiential, and low Rational/ medium Experiential. However, as the research goal was to attempt to mimic enforced median splits, a four cluster solution was subsequently sought (Table 1, goodness-of-fit also 0.5). To confirm the statistical decisions underpinning cluster formation, oneway ANOVAs were conducted comparing cluster membership with continuous Rational and Experiential scores. As expected, both ANOVAs produced highly significant results (Rational F(3,209) = 78.64, p < .001; Experiential F(3,209) = 193.54, p < .001) with Bonferroni post hoc tests indicating that all clusters differed significantly for both Rational and Experiential thinking. The relevant means are shown in Table 1. Cluster 1 (n = 31, 14.6%) comprised individuals who reported relatively low scores for both Rational and Experiential thinking (low R/low E), while Cluster 2 (n = 48, 22.5%) was also characterized by comparatively low Rational scores but relatively high Experiential scores (low R/high E). Cluster 3 (n = 60, 28.2%) comprised individuals with relatively high Rational scores and relatively low Experiential scores (high R/low E) and Cluster 4 (n = 74, 34.7%) included those with comparatively high Rational and high Experiential scores (high R/high E). It should be noted that these labels are relative to the obtained sample distributions rather than the theoretical ranges of the scales. Traditional median splits were also applied to the continuous Rational and Experiential scores to enable comparisons with the above cluster memberships. While these analyses produced similar patterns, with the overall agreement between the two methods significant (kappa = .50, p < .001), the concordance at the individual cluster level was variable. For the low R/low E cluster, the median split provided 74.2% agreement, while for the low R/high E cluster it was only 35.4%. Agreement for the high R/low E cluster was a more impressive 81.7%, but for the high R/high E cluster it was only 59.5%.
3.2. Smoking status and cognitive styles The sample comprised 22 participants who smoked currently (10.4%), 69 ex-smokers (32.5%) and 121 who had never smoked (57.1%). Given the ad hoc nature of this enquiry relative to the aims of the parent study, these unequal percentages are unsurprising as they tend to characterize Australian prevalence figures (ABS, 2013). Descriptive data for the continuous Rational and Experiential scores are shown in Table 2 according to smoking status. A oneway ANOVA conducted with each thinking style demonstrated a significant group difference for Rational (F(2,209) = 5.72, Table 1 Cognitive style scores by cluster membership. Rational
Cluster Cluster Cluster Cluster
1 2 3 4
(low R/low E) (low R/high E) (high R/low E) (high R/high E)
Experiential
Range
M
(SD)
Range
M
(SD)
35–53 13–43 44–58 40–58
43.6 37.0 49.5 47.0
(4.0) (5.8) (3.8) (4.1)
24–37 35–48 30–44 43–57
32.7 41.8 38.9 47.3
(2.6) (5.6) (3.1) (3.3)
Note: R = Rational; E = Experiential.
Smokers Ex-smokers Non-smokers
Experiential
Range
M
(SD)
Range
M
(SD)
32–57 26–58 13–58
43.1 43.5 46.3
(6.8) (6.1) (6.2)
34–54 24–56 29–57
41.5 41.1 41.8
(4.6) (5.8) (6.1)
p < .01) but not Experiential thinking (F(2,209) = 0.33, p > .05). For the former, Bonferroni post hoc tests indicated that ex-smokers reported significantly lower Rational scores than non-smokers. No significant pairwise differences involved current smokers. However, significantly higher Rational scores were noted among non-smokers (t(141) = 2.20, p < .05) when compared directly with smokers. No difference was evident for Experiential thinking (t(141) = 0.27, p > .05). Table 3 presents cluster membership crosstabulated by smoking status, with a significant association noted (v2(6) = 17.20, p < .01). An inspection of column percentages indicates that current smokers and ex-smokers were overrepresented in the high Experiential clusters and non-smokers were overrepresented in high Rational clusters. There was a particular tendency for low Rational/ high Experiential preferences among smokers, and a substantial proportion of ex-smokers had membership of the high Rational/low Experiential cluster. If the results are interpreted according to row percentages, it is noted that the composition of the high Rational/ low Experiential and high Rational/high Experiential clusters is essentially identical. In each case around two-thirds of the members were non-smokers, with current smokers only very modestly represented. There were similar patterns for the low Rational/low Experiential cluster though there was a comparatively higher proportion of ex-smokers in this subgroup. The modal group in the low Rational/high Experiential cluster was ex-smokers (approximately half of the cases). Such associations between smoking status and thinking styles derived using median splits were not evident (v2(6) = 12.48, p > .05). 