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Volume 39 / Number 1 / 2018

Journal of

Individual Differences Editor-in-Chief Martin Voracek Associate Editors Philip J. Corr Sam Gosling Jürgen Hennig Philipp Y. Herzberg Aljoscha Neubauer Karl-Heinz Renner Willibald Ruch Astrid Schütz Andrzej Sekowski Jutta Stahl


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Journal of

Individual Differences Volume 39/Number 1/2018


Editor-in-Chief

Prof. Martin Voracek, Department of Basic Psychological Research and Research Methods, University of Vienna, Liebiggasse 5, 1010 Vienna, Austria

Associate Editors

Philip J. Corr, UK Sam Gosling, USA Jürgen Hennig, Germany Philipp Y. Herzberg, Germany Aljoscha Neubauer, Austria

Karl-Heinz Renner, Germany Willibald Ruch, Switzerland Astrid Schütz, Germany Andrzej Sekowski, Poland Jutta Stahl, Germany

Editorial Board

Philipp L. Ackerman, USA José Bermudez, Spain Peter Borkenau, Germany John Brebner, Australia Burkhard Brocke, Germany Ian Deary, UK Richard Depue, USA Richard Ebstein, Israel Aiden P. Gregg, UK Hartmut Häcker, Germany Willem B. Hofstee, The Netherlands Klaus Kubinger, Austria

Bernd Marcus, Germany Robert R. McCrae, USA Carolyn C. Morf, Switzerland Pierre Mormede, France Kurt Pawlik, Germany Robert Plomin, UK Rainer Riemann, Germany Kurt Stapf, Germany Bob Stelmack, Canada Gerhard Stemmler, Germany Jan Strelau, Poland

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Journal of Individual Differences (2018), 39(1)

Ó 2018 Hogrefe Publishing


Contents Original Articles

Ó 2018 Hogrefe Publishing

The Self-Access Form: Development and Validation in the Context of Personality Functioning and Health Markus Quirin and Julius Kuhl

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UV Radiation Associates With State Income Through Complex Cognitive Ability in the USA Federico R. León and Andrés Burga-León

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Differences in the Way to Conceive Happiness Relate to Different Reactions to Negative Events Giulia Fuochi, Chiara A. Veneziani, and Alberto Voci

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Nonlinear Effects of Cognitive Ability on Economic Productivity: A Country-Level Analysis Thomas R. Coyle, Heiner Rindermann, Dale Hancock, and Jacob Freeman

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Adults’ Sex Difference in a Dynamic Mental Rotation Task: Validating Infant Results Martin Heil, Markus Krüger, Horst Krist, Scott P. Johnson, and David S. Moore

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CHC Model According to Weiss: Evidence From the WAIS-IV Administration to Italian Adults and Elders Lina Pezzuti, Margherita Lang, Serena Rossetti, and Clara Michelotti

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Journal of Individual Differences (2018), 39(1)


Original Article

The Self-Access Form Development and Validation in the Context of Personality Functioning and Health Markus Quirin1,2 and Julius Kuhl3 1

Department of Psychology, Stanford University, CA, USA

2

Department of Psychiatry & Psychotherapy, Philipps University Marburg, Germany

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Department of Psychology, Individual Differences and Personality Research, Osnabrück University, Germany

Abstract: Different lines of research suggest that individuals differ in accessing self-referential information, that is, to know who they are, what they think, want, need, or feel, and that this construct is positively associated with emotion regulation, adaptive functioning, well-being, and meaning in life. We developed a brief scale of five items, the Self-Access Form (SAF) and conducted four studies to approve its validity with respect to markers of adaptive personality functioning and health. Study 1 shows a clear, unidimensional factor structure for the SAF. Selfaccess correlates positively with adaptive self- and emotion regulation, as well as with psychological and physical health, but does not correlate with private self-consciousness (Study 2). Additionally, self-access is positively related to self-complexity and self-integration as two markers of adaptive self-development (Study 3). It is also inversely related to self-infiltration, that is, the misconception of other individuals’ expectations as own goals (Study 4). We conclude that self-access can validly be measured by a brief scale and positively relates to adaptive functioning and health. Keywords: self-access, personality systems interactions theory, emotion regulation, self-integration, health

The aphorism Know Thyself inscribed over the entrance of the oracle of Delphi alludes to the ancient Greek’s conception that having access to one’s inner life is an important, adaptive human virtue. On the flip side, it alludes to the fact that having access to needs, goals, values, or emotions can also be difficult. This issue has not lost appeal up to the present day as people incessantly ask questions about themselves, as philosophers continue the scientific debate, and as tons of self-help books highlight the importance of knowing oneself for making adequate life decisions and for leading a more meaningful and satisfying life. In fact, research has demonstrated that accessibility to one’s self-aspects is important for self-congruent selfregulation as it can help individuals to bring their actions in line with their needs, goals, and attitudes (e.g., Ryan & Deci, 2000). In the end, self-congruent self-regulation is associated with a number of health-related aspects (Ryan & Deci, 2000) such as emotion regulation (Koole & Jostmann, 2004; Kuhl & Baumann, 2000), meaning (Schlegel, Hicks, Arndt, & King, 2009), or well-being (Quirin & Kuhl, 2008). Despite the importance of possessing accurate access to one’s personality, strivings, or emotions, hardly any Ó 2018 Hogrefe Publishing

questionnaire exists that directly assesses self-access. This is the case although it is obvious, despite some limitations, that individuals are principally able to report on their inner life. Because they are, psychologists have been using self-report questionnaires of personality throughout several decades. Following this methodology, the present research aims at validating an economic, unidimensional self-report scale for the assessment of accessibility to the self, the SelfAccess Form (SAF). We predominantly base the present research on Personality Systems Interactions (PSI) Theory (Kuhl, 2000, 2001), which conceptualizes the self as a complex knowledge structure comprising personal traits, needs, emotions, and values, integrating positive and negative self-representations, operating largely at an implicit level, and facilitating intuitive, efficient emotion regulation. As we argue on the basis of PSI theory, having access to this structure goes hand in hand with the development of a differentiated and integrated self, which includes the ability to differentiate between personal goals and others’ expectations, and is positively related to adaptive functioning and mental health. In what follows, we review constructs that may resemble self-access but also outline in which way they are different. Next, we describe a model of the self as Journal of Individual Differences (2018), 39(1), 1–17 https://doi.org/10.1027/1614-0001/a000244


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formulated in PSI theory that describes the functional mechanisms underlying the relationship between selfaccess and health. Thereafter, we report on existing research on the relationship between self-access and health-related variables. Last but not least, we introduce the SAF and four studies supporting its reliability, as well as its validity in the context of emotion regulation, adaptive functioning, and health.

Self-Access Individuals are generally motivated to strive to know who they are, what they want, need, and feel (e.g., Asneel & Lievens, 2007; Gosling, Rentfrow, & Swann, 2003; Trope & Brickman, 1975). Despite individual differences in introspection or self-serving biases, they are generally able to report on these self-aspects such as on their personality, emotions, or needs, and have more than others privileged access to their own psychological world. In fact, most personality researchers over the last decades have been using self-report measures to coax information about individuals’ personality or emotions. Access to self-referential information can be gathered via a number of ways (e.g., Back & Vazire, 2012; Wilson & Dunn, 2004). For example, individuals may directly sense or monitor their thoughts, needs, or emotions via introspection and interoception (Craig, 2009). Alternatively, they might observe their behavior in order to draw conclusions about their motives and personality (Bem, 1972). Individuals can engage in extensive self-reflection to interpret their received impressions about themselves. Not least, other individuals’ appraisal of one’s behavior can be used as a source of information about the self (Cooley, 1902; Srivastava, 2012). No matter which way individuals prefer to gather self-access, we assume that even those having difficulties in doing so can principally become aware of it and accordingly be able to report on it (as, e.g., individuals sometimes are asked to describe themselves or to tell how they feel). However, the existence of the ancient Greeks’ selfknowledge motto mentioned in the beginning implies that it cannot be taken for granted that individuals possess outright access to their self, that is, to instant knowledge about personality, personal needs, wishes, thoughts, goals, emotions, or attitudes. In fact, a number of related motivational factors such as repression, social desirability, and self-enhancement can render self-access difficult. Moreover, cognitive factors such as natural constraints of autobiographical memory encoding and retrieval, introspection, or self-observation set relative bounds to exhaustive self-access (e.g., Chin, Mrazek, & Schooler, 2012; Hofree & Winkielman, 2012; Paulhus & Buckels, 2012; Taylor Journal of Individual Differences (2018), 39(1), 1–17

M. Quirin & J. Kuhl, Self-Access and Health

& Brown, 1988; Wilson & Dunn, 2004). These factors might lead individuals to experience that they do not really have accessibility to self-aspects, for example, when they are unable to identify the causes of their emotions or to spontaneously describe themselves as a person. As such, self-access or deficiencies thereof should be assessable via questionnaire. There is evidence from related research suggesting that self-access may be considered a personality difference. Specifically, the phenomenon of alexithymia, as frequently observed in patients with psychosomatic symptoms, refers to deficiencies in recognizing, describing, and communicating one’s emotions (Taylor & Bagby, 2004; see also Samur et al., 2013) and can be assumed to be inversely related to self-access. In fact, according to our conceptualization of self-access, the alexithymia component of impaired emotion recognition constitutes one aspect of self-access. However, in addition to access to emotions, the notion of self-access includes other types of self-referential information as well, such as personal preferences, needs, goals, values, and dispositions. Another construct that appears to be related to self-access at first sight is self-consciousness (Fenigstein, Scheier, & Buss, 1975; or “self-awareness”: Duval & Wicklund, 1972), that is, the degree to which individuals engage in introspective activity and mental preoccupation with themselves. Individuals with high levels of self-consciousness are attentive to how they appear and present themselves to others and tend to produce imaginations and fantasies featuring themselves. It is particularly the latter tendency that carries the risk that self-representations might drift apart from representations of the actual self. In fact, while it has long been assumed that high levels of self-consciousness lead to higher levels of accurate self-access (e.g., Carver & Scheier, 1981; Gibbons, 1983; Kihlstrom & Cantor, 1984), there is little or no support for this assumption since subjective perceptions or interpretations of one’s mental processes or behavior can be strongly biased (Briñol, Petty, & Wheeler, 2006; Hofmann, Gawronski, Gschwendner, Le, & Schmitt, 2005; Petty, Tormala, Briñol, & Jarvis, 2006). Similarly, there is much debate and contradictory evidence about whether self-awareness buffers against (e.g., Suls & Fletcher, 1985) or whether it enhances stress and negative affect (Ingram, 1990).

Self-Access, Adaptive Functioning, and Health Having self-access in critical situations is crucial for efficient downregulation of negative affect as well as for well-being and health in the long run (Kuhl, 2000, 2001; Linville, 1987; Showers & Kling, 1996). Specifically, if an Ó 2018 Hogrefe Publishing


M. Quirin & J. Kuhl, Self-Access and Health

individual has access to the self (which integrates negative and positive experiences) encountering or remembering a yet non-integrated unpleasant experience immediately activates positive representations, which facilitates the downregulation of negative affect. At the same time, this enables the structural integration of the negative experience in the self (Kuhl, 2000, 2001; Quirin, Kent, Boksem, & Tops, 2015). Consequently, the better individuals are able to access emotions, needs, or representations of personal experiences, the better they should be able to modulate them (e.g., Brosschot, Gerin, & Thayer, 2006; Kuhl, 2000). For example, much research has shown that awareness of one’s emotions and the ability to appropriately describe and communicate them is associated with emotion regulation and health (e.g., Lane, 2008). Likewise, self-access operationalized as the congruency between self-reported and indirectly measured motives predicts well-being, life satisfaction, and health (e.g., Baumann, Kaschel, & Kuhl, 2005; Kehr, 2004; Thrash, Elliot, & Schultheiss, 2007). It has also been demonstrated that momentary access to self-representations facilitates intuitive emotion regulation (Koole & Jostmann, 2004; Quirin, Bode, & Kuhl, 2011). Across the lifespan, the ability to access selfrepresentations should continuously lead to changes in structural aspects of the self. First and foremost, when individuals know themselves they can develop a differentiated self and accordingly describe themselves in a differentiated and complex rather than in a simple and parsimonious manner (Linville, 1985). Likewise, self-access should involve emotional self-integration, a tendency to integrate more and more conflicting (positive and negative) experiences and self-aspects rather than to repress and organize them in separate compartments (Showers, 1992a, 1992b, 1995). This emotional potential should facilitate coping with difficult situations encountered in the future (e.g., Brandstädter, Rothermund, & Schmitz, 1998; Kuhl, 2000). Notably, previous research has demonstrated the benefits for mental health of both self-complexity (Linville, 1987; Rothermund & Meiniger, 2004) and self-integration (Showers & Kling, 1996), which is compatible with the notion that self-access should be positively related to health.

The Self in Personality Systems Interactions (PSI) Theory A theory that might have the potential to explain some functional mechanisms underlying the relationships of self-access with adaptive functioning and health is PSI theory (Kuhl, 2000, 2001). This theory conceptualizes the self as an extended parallel-distributed processing network (PDP; Rumelhart, McClelland, & The PDP Research Group, 1986) comprising integrated representations of Ó 2018 Hogrefe Publishing

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personal emotions, needs, attitudes, values, identities, and other self-relevant information. Access to the self-system facilitates effective and flexible regulation of emotion and behavior that is congruent with the individual’s needs, values, and goals (e.g., Koole & Jostmann, 2004; Quirin et al., 2011, for empirical evidence). The self-system resembles an associative network model in some respects, for instance, because it consists of an extended network of nodes and connections (Greenwald & Banaji, 1989). However, unlike simple associative networks, the selfsystem comprises higher executive functions (Kuhl, 2000), as described in the following paragraph. First, accessibility to the self-system enables the processing of remote associations that facilitate creative problem solving (Isen, Daubman, & Nowicki, 1987; Isen, Johnson, Mertz, & Robinson, 1985; Mednick, 1962), which counteracts the adoption of a tunnel vision during emotionally arousing situations and is thus an integral feature of efficient coping (Kuhl, 2000). Second, the self-system allows individuals to maintain positive affect in the face of negative feedback or experiences (Koole & Jostmann, 2004; Quirin et al., 2012), for example, by putting painful experiences in a broader perspective (Linville, 1985; Simon, Greenberg, & Brehm, 1995). This characteristic, which is not unrelated to the processing of remote associates, can be derived from the multiple constraint satisfaction nature of PDP. Specifically and in contrast to the dichotomous nature of analytical thinking (where a proposition is either true or false or a self-aspect is either good or bad), parallel processing of multiple experiential contents increases the likelihood that the impact of a single aversive event can be ameliorated as it makes contact with a variety of personal experiences that suggest ways of coping with it (e.g., by controlling, giving meaning to, or learning from it). As a consequence, a PDP network has a higher potential for integrating seemingly contradictory contents or states and thus for effective and sustainable downregulation of negative affect in terms of an integrative form of coping.

Present Research and Hypotheses Our goal in the present work is to develop a measure of individual differences of self-access, the SAF. We validate it primarily in the context of adaptive personality functioning and well-being. Study 1 provides data on internal consistency and factor pattern of the SAF. We started out in a pilot study to develop items that grasp different aspects of self-access such as present or absent access to personal needs, wishes, and emotions, as well as the ability to describe oneself as a person or impairments thereof. Studies 2–4 aim to validate the SAF with a particular focus on the function of the self to regulate negative affect.

Journal of Individual Differences (2018), 39(1), 1–17


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M. Quirin & J. Kuhl, Self-Access and Health

Specifically, in Study 2, we investigate construct validity by relating a number of diverse psychological constructs to self-access, such as private self-consciousness, alexithymia, and constructs related to mental or physical health. Study 3 examines the hypothesis that self-access is positively related to self-growth. Specifically, a tendency to access and confront with personal needs, emotions, and attitudes, especially socially undesired ones, should foster the development of a differentiated (complex) and integrated self (e.g., Kuhl, 2000). Therefore, a trait measure of self-access should be related to self-complexity in terms of a high number or interconnectedness of self-aspects (Linville, 1987) or to self-integration in terms of the integration of positive and negative self-aspects (Showers, 1992a, 1992b). Both aspects will be measured by a card sorting test (Linville, 1985). Finally, Study 4 further examines validity of the test by investigating the relation between self-access and self-infiltration, which describes the tendency to mistake alien goals as self-referential goals on the basis of an experimental paradigm (e.g., Kuhl & Kazén, 1994). We expect that self-access is inversely related to this objective measure of reduced self-access.

Study 1 Method We composed the current 5-item form by starting with six items, removing one item and later exchanging one more item by another one. We used the following instructions: We are interested in how easy or difficult it is for individuals to describe or explain various aspects of themselves in different situations. Please report about the extent to which you agree or disagree with the following statements. Rating alternatives are (0) doesn’t fit at all, (1) fits somewhat, (2) fits mostly, and (3) fits completely. The final version of the SAF was applied to 815 participants (552 female, 315 nonstudent, Mage = 29.1 years, SD = 11.9).

Results and Discussion We used a generalized least squares principal axis factor analysis to investigate the factor structure of the SAF using SPSS version 23. Because the SAF produces ordinal rather than metric data we used polychoric rather than productmoment correlations between items as an input matrix (Lee, Zhang, & Edwards, 2012),1 which we computed by the SPSS program Polymat-C (Lorenzo-Seva & Ferrando,

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2015). We conducted analyses separately for female and male participants to cross-validate the results. Using the Kaiser criterion of eigenvalues greater than 1 for factor extraction, either analysis resulted in the extraction of one factor. Specifically, in the female sample this factor explained 57.7% of the total variance, whereas it explained 59.4% in the male sample. Factor loadings are listed in Table 1. Table 1 also shows the results of analyses of internal consistency as well as item means and standard deviations. Cronbach’s α were .78 for women and .74 for men. Corrected item-total correlations varied between .65 and .77. Item means ranged from 1.49 to 2.25, indicating a range of low to moderate item applicability. Standard deviations ranged from 0.77 to 0.89, indicating broad usage of the response alternatives. The mean of the total scale score (after recoding inverse item 4: M = 1.91; SD = 0.61) lies above the theoretical midpoint of the scale (1.5), suggesting that individuals in general tend to report high rather than low self-access. In sum, the data suggest that the SAF constitutes a reliable, unidimensional measure of self-access.