4. Discussion The current analyses progress both the evaluation of thinking styles, as conceptualized by CEST, and their application to addictive behavior as illustrated by smoking. Primarily, given the complexity which surrounds the relationship between the rational and experiential components of CEST, the current research advanced approaches to characterizing the independent yet interactive nature of these styles by comparing median split and cluster analysis methods. These approaches were then evaluated through their association with smoking status. The application of cluster analysis to Rational and Experiential scores has offered an alternative to characterizing the relationship between these constructs. The ‘independence’ of Rational and Experiential thinking styles is an axiom of CEST (Epstein, 2003; Handley et al., 2000; Newstead et al., 2004), and Rational and Experiential scores certainly do not share a linear relationship. Therefore, while they should not be described as two extremes of a single continuum, it is perhaps equally unlikely that their relationship is completely random. Rather, the precise association between Rational and Experiential thinking styles is likely to be complex. With no preconception as to the nature of the association, an empirical decision-making tool such as cluster analysis becomes an entirely defensible strategy. The current data supported four clusters that might be termed ‘thinking profiles’. These were low Rational/low Experiential, low Rational/high Experiential, high Rational/low Experiential, and high Rational/high Experiential. While this is acknowledged to
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L.J. Brown, M.J. Bond / Personality and Individual Differences 82 (2015) 76–80 Table 3 Cluster membership according to smoking status. Smokers
Low Rational/Low Experiential Low Rational/High Experiential High Rational/Low Experiential High Rational/High Experiential
Ex-smokers
Non-smokers
n
Column (%)
Row (%)
n
Column (%)
Row (%)
n
Column (%)
Row (%)
2 10 4 6
(9.1) (45.5) (18.2) (27.3)
(6.5) (21.3) (6.7) (8.1)
12 21 15 21
(17.4) (30.4) (21.7) (30.4)
(38.7) (44.7) (25.0) (28.4)
17 16 41 47
(14.0) (13.2) (33.9) (38.8)
(54.8) (34.0) (68.3) (63.5)
mimic the pattern obtained using median splits, the two procedures produce groupings using different statistical strategies. Median splits identify the end points of subgroup distributions, while cluster analysis creates subgroups based on centroids (means). This has the potential to make each resultant cluster representative of a greater number of its members. The obtained results beg the question not only of the pattern of association between rational and experiential thinking per se, but also whether the absolute level of the two styles endorsed by an individual, or the relative magnitude of the two styles when considered together as a profile, is more important to the understanding of behavior or behavior potential. Such an observation remains speculative pending further studies of thinking profiles. When exploring group differences using continuous Rational and Experiential scores according to smoking status there was variation among groups on the Rational scale, but not the Experiential scale. Similarly, when examining patterns of results for smoking status and thinking styles based on median splits, there was little differentiation in terms of the profiles which contain high Experiential preferences. In contrast, thinking style clusters provided greater depth, illustrating significant differences between each smoking status group. That is, if analyzed independently, Experiential preferences were not salient to smoking status, whereas when analyzed in conjunction with Rational preferences to create clusters, they became clearly relevant. In summary, what is clear is that the procedure we have reported is a significant advance on previously used median splits. An important caveat of the current research is that the obtained clusters must not be considered definitive. Cluster analysis is a statistical technique, the results from which are expressly sample-specific. That is, replication of the obtained clusters need not be expected if the procedure were to be repeated with samples of differing composition, or indeed samples of similar composition. Again, however, this is also true of median splits. Given that the parent study from which the reported data were drawn comprised only men (Brown & Bond, 2008), and there is a known association between gender and rational and experiential thinking (Sladek, Phillips, & Bond, 2010), future studies involving women, or indeed both genders, should be conducted. Further, just as the sample comprised only men, the numbers of smokers, ex-smokers and non-smokers available were less than ideal for the current aims. Future research should seek to compare relatively equal numbers across these groups (with larger Ns). Such sample challenges limited the ability to conduct more complex analyses. Not only has the current study been able to identify a novel approach to describing cognitive style profiles but it has been able to further the evidence base by contributing to the modest existing research that has evaluated Rational and Experiential thinking as they may be associated with smoking. In our data, differences involved Rational thinking, with evidence that smokers and ex-smokers report lower scores than non-smokers. This is slightly at odds with previous data for which Experiential thinking has been the differentiating factor, with smokers reporting significantly higher scores than non-smokers (de Stadelhofen et al.,
2004; Marks et al., 2008). Taken together these studies suggest that either higher Rational scores or lower Experiential scores may be indicative of non-smokers, with the explanation of this difference likely to be associated with specific sample characteristics. Notwithstanding this comment, an important contribution of the current study was the inclusion, for the first time, of ex-smokers. If a full understanding of the place of thinking styles in smoking is to be achieved, it is necessary to have an appreciation of the potential role of rational and experiential thinking among individuals who have successfully ceased the behavior. The key findings to emerge from the available data were that ex-smokers were equally represented across the low Rational/high Experiential and high Rational/high Experiential clusters. That is, ex-smokers essentially reflected the thinking style profile of current smokers. It needs to be acknowledged that an understanding of the role of thinking styles in smoking, and indeed potentially other addictive behaviors, is two-fold. The identification of unique profiles of thinking styles associated with smokers, ex-smokers and nonsmokers is only stage one of this understanding. If thinking style profiles are ultimately determined to be related to the decision to smoke and/or the decision to cease, then the use of rational and experiential messages in targeted campaigns for smoking prevention, on the one hand and smoking cessation on the other, may need to be considered. In short, the content and focus of such programs may need to be designed specifically to match the dominant profile of the designated audience (Hine, Marks, & O’Neill, 2009). In exploring future research related to this work, we suggest that a more detailed understanding of the role of rational and experiential thinking in the process of smoking cessation can only be obtained by conducting a study with the specific aim of identifying thinking styles directly linked to the change process. It is possible that this can only be achieved through a longitudinal investigation that records thinking styles concurrently with the act of quitting. It may also be of interest to determine whether successful and unsuccessful cessation attempts are associated with specific thinking style profiles, and indeed whether success is associated with specific cessation techniques for different thinking style profiles. Further, given that age is associated with changes in the relative dominance of rational and experiential thinking (Sladek et al., 2010), either the age at which, or the timeframe over which, successful smoking cessation occurred may also be key data. In summary, this research has presented a novel strategy for measuring the components of CEST, and applied this technique to smoking status. This strategy represents a fruitful approach for the assessment of styles of reasoning and decision-making. It is hoped that it may provide a useful model for applications in other fields both related to, and beyond, addiction.
Conflict of interest None declared.
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Thinking about smoking: A novel approach to describing cognitive style profiles Lynsey J. Brown a, Malcolm J. Bond b,⇑ a b
General Practice, School of Medicine, Flinders University, GPO Box 2100, Adelaide 5001, Australia Health Professional Education, School of Medicine, Flinders University, GPO Box 2100, Adelaide 5001, Australia
a r t i c l e
i n f o
Article history: Received 1 September 2014 Received in revised form 25 February 2015 Accepted 4 March 2015 Available online 20 March 2015 Keywords: Cluster analysis Median splits Cognition Addiction Smoking
a b s t r a c t Cognitive-Experiential Self-Theory (CEST) emphasizes the dual roles of rational and experiential thinking, with individuals having varying preferences for each style. This study explored the relationship between these constructs, illustrating the value of the derived model in addictive behavior, as illustrated by smoking. Data were extracted from a study of the predictors of men’s health behavior. Participants comprised 212 Australian men (aged 25–65 years) who completed a self-report questionnaire which assessed thinking styles and recorded smoking status. Rational and experiential data were subjected to cluster analysis and median splits to identify logical subgroups based on participants’ dual responses. The four derived clusters were more representative of smoking status than groups defined by median splits. In general, both smokers and ex-smokers preferred experiential thinking and non-smokers preferred rational thinking. There was a strong tendency for smokers to report both low rational and high experiential thinking. The use of cluster analysis advanced the evaluation of the interactive nature of rational and experiential thinking by allowing an empirical test of their potential relationship. The thinking profiles reported represent an advance in the assessment of CEST which may provide a useful model for applications in fields both related to, and beyond, addiction. Ó 2015 Elsevier Ltd. All rights reserved.