Study 2 In Study 2, we took an initial step toward establishing the construct validity of the SAF. Specifically, we focused on relationships with trait measures of affectivity, affect, and self-regulation, as well as mental and physical health. In addition, we investigated correlations with private selfconsciousness and alexithymia as two potentially related constructs. It has been found that self-consciousness does not necessarily imply self-access (Briñol et al., 2006; Hofmann et al., 2005; Petty et al., 2006). This is probably because deliberate reflection on the self carries the risk that selfrepresentations drift apart from the actual self. Therefore, we predicted that self-consciousness and self-access show a weak or moderate but not a strong relationship. Because alexithymia is considered an important component of (reduced) self-access, we hypothesized to find an inverse relationship as an indicator of convergent validity. Whereas alexithymia relates to impairments in recognizing one’s emotions (Taylor & Bagby, 2004), self-access refers to the person’s ability to access a broad range of self-referential information including personal preferences, needs, goals, values, and personality dispositions. Thus, we expected that self-access and alexithymia would be strongly correlated, but would not constitute redundant constructs.

We thank an anonymous reviewer for the suggestion to use the polychoric correlation matrix for factor analysis.

Journal of Individual Differences (2018), 39(1), 1–17

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M. Quirin & J. Kuhl, Self-Access and Health

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Table 1. Means, standard deviations, corrected item-total correlations (CITC), and factor loadings of the Self-Access Form (SAF) M (SD) Item 1. When I feel cranky, I sometimes don’t know why. [Wenn ich launisch bin, kommt es vor, dass ich gar nicht so recht weiß weshalb.] 2. Sometimes I am not sure why I behave like this or that. [Ich bin mir manchmal nicht im Klaren darüber, warum ich mich so oder so verhalte.] 3. Whenever I am asked to describe myself as a person I notice that I don’t actually know myself well. [Dass ich mich eigentlich gar nicht so gut kenne, fällt mir auf, wenn ich mich als Person beschreiben soll.] 4. Whenever I feel tense I typically know the reason. [Wenn ich angespannt bin, kenne ich meist den Grund dafür.] 5. When I recover from a bad mood, I sometimes don’t know any more what triggered the mood in the first place. [Wenn ich aus einer schlechten Stimmung wieder herauskomme, weiß ich manchmal nicht mehr, was eigentlich der Auslöser war.]

CITC

LOAD

Women

Men

Women

Men

Women

Men

1.49 (0.89)

1.88 (0.84)

.72

.65

.84

.93

1.71 (0.81)

1.95 (0.83)

.70

.65

.77

.78

2.04 (0.87)

2.21 (0.83)

.77

.72

.67

.76

2.12 (0.73)

2.24 (0.77)

.77

.76

.61

.54

1.86 (0.79)

2.02 (0.80)

.75

.70

.59

.36

Note. Original German items are included in square brackets.

Because neuroticism is associated with a high frequency of negative emotions, we expected that self-access would be negatively related to neuroticism. We also explored the relationship between self-access and extraversion. Because the intuitive self has a positivity bias (Greenwald & Farnham, 2000; Koole, Dijksterhuis, & van Knippenberg, 2001), and because extraversion is typically related to sensitivity to positive emotions (e.g., Larsen & Ketelaar, 1991), we hypothesized to find a positive relationship between self-access and extraversion. Moreover, we hypothesized that self-access is related to efficient emotion regulation abilities or strategies. Selfrelaxation refers to the degree to which individuals are able to control (reduce) ruminative thoughts or worries in order to maintain agency (Kuhl, 1994). By contrast, selfmotivation refers to the degree to which individuals are able to start pending decisions or tasks rather than to procrastinate (Kuhl, 1994). Whereas the former construct is theoretically associated with the ability to downregulate negative affect, the latter construct is theoretically associated with the ability to upregulate positive affect to start difficult tasks (Kuhl, 2000). Because the two types of action-oriented emotion regulation are considered to be based on self-access (Kuhl, 2000; for evidence, see Koole & Jostmann, 2004; Kazén, Baumann, & Kuhl, 2003), selfaccess should be positively related to both self-relaxation and self-motivation. We also investigated the relationship between self-access and individual differences in reappraisal and suppression tendencies (Gross & John, 2003). Reappraisal refers to the degree to which individuals tend to positively reinterpret upcoming or already encountered negative experiences. We hypothesized a positive relationship between Ó 2018 Hogrefe Publishing

self-access and reappraisal tendencies because self-access is considered a non-deliberative process contributing to effective reappraisal of events, that is, connecting negative with positive aspects of a situation (see Williams, Bargh, Nocera, & Gray, 2009, on implicit reappraisal processes). By contrast, suppression refers to the deliberate attempt to inhibit emotional reactions and expressions while the emotional process is in full swing. Suppression is conceived of as a less than optimal emotion regulation mechanism because emotional and physiological arousal pertains to be present and cannot be sustainably attenuated (Gross & Levenson, 1993, 1997). We predicted a negative relationship between self-access and suppression because selfaccess is associated with integrative processes which require that negative experiences are permitted and attended to rather than suppressed (Wegner, 1994). We also predicted that self-access would be positively associated with self-determination and self-esteem. Selfdetermination refers to the extent to which an individual experiences that his/her goals are autonomously chosen and actions are taken based on his/her intrinsic preferences and not based on any kind of external pressure. Because personal preferences and needs are stored and processed by the intuitive self, access to this system can be considered to be a prerequisite of self-determination and should therefore be positively related to this construct. Likewise, because self-representations are typically positively biased in healthy individuals (Taylor & Brown, 1988), access to the self should also provide high levels of self-esteem. This is why we expect a positive relationship between the two constructs. Finally, we predicted that self-access would be related to transient levels of well-being, life satisfaction, low stress, Journal of Individual Differences (2018), 39(1), 1–17


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and physical health. Because self-access is assumed to facilitate downregulation of negative affect (and vice versa, cf. Kuhl, 2000) and because these variables are inherently connected to the absence or presence of negative affect, self-access should be positively related to satisfaction with life and well-being as well as inversely related to perceived stress or physical complaints. By contrast, because the literature is inconsistent with respect to the relationship between self-consciousness and well-being, with some studies finding a positive relationship (e.g., Mullen & Suls, 1982; Suls & Fletcher, 1985; cf. Frone & McFarlin, 1989) but others showing a negative relationship (for a review, see Ingram, 1990), we did not expect significant relationships.

Method Samples and Procedure Sixty-three students (43 women; Mage = 24.3, SD = 4.3) at the University of Osnabrück participated in the study for 10€. To investigate construct validity of the SAF, we administered the measure along with questionnaires for the assessment of several relevant personality factors, emotion regulation tendencies, perceived stress, as well as mental and physical health. Investigation of the relationship of self-access with reappraisal and suppression (see below) was based on an additional sample of 37 students from the same university (28 women, 9 men; Mage = 23.3, SD = 4.7). Measures Private self-consciousness was measured by the samenamed scale by Fenigstein et al. (1975; German version by Filipp, 1989). Alexithymia was measured by the TorontoAlexithymia Scale (Taylor, Bagby, & Parker, 1992; Kupfer, Brosig, & Brähler, 2001, for a German version). Neuroticism and extraversion were assessed by the respective subscales of the NEO Five-Factor Inventory (Costa & McCrae, 1992; see Borkenau & Ostendorf, 1993, for a German version). Self-relaxation and self-motivation were measured via the Action Control Scale (Kuhl, 1994), using the threat-related and decision-related action orientation scales, respectively. Reappraisal and suppression were measured as two further types of emotion regulation using the Emotion Regulation Questionnaire (Gross & John, 2003; Abler & Kessler, 2009, for the German version). Self-determination was measured by the respective subscale from the Volitional Components Inventory (Kuhl & Fuhrmann, 1998), whereas self-esteem was measured by the Rosenberg Self-Esteem Scale (Rosenberg, 1965; German version: Ferring & Filipp, 1996). Satisfaction with life was measured by the Satisfaction with Life Scale (Diener, Emmons, Larsen, & Griffin, 1985). Well-being was assessed by the WHO well-being Journal of Individual Differences (2018), 39(1), 1–17

M. Quirin & J. Kuhl, Self-Access and Health

scale (Bonsignore, Barkow, Jessen, & Heun, 2001; Heun, Burkhard, Maier, & Bech, 1999). Items of this scale tap into the absence or presence of chronic levels of dysphoric mood that has been experienced during the last two weeks. Global levels of chronic stress were measured by the Perceived Stress Scale (Cohen, Kamarck, & Mermelstein, 1983), the items of which focus on stressful situations that have been experienced over the last month. Finally, we assessed physical complaints via the somatization subscale of the Hopkins Symptom Check List (Derogatis, Lipman, Rickels, Uhlenhuth, & Covi, 1974). This scale asks about experiencing 12 common physical symptoms during the last seven days such as headache, back pain, dizziness, and nausea. Because this scale refers to complaints during the last week, we additionally asked one question about participants’ general physical health status during the last 4 weeks.

Results and Discussion Table 2 presents Pearson correlations between SAF and other questionnaire scores. In order to provide data on incremental validity of the scale, we additionally report correlations of private self-consciousness with the respective questionnaires, as well as partial correlations between SAF and validating variables controlled for private selfconsciousness. Self-access was only marginally correlated with self-consciousness, r(61) = .23, p < .10, which corroborates our assumption that the two constructs are distinct. In contrast, the SAF was strongly correlated with the Toronto-Alexithymia Scale, r(61) = .57, p < .001, suggesting high concordant validity of the test. As argued, despite strong overlap between the two concepts, we suppose that self-access is a broader concept that includes access to self-representations other than emotions (e.g., motives, values, self-concepts; cf. Study 4). Further, because neuroticism is commonly related to sensitivity toward negative affect (Gupta & Nagpal, 1978; Larsen & Ketelaar, 1991; Rusting & Larsen, 1998; for theoretical notions, see Gray, 1987), the inverse relationship between SAF and neuroticism, r(61) = .55, p < .001, is congruent to the notion that self-access attenuates negative affect. Moreover, SAF scores were associated with self-relaxation, r(61) = .54, p < .001, and with self-motivation, r(61) = .39, p < .01, which is consistent with the hypothesis that self-access facilitates self-regulation of affect (Koole & Jostmann, 2004). In addition, the finding of a positive relationship between SAF and self-motivation supports the notion that self-access is necessary for making and enacting decisions. As expected, SAF was also related to reappraisal, r(35) = .46, p < .01, and inversely related to suppression, r(35) = .47, p < .01, which suggests that self-access is associated with efficient and adaptive coping Ó 2018 Hogrefe Publishing


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Table 2. Study 2: Pearson correlations of the Self-Access Form (SAF) as compared to the Private Self-Consciousness Scale as well as means and standard deviations of all variables r SAF Private self-consciousness

Self-consciousness

M

SD

3.74

0.48

.22 ( )

Alexithymia

.57*** ( .61***)

.14

1.81

0.68

Neuroticism

.55*** ( .60***)

.11

2.72

0.66

Extraversion

.27* (.37**)

.01

3.42

0.59

Rumination

.54*** ( .50***)

.22

4.89

3.46 3.40

Procrastination

.39** ( .34**)

.21

6.54

Reappraisal

.46** ( )

4.70

0.84

Suppression

.47** ( )

2.87

1.09

Self-determination

.50*** (.46***)

.29

8.11

2.33

Self-esteem

.55*** (.52***)

.14

2.31

0.49

Satisfaction with life

.51*** (.44***)

.12

4.07

1.07

Well-being

.29* (.35**)

.11

53.21

21.30 0.38

Perceived stress

.38** ( .34**)

.05

2.91

General health

.48*** (.57***)

.02

7.25

1.89

Physical complaints

.29* ( .33**)

.06

0.53

0.44

Notes. N = 63. SAF = Self-Access Form. Coefficients in parentheses (2nd column) refer to semipartial correlations controlling for private self-consciousness (df = N 2); correlations with reappraisal and suppression were based on a different sample (N = 37, see text). *p < .05; **p < .01; ***p < .001 (all twotailed).

(Gross & John, 2003). Moreover, self-access was positively related to self-determination, r(61) = .50, p < .001, in line with the idea that self-access promotes self-integrated goal pursuit (Deci & Ryan, 2000). The association between self-access and self-esteem, r(61) = .55, p < .001, fits with the notion that intuitive self-representations have a positivity bias (e.g., Greenwald & Farnham, 2000; Koole et al., 2001). Likewise, relationships with satisfaction with life, r(61) = .51, p < .001, wellbeing, r(61) = .29, p < .05, and, inversely, with perceived stress, r(61) = .38, p < .01, again confirm the affectregulatory role of self-access. Relationships with a general health statement, r(61) = .48, p < .001, and physical symptoms, r(61) = .29, p < .05, suggest that self-access is potentially relevant for physical health (see also Baumann, Kaschel, et al., 2005; McClelland, Koestner, & Weinberger, 1989). The size and significance of the correlations practically did not change after controlling these relationships for private self-consciousness (coefficients presented in Table 2). In sum, Study 2 observed all the predicted relationships between self-access and emotion regulation, personality, and indicators of psychological and physical health. Moreover, in support of the discriminant validity of the construct, self-access was only weakly associated with private self-consciousness, which itself did not show significant relationships with the variables related to self-access. The finding that self-consciousness is not significantly related to affectivity and health variables is in line with the inconsistent literature on this issue (Wilson & Dunn, 2004). Ó 2018 Hogrefe Publishing

Study 3 Study 3 investigated the empirical relationship of selfaccess with two structural features of the self, the degree of self-complexity and self-integration (vs. self-compartmentalization), which were indirectly measured by a selfaspects classification task. The present study thus touches upon implicit and partly non-explicable aspects of selfaccess. We hypothesized that self-access but not (low) alexithymia is positively associated with self-complexity and negatively associated with self-compartmentalization. Additionally, we also assessed alexithymia. The concept of alexithymia does not relate to structural aspects of the self and refers to accessibility of emotions exclusively rather than of self-aspects such as personal goals or needs. Therefore, we expected to find no relations between alexithymia and self-complexity.

Method Sample, Procedure, and Measures Forty female and 17 male psychology students (Mage = 24.2, SD = 4.5) from the University of Osnabrück participated in the study in exchange for 8€. Upon arrival in the laboratory, participants filled out the SAF, the TorontoAlexithymia Scale (Taylor, Parker, Michael Bagby, & Acklin, 1992), and completed a computerized version of the Card Sorting Test (Kazén & Halbruegge, 2002). In this version, a list of 20 positive and 20 negative trait attributes Journal of Individual Differences (2018), 39(1), 1–17


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is provided. To create self-aspects, participants were instructed to open blank windows for each domain and transfer attributes from the list to these windows. Moreover, they were asked to use as many trait adjectives as they liked and to rearrange them as often as they preferred to describe their self-aspects. Participants did not need to use every trait and can use one and the same trait to describe different self-domains. For the exact instructions, see Linville (1987). The computerized version of this test calculated the number of self-aspects described by the individual and an additional index of self-complexity, the so-called H statistic. The H statistic is a measure of dispersion derived from information theory (Attneave, 1959; Scott, 1969; see also Linville, 1987, for computation). High values of the H statistic indicate high self-complexity. Additionally, as an index of self-compartmentalization, the computerized version of the card sorting test also calculated Cramér’s V coefficient for each individual (e.g., Showers & Kling, 1996). Here, the V coefficient provides information about the distribution of traits across a 2 (positive, negative)  k (numbers of selfaspects) contingency table for each individual. The coefficient varies between 0 and 1, with a low coefficient indicating self-integration (integrating positive and negative attributes within self-domains) and a high coefficient indicating self-compartmentalization into affectively rather homogeneous self-domains in which most or all attributes are either positive or negative. Participants accomplished the card sorting task within 10–30 min.

Results and Discussion The mean number of self-aspects was 6.25 (SD = 3.07) while the means for the H statistic and the V coefficient were 3.23 (SD = .96) and .46 (SD = .23), respectively. To examine the relationships of self-access with self-complexity and selfcompartmentalization, we calculated Pearson correlations between self-access score and the number of self-aspects, H statistic, as well as the V coefficient. Consistent with our hypotheses, self-access was positively correlated with selfcomplexity as indicated by either the number of self-aspects, r = .29, p < .05, or the H statistic, r = .28, p < .05. Moreover and also in line with our hypotheses, self-access was inversely correlated with self-compartmentalization, r = .34, p < .01. By contrast, alexithymia was uncorrelated with both self-complexity, r = .15, ns, and self-compartmentalization, r = .20, ns. Although the present data do not allow causal interpretations, they are in accordance with the notion that selfaccess fosters the development of a well-differentiated and integrated self. By contrast, alexithymia was uncorrelated with both measures of self-complexity. This supports our reasoning that self-access is a broader construct than Journal of Individual Differences (2018), 39(1), 1–17

M. Quirin & J. Kuhl, Self-Access and Health

alexithymia, in that self-access has links with a greater number of self-related variables. Because self-complexity and self-integration were measured indirectly, the present finding suggests that the SAF, although a self-report measure, is able to tap into implicit features of the self.

Study 4 Study 4 was designed to validate self-access with a measure of reduced access to implicit self-representations. Specifically, we investigated the relationship between self-access and self-infiltration, which refers to a tendency to unconsciously introject other individuals’ goals, that is, to misattribute imposed goals to self-choice (Kuhl & Kazén, 1994). Chronic introjection of alien goals as a form of reduced self-determination has been found to be associated with reduced well-being and health (e.g., Deci & Ryan, 2000). Previous research has demonstrated that under certain specified conditions the process of introjecting a goal can result in false attributions of agency. In this case individuals, after having made some choices among several goals or activities and being assigned some other activities, mistakenly recall some activities as self-chosen that were in fact assigned or recommended by another person (Baumann & Kuhl, 2003; Kuhl & Kazén, 1994). This false attribution amounts to a dissociation between conscious representation of agency and actual, though implicit, agency. To the extent that this self-infiltration effect can be regarded as a measure of reduced implicit self-access, individual differences in self-access should be negatively correlated with the number of false self-ascriptions of assigned activities in the selfinfiltration task.

Method Sample and Procedure Thirty-three female and 15 male students (Mage = 22.7, SD = 3.7) studying psychology at the University of Osnabrück participated in exchange for 8€. Participants were tested individually in small booths. They first filled in the SAF, the Private Self-Consciousness Scale, and the Toronto-Alexithymia Scale and then performed the selfdiscrimination task (Kuhl & Kazén, 1994). This task attempts to measure self-infiltration by the number of imposed tasks falsely misremembered as self-selected. It has been successfully applied in a number of studies linking self-infiltration to impaired emotion regulation (Baumann & Kuhl, 2003; Kazén et al., 2003; Kuhl & Kazén, 1994), increased cortisol (Quirin, Koole, Baumann, Kazén, & Kuhl, 2009), or left hemisphere processing (Baumann, Kuhl, & Kazén, 2005). Ó 2018 Hogrefe Publishing


M. Quirin & J. Kuhl, Self-Access and Health

As in previous studies, participants were informed that this procedure constitutes a simulation of an office working day. Participants received a set of 36 small routine tasks that are typically part of the work day of an office secretary and were asked to select 12 tasks from the list for later enactment. Examples of the tasks that participants could select were writing labels on files, sharpening pencils, renewing the supply of paper clips, and looking up telephone numbers (in the German version applied, each item consists of two words, a verb and an object). Following the self-selection phase of the self-discrimination task, participants were asked to carry out some short filler tasks and then relax until the experimenter returned. After 5 min, the experimenter reentered the room and handed out the same list of routine tasks used earlier one more time. This time, however, 12 different tasks were marked and participants were asked to acknowledge them, because their “supervisor” (experimenter) wanted them to carry out these tasks as well. After another filler task of 10 min, memory for the source of the office tasks was tested by sequentially presenting all 36 tasks twice to participants in random order. In the self-classification task, participants had to decide whether or not each presented item was originally self-selected. In the other-classification task, participants had to decide whether or not the presented item was assigned to them by their supervisor. The order of the classification tasks was counterbalanced between participants. Measures of Memory Performance Participants’ rates of false self-ascriptions of assigned tasks were calculated as the percentage of activities assigned by the experimenter that the participant mistook as selfchosen. To control for general memory deficits, we subtracted the rates of false self-ascriptions of remaining activities that were neither self-selected nor assigned from the rate of false self-ascriptions of tasks assigned by the experimenter, following the usual procedure reported in the literature (Baumann & Kuhl, 2003; Kazén et al., 2003; Kuhl & Kazén, 1994). For the sake of brevity, we refer to the corrected rates of false self-ascriptions of assigned items simply as “false self-ascriptions.” A second way in which we controlled for global memory deficits processes was to consider participants’ rates of false other-ascriptions, that is, activities originally self-selected by the participant that he or she falsely classified as externally assigned. We corrected participants’ rates of false other-ascriptions of originally self-selected tasks for the rate of false other-ascriptions of remaining activities that were neither self-selected nor assigned by subtracting the latter from the former values. For the sake of brevity, we refer to corrected rates of false other-ascriptions of assigned items simply as “false other-ascriptions.” A significant Ó 2018 Hogrefe Publishing

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relationship between self-access and false self-ascriptions rather than false other-ascriptions would support the assumption that low self-access is specifically associated with introjection as opposed to more global self-other discrimination impairments associated with source monitoring (cf. Johnson, 1988).

Results and Discussion In line with our hypothesis, self-access was significantly and negatively related to the rate of false self-ascriptions, r(51) = .39, p < .01. By contrast, private self-consciousness was unrelated to false self-ascriptions, r(51) = .12, ns. This fits with the view that self-infiltration is a non-conscious form of introjection and that self-access rather than explicit selfconsciousness should predict introjection processes. Alexithymia was unrelated to self-infiltration as well, r(51) = .22, ns. This suggests that, despite conceptual and empirical overlap between the two constructs, they are not identical. Specifically, the present findings fit with the idea that self-access is more closely related to mental phenomena associated with self-representations other than emotions, such as personal goals or decisions than (mild) alexithymia. Neither self-access nor self-consciousness nor alexithymia was related to the rate of false other-ascriptions, r(51) = .07, ns, r(51) = .17, ns, and r(51) = .06, ns, respectively. This suggests that the relationship between false self-ascriptions and self-access cannot be attributed to general memory deficits in individuals with low scores on the SAF. The results of Study 4 bolster the notion that self-access safeguards against the involuntary introjection of self-alien goals, which can itself be regarded as a measure of (impaired) implicit self-representation. In fact, introjection of alien goals has been associated with reduced well-being and mental health (Ryan & Deci, 2000). In particular, selfinfiltration as a case of unconscious introjection can lead to uncontrollable, chronic discrepancies between personal belongings and external expectations undermining wellbeing and health in the long run (Baumann, Kaschel, et al., 2005; Brunstein, Schultheiss, & Grässman, 1998; Hofer & Chasiotis, 2003; Hofer, Chasiotis, & Campos, 2006; Kehr, 2004; Ryan & Deci, 2000). As such, although not directly tested here, self-access may be seen as a constituent of chronic self-congruency.

General Discussion Individual differences in self-access are conceived of as the degree to which people are able to be aware of selfrepresentations such as personal needs, life goals, values, emotions, and past experiences. In the present research,

Journal of Individual Differences (2018), 39(1), 1–17


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we developed a brief self-report measure of individual differences in self-access, the SAF. We validated the scale predominantly by investigating its relationship to diverse markers of adaptivity, emotion regulation, and mental health. Our findings demonstrate adequate reliability, factorial and construct validity, as well as criterion-based validity (Study 1), which suggests that self-access can meaningfully be assessed by only five items. We also reported that self-access differs from individual differences in deliberate self-reflection, both with respect to their relationship with each other and with other variables. Specifically, self-access but not private self-consciousness was significantly associated with a number of affect-related personality traits as well as with health-related variables. This suggests that self-access rather than deliberate selfreflection constitutes a resource for adaptivity and health. However, because all of our data were correlational, it cannot be excluded that emotion regulation and health do influence levels of self-access (see Kuhl, 2000, for bidirectional interactions of these variables postulated in PSI theory). Self-reports on self-knowledge have been criticized not to objectively reflect self-access but how clear one perceives one’s self-concept, independent of whether this knowledge refers to true self contents or not, which has led to coining the term self-concept clarity (Campbell et al., 1996). Although we agree that self-reports are biased in this way, individuals can have at least partial knowledge about their true self. As such, the degree of self-access is assessable via self-report, and results from Studies 3 and 4 are in line with this notion. Specifically, Study 4 investigated introjection of alien expectancies, that is, a process that unconsciously corrupts access to self-referential goals. The finding that SAF scores were inversely related to false selfascriptions of alien goals supports the view that SAF does not only reflect an aspect of how individuals believe how clearly they perceive themselves (Campbell et al., 1996), but in fact taps the extent to which they have true self-access (cf. Robins & John, 1997; Vazire & Carlson, 2010). Likewise, the relationships found in Study 3 between SAF and selfcomplexity as well as self-integration, both concepts measured by indirect procedures, are in line with our assumption that our test does assess self-access rather than a mere belief about how clear the self-concept is perceived. Previous research relying on the measure of introjection used here found that the incongruence between actual and perceived choice is closely related to pathogenic variables such as impaired emotion regulation (Baumann & Kuhl, 2003; Kuhl & Kazén, 1994) or increased levels of cortisol (Quirin et al., 2009). The case of unconscious as compared to conscious introjection of alien goals constitutes a particular threat to self-determination because the possibility of bringing one’s behavior in line with one’s Journal of Individual Differences (2018), 39(1), 1–17

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needs and goals is foredoomed to fail. As such, self-access as the ability to access one’s personal needs and goals constitutes an important prerequisite for self-determined volition and behavior (Deci & Ryan, 2000) or for meaning in life (McGregor & Little, 1998; Goldman & Kernis, 2002; Schlegel et al., 2009), and may even lead to less defensive behavior (Schimel, Arndt, Pyszczynski, & Greenberg, 2001). Notably, meta-analyses converge in the role of the ventromedial prefrontal cortex in self-referential processing (Northoff et al., 2006; Van Overwalle, 2009). In a recent study using functional magnetic resonance imaging (fMRI), we found increased activity in the right ventromedial prefrontal cortex as a correlate of self-chosen as compared to imposed goals (cf. Study 4). Notably, individuals with high levels in self-access as measured by the instrument presented here showed increased activity in this area. This evidence provides further validation of our measure and thus supports the usefulness of this construct in general and in neuroscientific research in particular. If self-access is intimately associated with emotion regulation, the absence of self-access or concomitant selfcongruent behavior may constitute a risk factor for the development of diverse psychological disorders that are related to any kind of negative affectivity such as depression, anxiety disorders, and posttraumatic stress disorder. According to our findings, low scores on the SAF are associated with symptoms typically related to impaired emotion regulation such as perceived stress, physical symptoms, general health, and satisfaction with life (Table 2). In line with these ideas, a recent study found that selfaccess predicts adaptive physiological responses to stress (Quirin, Oathes, & Kuhl, 2017). Specifically, low self-access scores were related to reduced heart rate variability during a threat-arousing film clip, a physiological marker of emotion regulation (Appelhans & Luecken, 2006). Notably, self-access even mediated the relationship between reduced heart rate variability and scores of depression, anxiety, and physical complaints in this study. These findings suggest that impaired self-access may be a general factor underlying diverse psychological disorders. We highlighted the role of self-access in emotion regulation and health. However, it should be mentioned that high levels of self-access may come with some sort of vulnerability (e.g., Wilson & Dunn, 2004). Specifically, unpleasant experiences can immediately lead to enhanced negative affect in individuals with high self-access because the self, although typically equipped with predominantly positive self-aspects (Greenwald & Farnham, 2000; Koole et al., 2001), encompasses negative aspects as well. Unpleasant experiences may thus immediately prime negative selfrepresentations that individuals with high levels of selfaccess might engage in at first rather than immediately repress these unpleasant experiences (Kuhl, 2000; Schimel Ó 2018 Hogrefe Publishing


M. Quirin & J. Kuhl, Self-Access and Health

et al., 2001). However, because of elaborated connections between negative and positive self-aspects in the integrated self, the current negative experiences should soon become connected with positive ones, leading to mood recovery and increasing stability in the long run (Kuhl, 2000; see also Showers, 1995). This notion is compatible with our finding of a positive relationship of self-access (but not deliberate self-reflection) with self-complexity and self-integration – constructs that each have been found to relate to early affective sensitivity in previous research (Linville, 1987; Showers & Kling, 1996). Future research may tap into potential vulnerabilities of self-access by investigating the temporal dynamics of affective processes. It would also be instructive to investigate potential changes of self-access or its relationship to emotion regulation and health across the lifespan. In fact, relationships between self-access and simultaneously assessed selfintegration and self-complexity provide initial evidence that self-access is related to self-growth and emotional development and feeds the hypothesis that the link between selfaccess and emotion regulation might become increasingly stable. Similarly, investigating developmental antecedents of self-access would be a challenge for future research. It might be hypothesized that individual differences in self-access, besides differences based on hereditary influences, develop as a function of the quality of parental care. Specifically, based on the assumptions of attachment theory about the role of reactive and sensitive parenting for positive self-development (Bowlby, 1969), developmental research has shown that children’s ability to represent own and others’ mental states is promoted by caretakers mirroring their mental and emotional states (Fonagy, Gergely, Jurist, & Target, 2002). This also concerns the self-positivity assumption of PSI theory, which assumes that the implicit self is typically positively biased in healthy individuals. By contrast, individuals who were raised under pathogenic conditions that do not allow for the development of positive self-views and basic trust may not develop a positive implicit self. For example, it was found that individuals who developed a major depression early in their life showed low levels of implicit self-esteem, whereas those developing it later in their life showed positive implicit self-esteem (Van Randenborgh, Pawelzik, Quirin, & Kuhl, 2016). Intuitive self-access might at first sight resemble the concept of mindfulness (e.g., Bishop et al., 2004; Brown, Ryan, & Creswell, 2007; Kabat-Zinn, 1982). In fact, both concepts involve the idea of broad, holistic attention. Still, self-access differs from mindfulness in important aspects. First, both terms have their roots in different theoretical approaches. Specifically, self-access is embedded in a self-regulation approach that differentiates self-access from a number of psychological processes such as intentions, intuitive sensorimotor system, and focused attention, which interact in a particular way to Ó 2018 Hogrefe Publishing

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produce behavior. By contrast, mindfulness grounds in Buddhist philosophy and which was adopted by different Western clinical psychologists that do not make the same differentiations but subsume several of these processes under “mindfulness”. In fact, different theorists conceptualize mindfulness differently but many definitions merge the above-mentioned processes as they, for example, include purposefulness, which is not a feature of self-access (but of intention system). Therefore, mindfulness might to some degree describe how well these processes interact, and thus describes a state close to the output rather than the input of the dynamics of system interactions. Also, most conceptualizations of mindfulness refer to the way individuals observe and experience environmental rather than self-related aspects exclusively. In this regard, self-access is more selective than mindfulness. Moreover, because self-relevance involves personal evaluation and preferences by definition, it differs from mindfulness as a non-evaluative state. Not least, mindfulness refers to a state of “here and now,” which can be conceived of as an elementary state of information processing. By contrast, access to the self involves personal wishes and future life perspectives as well as the integration and differentiation of self-knowledge, and may thus refer, if at all, to a high-level rather than elementary form of mindfulness. Undoubtedly, the latter two processes might facilitate each other but refer to separate psychological processes. Future research might investigate the assumptions about conceptual differences and similarities between self-access and mindfulness empirically. SAF but not a measure of deliberate self-reflection (private self-consciousness) was associated with self-integration and self-complexity as well as with self-infiltration, that is, with implicit measures, that is, non-reflective aspects of the self. This suggests that the SAF measures self-access rather than self-concept clarity exclusively, that is, believes about alleged self-access (cf. Campbell et al., 1996). As argued before, when people do not really know what they want, what they feel or expect, they might still be aware of this impairment by intuition or by observation of everyday life situations (Bem, 1972) and might thus be able to report about this impairment resulting in a low score of self-access. Still, it would be desirable to see studies exploring relationships between self-access and other markers of self-access, such as reaction times indicating the decisiveness about selfevaluations (Schlegel et al., 2009), the degree of coherence between actual and ideal self-aspects (Higgins, 1987), or relatedly, the degree of coherence between implicit and explicit self-representations (Baumann, Kaschel, et al., 2005; Bosson, Swann, & Pennebaker, 2000; Hofmann et al., 2005; Kazén & Kuhl, 2011; Nosek, 2007; Rudolph, Schröder-Abé, Schütz, Gregg, & Sedikides, 2008). We assume that self-access can function as a moderator of the latter relationships. In fact, our finding of a relationship Journal of Individual Differences (2018), 39(1), 1–17


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between self-access buffering self-infiltration can already be conceived of as first evidence on such a moderating role since actual choices of activities can be considered as implicit goals and retrospective judgments about this choice can be considered as explicit goals (Kuhl & Kazén, 1994). The notion of self-access as a potential moderator between implicit and explicit self-representations might constitute one central mechanism behind the relationship between impaired self-access and psychopathology, as discussed above. For example, depressed people typically suffer from reduced self-esteem, yet, increasing evidence from studies using the implicit association test for measuring self-esteem (Greenwald & Farnham, 2000) suggests that depressed individuals have positive self-esteem on a nondeliberative level (Cai, 2003; De Raedt, Schacht, Franck, & De Houwer, 2006; Moritz, Werner, & Von Colani, 2006). These findings challenge traditional theories of depression, which exclusively rely on self-reported self-esteem or selfconcepts. When self-positivity constitutes an inherent characteristic of the implicit self-system as assumed in PSI theory and as supported by these findings, findings that some depressed individuals show negative self-esteem on an explicit level but positive self-esteem on an implicit level may be explained by a failure of depressed individuals to access the extended experiential network comprising the implicit self (Rotenberg, 2004). This failure may keep them from relying on implicit integrated, positively-biased self-memories, and may motivate them to think and ruminate explicitly about their self. In a similar vein, coherences between implicit and explicit motives, which have been found to predict well-being and health (Baumann, Kaschel, et al., 2005; Kehr, 2004), might be mediated by self-access. It also remains open to further debate to what self-access amounts in collectivist cultures (Hofstede, 1980) and whether it shows similar effects on well-being and health. Cultures differ in the degree to which their individuals tend to have independent or interdependent self-construals (Fernández, Paez, & González, 2005). Interdependent as compared to independent individuals include important others such as their parents in their definition of self (e.g., Elliott & Coker, 2008). In this regard, having access to personal wishes, values, or feelings might to a large part amount to follow other’s expectations. In this case, selfaccess in terms of being able to distinguish between self-referential aspects and expectations appears to be dispensable. Future research is thus needed to provide answers to these important questions.

Limitations and Outlook The present research primarily investigated and corroborated relationships of self-access with emotion regulation Journal of Individual Differences (2018), 39(1), 1–17

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and health. However, it would also be desirable to investigate how individual differences in self-access are related to other aspects of psychological functioning such as meaning in life. As such, Schlegel et al. (2009) demonstrated in a number of studies that both manipulated states and individual differences in the accessibility to self-representations predicted experiences of meaning in life. For example, the authors found in two studies that priming participants with traits identified as being related to the true self in advance increased their perception of meaning in life. In addition and most relevant to our work, they found in three studies that individual differences in true self-access as indicated by an indirect measure (i.e., fastened responses to the question of whether trait adjectives apply to oneself or not) predicted ratings on meaning of life scales. Some researchers may question whether self-access can be assessed via self-report at all. However, we don’t see why individuals should not in principle become aware of their difficulties (if there are any) in reporting their needs or feelings or to describe themselves as a person. We agree that self-report measures of personality and abilities have their weaknesses and can be influenced by a number of cognitive and motivational biasing factors; however, this is not a concern specific to the measurement of subjective self-access but to subjective assessments about personality traits in general (extraversion, neuroticism, self-esteem, etc.). Still, we welcome research that attempts to measure self-access via indirect methods (e.g., Schlegel et al., 2009), which, just like self-report measures, are limited with respect to their validity (or even reliability) to some degree as well. Therefore, future research might benefit from multimethodical studies that apply self-report and indirect measures of self-access in combination in order to compare their strengths and weaknesses. Future research should also investigate relationships between self-access and decision-making. Specifically, individuals with high self-access should be able to make decisions that (a) are in line with their personal needs, values, and emotions and, because of the integrated, parallel-processing nature of the self, that (b) take a great amount of relevant aspects into account simultaneously (Kuhl, 2000). This idea is also compatible with the somatic marker hypothesis (Damasio, 1994) according to which appropriate decisions are based on intuitive, emotional cues, as represented by the ventromedial prefrontal cortex. In fact, the finding of a positive relationship with selfmotivation as measured by decision-related action orientation provides initial evidence to such a relationship but more systematic research is required. Not least, studies 2–4 are based on sample sizes between 30 and 70. Although in line with theory and hypotheses, the results of these studies warrant replication. Ó 2018 Hogrefe Publishing


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Concluding Remarks The present findings indicate that trait individual differences in self-access can reliably and validly be assessed via a brief self-report scale. Self-access appears to be an intuitive process and can be distinguished from deliberate forms of self-reflection. More so than the latter, it appears to play an important role for adaptive functioning, emotional development, and mental health. Acknowledgments This research was facilitated by the Graduate School Integrative Competences and Well-Being funded by Deutsche Forschungsgemeinschaft (Grant No. 772/3), as well as by German Academic Exchange Service (DAAD) with funds from the German Federal Ministry of Education and Research (BMBF) and the People Programme (Marie Curie Actions) of the European Union’s Seventh Framework Programme (FP7/2007-2013) under REA Grant Agreement No. 605728 (P.R.I.M.E. – Postdoctoral Researchers International Mobility Experience). The authors thank Sander Koole and Regina Bode for providing helpful comments on a former version of the paper as well as Victoria Stobe for assistance in formatting it.