1. Introduction Cognitive-Experiential Self-Theory (CEST; Epstein, 1973, 1994, 2003) is a dual processing model of reasoning and decision-making based on cognitive styles known as ‘need for cognition’ (rational thinking) and ‘faith in intuition’ (experiential thinking). Rational thinking refers to an analytical and logical style characterized by the desire to seek, appraise and apply information. It demands high levels of cognitive resources and is considered to be reflective and deliberate (Cacioppo, Petty, Feinstein, & Jarvis, 1996). Experiential thinking is more intuitive, innate and adaptive, relying on past experiences in problem solving, such as those related to the experience of affect, leading to the avoidance of negative, and facilitation of positive, emotions (Cacioppo et al., 1996; Epstein, Pacini, DenesRaj, & Heier, 1996). A key tenet of CEST is that the world is interpreted through the simultaneous operation of these two thinking styles, with the relative dominance of either determined by situational (environmental) and dispositional (individual) factors. The former may include the social, economic, administrative or ⇑ Corresponding author. Tel.: +61 8 7221 8503. E-mail addresses: lynsey.brown@flinders.edu.au (L.J. Brown), malcolm.bond@flinders.edu.au (M.J. Bond). http://dx.doi.org/10.1016/j.paid.2015.03.009 0191-8869/Ó 2015 Elsevier Ltd. All rights reserved.
organizational contexts in which reasoning occurs, while the latter embrace psychosocial characteristics such as attitudes, values, affect, knowledge, and skills (Burns & D’Zurilla, 1999; Kahneman, 2003; Sinclair & Ashkanasy, 2005). Research concerning the relative roles of the two thinking styles has reviewed an eclectic mix of variables. For example, the preference for rational thinking has been associated with aspects of personality and psychological adjustment, mathematical and verbal abilities, academic performance, lower depression and state-trait anxiety, less stress among college students, and lower perceived anthrax poisoning risk and apprehension (Berger, Johnson, & Lee, 2003; Epstein et al., 1996); whereas higher experiential thinking has been associated with less clinical guideline concordant behaviors among doctors with respect to treating acute coronary syndromes, but with a higher observed hand hygiene compliance rate (Sladek, Bond, Huynh, Chew, & Phillips, 2008; Sladek, Bond, & Phillips, 2008). Further, both lower rational thinking and higher experiential thinking have been associated with creativity, a more positive attitude towards organic foods, less positive attitudes toward genetically modified foods, paranormal beliefs and more positive attitudes toward, and use of, complementary and alternative medicines (Lindeman & Aarnio, 2006; Raidl & Lubart, 2000/ 2001; Saher, Lindeman, & Hursti, 2006; Wheeler & Hyland, 2005).