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Showers, C. J. (1992b). Evaluatively integrative thinking about characteristics of the self. Personality and Social Psychology Bulletin, 18, 719–729. https://doi.org/10.1177/ 0146167292186008 Showers, C. J. (1995). The evaluative organization of selfknowledge: Origins, processes, and implications for selfesteem. In M. H. Kernis (Ed.), Efficacy, agency, and self-esteem (pp. 101–120). New York, NY: Plenum Press. https://doi.org/ 10.1007/978-1-4899-1280-0_6 Showers, C. J., & Kling, K. C. (1996). Organization of selfknowledge: Implications for recovery from sad mood. Journal of Personality and Social Psychology, 70(3), 578–590. https:// doi.org/10.1037/0022-3514.70.3.578 Simon, L., Greenberg, J., & Brehm, J. (1995). Trivialization: The forgotten mode of dissonance reduction. Journal of Personality and Social Psychology, 68, 247–260. https://doi.org/10.1037/ 0022-3514.68.2.247 Srivastava, S. (2012). Other people as a source of self-knowledge. In S. Vazire & T. D. Wilson (Eds.), Handbook of self-knowledge (pp. 90–104). New York, NY: Guilford Press. Suls, J., & Fletcher, B. (1985). The relative efficacy of avoidant and nonavoidant coping strategies: A meta-analysis. Health Psychology, 4, 249–288. https://doi.org/10.1037/0278-6133. 4.3.249 Taylor, G. J., & Bagby, R. M. (2004). New trends in alexithymia research. Psychotherapy and Psychosomatics, 73, 68–77. https://doi.org/10.1159/000075537 Taylor, G. J., Bagby, R. M., & Parker, J. D. A. (1992). The Revised Toronto Alexithymia Scale: Some reliability, validity, and normative data. Psychotherapy and Psychosomatics, 57, 34–41. https://doi.org/10.1159/000288571 Taylor, G. J., Parker, J. D. A., Michael Bagby, R., & Acklin, M. W. (1992). Alexithymia and somatic complaints in psychiatric outpatients. Journal of Psychosomatic Research, 36, 417–424. https://doi.org/10.1016/0022-3999(92)90002-J Taylor, S. E., & Brown, J. D. (1988). Illusion and well-being: A social psychological perspective on mental health. Psychological Bulletin, 103, 193–210. https://doi.org/10.1037/0033-2909. 103.2.193 Thrash, T. M., Elliot, A. J., & Schultheiss, O. C. (2007). Methodological and dispositional predictors of congruence between implicit and explicit need for achievement. Personality and Social Psychology Bulletin, 33, 961–974. https://doi.org/ 10.1177/0146167207301018 Trope, Y., & Brickman, P. (1975). Difficulty and diagnosticity as determinants of choice among tasks. Journal of Personality and Social Psychology, 31, 918–925. https://doi.org/10.1037/ h0076792 Van Overwalle, F. (2009). Social cognition and the brain: A metaanalysis. Human Brain Mapping, 30, 829–858. https://doi.org/ 10.1002/hbm.20547 Van Randenborgh, A., Pawelzik, M., Quirin, M., & Kuhl, J. (2016). Bad Roots to Grow: Deficient Implicit Self-Evaluations in Chronic Depression with an Early Onset. Journal of Clinical Psychology, 72, 580–590. https://doi.org/10.1002/jclp.22275 Vazire, S., & Carlson, E. N. (2010). Self-Knowledge of personality: Do people know themselves? Social and Personality Psychology Compass, 4, 605–620. https://doi.org/10.1111/j.1751-9004. 2010.00280.x Wegner, D. M. (1994). Ironic processes of mental control. Psychological Review, 101(1), 34–52. https://doi.org/10.1037/0033295X.101.1.34 Williams, L. E., Bargh, J. A., Nocera, C. C., & Gray, J. R. (2009). The unconscious regulation of emotion: Nonconscious reappraisal goals modulate emotional reactivity. Emotion, 9, 847–854. https://doi.org/10.1037/a0017745

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Wilson, T. D., & Dunn, E. W. (2004). Self-knowledge: its limits, value, and potential for improvement. Annual Review of Psychology, 55, 493–518. https://doi.org/10.1146/annurev. psych.55.090902.141954 Received November 3, 2015 Revision received February 24, 2017 Accepted April 30, 2017 Published online January 12, 2018

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Markus Quirin Jordon Hall 450 Serra Mall Stanford, CA 94305 USA mquirin@uos.de

Journal of Individual Differences (2018), 39(1), 1–17


Original Article

UV Radiation Associates With State Income Through Complex Cognitive Ability in the USA Federico R. León1 and Andrés Burga-León2 1

Research Center, Universidad Científica del Sur, Lima, Peru

2

Facultad de Psicología, Universidad de Lima, Peru

Abstract: Economic development and national intelligence decline with proximity to the equator. Absolute latitude associates with both, income and IQ, but the nature of their relationship is ambiguous. This study applied structural equation modeling using secondary data pertaining to the 48 contiguous states of the United States of America to test the hypothesis that UV (ultraviolet) radiation associates with income through complex cognitive ability vis-a-vis the hypothesis that UV radiation associates with complex cognitive ability through income. The resulting evidence was consistent with the ability ? income pathway and unsupportive of the income ? ability model. The findings uphold the cognitive capitalism perspective and may throw light on the evolvement of regional differences in the USA. Keywords: UV radiation, complex cognitive ability, income per capita

Ram (1997, 1999) reported declining wealth of countries and states of the United States as they approach the equatorial line and, since then, several studies in various parts of the world have demonstrated the effects of tropical climate on disease environment and of the latter on economic development (Bhattacharyya, 2009; Bloom, Sachs, Collier, & Udry, 1998; Carstensen & Gundlach, 2006; Gallup, Sachs, & Mellinger, 1999; Sachs, 2003; Sachs & Melaney, 2002). Tropical ecozones and/or temperature and/or yearly number of days of frost predict average income (Bhattacharyya, 2009; Bleany & Dimico, 2010; Gallup et al., 1999; McArthur & Sachs, 2001; Olson & Hibbs, 2005; Sachs, 2001), investment in farm inputs (Masters & Wiebe, 2000), economic growth (Gallup et al., 1999; Masters & McMillan, 2001), intensity of cultivation (Masters & McMillan, 2001), product per 1° latitude  1° longitude cell (Nordhaus et al., 2006; Nordhaus & Chen, 2009), and agricultural labor productivity (Gutierrez, 2002). The evidence suggests that the stronger and longer winters of countries located far from the equator created conditions for the adoption of capital-intensive modes of production (Zuleta, 2012). On the other hand, some economic studies indicate that national IQ is a strong and robust explanatory variable of Gross domestic product (GDP) growth rates (Jones, 2011; Jones & Schneider, 2010; Ram, 2007; Weede & Kämpf, 2002) and also of total factor productivity growth (Jones, Journal of Individual Differences (2018), 39(1), 18–26 https://doi.org/10.1027/1614-0001/a000245

2012). According to evolutionary psychologists, national differences in wealth are a consequence of national differences in IQ. Lynn and Vanhanen (2002, 2006) argued that the wealth of nations depends on their mean IQ and there is evidence suggesting that IQ is a positive influence on national GDP (Meisenberg & Lynn, 2012). The LynnVanhanen methodology has been severely criticized (Bernahu, 2007; Hunt & Wittmann, 2008; Volken, 2003; Wicherts, Borsboon, & Dolan, 2010), but Whetzel and McDaniel (2006) showed that their results were robust. Moreover, Rindermann and Thompson (2011) and Rindermann (2012) have reported that cognitive ability has a positive influence on national GDP rather than vice versa, based not only on IQ scores but also on math, reading, and science scores from various Programme for International Student Assessment (PISA), Trends in International Mathematics and Science Study (TIMMS), and Progress in International Reading Literacy Study (PIRLS) international rounds standardized by Rindermann (2007). Christainsen (2013) also found a similar direction of causality. The generation of wealth requires able individuals capable of developing science and technology, designing and implementing innovations in economic life, and effectively managing production and service units. Individual IQ positively influences trading behavior, performance, and transaction costs (Grinblatt, Keloharju, & Linnainmaa, Ó 2018 Hogrefe Publishing


F. R. León & A. Burga-León, UV Radiation

2011). Thus, Dickerson (2006) calculated that an increase of 10 points in mean IQ results in a doubling of the per capita GDP and Jones and Schneider (2010) showed that 1 IQ point of the country of origin predicts 1% higher wages of immigrants in the United States. Technological achievement appears to mediate the relationship between national IQ and per capita GDP (Gelade, 2008). Furthermore, the quality of governance, the degree of economic freedom, the rate of innovation, and country competitiveness, all of which may have an impact on the level of productivity and wealth of a country, appear to depend on the attributes of the people involved (the cognitive human capital of the society as a whole, of the intellectual class, and of leading politicians; Rindermann, Kodila-Tedika, & Christainsen, 2015). The final cause would be genetic. The well-known fact that light-skinned populations, who prevail in regions of the world close to the poles, attain higher IQ scores than dark-skinned ones, who prevail in regions close to the equator, has been interpreted in evolutionary terms (Lynn & Vanhanen, 2002; Rushton & Jensen, 2005; Templer & Arikawa, 2006). The predictable harsh winters of temperate regions would have placed cognitive demands for survival on human beings that resulted in the evolution of higher levels of intelligence over several millennia; people at the tropics did not face such evolutionary challenges or opportunities (Lynn, 1991; Nyborg, 2013; Rushton, 1995). Thus, European ancestry has been reported to be the strongest determinant of intelligence in the Americas (Fuerst & Kirkegaard, 2016a, 2016b). This viewpoint has been criticized. In particular, Danielle (2013) argued that the genetic explanation does not account for the Flynn effect, that is, the massive IQ gains registered in more than 30 nations (Flynn, 1987, 2009), and challenged the IQ ? wealth nexus on grounds that the differences in the timing of agriculture transition and the history of States, rather than anything attributable to genetics, predict international IQ differences before the colonial era (circa 1500). Indeed, it took Europeans one millennium to catch up with Arab technology and 1.5 additional millennia to surpass it (Comin, Easterly, & Gong, 2007). Evolutionary concepts cannot account for the latitude-intelligence relationship found in the megathermal Amazonian region of Peru (León & Burga-León, 2014). Since individual variation in IQ is only partly determined by genetic factors (Bouchard, 2013; Haworth et al., 2010; McClearn et al., 1997; Nisbett et al., 2012), this leaves ample space for environmental factors to cause IQ variation. The latitude-intelligence relationship (Bakhiet & Lynn, 2015; Grigoriev, Lapteva, & Lynn, 2016; Kura, 2013; León, 2015, 2016; León & Burga-León, 2014, 2015; León & Hassall, 2017; Lynn, 2010, 2012; Lynn & Vanhanen, 2012; Pesta & Posnanski, 2014; Ryan, Bartels, & Townsend, 2010) has been attributed to UV radiation. It is UV radiation, Ó 2018 Hogrefe Publishing

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not temperature, what explains the latitude-intelligence relationship in the United States (León & Hassall, 2017). Augmented UV radiation causes cell oxidative stress (Meng, Zhang, Zhu, Wang, & Lei, 2009) and free liberals impair cognitive performance (Wang, Ge, Ning, & Wang, 2004). Likewise, folate is degraded by UV radiation (Jablonski & Chaplin, 2010) and reduced folate impairs cognitive performance (Kerac et al., 2014). Moreover, as UV radiation increases, production of vitamin D becomes more effective (Engelsen, Brustad, Aksnes, & Lund, 2005) and promotes production of sex hormones (Jones, Strungnell, & DeLuca, 1998) and dopamine (Kesby, Eyles, Bume, & McGrath, 2011), thus causing family and learning processes – larger families, smaller adults/children ratio, greater attraction of playing – which are likely to have negative consequences for children’s cognitive growth (León & Burga-León, 2014). The stronger UV radiation at higher altitude would explain the weaker cognitive ability in the western than eastern United States (León, 2015) and at higher than lower altitude above sea level in Peru (León & Avilés, 2016). Using saturated path models, León and Hassall (2017) showed that wealth mediates the effects of UV radiation on complex cognitive ability across states of the United States, but UV radiation also impaired income through complex cognitive ability. The former path would be consistent with the fact that cell oxidative stress associated with augmented UV radiation increases fatigue (Kennedy et al., 2005), possibly reducing industriousness (DeYoung, Quilty, & Peterson, 2007), a variable relevant to the creation of wealth. Therefore, alternative tests to those used in the past are needed to determine unambiguously whether UV radiation ? income ? ability or UV radiation ? ability ? income best explains the data. This research was based on structural equation modeling (SEM).

Method Subjects The present research is an extension of the León and Hassall (2017) study. The 48 contiguous states of the USA were the units of observation and analysis; Alaska and Hawaii are latitudinal and longitudinal outliers and were discarded.

Measurements UV Index The Climate Prediction Centre of the USA’s National Weather Service (2015a) reports the yearly number of days

Journal of Individual Differences (2018), 39(1), 18–26


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in which a specific UV-Index level occurred for each largest city per state with the exception of two states in which the capital city is targeted. The measurements are obtained under clear sky. The UV Index is proportional to the wavelength integral of the downward spectral UV irradiance weighted according to the erythemal action spectrum (Diffey, 2002). Detailed information on the yearly number of days in which a specific UV-Index level occurred is provided by the National Weather Service. The UV-Index values are grouped and reported into five categories: extreme (11–15), very high (8–10), high (6–7), moderate (3–5), and low (0–2). We assigned, respectively, 5, 4, 3, 2, and 1 points to these categories and multiplied them by the number of days in which such levels of radiation occurred to obtain a weighted sum per each year of interest (2003, 2013). Within-state variation in UV-Index values is not reported by the National Weather Service (2015b). State differences are stable; the 10-year correlation between weighted sums ranges from .96 to .99 (p = .001). Complex Cognitive Ability Rindermann (2007) has shown that math and reading scores, along with IQ scores, are part of the more general construct of complex cognitive ability (CCA). The National Assessment of Educational Progress program (NAEP, 2015) supplies math and reading scores for all USA states since 2003. The data come in two modalities: one, which compares Whites with African Americans and Hispanics and does not make gender distinctions was used by León and Hassall (2017); the other, used here, compares males and females in the general USA population. NAEP is the gold standard of measuring student achievements in the United States (Fuller, Gesicki, Kang, & Wright, 2006). The assessment stays essentially the same from year to year. At the state level, assessment is conducted in public schools only and every student has the same chance of being chosen. The present research targets 2003 and one decade later (2013). Information is systematically available for math and reading scores of 4th and 8th grade students. State differences in scores are stable (rs from .84 to .95, p = .001) and math and reading scores are highly correlated (rs from .70, p = .001 to .90, p = .001 across genders, grades, and years). Real Median Income Income per capita per state for the years 2003 and 2013 came from the US Department of Commerce (BEA, 2014; De Navas-Walt, Proctor, Mills, & US Census Bureau, 2004); rs between years range from .87 to .98, p = .001. Considering the stability of income differences between USA states and the perpetuation of the IQ according to parental socioeconomic status (Nisbett et al., 2012), this Journal of Individual Differences (2018), 39(1), 18–26

F. R. León & A. Burga-León, UV Radiation

study tests the UV radiation ? CCA ? income hypothesis treating children’s CCA scores as representative of the CCA of their recent ancestors, who assumedly created the state wealth differences. Analytic Strategy Bootstrapping was used to defend the analyses against biases derived from violations of statistical assumptions. The study hypotheses were tested using SEM; consistent with conventional standards in the handling of SEMs, the following criteria of good model adjustment were used: a w2 with probability > .05, normed fit index (NFI) > .95, comparative fit index (CFI) > .95, root mean square error of approximation (RMSEA) < .08, and standardized root mean residual (SRMR) < .08 (Schreiber, Stage, King, Nora, & Barlow, 2006).

Results Preliminary Analyses All the study variables, including physical and socioeconomic measurements, were approximately normally distributed according to the Kolmogorov-Smirnov test; the lowest ps observed were equal to .114 (male math), .150 (male reading), and .205 (female reading) in 8th grade. Consistent with the literature, math scores were greater among males than females whereas higher female than male scores were observed in reading; the ts for correlated samples ranged from 2.566 in 8th grade in 2013 to 41.980 in 8th grade in 2003, all significant at or below p = .014. Income was greater in 2013 (M = $43,605.21, SD = $6,628.02) than 2003 (M = $30,385.13, SD = $4,272.50).

Hypothesis Testing Figure 1 presents results of testing the study hypotheses in 4th grade in 2003. The UV Index ? CCA ? income SEM model achieves adjustment in terms of w2, NFI, CFI, RMSEA, and SRMR whereas the UV Index ? income ? CCA model does not. These results are closely replicated in 8th grade (Figure 2) and are also found one decade later (Figures 3 and 4). Addition of a UV Index ? income path in the successful SEM model deteriorated its level of adjustment (not shown). Similar was the case of adding temperature, percentage of White population, and rate of infectious diseases (not shown). The finding of adjusted SEMs entailing UV Index ? CCA ? income and unadjusted SEMs entailing UV Index ? income ? CCA naturally leads to the conclusion that the structure of the data is well represented by the former Ó 2018 Hogrefe Publishing


F. R. León & A. Burga-León, UV Radiation

(A)

21

(B)

.75

UV Index −.43***

.18 Income per Capita .67***

Math Male .75 Math Female .96 Reading Male .94 Reading Female

UV Index .89

−.67*** .45

Complex Cognitive Ability

.32

.45 Complex Cognitive Ability ***p = .001, two-tailed.

Chi-Square = 21.617, p < .003 NFI = 0.943 CFI = 0.960 RMSEA = .211 SRMR = .155

.67***

.45

Income per Capita ***p = .001, two-tailed.

.85 Math Male .84 Math Female .84

.82

Reading Male .83 Reading Female

.78

Chi-Square = 7.574, p = .372 NFI = 0.980 CFI = 0.998 RMSEA = .042 SRMR = .024

Figure 1. Results from structural equation modeling in 4th grade, 2003. (A) Income causing CCA. (B) CCA causing income.

(A)

(B)

.79

UV Index −.43***

.18 Income per Capita .70***

Math Male .79 Math Female .92 Reading Male .96 Reading Female

UV Index .92

.58

.03

.50 Complex Cognitive Ability ***p = .001, two-tailed.

−.76***

Chi-Square = 34.284, p < .001 NFI = 0.916 CFI = 0.931 RMSEA = .288 SRMR = .190

Complex Cognitive Ability .70***

.49

Income per Capita ***p = .001, two-tailed.

.80 Math Male .80 Math Female .90

.91

Reading Male .96 Reading Female

.24

Chi-Square = 5.359, p = .616 NFI = 0.987 CFI = 1.000 RMSEA = <.001 SRMR = .025

Figure 2. Results from structural equation modeling in 8th grade, 2003. (A) Income causing CCA. (B) CCA causing income.

and not the latter. Therefore, it strongly suggests that UV radiation affects income via affecting intelligence and not vice versa, at least in the USA.

Discussion Four methodological limitations of the study merit discussion. First, the study dealt with averaged state data which ignores UV variation within states. This within-state variation, however, is not large enough to distort the betweenstate variation; otherwise, the observed strong longitudinal correlations could not have been registered. The same applies to NAEP’s cognitive data and justifies the use of states as units of analysis, as in the studies by McDaniel (2006), Kanazawa (2006), Ryan et al. (2010), Pesta and Ó 2018 Hogrefe Publishing

Posnanski (2014), León and Hassall (2017), and others. Second, UV-Index measurements present spatial autocorrelation and, therefore, are prone to generate deflated significance levels. However, spatial autocorrelation has been shown to produce trivial effects in the data utilized in the present study (León & Hassall, 2017). Moreover, spatial autocorrelation remained constant across SEM models here. Consequently, the conclusion that the UV Index ? CCA ? income model is a more valid representation of the empirical evidence than the UV Index ? income ? CCA model is not invalidated by the lack of control for spatial autocorrelation. The third limitation entails the small number of cases (N = 48). But, rather than raw sample size, what should be considered is that, given that USA state CCA measurements are based on scores from dozens of thousands of students rigorously sampled, Journal of Individual Differences (2018), 39(1), 18–26


22

F. R. León & A. Burga-León, UV Radiation

(A)

(B)

.79 UV Index

−.40** .16 Income per Capita .53***

Math Male .82 Math Female .90 Reading Male .97 Reading Female

UV Index .87

−.77*** .59

Complex Cognitive Ability

.53

.28

Chi-Square = 51.976, p < .001 NFI = 0.872 CFI = 0.885 RMSEA = .370 SRMR = .271 **p = .01, ***p = .001, two-tailed.

.56***

Complex Cognitive Ability

.79 Math Male .77 Math Female .93 Reading Male .97 Reading Female

.31

Income per Capita ***p = .001, two-tailed.

.88

.35 .23

Chi-Square = 6.526, p = .367 NFI = 0.984 CFI = 0.999 RMSEA = .043 SRMR = .013

Figure 3. Results from structural equation modeling in 4th grade, 2013. (A) Income causing CCA. (B) CCA causing income.

(A)

.99 UV Index

−.40** .16 Income per Capita .46***

Math Male .97 Math Female .78 Reading Male .82 Reading Female

(B) −.21

UV Index

−.84*** .71

.75

.21

Chi-Square = 51.976, p < .001 NFI = 0.872 CFI = 0.885 RMSEA = .370 SRMR = .271 **p = .01, ***p = .001, two-tailed.

Complex Cognitive Ability

Complex Cognitive Ability .45***

.20

Income per Capita ***p = .001, two-tailed.

.87 Math Male .86 Math Female .89 Reading Male .93 Reading Female

.82

.47

Chi-Square = 7.400, p = .388 NFI = 0.982 CFI = 0.999 RMSEA = .035 SRMR = .014

Figure 4. Results from structural equation modeling in 8th grade, 2013. (A) Income causing CCA. (B) CCA causing income.

their amount of measurement error is minimal. Moreover, the findings recurred across grades (4th, 8th) and years (2003, 2013), suggesting considerable robustness. Finally, temperature and infectious diseases were omitted in the SEMs to prevent deterioration of the model adjustment indicators. But temperature and infectious diseases were shown to have nonsignificant effects on CCA in the León and Hassall (2017) study. On the other hand, it is noteworthy that the hypothesis was upheld with a methodology of the highest parsimony. Whereas multiple regression analysis would have required replication of the models across the four cognitive measurements (math male, math female, reading male, reading female), the use of SEMs allowed the researchers to deal with a single latent variable (CCA). Another advantage of the use of SEM was its clarity regarding the direction of influence; while it does not necessarily prove causality, it certainly contributes suggestive evidence. Journal of Individual Differences (2018), 39(1), 18–26

The present findings strengthen the view that, if the average CCA of a population increases, this will translate into greater economic efficiency (Meisenberg & Lynn, 2012; Rindermann, 2012; Rindermann & Thompson, 2011). This conclusion is important because psychology has focused mainly on how socioeconomic status determines children’s IQ (Nisbett et al., 2012) rather than the other way around. Danielle (2013) criticized the between-country genes ? IQ ? wealth hypothesis considering the Flynn effect. He adopted Nisbett et al.’s (2012) explanation that the Industrial Revolution produced a need for increased intellectual skills that modern societies somehow rose to meet, that is, Wealth ? IQ. The Flynn effect, however, is more parsimoniously explained by the increased use of contraception and consequent reduction in family sizes in recent decades (Bongaarts, 2008). Reduced families improve the intellectual stimulation of children (Zajonc & Mullally, 1997) and their schooling opportunities Ó 2018 Hogrefe Publishing


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(Booth & Kee, 2009), notwithstanding Kanazawa’s (2012) demonstration that intelligent parents have smaller families. Danielle’s (2013) argument that current IQ differences between countries were not the same centuries or millennia ago subtracts credibility to the between-country genes ? IQ ? wealth relationship but not necessarily to the UV radiation ? IQ ? wealth relationship. Arabs had a superior technology than that of Europeans 3,000 years ago and probably were more intelligent then. But Europeans were adapting to their new environment. It may have taken Europeans millennia to reverse the situation thanks to the benefits of a reduced UV radiation. Similar may have been the case in the United States; that is, Americans probably needed centuries to produce the observed North-South cognitive differences. On the other, the present findings do not necessarily contradict the specific wealth ? IQ linkage proposed by Danielle (2013) for Italy. It is possible that the IQ ? wealth linkage found in the United States is not a universal phenomenon but reflects the greater social mobility on the basis of ability existing in this country. Human groups more exposed to intensive UV radiation are less likely to develop higher CCA than groups less exposed to high UV radiation. This could be part of the explanation for the Flynn effect because children spend more time indoors than they used to in earlier times. If UV radiation impairs CCA with proximity to the equator and wealth depends on CCA, northern USA states can be expected to exhibit greater wealth than southern states and defeat them in a Civil War. That social research in the United States has generally ignored the latitudinal dimension should not be surprising considering that researchers lacked the adequate rationale to explain observed regional differences. Now UV radiation is available to help understand latitudinal social phenomena. For example, Cohen, Nisbett, Bowdle, and Schwarz (1996) tested whether in the USA South there is a “culture of honor.” They found that Southerners who had been bumped by an accomplice and called an “asshole,” compared to Northerners, became more upset, were more likely to feel their masculinity was threatened, became more physiologically and cognitively primed for aggression as measured by a rise of testosterone and cortisol levels, and were more likely to engage in aggressive behavior. Cohen et al. attributed these differences to the original Northerner settlers’ dedication to farming whereas most Southerner settlers would have been herders. But, more to the south, Mexicans probably show a more intense culture of honor and the observed North-South different “honor” reactions probably occur in Italy despite the absence of farming versus herding cultures in Mexico and Italy. The concept of UV radiation and its associated biological variables (oxidative stress, etc.) provides a rationale that should

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promote the conduct of studies on latitudinal differences both within and outside the United States. On the other hand, it should be noted that all these conclusions are tentative: they are based on correlations and plagued by omitted variable bias. Experimental studies on the biochemical processes assumed to mediate the UV radiation – cognitive ability relationship are needed, and future studies should incorporate other variables into the UV radiation ? cognitive ability ? wealth model without losing model adjustment. Acknowledgment The data used in this research can be found at https://doi. org/10.6084/m9.figshare.3439265.v1

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Federico R. León Research Center Universidad Científica del Sur Cantuarias 398, Miraflores Lima 18 Peru federicorleone@gmail.com

Received January 1, 2017 Revision received February 12, 2017 Accepted May 2, 2017 Published online January 12, 2018

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Original Article

Differences in the Way to Conceive Happiness Relate to Different Reactions to Negative Events Giulia Fuochi, Chiara A. Veneziani, and Alberto Voci Department of Philosophy, Sociology, Education, and Applied Psychology, University of Padova, Italy

Abstract: This paper aimed to assess whether differences in the way to conceive happiness, measured by the Orientations to Happiness measure, were associated with specific reactions to negative events. We hypothesized that among orientations to pleasure (portraying hedonism), to meaning (representing a eudaimonic approach to life), and to engagement (derived from the experience of flow), orientation to meaning would have displayed a stronger protective role against recent negative and potentially stressful events. After providing a validation of the Italian version of the Orientations to Happiness measure (Study 1), we performed regression analyses of the three orientations on positive and negative emotions linked to a self-relevant negative event (Study 2), and moderation analyses assessing the interactive effects of orientations to happiness and stressful events on well-being indicators (Study 3). Our findings supported the hypotheses. In Study 2, meaning was associated with positive emotions characterized by a lower activation (contentment and interest) compared to the positive emotions associated with pleasure (amusement, eagerness, and happiness). In Study 3, only meaning buffered the effect of recent potentially stressful events on satisfaction with life and positive affect. Results suggest that orientation to meaning might help individuals to better react to negative events. Keywords: pleasure, meaning, engagement, well-being, negative events

Although the search for well-being seems to characterize every human being, individuals may differ in their way to conceive happiness and in privileging certain pathways over others to achieve well-being. Seligman (2002), in his authentic happiness theory, distinguished three major routes to well-being: pleasure, meaning, and engagement. The pleasure pathway derives from the hedonic perspective on happiness (see Ryan & Deci, 2001), promoting the search for pleasure and the minimization of pain to achieve well-being. The meaning pathway stems from the eudaimonic perspective on happiness: well-being improves as individuals deem their experiences and life significant and purposeful (e.g., Ryan & Deci, 2001). The engagement pathway entails absorption in activities attenuating oneâ&#x20AC;&#x2122;s sense of self, but nurturing positive resources: it corresponds to the experience of flow (Csikszentmihalyi, 1990). These three different approaches to life can be assessed through the Orientations to Happiness (OTH) measure (Peterson, Park, & Seligman, 2005), a questionnaire with separate subscales for pleasure, meaning, and engagement orientations. Peterson et al. (2005) demonstrated how each of the three distinct orientations

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individually predicted life satisfaction. The psychometric properties and validity of this scale have been reassessed in later studies (e.g., Chen, 2010; Ruch, Harzer, Proyer, Park, & Peterson, 2010). The beneficial effects of orientations to happiness on life satisfaction hold across various studies and regardless of the geographical origin of the sample (e.g., Chen, 2010; Park, Peterson, & Ruch, 2009; Peterson, Ruch, Beermann, Park, & Seligman, 2007; Ruch et al., 2010). This relationship persists also with other well-being measures, such as happiness and positive affect, while all the orientations are negatively correlated with negative affect and depression (Schueller & Seligman, 2010; Vella-Brodrick, Park, & Peterson, 2009). For instance, Giannopoulos and VellaBrodrick (2011) randomly assigned 218 adults to one of four positive interventions based on orientations to happiness (pleasure, engagement, meaning, or a combination of them) or to control groups, finding that increases in well-being were larger in participants assigned to the interventions based on orientations to happiness than in participants in the control groups. A further study confirmed this result, by showing that the participants of a positive psychology

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intervention simultaneously involving all the three orientations to happiness reported higher increases in happiness than the control group, both at posttest and at follow-up (Proyer, Gander, Wellenzohn, & Ruch, 2016).

Are all the Three Approaches to Life Equally Valuable for Well-Being? Not all the routes to well-being show the same patterns. Many scholars have highlighted how both orientations to meaning and to engagement correlated more strongly with well-being measures than orientation to pleasure (Park et al., 2009; Peterson et al., 2007; Schueller & Seligman, 2010; Vella-Brodrick et al., 2009), while others found that engagement was more relevant to well-being (Buschor, Proyer, & Ruch, 2013). These patterns also depend on the well-being variable and the country considered (Avsec, Kavčič, & Jarden, 2016; Vella-Brodrick et al., 2009). In a study comparing the three orientations in a large US sample, orientation to meaning had the largest effect on satisfaction with life, positive and negative affect among the three orientations, while orientation to pleasure had the weakest effect. However, when comparing the effect of pleasure across these well-being measures, it was weaker in the case of negative affect and life satisfaction, and stronger on positive affect (Vella-Brodrick et al., 2009). The beneficial effects of orientation to meaning could be interpreted in light of the studies reporting that the presence of meaning in life and, to some extent, the search for meaning are positively correlated with good mental health (e.g., Zika & Chamberlain, 1992), even in case of poor health conditions (e.g., Dezutter, Luyckz, & Wachholtz, 2015). Indeed, the ability to find meaning in life experiences appeared also associated with resilience and the ability to feel positive emotions when facing negative events (Tugade & Fredrickson, 2004). It might be argued that individuals who are permanently more oriented to meaning could also be more able to actually find meaning in life and to reap all the meaning-making benefits envisaged by the literature. The debate on the most beneficial orientation to happiness is still open. An intensive longitudinal study, based on mobile experience sampling, showed that each orientation was simultaneously correlated with momentary ratings of pleasure, engagement, and meaning found in the activity of the moment (Grimm, Kemp, & Jose, 2015). Moreover, it appeared more important for daily well-being to have a balanced and strong portfolio of the three orientations than to have a dominant one (Grimm et al., 2015). Until now, the relationship between orientations to happiness and well-being has been studied from a general

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G. Fuochi et al., Orientations to Happiness and Negative Events

perspective. But what happens when bad events occur? Can certain orientations act for the preservation of an individual’s well-being? The present study aims to test, as far as we know for the first time, whether differences in the way to conceive happiness are associated with differences in the reactions to negative or potentially stressful events.

Individual Characteristics Buffering the Consequences of Negative Events Major negative life events (e.g., divorce, spousal bereavement, losing a job) have a deep impact on well-being (e.g., Luhmann, Hofmann, Eid, & Lucas, 2012), but minor daily stressors, such as arguments with the partner, work deadlines or commuting, might have more cumulative and long-term effects (Almeida, 2005; Chamberlain & Zika, 1990; DeLongis, Folkman, & Lazarus, 1988). Indeed, affective reactivity in response to daily hassles predicts general affective distress and an increased likelihood of reporting chronic physical health conditions or affective disorders 10 years later (Charles, Piazza, Mogle, Sliwinski, & Almeida, 2013; Piazza, Charles, Sliwinski, Mogle, & Almeida, 2013). This suggests that negative emotions provoked by any potentially stressful situation can compromise well-being and health, and that this negative effect is not exerted by the event itself, but mostly by the emotional reactivity connected to it. Certain individual characteristics can counteract the negative emotional consequences of stressful events. For instance, high social support and self-esteem decrease the likelihood of experiencing psychological and somatic problems due to hassles (DeLongis et al., 1988), while for people low in neuroticism daily stress is less likely to lead to negative affect (Mroczek & Almeida, 2004). Perceived control reduces physical and psychological reactivity to interpersonal, network, home, and health stressors (Hay & Diehl, 2010). Other factors buffering the impact of bad events are optimism (Scheier & Carver, 1992), emotional self-regulation (Gross, 2014), adaptive coping strategies (e.g., Brown, Westbrook, & Challagalla, 2005), and humility (Krause, Pargament, Hill, & Ironson, 2016). Consistent with the research on the positive effects of meaning-making described above, Krause (2007) showed that finding a meaning in life alleviated the harmful impact of traumatic life events that happened at any point in life on depressive symptoms of older adults. As far as we know, however, no previous study explored the possibility that the three orientations to happiness may be able to protect the individual against life hassles and other stressful events.

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G. Fuochi et al., Orientations to Happiness and Negative Events

Aims and Overview of the Studies The aim of this paper is to test the orientations to happiness framework when potentially stressful events occur. In particular, we explored whether differences in the way to conceive happiness were associated with differences in the reactions to daily hassles and other stressful events. We intended and assessed reactions in two distinct ways: first as emotional reactions to a self-relevant negative event, because emotional reactivity connected to hassles is an important predictor of mental health (e.g., Charles et al., 2013; Piazza et al., 2013), and second as changes in various well-being indicators vis-à-vis potentially stressful situations, to investigate reactions in a broader perspective. Across three studies, with three independent samples, we provided a preliminary validation of the Italian version of the OTH measure (Study 1), and we examined the effect of the orientations to happiness on reactions to negative events, both in terms of emotions (Study 2) and well-being (Study 3). In particular, in Study 2 we tested the effects of engagement, meaning, and pleasure orientations on negative and positive emotions felt when recalling an impactful, self-relevant, negative event. In Study 3, we analyzed the relationships of the three orientations with well-being indicators, that is, life satisfaction, positive and negative affect, interacting the self-reported frequency of recent potentially stressful events with each OTH, to assess potential protective effects of the three orientations when bad events occur. Based on the stronger correlation of orientation to meaning with well-being compared to the other orientations (e.g., Schueller & Seligman, 2010; VellaBrodrick et al., 2009), and on the positive effects of the ability to find a meaning in life (e.g., Dezutter et al., 2015; Krause, 2007), we hypothesized that orientation to meaning would be more able to buffer the effect of recent potentially stressful events. In particular, we hypothesized that (a) mostly orientation to meaning would lower negative emotions and increase positive emotions connected to a negative event in Study 2, and that (b) orientation to meaning would be more able to protect well-being from the negative effect of potentially stressful situations in Study 3.

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Method Participants A total of 345 respondents (160 men, 185 women) were recruited by 90 psychology master students attending a social psychology course at the University of Padua, Italy. Each student, in return for course credits, had to contact four respondents who did not know each other and who were not attending the course, in order to decrease possible dependence among observations. Some of them contacted only three respondents. Participants’ age ranged from 18 to 67 years (M = 27.41; SD = 10.71). Concerning the job position, 7.8% were manual or office workers; 15.9% were retailers, employees, or teachers in primary schools; 9% were professionals, teachers in secondary schools or academics, while 2.6% were housekeepers or unemployed. Finally, 60.9% were students (3.8% did not indicate the occupation). Materials and Procedure The 18 items of the OTH scale were translated into Italian by the authors with the support of a bilingual psychologist who has spent half of her life in Australia and the other half in Italy, and currently lives in Italy. Following test translation guidelines (e.g., Gudmundsson, 2009), we then contacted a bilingual professional (native Italian speaker) to have a backward translation of our Italian version of the OTH measure. The backward translation confirmed the appropriateness of the forward translation. The Italian items are reported in Table A1, see Appendix. Then, this Italian version of the OTH scale became part of an online questionnaire containing also other measures not analyzed here and sociodemographic information. At the beginning of the online page, respondents were briefly informed about the general focus of the questionnaire, the anonymity of their responses, and the possibility to withdraw from the research study at any time. Sample items of the OTH measure are: “I have spent a lot of time thinking about what life means and how I fit into its big picture” (meaning), “I am always very absorbed in what I do” (engagement), and “In choosing what to do, I always take into account whether it will be pleasurable” (pleasure). As in the original version, participants had to rate the items on a 5-point Likert-type scale, from 1 (= very much unlike me) to 5 (= very much like me). Higher scores on a subscale indicated higher levels in the respective orientation to happiness.