L.J. Brown, M.J. Bond / Personality and Individual Differences 82 (2015) 76–80
Importantly, this growing body of research has consistently supported the assertion that rational and experiential thinking styles are independent, albeit interactive, constructs, rather than the two extremes of a single continuum (Epstein, 2003; Handley, Newstead, & Wright, 2000; Newstead, Handley, Harley, Wright, & Farrelly, 2004). That is, CEST assumes that both styles are used, with individuals having a varying degree of preference for each. Indeed, behavior is assumed to be the product of the two styles, which interact both simultaneously and sequentially (Epstein, 2003). The experiential style can influence the rational by making quick cognitions that are incorrect or biased (impulsive thoughts or behavior). Yet it also offers the rational style access to novel information (e.g., creative ideas). Conversely, the rational style is able to moderate the experiential system and also be taught to understand potential biases inherent in the experiential system (e.g., understanding that impulsive behavior may be counterproductive and thus resisting it). However, through repetition, rational style activities may become proceduralized (habitualized), with their control then shifted to the experiential style. Notwithstanding these hypothesized mechanisms of interaction between rational and experiential styles, as stated earlier, they are viewed as independent constructs. Therefore, analysis can either literally treat them as such, as illustrated by de Stadelhofen, Rossier, Rigozzi, Zimmerman, and Berthoud (2004) and Marks, O’Neill, and Hine (2008), for example, or accommodate possible associations between them. The most common such strategy is to apply median splits to classify participants as high or low on rational and experiential thinking, respectively (Edmond & Marmurek, 2010; Pacini & Epstein, 1999; Shiloh, Salton, & Sharabi, 2002). While this procedure allows for four thinking style ‘profiles’, cut-points are relatively arbitrary, and do not allow scores close to the median to be meaningfully interpreted. The empirical alternative presented in the current paper is the application of 2-step cluster analysis to rational and experiential scores. The goal was to identify unique subgroups of participants, characterized by low within group variance and high between group variance, that might provide a better representation of thinking style profiles than traditional median splits. To that end, the desired outcome was a novel measurement strategy leading to a more informed interpretation of the components of CEST. To evaluate the obtained clusters, their utility in describing the thinking style profiles of smokers, ex-smokers and non-smokers was examined. This enquiry is particularly relevant given the contemporary focus on implicit cognition as a key enabler of addictions and addictive behaviors (Fazio & Olson, 2003; Robinson & Berridge, 2001; Strack & Deutsch, 2004; Wiers & de Jong, 2006; Wiers & Stacy, 2006). While explicit cognitions refer to conscious, deliberate mental processes, implicit cognitions are influences on behavior such as knowledge, perception or memory that occur without conscious awareness (Stacy & Wiers, 2006). In short, implicit cognitive processing is hypothesized to increase the salience of addiction-related cues which in turn facilitate addictive behaviors. For the smoker, cravings are proposed to be initiated by automatic unconscious triggers, followed by associated cognitions concerning methods to regain the positive feeling associated with smoking (Bernheim & Rangel, 2004; Glautier, 2004). Despite the acknowledged overlap between implicit cognitions and experiential thinking, and explicit cognitions and rational thinking (Evans, 2008; Rooke, Hine, & Thorsteinsson, 2008), few studies have directly applied CEST. That is, limited research has tested whether addicted, as opposed to non-addicted, individuals have a greater preference for experiential thinking and/or a lesser preference for rational thinking. There is, for example, little data pertaining to smoking, although two studies are illustrative. de Stadelhofen et al. (2004) noted that smokers reported significantly higher experiential thinking than non-smokers. There was
77
also a trend toward non-smokers reporting higher levels of rational thinking. Further, Marks et al. (2008) reported that experiential thinking (but not rational thinking) was a significant predictor of smoking, in conjunction with automatic affective evaluations of smoking. Smoking status (current smokers, ex-smokers and nonsmokers) was used as the exemplar to demonstrate the derived cognitive style profiles in the current research. Ex-smokers have not previously been considered, yet given that CEST is a model of reasoning, and may therefore be used as a framework to understand decision-making, the fact that these individuals have implemented change (smoking cessation) is of particular interest, with their cognitive style potentially differing from other participants. In summary, smoking status comparisons were used as an initial commentary on the validity of the obtained clusters.
2. Materials and methods 2.1. Participants and procedure The data reported were extracted from a study of predictors of men’s health behaviors (Brown & Bond, 2008). Based on the stereotypical belief that men are reluctant to engage in appropriate health behaviour (Australian Bureau of Statistics [ABS], 2006; Courtenay, 2000a, 2000b), this previous research explored the potential influence of health status, masculinity, social support, and somatic awareness on help-seeking and health promotion behaviours. Neither smoking status nor thinking styles were reported. Approval for the study was provided by the authors’ institutional Research Ethics Committee. Data were available from 212 Australian men aged between 25 and 65 years, all of whom had sufficient command of English to complete a self-report questionnaire. Volunteers were recruited from community groups based on sport, special interests, leisure and occupation. They were sourced during meetings of such groups to which the researchers were invited. Consenting attendees were provided with information about the study, the questionnaire and a reply-paid envelope for its confidential return. The mean age of the sample was 45.5 years (SD = 10.8). Most participants (83.6%) were married and employed full-time (89.9%). While 45.3% had been educated to tertiary level, a further 32.7% held a trade certificate. 2.2. Measures 2.2.1. Thinking styles The 24-item version of the Rational-Experiential Inventory (REI; Pacini & Epstein, 1999) was used. Two scales, defined as Rational (e.g., ‘I enjoy intellectual challenges’) and Experiential thinking (e.g., ‘I believe in trusting my hunches’) are measured using 12 items each. Respondents use a 5-point scale (definitely false to definitely true), with total scores ranging from 12 to 60 for each thinking style. Higher Rational scores suggest a tendency to enjoy cognitive activities such as critical thinking, while higher Experiential scores relate to a preference for intuitive activities. Internal reliability coefficients (a) with the current sample were .85 for Rational thinking and .83 for Experiential thinking. The obtained correlation between the scales (r = .09, p > .05) supports the claim that they operationalize two independent information processing systems (Epstein, 1994). 2.2.2. Smoking status Embedded in an assessment of common health behaviors was a single item that sought smoking status (smoke currently, smoked but have ceased, have never smoked).