Study 1 The aim of this study was to investigate, through a confirmatory factor analysis, the factorial structure of the Italian version of the OTH scale and the reliability of the subscales assessing each orientation. As far as we know, no Italian adaptation of the scale is available in the literature. Ó 2018 Hogrefe Publishing

Results and Discussion Before analyzing the data, normal distribution and multivariate normality were checked. For skewness, absolute values ranged from 0.10 (item 14) to 0.70 (item 15), with a mean value of 0.38. For kurtosis, absolute values ranged from 0.05 (item 16) to 0.92 (item 11), with a mean value of Journal of Individual Differences (2018), 39(1), 27–38


30

0.49. We performed Mardia’s test to test the hypothesis of multivariate normality, which had to be rejected (multivariate skewness: b1p = 31.86, p < .001; multivariate kurtosis: b2p = 399.22, p < .001). However, Curran, West, and Finch (1996) outlined that relevant problems arise when univariate skewness is 2.0 and kurtosis is 7.0. As reported above, all the values of skewness and kurtosis in our data were far from these problematic values. Additionally, confirmatory factor analysis may be performed also on variables moderately affected by skewness and kurtosis (Muthén & Kaplan, 1985). However, according to the partial non-normality of our data, the three-factor structure was tested employing the Robust Maximum Likelihood (RML) estimation procedure, which starts from the asymptotic covariance matrix of polychoric correlations, computing the Satorra-Bentler scaled chi-square (SBw2; Chou, Bentler, & Satorra, 1991; Satorra & Bentler, 1994). We performed confirmatory factor analysis on the Italian version of the OTH measure using the Statistical Software Mplus Version 7 (Muthén & Muthén, 2012). As suggested by Hu and Bentler (1999), several goodness-of-fit indexes were taken into account: the Satorra-Bentler scaled chi-square (SBw2), the w2/df Ratio, the Root Mean Square Error of Approximation (RMSEA), the Comparative Fit Index (CFI), and the Standardized Root Mean Square Residual (SRMR). A nonsignificant chi-square is conceived as an indicator of a good fit of the model to the data (Hu & Bentler, 1999). However, when a sample is large, the chi-square usually emerges as significant. It is therefore recommended to compute the w2/df ratio, which indicates an adequate fit with values lower than 3. Additionally, values of RMSEA between .05 and .08, a CFI that is higher than .90, and a SRMR lower than .08 are indicators of an acceptable fit (Hu & Bentler, 1999). As we aimed to preserve as much as possible the meaning and the psychometric characteristics of the original version of the scale, we first tested a three-factor model identifying engagement, meaning, and pleasure, without allowing cross-loadings of items and correlated errors between items. The indexes suggested an adequate fit: SBw2(132, N = 345) = 343.11, p ffi .00; w2/df = 2.60, RMSEA = .07; CFI = .82; SRMR = .08. Although a CFI higher than .90 is recommended for an adequate fit, it has to be outlined that the CFI computed in Mplus is lower than the one calculated by other similar packages, as in Mplus covariances among exogenously measured variables are not constrained to zero (e.g., Muthén & Muthén, 2012). Indeed, repeating the same confirmatory factor analysis with LISREL 8.71 (Jöreskog & Sörbom, 2004) yielded a CFI equal to .91. The standardized factor loadings for engagement ranged from .33 (item 9) to .83 (item 7), for meaning they ranged from .33 (item 17) to .69 (item 14), while for pleasure, scores were between .36 (item 8) and Journal of Individual Differences (2018), 39(1), 27–38

G. Fuochi et al., Orientations to Happiness and Negative Events

.73 (item 15). Notably, all standardized factor loadings were significant at p < .001. As usual, engagement was positively associated both to meaning (ϕ = .52, p < .001) and to pleasure (ϕ = 32, p < .001), which were in turn related (ϕ = 27, p = .001). We additionally tested a one-factor model. As predicted, the fit indexes did not sustain the unidimensional solution (SBw2(135, N = 345) = 667.65, p ffi .00; w2/df = 4.95, RMSEA = .11; CFI = .53; SRMR = .10), further proving the distinctiveness of the three OTH. Cronbach’s alpha reliability coefficients were in line with the original OTH scale (Park et al., 2009). They were satisfactory for all the subscales (αmeaning = .70; αengagement = .64; αpleasure = .76), although lower for engagement, as already found in the literature (Chen, 2010; Park, Peterson, & Ruch, 2009; Ruch et al., 2010). The Italian version of the OTH scale preserved the main psychometric characteristics of the original version. Based on these findings, we proceeded to test our hypotheses using this instrument.

Study 2 This study aimed to test the effect of orientations to happiness on emotional reactions to a self-relevant negative event. We hypothesized that orientation to meaning would lower negative emotions and increase positive emotions connected to a negative event, because individuals more oriented to meaning might be more able to find meaning in life, and this ability helps in preserving mental health in case of stressful situations (e.g., Dezutter et al., 2015). We considered both negative and positive emotions for multiple reasons: first, they are both indicators of mental health after negative events; second, negative emotional reactivity in response to daily hassles has been shown detrimental to well-being in the long term (e.g., Charles et al., 2013; Piazza et al., 2013); third, the ability to recall positive emotions when facing negative events is a remarkable ability connected to resilience (Tugade & Fredrickson, 2004).

Method Participants A total of 299 participants (101 males, 198 females) were recruited by two research assistants. Participants’ age ranged from 18 to 72 years (M = 31.15; SD = 12.10). Concerning the job position, 13.7% were manual or office workers; 37.8% were retailers, employees, or teachers in primary schools; 8% were professionals, teachers in secondary schools or academics; 6% were housekeepers, unemployed, or retired; and 22.1% were students (12.4% did not indicate any occupation). Ó 2018 Hogrefe Publishing


G. Fuochi et al., Orientations to Happiness and Negative Events

Materials and Procedure Participants completed an online questionnaire containing socio-demographic information, the Italian version of the OTH scale validated in Study 1, questions on a recent self-relevant negative event, and other measures not reported in this study. As in Study 1, at the beginning of the online page respondents were briefly informed about the general focus of the questionnaire, the anonymity of their responses, and the possibility to withdraw from the research study at any time. Measures OTH Measure Details on the Italian version of the OTH scale are presented in Study 1. Before analyzing the data, we performed a Confirmatory Factor Analysis on the Italian version of the OTH measure also in Study 2, to confirm the three-factor solution of the original scale. As in the previous study, the indexes suggested an adequate fit: SBw2(132, N = 292) = 342.95, p ffi .00; w2/df = 2.60, RMSEA = .07; CFI = .80; SRMR = .07. Standardized factor loadings for engagement ranged from .27 (item 10) to .70 (item 7), while for meaning they ranged from .40 (item 17) to .72 (item 11), and pleasure scores were between .53 (item 8) and .73 (item 15). All standardized factor loadings were significant at p < .001. As in the previous findings, meaning was positively related both to engagement (ϕ = .48, p < .001) and to pleasure (ϕ = .32, p < .001), which were in turn associated (ϕ = .48, p < .001). Cronbach’s α in the sample of this study was .72 for meaning, .59 for engagement, and .79 for pleasure. Negative Event Participants were asked to select the most impactful negative event happened to them in the period preceding the filling out of the questionnaire. Then, they had to report how much negative the event was on a scale from 1 to 10, how many weeks had passed since that event (being 0 if the event was happened in the same week), and how they felt when recalling that event using the Emotion Report. Emotion Report As introductory question, we asked “When you think about this event, to what extent do you feel the following emotions on a scale from 0 (= not at all) to 8 (= a great deal)?”. Then, participants had to rate 14 emotions (half positive, half negative) already used in Tugade and Fredrickson (2004) to assess emotional reactions during a stressful situation. The emotions were fear, amusement, anger, anxiety, contentment, disappointment, disgust, eagerness, excitement, frustration, happiness, interest, surprise, and sadness. Tugade and Fredrickson (2004) analyzed the emotions both separately and by computing a composite

Ó 2018 Hogrefe Publishing

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emotionality index appropriate for their research goals. Here we preferred to consider the singular emotions, in order to capture more variation in emotional reactions to a self-relevant negative event. Hence, we did not compute aggregate indices.

Statistical Analyses Means, standard deviations, and zero-order correlations between measures are presented in Table S1 in Electronic Supplementary Material, ESM 1. Then, we performed regression models of the three orientations to happiness on each emotion of the Emotion Report, also controlling for age, gender, the self-assessed negativity of the event and for the number of weeks passed since the event. Age and gender are common socio-demographic controls in regression models involving orientations to happiness (e.g., Peterson et al., 2005; Schueller & Seligman, 2010), while we controlled for time passed since the event and self-assessed negativity of the event because emotional reactions to events could also depend on the type of event occurred (e.g., Hay & Diehl, 2010). We started with linear regression models involving the variables previously listed. However, when we plotted the residuals to see if model assumptions were satisfied, we observed that for positive emotions a slight relationship emerged between residuals and fitted values, and that residuals’ distribution was not close to normality. Therefore, standard linear regression seemed to be appropriate only for negative emotions. Indeed, while the seven negative emotions felt when recalling a negative event had a quite symmetric distribution (skewness ranging from 0.53 to 0.48), the distribution of positive emotions was far more asymmetric, with skewness ranging from 2.00 to 2.42 for all the positive emotions, except interest (0.82) and surprise (0.65). For the large majority of people, the recalled negative event did not generate any positive emotion, but a minority of individuals reported them, although the frequency of individuals reporting a positive emotion decreased with increasing emotion intensity. To be clearer, more people experienced low levels of positive emotions, less people reported high levels of positive emotions (see Figure S1 in Electronic Supplementary Material, ESM 2). Therefore, we employed the most appropriate family of distributions for modeling this kind of asymmetry, that is, the gamma family, and implemented generalized linear models with gamma family and log link function for positive emotions. The gamma distribution requires positive values, so we rescaled the answers to positive emotions from 1 to 9 before the analyses. After having tried both identity link and log link functions, we chose the latter because of lower deviances and better model fit according

Journal of Individual Differences (2018), 39(1), 27–38


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G. Fuochi et al., Orientations to Happiness and Negative Events

Table 1. Gamma-family generalized linear models of OTH on positive emotions linked to a negative event (unstandardized coefficients, Study 2) Amusement B

Contentment

Eagerness

Excitement

Happiness

Interest

Surprise

SE

B

SE

B

SE

B

SE

B

SE

B

SE

B

SE

Age

0.00

.00

0.00

.00

0.00

.00

0.00

.00

0.00

.00

0.00

.00

0.00

.00

Gender (= female)

0.18

0.17

0.19

0.01

.11

0.10

.11

.11

0.29*

.11

.12

0.06

.11

Pleasure

0.15*

.07

0.10

.08

0.15*

.08

0.14

.08

0.16*

.08

0.10

.07

Meaning

0.07

.08

0.21*

.08

0.12

.08

0.04

.08

0.15

.08

0.21**

.08

0.02

Engagement

0.05

.10

0.01

.10

0.06

.10

0.08

.10

0.04

.10

0.12

.10

0.12

.09

Event negativity

0.06**

.02

0.05*

.02

0.04

.02

0.04

.02

0.05*

.02

0.01

.02

0.02

.02

Time since event

0.01

.01

0.01

.01

0.01

.01

0.01

.01

0.02*

.01

0.01

.01

0.01

.01

AIC R2Nagelkerke

0.17*

.10 .07 .07

718.940

821.500

751.607

770.486

771.311

1,125.144

1,161.269

.203

.149

.173

.188

.211

.085

.073

Notes. For Gender, Male = 1; Female = 2; *p < .05; **p < .01; ***p < .001 (all two-tailed).

to Akaike Information Criterion (AIC; Hardin & Hilbe, 2012). In these models as well we controlled for the selfassessed negativity of the event and for the number of weeks passed since the event, so as for respondents’ age and gender. Probability densities for each positive emotion with the density of the fitted values plotted over are reported in Figure S1 in ESM 2.

Results and Discussion Table 1 reports the gamma-family generalized linear regression models for positive emotions. The effects are multiplicative, that is, the exponentiated coefficients give the multiplier on the expected value of the outcome when the independent variables change by 1. As can be seen from Table 1, only orientations to pleasure and to meaning increased the likelihood that one felt also positive emotions when recalling an impactful, self-relevant, negative event. Interestingly, orientation to pleasure and orientation to meaning had nonoverlapping effects: feeling amused, eager, happy, or surprised was positively associated with pleasure orientation, while feeling content or interested was linked to meaning. The negativity of the event was negatively related to self-reports of amusement, contentment, and happiness. The results suggest that being more oriented to meaning stimulates a different set of emotions compared to being more oriented to pleasure. A possible interpretation of these findings stems from the fact that amusement, eagerness, and happiness are characterized by higher levels of activation, while contentment and interest share a lower activation (Feldman Barrett & Russell, 1998; Fredrickson & Branigan, 2005). Consistently with this, the physiological response pattern of contentment is analogous to a relaxation response (Kreibig, 2010), while interest is spurred by challenging events, creating the desire to explore and understand (Fredrickson, 2013; Silvia, 2008). On the other hand, amusement, eagerness, and Journal of Individual Differences (2018), 39(1), 27–38

happiness generate joyful sensations and make the individual more prone to action and to social bonds, for example, creating the desire to share a laugh (Fredrickson, 2013). The last negative emotion related to pleasure orientation, surprise, is usually identified as a positive emotion, but its valence also depends on the triggering event (Noordewier & Breugelmans, 2013). In fact, as we reported before, responses of surprise were less asymmetric compared to the other positive emotions. We also have to acknowledge that for interest and surprise the model fit, according to AIC and Nagelkerke pseudo R squared, was worse compared to the other emotions, suggesting that they might be explained by other variables not included in the model. In conclusion, consistent with our hypothesis, orientation to meaning was positively related to positive emotions linked to a negative event, but surprisingly, also orientation to pleasure showed a positive relationship with positive emotions. Interestingly, the patterns diverged for the two sets of emotions respectively linked with the two orientations. These findings, while preliminary, suggest that although both these orientations are associated with increased likelihood of feeling also positive emotions when recalling a negative event, orientation to meaning is associated with a lower level of reactivity compared to pleasure. These results may translate into different consequences for an individual’s well-being in a broader perspective; Study 3 will give a contribution in this direction. Standard linear regressions of the same set of independent variables on negative emotions belonging to the Emotion Report revealed a strong positive effect of the perceived negativity of the self-relevant negative event, while orientations to happiness did not show any effect, except for one emotion. Orientation to engagement was associated with increased reported fear (β = 0.15, p = .03) when recalling the negative event. In this case, our hypothesis on the negative effect of orientation to meaning on negative emotions connected to a self-relevant bad event was not confirmed. Ó 2018 Hogrefe Publishing


G. Fuochi et al., Orientations to Happiness and Negative Events

Study 3 The aim of Study 3 was to explore the possibility that orientations to happiness might buffer the aversive impact of negative events on different well-being indicators. As orientation to meaning is more strongly correlated with wellbeing than the other orientations (e.g., Vella-Brodrick et al., 2009), and finding meaning in stressful life experiences protects well-being (e.g., Krause, 2007), we hypothesized that orientation to meaning would be more able to protect well-being against the occurrence of recent potentially stressful events.

Method Participants Four research assistants recruited 275 Italian respondents (113 men, 161 women; 1 unknown gender). Age ranged from 18 to 82 years (M = 35.01; SD = 14.61). For this sample, we also collected respondents’ educational level: 1.1% of participants had attended primary or basic school, 16.7% secondary school; 51.3% high school; and, finally, 29.5% had a university degree (1.5% did not indicate the level of education). Regarding occupations, 12.4% were manual or office workers; 28% were retailers, employees, or teachers in primary schools; 12.7% were professionals, teachers in secondary schools or academics, while 8.8% were retired, unemployed, or housekeepers. Finally, 35.6% were students (2.5% did not indicate the occupation). Measures OTH Measure The Italian version of the OTH scale is explained in Study 1. Cronbach’s α for the three orientations were .77 for pleasure, .63 for engagement, and .69 for meaning. Potentially Stressful Events Nine items assessed the experience of recent potentially stressful situations, that is, work overload, urgent organizational issues, personal health problems, health problems of close persons, family troubles, personal or close persons’ financial difficulties, changes related to work, relational problems inside the working environment, and relational problems outside the working environment. Participants were asked to indicate to what extent they faced each of these events in the preceding two months. Ratings were on a scale ranging from 1 (= not at all) to 5 (= very much). Unlike the Daily Hassles Scale (DeLongis et al., 1988), this set of items on negative events did not have the goal of measuring a construct and constituting a scale with a factor structure, so we considered it only as the occurrence of recent potentially stressful situations. Ó 2018 Hogrefe Publishing

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Satisfaction With Life Scale (SWLS) The SWLS (Diener, Emmons, Larsen, & Griffin, 1985) was used to measure one’s global life satisfaction (e.g., “So far I have gotten the important things I want in life”). The Italian version was retrieved by the set of SWLS translations reported in the website http://internal.psychology.illinois. edu/ediener/SWLS.html. Participants rated each item using a scale from 1 (= strongly disagree) to 7 (= strongly agree). The scale showed good reliability (α = .79). The Positive and Negative Affect Schedule (PANAS) The 20-item version of the PANAS (Watson, Clark, & Tellegen, 1988; Italian version by Terracciano, McCrae, & Costa, 2003) was employed to assess positive (α = .86) and negative affectivity (α = .87). Using a 5-point scale, from 1 (= not at all) to 5 (= very much), respondents indicated the extent to which they experienced each of the 20 mood states (e.g., “upset,” “excited”) during the previous weeks.