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L.J. Brown, M.J. Bond / Personality and Individual Differences 82 (2015) 76–80 Table 2 Cognitive style scores by smoking status.
3. Results 3.1. Determination of cluster membership
Rational
Continuous Rational and Experiential responses were subjected to a 2-step cluster analysis. The optimal statistical outcome was a three cluster solution, providing a cohesion and separation index (goodness-of-fit) of 0.5 (the upper end of ‘fair’; Mooi & Sarstedt, 2011). These clusters were determined to be high Rational/high Experiential, high Rational/low Experiential, and low Rational/ medium Experiential. However, as the research goal was to attempt to mimic enforced median splits, a four cluster solution was subsequently sought (Table 1, goodness-of-fit also 0.5). To confirm the statistical decisions underpinning cluster formation, oneway ANOVAs were conducted comparing cluster membership with continuous Rational and Experiential scores. As expected, both ANOVAs produced highly significant results (Rational F(3,209) = 78.64, p < .001; Experiential F(3,209) = 193.54, p < .001) with Bonferroni post hoc tests indicating that all clusters differed significantly for both Rational and Experiential thinking. The relevant means are shown in Table 1. Cluster 1 (n = 31, 14.6%) comprised individuals who reported relatively low scores for both Rational and Experiential thinking (low R/low E), while Cluster 2 (n = 48, 22.5%) was also characterized by comparatively low Rational scores but relatively high Experiential scores (low R/high E). Cluster 3 (n = 60, 28.2%) comprised individuals with relatively high Rational scores and relatively low Experiential scores (high R/low E) and Cluster 4 (n = 74, 34.7%) included those with comparatively high Rational and high Experiential scores (high R/high E). It should be noted that these labels are relative to the obtained sample distributions rather than the theoretical ranges of the scales. Traditional median splits were also applied to the continuous Rational and Experiential scores to enable comparisons with the above cluster memberships. While these analyses produced similar patterns, with the overall agreement between the two methods significant (kappa = .50, p < .001), the concordance at the individual cluster level was variable. For the low R/low E cluster, the median split provided 74.2% agreement, while for the low R/high E cluster it was only 35.4%. Agreement for the high R/low E cluster was a more impressive 81.7%, but for the high R/high E cluster it was only 59.5%.
3.2. Smoking status and cognitive styles The sample comprised 22 participants who smoked currently (10.4%), 69 ex-smokers (32.5%) and 121 who had never smoked (57.1%). Given the ad hoc nature of this enquiry relative to the aims of the parent study, these unequal percentages are unsurprising as they tend to characterize Australian prevalence figures (ABS, 2013). Descriptive data for the continuous Rational and Experiential scores are shown in Table 2 according to smoking status. A oneway ANOVA conducted with each thinking style demonstrated a significant group difference for Rational (F(2,209) = 5.72, Table 1 Cognitive style scores by cluster membership. Rational
Cluster Cluster Cluster Cluster
1 2 3 4
(low R/low E) (low R/high E) (high R/low E) (high R/high E)
Experiential
Range
M
(SD)
Range
M
(SD)
35–53 13–43 44–58 40–58
43.6 37.0 49.5 47.0
(4.0) (5.8) (3.8) (4.1)
24–37 35–48 30–44 43–57
32.7 41.8 38.9 47.3
(2.6) (5.6) (3.1) (3.3)
Note: R = Rational; E = Experiential.