Statistical Analyses Means, standard deviations, and zero-order correlations between measures are presented in Table S2 in ESM 1. For each well-being indicator, we considered a regression model in which the predictors were socio-demographic variables (age, gender, and educational level), the three OTH, potentially stressful events, and two-way products between the latter and the three OTH. Before proceeding to the computation of two-way products, we centered at zero the means of the variables (Aiken & West, 1991). Finally, we decomposed the statistically significant interactions, computing the effects of potentially stressful situations for high vs. low (±1 SD) levels of the moderator (Aiken & West, 1991).

Results and Discussion As reported in Table 2, all the orientations to happiness were positively related to positive affect, whereas only meaning orientation showed a positive effect on life satisfaction. Besides these main effects, the goal of this study was to assess the buffering effects of the three orientations on well-being when bad events occur. Looking at the products between potentially stressful events and OTH (see Table 2), we found that only orientation to meaning had a protective effect on two well-being indicators, that is, satisfaction with life and positive affectivity. Notably, neither orientation to pleasure nor orientation to engagement exerted a relevant buffering role. The decomposition of these moderation effects (Figure 1) showed that potentially stressful events were negatively related to positive affect only with low levels of meaning Journal of Individual Differences (2018), 39(1), 27–38


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G. Fuochi et al., Orientations to Happiness and Negative Events

Table 2. Regression analyses of orientations to happiness and potentially stressful events on well-being indicators (Study 3) Satisfaction with life

Positive affect

Negative affect

B

SE

β

B

SE

β

Age

0.00

.01

.04

0.00

.00

.04

0.02

.00

Gender (= female)

0.02

.06

.02

0.10

.04

.15**

0.12

.04

.15**

Level of education

0.12

.09

.08

0.17

.06

.18**

0.10

.06

.09

Meaning

0.31

.10

.19**

0.15

.06

.13*

0.06

.07

.05

Pleasure

0.16

.09

.11

0.16

.05

.18**

0.06

.06

.06

Engagement

0.19

.11

.11

0.34

.07

.29***

0.03

.07

.02

0.41

.11

.24***

Meaning  PSE

0.28

.14

.12*

Pleasure  PSE

0.01

.14

Engagement  PSE

0.13

.16

PSE

R2

0.12

.06

0.19

.09

.01

0.06

.08

.05

0.05

.10

.16***

B

.10

SE

β .29***

0.57

.07

0.02

.09

.04

0.13

.09

.08

.03

0.15

.11

.08

.12*

.27***

.44*** .01

.29*** 2

Notes. PSE = Potentially Stressful Events. For Gender: Male = 1; Female = 2. Significance levels on the R represent the overall significance of the models assessed with F-test; *p < .05; **p < .01; ***p < .001 (all two-tailed).

Figure 1. Moderation of orientation to meaning in the relation between potentially stressful events and well-being indicators (Study 3).

(b = .25, SE = .08, t = 3.24, p = .001; for high levels of meaning: b = .01, SE = .09, t = .06, p = .952). Likewise, potentially stressful events played a negative effect on satisfaction with life only with low levels of meaning (b = .59, SE = .3, t = 4.44, p < .001), while they were not related to life satisfaction for high levels of meaning (b = .23, SE = .14, t = 1.57, p = .116). These results suggest that privileging the meaning pathway to achieve well-being may result in beneficial effects when bad events occur compared to the other pathways. There are several possible explanations for this result. First, meaningfulness-related thoughts entail mental (both spatial and temporal) simulation (Waytz, Hershfield, & Tamir, 2015) and integration of past, present, and future (Baumeister, Vohs, Aaker, & Garbinsky, 2013). Consistently with this evidence, Martela and Steger (2016) have highlighted that meaning in life has three facets, namely Journal of Individual Differences (2018), 39(1), 27–38

significance, purpose, and coherence, and two of them are future-oriented. In particular, significance involves evaluating one’s life as a whole, including past, present, and future, while purpose recalls the future life’s value, evaluated through achieved goals (Martela & Steger, 2016). As Tov and Lee (2016) suggest, such long-term commitment and projection into the future may help the individual to revaluate immediate affective (negative) experiences and to put them into a broader perspective.

General Discussion The aim of this paper was to examine whether different orientations to happiness were associated with differences in the reactions to daily hassles and other negative events, Ó 2018 Hogrefe Publishing


G. Fuochi et al., Orientations to Happiness and Negative Events

considering both the emotional reactions to a recalled selfrelevant negative event and the interactive effect of each orientation and potentially stressful events on well-being. We hypothesized that mostly orientation to meaning would lower negative emotions and increase positive emotions connected to a negative event (Study 2), and that buffering effects on recent potentially stressful events would have been observed especially for meaning (Study 3). We found support for most of our hypotheses. In Study 2, the three orientations did not have effects on negative emotions felt when thinking about a negative self-relevant event (except engagement being positively associated with fear), but orientations to meaning and to pleasure were positively related to positive emotions. In particular, meaning was associated with positive emotions characterized by lower activation (contentment and interest) compared to the ones associated with pleasure (amusement, eagerness, and happiness). Although the ability to feel also positive emotions when recalling an impactful negative event may not seem easily interpretable, several underlying mechanisms can be hypothesized. First, this ability might be linked with reappraisal: through a cognitive reevaluation, individuals might be able to attach to the past bad event not only a negative, but also a positive relevance (Gross & John, 2003). Second, individuals might be able to recall positive emotions amidst negative emotions already during stressful situations. These abilities have been found connected to trait resilience as measured by the Ego-Resiliency Scale (Block & Kremen, 1996) and with effective emotion regulation strategies (Tugade & Fredrickson, 2004). In Study 3, we found complete support for our hypothesis on the protective role of orientation to meaning on well-being. Indeed, orientation to meaning buffered the effect of recent potentially stressful events on both satisfaction with life and positive affect, whereas the other orientations did not show any buffering effect. The results emerging from Study 2 and Study 3 are consistent in two ways. First, the lack of associations with negative emotions in Study 2 and with negative affect in Study 3 may indicate that the role of orientations to happiness on well-being could be more conveyed by an enhancement of positive feelings, rather than by an attenuation of negative emotions. Second, orientation to meaning, although in different ways, confirmed its buffering role in both studies: in Study 2 it was a predictor of positive emotions characterized by low reactivity, while in Study 3 it reduced the effects of potentially stressful events on two different well-being indicators. These results are in line with the finding according to which the harmful effects of stressful events (both daily hassles and life events) on well-being are not exerted by the event itself, but by the emotional reactivity connected to events (Charles et al., 2013; Piazza et al., 2013). Ă&#x201C; 2018 Hogrefe Publishing

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The evidence that sense of meaning helps individuals coping with stressful situations is not new in the literature. Meaning in life has been proved able to promote optimal adjustment in chronic pain patients (Dezutter et al., 2015), and coping skills in people facing cancer (e.g., Lethborg, Aranda, Cox, & Kissane, 2007), or war-related posttraumatic stress disorder (Owens, Steger, Whitesell, & Herrera, 2009). The novelty of our analysis is shedding light on the mechanisms connected to orientations to happiness through which individuals react to bad events. Despite both pleasure and meaning enhancing the likelihood that an individual feels positive emotions amidst negative emotions when thinking about a self-relevant negative event, a remarkable ability connected to resilience (Tugade & Fredrickson, 2004), orientation to meaning may produce additional benefits. These benefits are reduced emotional reactivity in front of a recalled negative event, protecting well-being and health in the long term, and a buffering role in the effect of recent potentially stressful events on well-being. Summarizing, conceiving happiness as a search for meaning in life, compared to privileging engagement or pleasure as pathways to happiness, may have long-term positive consequences on an individualâ&#x20AC;&#x2122;s well-being. This is also consistent with the results of an intervention study based on increasing hedonic and eudaimonic pursuits, respectively, equivalent to pleasure and meaning: hedonic pursuits were related to higher well-being mostly in the short term, whereas the positive effect of eudaimonic pursuits appeared at 3-month follow-up (Huta & Ryan, 2010). We have to acknowledge some limitations in our analysis. First, we employed convenience, non-representative samples of Italian respondents, and thus our findings may not be necessarily generalizable to the Italian population or other cultural contexts. Second, we employed only selfreport measures, which may be affected by socially desirable responding (see Podsakoff, MacKenzie, Lee, & Podsakoff, 2003). Third, the correlational nature of our data prevents us from identifying the direction of the effects and causal relations between the variables. To overcome these limitations, future studies could rely on longitudinal data and on more sophisticated analytical strategies. Another limit stems from the use of retrospective ratings of negative events in Study 2. The self-reported negativity of the event and emotions connected to that event might be influenced by memory retrieval abilities and individual coping strategies used to deal with the negative event. Future studies could rely on diary data or experience sampling to decrease the time span between the occurrence and the reporting of the event. Lastly, our translation process did not follow all the steps of the guidelines for adapting scales (Hambleton, Merenda, & Spielberger, 2005), and this may produce an additional limitation. Journal of Individual Differences (2018), 39(1), 27â&#x20AC;&#x201C;38


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Despite these limitations, our findings suggest that differences in the way to conceive and achieve happiness might have important consequences on individual reactions to daily hassles and other negative life events. Future studies could further explore the buffering effect of orientations to happiness when potentially stressful events occur, taking into account a longer time perspective or other related constructs able to keep the well-being of the individual more resistant to negative shocks. This may be particularly relevant not only to the understanding of inner mechanisms fostering well-being in individuals facing daily life, but also to positive psychology intervention programs. Electronic Supplementary Material The electronic supplementary material is available with the online version of the article at https://doi.org/10.1027/ 1614-0001/a000246 ESM 1. Tables S1–S2 (docx). The tables show means, standard deviations, and zeroorder pairwise correlations of Study 2 and Study 3 variables. ESM 2. Figure S1 (docx). The figure shows probability densities of positive emotions and density of the fitted values after regression models (Study 2).

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Alberto Voci Department of Philosophy, Sociology, Education, and Applied Psychology University of Padova via Venezia 14 35131 Padova Italy alberto.voci@unipd.it

Received December 27, 2016 Revision received April 23, 2017 Accepted May 19, 2017 Published online January 12, 2018

Appendix Table A1. Italian version of the Orientations to Happiness (OTH) measure and standardized factor loadings Item position in the scale

Orientation

Italian item

Factor loadings

1

E

Indipendentemente da quello che sto facendo, il tempo passa molto velocemente

.38

2

M

La mia vita ha uno scopo più alto

.53

3

P

La vita è troppo breve per rimandare i piaceri che può fornire

.73

4

E

Cerco situazioni che mettano alla prova le mie competenze e capacità

.48

5

M

.38

6

E

7

E

Nel decidere cosa fare, prendo sempre in considerazione se le altre persone potranno trarne beneficio Sia al lavoro o in momenti di svago, di solito sono talmente assorbito in quello che faccio da non essere più consapevole di me stesso Sono sempre molto assorbito/a in quello che faccio

.83

8

P

Faccio di tutto per sentirmi euforico/a

.36

9

E

Nel decidere cosa fare, prendo sempre in considerazione se posso perdermi in quell’attività

.33

10

E

Vengo distratto/a raramente da ciò che mi succede attorno

.37

11

M

Ho la responsabilità di rendere il mondo un posto migliore

.68

12

M

La mia vita ha un significato stabile nel tempo

.63

13

P

Nel decidere cosa fare, prendo sempre in considerazione se sarà piacevole

.52

14

M

Ciò che faccio è importante per la società

.69

.61

15

P

Sono d’accordo con la frase: “la vita è breve – goditela!”

.73

16

P

Adoro fare ciò che stimola i miei sensi

.63

17

M

.33

18

P

Ho impiegato molto tempo a pensare a ciò che la vita significa e a come posso inserirmi in questo grande disegno Per me la bella vita è la vita ricca di piaceri

.57

Note. P = pleasure; M = meaning; E = engagement.

Journal of Individual Differences (2018), 39(1), 27–38

Ó 2018 Hogrefe Publishing


Original Article

Nonlinear Effects of Cognitive Ability on Economic Productivity A Country-Level Analysis Thomas R. Coyle,1 Heiner Rindermann,2 Dale Hancock,1 and Jacob Freeman3 1

Department of Psychology, University of Texas at San Antonio, TX, USA

2

Department of Psychology, Chemnitz University of Technology, Chemnitz, Germany Department of Sociology, Social Work, and Anthropology, Utah State University, Logan, UT, USA

3

Abstract: Cognitive capitalism theory argues that the positive effects of cognitive ability on economic productivity should increase nonlinearly, with increases in ability amplifying increases in productivity. The theory was tested using country-level indicators of cognitive ability and productivity. Cognitive ability was based on international student assessments (e.g., Program for International Student Assessment, PISA), and productivity was based on economic inputs (e.g., scientific achievements and competitiveness) and outputs (e.g., gross domestic product). As predicted, the effects of cognitive ability on all productivity measures increased nonlinearly at higher levels of ability, suggesting that higher ability levels disproportionately boost a nation’s productivity. The findings are discussed in light of standard theories of cognitive ability (e.g., Spearman’s law of diminishing returns and differentiation theories), and suggest that interventions that boost cognitive ability can have large, amplifying effects on economic productivity. Keywords: cognitive capitalism, cognitive ability, economic productivity, nonlinear effects, quadratic effects

Cognitive capitalism theory predicts that the effects of cognitive ability on economic productivity increase nonlinearly, with increasing returns of cognitive ability to productivity at higher ability levels (e.g., Rindermann & Thompson, 2011; see also, Coyle, Rindermann, & Hancock, 2016; Lubinski, 2009; Wai, 2013). The theory is based on the assumption that higher ability people contribute disproportionately to economic gains by creating innovations that amplify productivity. Such a theory contrasts with standard theories of cognitive ability (e.g., Spearman’s law of diminishing returns), which imply that the positive effects of ability on productivity decrease nonlinearly at higher ability levels (e.g., Coyle & Rindermann, 2013). These latter theories are based on the proposition that cognitive ability has diminishing returns to productivity at higher ability levels, because noncognitive factors (e.g., personality traits) drive productivity at higher ability levels. Although positive (linear) effects of cognitive ability on economic productivity have been repeatedly demonstrated (e.g., Jones, 2016; Meisenberg, 2012), the current study is the first to use country-level data to systematically examine whether the positive effects of ability on productivity increase nonlinearly at higher ability levels. The predicted nonlinear pattern would manifest in regression as a positive Ó 2018 Hogrefe Publishing

quadratic effect of ability on productivity, and would be depicted on a scatterplot (of productivity against ability) as a curve whose slope increased from lower to higher levels of ability. Such a pattern would support the predictions of cognitive capitalism, and suggest that policies boosting cognitive ability through country-level interventions (e.g., better nutrition) can have large, amplifying effects on economic productivity (e.g., Coyle et al., 2016). To examine the predictions of cognitive capitalism, cognitive ability was measured using three international standardized tests: Program for International Student Assessment (PISA), Trends in International Mathematics and Science Study (TIMSS), and Progress in International Reading Literacy Study (PIRLS). These tests are given to students throughout the world and can estimate cognitive ability at the country level. The tests yield estimates of cognitive ability that correlate strongly with adult IQs (r  .90) and also with a general intelligence (g) factor (r  .99; Coyle & Rindermann, 2013; Rindermann, 2007), which drives the predictive validity of tests (Jensen, 1998, pp. 270–305). Following prior research (Coyle et al., 2016), cognitive ability levels were estimated for two classes of people in each country: average ability classes, which represent ability levels at the 50th percentile, and intellectual classes, which Journal of Individual Differences (2018), 39(1), 39–47 https://doi.org/10.1027/1614-0001/a000247


40

represent ability levels at the 95th percentile. Intellectual classes are assumed to contribute disproportionately to economic productivity, which is strongly influenced by people with the highest ability levels (Park, Lubinski, & Benbow, 2007; Robertson, Smeets, Lubinski, & Benbow, 2010; Wai, 2013). The ability levels of both classes predicted economic inputs of productivity (science achievements, innovation, competitiveness, and economic freedom) and economic outputs of productivity (gross domestic product [GDP] and wealth). The main hypothesis was that the effects of cognitive ability on economic productivity would increase nonlinearly at higher ability levels. In particular, cognitive ability was expected to have positive quadratic effects (beyond linear effects) on productivity inputs and outputs. Based on cognitive capitalism, the effects of cognitive ability were predicted to be relatively weak at lower ability levels and to strengthen at higher ability levels. The pattern was predicted for both ability classes (average and intellectual classes), whose ability levels correlate strongly at the country level (r > .90), and for all productivity measures, which also correlate strongly at the country level (r  .74, Coyle et al., 2016). The hypothesis was tested by regressing each measure of productivity on the ability levels of different countries. If the effects of cognitive ability on productivity increase nonlinearly, then quadratic effects of ability should significantly predict productivity beyond linear effects. Moreover, the quadratic effects should be represented by a curve whose slope increases from lower to higher levels of ability. Such a pattern, if confirmed, would be the first to show that the effects of cognitive ability (on productivity) are nonlinear and would support the predictions of cognitive capitalism.

Method All data are measured at the country level (N = 99 countries) and were obtained from public sources.1 All variables have been described elsewhere (Coyle et al., 2016), and are summarized below. The data used in the analyses, and the correlations among variables, are provided as electronic supplementary material (Tables S1 and S2 in Electronic Supplementary Material, ESM 1).

Variables Cognitive Ability Cognitive ability was based on international student assessments for PISA, TIMSS, and PIRLS, from 99 countries in 1

T. R. Coyle et al., Nonlinear Effects of Cognitive Ability

years 1995–2012. The assessments measure reading, math, and science abilities in 15-year-olds (PISA); math and science abilities in fourth or eighth grade (TIMSS); and reading abilities in fourth grade (PIRLS). Results from the assessments were corrected for cross-country differences in school attendance (low attendance decreases test scores) and age at grade level (cognitive ability increases with age) (Coyle & Rindermann, 2013, pp. 407–408). In addition, results were averaged across subject (math, science, and reading), developmental level (age or grade), year (1995–2012), and assessment (PISA, TIMSS, and PIRLS; Rindermann, Sailer, & Thompson, 2009, pp. 6–7). The averages were standardized and converted to Greenwich IQs (UK IQ = 100, SD = 15). The IQs were used to estimate the ability levels of intellectual (95th percentile) and average (50th percentile) classes in each country. Compared to psychometric IQ tests, student assessments are administered to larger and more representative samples, increasing their validity as ability estimates in countries where psychometric IQ data are sparse (e.g., African countries; see Rindermann, 2013). Science, Technology, Engineering, and Math (STEM) Achievement STEM achievement was based on patent rates, Nobel Prizes, scientist rates, and high-tech export rates (Cronbach’s α = .70). Data were available for 188 countries; 97 countries also had cognitive ability data and were used here. Innovation Innovation was based on the Global Innovation Index (GII) of the World Intellectual Property Organization (Dutta & Lanvin, 2013), which measures innovations in science, technology, and the economy. The GII is based on seven country-level variables (institutions, human capital, infrastructure, market sophistication, business sophistication, technology outputs, and creative outputs). GII data were available in years 2006–2013 for 142 countries; 95 countries also had cognitive ability data and were used here. Competitiveness Competitiveness was based on the Global Competitiveness Index (GCI) of the World Economic Forum (Schwab, 2013). The GCI measures factors that determine the level of productivity of a country. It is based on 12 country-level factors (quality of institutions, quality of infrastructure, macroeconomic environment, health and primary education, higher education and training, efficient goods markets, labor market efficiency, financial market efficiency, technological readiness, market size, business sophistication, and

The same data were analyzed by Coyle et al. (2016), who examined whether economic freedom moderated the (linear) effects of cognitive ability on economic productivity. The study by Coyle et al. (2016) did not examine whether the effects of cognitive ability on productivity increase nonlinearly at higher levels of ability, the question central to the current study.