Smokers Ex-smokers Non-smokers
Experiential
Range
M
(SD)
Range
M
(SD)
32–57 26–58 13–58
43.1 43.5 46.3
(6.8) (6.1) (6.2)
34–54 24–56 29–57
41.5 41.1 41.8
(4.6) (5.8) (6.1)
p < .01) but not Experiential thinking (F(2,209) = 0.33, p > .05). For the former, Bonferroni post hoc tests indicated that ex-smokers reported significantly lower Rational scores than non-smokers. No significant pairwise differences involved current smokers. However, significantly higher Rational scores were noted among non-smokers (t(141) = 2.20, p < .05) when compared directly with smokers. No difference was evident for Experiential thinking (t(141) = 0.27, p > .05). Table 3 presents cluster membership crosstabulated by smoking status, with a significant association noted (v2(6) = 17.20, p < .01). An inspection of column percentages indicates that current smokers and ex-smokers were overrepresented in the high Experiential clusters and non-smokers were overrepresented in high Rational clusters. There was a particular tendency for low Rational/ high Experiential preferences among smokers, and a substantial proportion of ex-smokers had membership of the high Rational/low Experiential cluster. If the results are interpreted according to row percentages, it is noted that the composition of the high Rational/ low Experiential and high Rational/high Experiential clusters is essentially identical. In each case around two-thirds of the members were non-smokers, with current smokers only very modestly represented. There were similar patterns for the low Rational/low Experiential cluster though there was a comparatively higher proportion of ex-smokers in this subgroup. The modal group in the low Rational/high Experiential cluster was ex-smokers (approximately half of the cases). Such associations between smoking status and thinking styles derived using median splits were not evident (v2(6) = 12.48, p > .05). 4. Discussion The current analyses progress both the evaluation of thinking styles, as conceptualized by CEST, and their application to addictive behavior as illustrated by smoking. Primarily, given the complexity which surrounds the relationship between the rational and experiential components of CEST, the current research advanced approaches to characterizing the independent yet interactive nature of these styles by comparing median split and cluster analysis methods. These approaches were then evaluated through their association with smoking status. The application of cluster analysis to Rational and Experiential scores has offered an alternative to characterizing the relationship between these constructs. The ‘independence’ of Rational and Experiential thinking styles is an axiom of CEST (Epstein, 2003; Handley et al., 2000; Newstead et al., 2004), and Rational and Experiential scores certainly do not share a linear relationship. Therefore, while they should not be described as two extremes of a single continuum, it is perhaps equally unlikely that their relationship is completely random. Rather, the precise association between Rational and Experiential thinking styles is likely to be complex. With no preconception as to the nature of the association, an empirical decision-making tool such as cluster analysis becomes an entirely defensible strategy. The current data supported four clusters that might be termed ‘thinking profiles’. These were low Rational/low Experiential, low Rational/high Experiential, high Rational/low Experiential, and high Rational/high Experiential. While this is acknowledged to
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L.J. Brown, M.J. Bond / Personality and Individual Differences 82 (2015) 76–80 Table 3 Cluster membership according to smoking status. Smokers
Low Rational/Low Experiential Low Rational/High Experiential High Rational/Low Experiential High Rational/High Experiential
Ex-smokers
Non-smokers
n
Column (%)
Row (%)
n
Column (%)
Row (%)
n
Column (%)
Row (%)
2 10 4 6
(9.1) (45.5) (18.2) (27.3)
(6.5) (21.3) (6.7) (8.1)
12 21 15 21
(17.4) (30.4) (21.7) (30.4)
(38.7) (44.7) (25.0) (28.4)
17 16 41 47
(14.0) (13.2) (33.9) (38.8)
(54.8) (34.0) (68.3) (63.5)
mimic the pattern obtained using median splits, the two procedures produce groupings using different statistical strategies. Median splits identify the end points of subgroup distributions, while cluster analysis creates subgroups based on centroids (means). This has the potential to make each resultant cluster representative of a greater number of its members. The obtained results beg the question not only of the pattern of association between rational and experiential thinking per se, but also whether the absolute level of the two styles endorsed by an individual, or the relative magnitude of the two styles when considered together as a profile, is more important to the understanding of behavior or behavior potential. Such an observation remains speculative pending further studies of thinking profiles. When exploring group differences using continuous Rational and Experiential scores according to smoking status there was variation among groups on the Rational scale, but not the Experiential scale. Similarly, when examining patterns of results for smoking status and thinking styles based on median splits, there was little differentiation in terms of the profiles which contain high Experiential preferences. In contrast, thinking style clusters provided greater depth, illustrating significant differences between each smoking status group. That is, if analyzed independently, Experiential preferences were not salient to smoking status, whereas when analyzed in conjunction with Rational preferences to create clusters, they became clearly relevant. In summary, what is clear is that the procedure we have reported is a significant advance on previously used median splits. An important caveat of the current research is that the obtained clusters must not be considered definitive. Cluster analysis is a statistical technique, the results from which are expressly sample-specific. That is, replication of the obtained clusters need not be expected if the procedure were to be repeated with samples of differing composition, or indeed samples of similar composition. Again, however, this is also true of median splits. Given that the parent study from which the reported data were drawn comprised only men (Brown & Bond, 2008), and there is a known association between gender and rational and experiential thinking (Sladek, Phillips, & Bond, 2010), future studies involving women, or indeed both genders, should be conducted. Further, just as the sample comprised only men, the numbers of smokers, ex-smokers and non-smokers available were less than ideal for the current aims. Future research should seek to compare relatively equal numbers across these groups (with larger Ns). Such sample challenges limited the ability to conduct more complex analyses. Not only has the current study been able to identify a novel approach to describing cognitive style profiles but it has been able to further the evidence base by contributing to the modest existing research that has evaluated Rational and Experiential thinking as they may be associated with smoking. In our data, differences involved Rational thinking, with evidence that smokers and ex-smokers report lower scores than non-smokers. This is slightly at odds with previous data for which Experiential thinking has been the differentiating factor, with smokers reporting significantly higher scores than non-smokers (de Stadelhofen et al.,
2004; Marks et al., 2008). Taken together these studies suggest that either higher Rational scores or lower Experiential scores may be indicative of non-smokers, with the explanation of this difference likely to be associated with specific sample characteristics. Notwithstanding this comment, an important contribution of the current study was the inclusion, for the first time, of ex-smokers. If a full understanding of the place of thinking styles in smoking is to be achieved, it is necessary to have an appreciation of the potential role of rational and experiential thinking among individuals who have successfully ceased the behavior. The key findings to emerge from the available data were that ex-smokers were equally represented across the low Rational/high Experiential and high Rational/high Experiential clusters. That is, ex-smokers essentially reflected the thinking style profile of current smokers. It needs to be acknowledged that an understanding of the role of thinking styles in smoking, and indeed potentially other addictive behaviors, is two-fold. The identification of unique profiles of thinking styles associated with smokers, ex-smokers and nonsmokers is only stage one of this understanding. If thinking style profiles are ultimately determined to be related to the decision to smoke and/or the decision to cease, then the use of rational and experiential messages in targeted campaigns for smoking prevention, on the one hand and smoking cessation on the other, may need to be considered. In short, the content and focus of such programs may need to be designed specifically to match the dominant profile of the designated audience (Hine, Marks, & O’Neill, 2009). In exploring future research related to this work, we suggest that a more detailed understanding of the role of rational and experiential thinking in the process of smoking cessation can only be obtained by conducting a study with the specific aim of identifying thinking styles directly linked to the change process. It is possible that this can only be achieved through a longitudinal investigation that records thinking styles concurrently with the act of quitting. It may also be of interest to determine whether successful and unsuccessful cessation attempts are associated with specific thinking style profiles, and indeed whether success is associated with specific cessation techniques for different thinking style profiles. Further, given that age is associated with changes in the relative dominance of rational and experiential thinking (Sladek et al., 2010), either the age at which, or the timeframe over which, successful smoking cessation occurred may also be key data. In summary, this research has presented a novel strategy for measuring the components of CEST, and applied this technique to smoking status. This strategy represents a fruitful approach for the assessment of styles of reasoning and decision-making. It is hoped that it may provide a useful model for applications in other fields both related to, and beyond, addiction.
Conflict of interest None declared.
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