Journal of Individual Differences (2018), 39(1), 39–47

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knowledge and innovation). GCI data were available for 148 countries; 94 countries also had cognitive ability data and were used here. Economic Freedom Economic freedom was based on the Heritage Foundation Index of Economic Freedom (Miller, Holmes, & Feulner, 2013), which measures rule of law, limited government, regulatory efficiency, and open markets; and the Fraser Institute Index (Gwartney, Lawson, & Hall, 2013), which measures size of government, legal system and property rights, sound money, trade freedoms, and labor regulations. The Heritage and Fraser indices were standardized and averaged to produce a composite measure of economic freedom (Cronbach’s α = .93). Data were available in year 2013 for 182 countries; 97 of these countries also had cognitive ability data and were used here. Gross Domestic Product (GDP) GDP measures the market value of goods and services produced by a country. GDP per capita was obtained for year 2010 and converted to a log scale. The measure was based on data from the Maddison project (Maddison, 2008; 2010 GDP data from Bolt & van Zanden, 2013). The final logged GDP variable was available for 161 countries; 92 countries also had cognitive ability data and were used here. Wealth Wealth measures the market value of financial plus nonfinancial assets (housing and land), less debts, for a country. Wealth per adult was obtained for year 2013 and converted to a log scale (Credit Suisse, 2013). Wealth data were available for 174 countries; 96 countries also had cognitive ability data and were used here.

Statistical Analyses The main hypothesis was that the effects of cognitive ability on economic productivity would increase nonlinearly at higher ability levels. To test this hypothesis, regressions estimated the linear effects of ability in an initial step, followed by quadratic (nonlinear) effects of ability in a second step. Each analysis regressed a productivity measure on cognitive ability, separately for intellectual or average classes. To facilitate interpretation, all measures were standardized and centered (M = 0, SD = 1) prior to analyses (Cohen, Cohen, West, & Aiken, 2003, pp. 201–204). Linear effects involved a centered ability measure; quadratic effects involved the square of the centered ability measure. To minimize collinearity, regressions were performed separately for each productivity measure. Ó 2018 Hogrefe Publishing

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Parallel regressions predicted a “criterion G,” which measured the variance common to all productivity measures. (By convention, G refers to aggregate-level common factor variance, whereas g refers to individual-differences level common factor variance.) The criterion G was based on the first unrotated factor in principal axis factoring of all productivity measures and accounted for most of the variance in the productivity measures (variance = 80%; eigenvalue = 4.84; criterion G loadings = .71, .86, .84, .76, .83, .59, for STEM, GII, GCI, GDP, wealth, freedom, respectively). Criterion G factor scores were estimated for each country using regression, which weighted productivity measures by factor score coefficients (e.g., Tabachnick & Fidell, 2007, pp. 622–625). Key statistics were β, which measured standardized effects at each step; R2, which measured the variance explained at each step; and ΔR2, which measured the change in variance explained from the first to second step. ΔR2 measured the increment in variance explained by quadratic effects, beyond linear effects. If the effects of cognitive ability strengthen with increases in ability level (as predicted by cognitive capitalism), and if these effects manifest as quadratic effects, then quadratic effects should explain significant variance beyond linear effects. In addition, the sign of the quadratic effects should be positive, which (along with positive linear effects) would indicate that the effects of ability on productivity strengthen at higher ability levels. All effects are reported as standardized coefficients (R2 or ΔR2), with mean effects (MR2 or MΔR2) in parentheses.

Results Table 1 reports the regressions of productivity measures on linear effects of cognitive ability (Step 1), followed by quadratic effects of cognitive ability (Step 2). The results of each analysis are reported in the rows of Table 1, separately for average classes (50th percentile ability level) and intellectual classes (95th percentile ability level). A key statistic is the increment in variance explained by quadratic effects beyond linear effects (i.e., ΔR2). If the effects of ability on productivity increase nonlinearly at higher ability levels (as predicted by cognitive capitalism), quadratic effects should explain significant variance beyond linear effects (and have a positive sign). Table 1 (Average class) reports regressions for average classes (50th percentile ability level). As predicted, cognitive ability had strong linear effects at Step 1 (MR2 = .43, range = .21–.62), and modest but significant quadratic effects at Step 2 (MΔR2 = .06, range = .03–.09). In addition, the quadratic effects were slightly stronger for economic Journal of Individual Differences (2018), 39(1), 39–47


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T. R. Coyle et al., Nonlinear Effects of Cognitive Ability

Table 1. Change in R2 (ΔR2) after adding a quadratic term (Step 2) to a linear term (Step 1) for ability level Step 1 Criterion

N

2

R

βlinear

Δ Statistics

Step 2 Fmodel

2

R

βlinear

βquad

ΔR

2

Fmodel

ΔF

Average class STEM

97

.26

.51**

33.48**

.34

.69**

.34**

24.46**

.082

11.68**

Innovation

95

.62

.79**

152.47**

.71

.98**

.36**

112.63**

.089

28.20**

Competitiveness

94

.45

.67**

74.32**

.51

.82**

.29**

47.54**

.064

11.93**

Freedom

97

.21

.45**

24.54**

.28

.63**

.33**

18.48**

.077

10.09**

GDP

92

.58

.76**

123.75**

.61

.85**

.19*

68.20**

.026

5.90*

Wealth

96

.44

.66**

73.69**

.48

.79**

.24**

43.48**

.044

7.87**

Criterion G

87

.55

.74**

103.96**

.62

.90**

.31**

69.10**

.072

15.95**

Intellectual class STEM

97

.29

.54**

39.45**

.38

.70**

.33**

28.56**

.085

12.77**

Innovation

95

.66

.81**

180.41**

.73

.96**

.30**

123.84**

.069

23.54**

Competitiveness

94

.47

.69**

82.79**

.52

.80**

.25**

50.20**

.051

9.73**

Freedom

97

.24

.49**

30.59**

.33

.65**

.33**

22.86**

.084

11.76**

GDP

92

.62

.79**

149.06**

.65

.87**

.17*

81.57**

.024

5.93*

Wealth

96

.48

.69**

86.97**

.53

.80**

.25**

52.22**

.048

9.56**

Criterion G

87

.60

.77**

125.60**

.66

.89**

.27**

79.73**

.059

14.26**

Notes. Average class = average class ability levels (50th percentile); Intellectual class = intellectual class ability levels (95th percentile); STEM = achievements in science, technology, engineering, and math; Innovation = Global Innovation Index; Competitiveness = Global Competitiveness Index; Freedom = economic freedom index; GDP = gross domestic product per capita (log scale); Wealth = wealth per capita; Criterion G = factor scores based on all six productivity measures. *p < .05, **p < .01 (two-tailed).

inputs (STEM, GII, GCI, and freedom; MΔR2 = .08) than outputs (GDP and wealth; MΔR2 = .04). Results were similar for the criterion G (based on all productivity measures), which also showed significant linear (R2 = .55) and quadratic effects (ΔR2 = .07). Consistent with predictions, scatterplots indicated that the effects of cognitive ability increased nonlinearly, with increasing returns of cognitive ability to productivity at higher ability levels (Figures 1A–1G). Table 1 (Intellectual class) also reports regressions for the intellectual classes (95th percentile ability level). The results confirmed the analyses for the average classes. Cognitive ability still had strong linear effects at Step 1 (MR2 = .46, range = .21–.62), and significant quadratic effects at Step 2 (MΔR2 = .06, range = .02–.09). As before, the quadratic effects were slightly stronger for economic inputs (MΔR2 = .07) than outputs (MΔR2 = .04). Results were similar for the criterion G, which showed significant linear (R2 = .60) and quadratic effects (ΔR2 = .06). Consistent with theory, scatterplots indicated that the effects of cognitive ability strengthened at higher levels of ability (Figure 2A–2G). Differences in analogous effects for the two ability classes (intellectual-average) were very small for linear (MR2 difference = .033) and quadratic effects (MΔR2 difference = .004).2 The small differences could be attributed to the 2

strong correlation between the ability levels of the two classes (r = .98, Table S1). The significant quadratic effects were probed by computing simple effects of cognitive ability on economic productivity at five levels of ability: 2 SDs below average, 1 SD below average, average (country mean), 1 SD above average, and 2 SDs above average. Simple effects were computed separately for each productivity measure and ability class, after zero centering the linear and quadratic effects of cognitive ability (cf. Cohen et al., 2003, pp. 206–207). The simple effects measured the slope of the tangent line to the quadratic curve at a particular level of cognitive ability. Table 2 reports the simple effects, which bolstered the pattern depicted in scatterplots (Figures 1 and 2). Simple effects of ability on all productivity measures increased from lowest ( 2 SD, 1 SD) to average ability levels, and stabilized (at stronger values) from average to the highest levels (1 SD, 2 SD). The pattern was found for all productivity measures and both ability classes (grand M = .59, .68, .77, .80, .81, from lowest to highest ability levels, respectively). Differences in analogous effects for the two ability classes (intellectual – average) were trivial (Mβ difference = .01, range = .02 to .04).

Parallel regressions of STEM on cognitive ability were performed after omitting an extreme STEM value in the upper-right quadrant (Figures 1A and 2A). The value corresponded to Luxembourg, a country with very high-patent rates, which inflated its STEM rating (Rindermann et al., 2009, Table 1). Consistent with the prior results, the effects of cognitive ability on STEM still increased nonlinearly (and significantly) for average classes (ΔR2 = .12) and intellectual classes (ΔR2 = .12).

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(A)

(B)

(C)

(D)

(E)

(F)

(G)

Figure 1. Scatterplots of average class ability levels and productivity criteria. Plots are fitted with linear and quadratic curves for the six productivity measures (Panels A–F) and the criterion G (Panel G). R2 Linear = linear effects. R2 Quadratic = quadratic effects.

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T. R. Coyle et al., Nonlinear Effects of Cognitive Ability

Figure 2. Scatterplots of intellectual class ability levels and productivity criteria. Plots are fitted with linear and quadratic curves for the six productivity measures (Panels A–F) and the criterion G (Panel G). R2 Linear = linear effects. R2 Quadratic = quadratic effects.

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Table 2. Simple effects (β) between ability levels and productivity measures at different levels of ability, for average and intellectual classes 2 SD

1 SD

Average

+1 SD

+2 SD

Average class STEM

.47

.60

.67

.69

.70

Innovation

.75

.88

.96

.98

.99

Competitiveness

.54

.62

.73

.77

.79

Freedom

.35

.45

.55

.59

.61

GDP

.72

.78

.83

.85

.85

Wealth

.59

.67

.74

.77

.78

Criterion G

.65

.75

.84

.87

.88

M

.58

.68

.76

.79

.80

Intellectual class STEM

.47

.58

.68

.71

.71

Innovation

.76

.86

.94

.97

.97

Competitiveness

.56

.60

.71

.76

.78

Freedom

.39

.47

.59

.63

.65

GDP

.76

.82

.87

.88

.88

Wealth

.62

.69

.77

.79

.80

Criterion G

.68

.75

.84

.87

.88

M

.61

.68

.77

.80

.81

.59

.68

.77

.80

.81

Grand M

Notes. Average class = average class ability level (50th percentile); Intellectual class = intellectual class ability level (95th percentile); STEM = achievements in science, technology, engineering, and math; Innovation = Global Innovation Index; Competitiveness = Global Competitiveness Index; Freedom = economic freedom index; GDP = gross domestic product per capita (log scale); Wealth = wealth per capita; Criterion G = factor scores based on all six productivity measures; M = mean effect; Grand M = grand mean, averaged across all effects and ability classes. Effects are computed at the following ability levels: 2 SD (2 SD below average), 1 SD (1 SD below average), Average (country average), +1 SD (1 SD above average), and +2 SD (2 SD above average).

Discussion The current study is the first to use country-level data to systematically examine whether the positive effects of cognitive ability on economic productivity increase nonlinearly at higher levels of ability. Such a pattern is predicted by cognitive capitalism theory (Rindermann & Thompson, 2011), which predicts that higher levels of ability disproportionately account for higher levels of economic productivity. To test cognitive capitalism, economic productivity was regressed on ability levels for intellectual (95th percentile) and average classes (50th percentile), using six measures of productivity (STEM, innovation, competitiveness, freedom, GDP, and wealth). Linear effects of ability were estimated at an initial step, followed by quadratic effects at a second step, which examined whether the effects of ability increased nonlinearly at higher levels. Consistent with theory, quadratic effects of ability explained significant 3

unique variance beyond linear effects (Table 1). Moreover, the effects of ability increased sharply from the lowest to average ability levels and stabilized (at strong levels) thereafter, demonstrating increasing returns of ability to productivity (Table 2). The nonlinear effects of cognitive ability replicated for both intellectual and average classes (Table 1), suggesting that the effects apply throughout the ability spectrum. In addition, the nonlinear effects of ability replicated for all productivity measures, with slightly stronger effects for economic inputs than outputs, suggesting that cognitive ability has slightly greater impact on precursors of productivity (i.e., STEM, innovation, competitiveness, freedom). The similar effects were partly attributable to the strong relations among productivity measures, as indicated by their high loadings on a common productivity factor (i.e., criterion G; M loading = .77). This common factor reflected variance common to all productivity measures, and yielded factor scores that showed a pattern similar to the individual productivity measures (Tables 1 and 2). The results are the first to demonstrate that the effects of cognitive ability on economic productivity increase nonlinearly at higher ability levels, a pattern consistent with the predictions of cognitive capitalism theory (Rindermann, 2012). The results suggest that prior research on countrylevel differences in cognitive ability, which has examined linear effects, may have inadvertently missed nonlinear increases by excluding nonlinear (quadratic) terms from statistical models. The robustness of the results, which replicated with different measures of ability and productivity, suggests that future studies should check for nonlinear effects by including quadratic terms in statistical models. The pattern of effects is inconsistent with theories of intelligence (e.g., Spearman’s law of diminishing returns), which imply that relations of cognitive ability with various criteria should decrease nonlinearly at higher levels of ability (cf. Coyle & Rindermann, 2013; see also, Coyle, 2015). Such theories are based on the assumption that, at higher ability levels, measures of cognitive ability become less loaded with g (i.e., variance common to tests), which drives predictive validity, and more loaded with non-g factors, which contribute less to predictive validity (Jensen, 1998, pp. 270–305). The results of the current study support the opposite pattern. The effects of cognitive ability (on all productivity measures) increased nonlinearly at higher ability levels, suggesting that productivity is amplified at higher levels of ability. An alternative interpretation of the results is based on differentiation theories (e.g., Deary et al., 1996; see also, Woodley, 2012).3 Differentiation theories focus on specific abilities (e.g., math, verbal, and spatial), which are partly

We thank Michael Woodley of Menie for suggesting the alternative interpretation.

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distinct from g. According to these theories, the effects of specific abilities increase (and the effects of g decrease) at higher ability levels, a pattern that reflects cognitive specialization in narrow domains. This specialization may lead to increased divisions of labor and enhanced comparative advantage and economic efficiency, which may boost economic growth. Cognitive specialization may also contribute to the Flynn effect, which is associated with increased effects of specific abilities (rather than gains on g; te Nijenhuis & van der Flier, 2013), and is predictive of GDP growth, both across countries (Pietschnig & Voracek, 2015) and over time (Woodley, 2012). Future research could test for cognitive specialization by partitioning the effects of g and specific abilities (obtained after removing g) and examining their effects at different ability levels. According to differentiation theories, the effects of specific abilities may increase at higher ability levels, and the pattern of effects may be nonlinear, reflecting increased cognitive specialization at higher ability levels. The results indicated that the effects of cognitive ability increased disproportionately from the lowest to average ability levels, and stabilized (at strong levels) thereafter. In particular, the effects of cognitive ability changed most rapidly at the lower end of the ability spectrum and plateaued at the higher end of the spectrum. Such a pattern suggests that boosting cognitive ability through environmental interventions (e.g., adequate nutrition or better health care) may yield disproportionate gains in productivity at the lower end of the ability spectrum, where secular increases in ability are most rapid (cf. Rindermann & Thompson, 2013). The results are based on country-level ability estimates, which have drawn criticism (e.g., Wicherts & Wilhelm, 2007). One concern is that the ability estimates are based on student assessments (e.g., PISA, TIMSS, and PIRLS). Student assessments measure cognitive ability in children, who are not economically productive, and may not accurately measure ability in adults. Such a concern is minimized by strong relations between ability estimates from student assessments and adult IQs (r  .90, Rindermann, 2012), suggesting that countries with bright children tend to have bright adults. A second concern is that country-level ability estimates may be distorted by country-level differences in the timing of the Flynn effect (e.g., Pietschnig & Voracek, 2015; Rindermann & Thompson, 2013), which describes secular gains in ability levels. This concern is minimized by the temporal stability of ability estimates (r  .86, Rindermann, 2012, Figure 2), indicating that countries maintain their rank order in ability over time, which would minimize distortions from the Flynn effect. A final issue is the assumption that student assessments are weak indicators of the cognitive g factor, which measures variance common to cognitive tests and drives the predictive validity of tests (Jensen, 1998, pp. 270–305). Journal of Individual Differences (2018), 39(1), 39–47

T. R. Coyle et al., Nonlinear Effects of Cognitive Ability

In fact, student assessments load strongly on the g factor, which is based on diverse measures of ability (λ > .90; Coyle & Rindermann, 2013; Rindermann, 2007). Future research should explore nonlinear effects of ability on noneconomic criteria such as government effectiveness, disease rates, happiness, and well-being, which have been linked to linear effects of cognitive ability (Jones, 2016; see also, Lynn & Vanhanen, 2012; Rindermann, Kodila-Tedika, & Christainsen, 2015). Given the assumption that higher ability levels contribute disproportionately to outcomes, the effects of cognitive ability may increase nonlinearly for noneconomic criteria. Future research should also explore the influence of personality traits on ability and economic productivity (Heckman & Kautz, 2012). Personality traits include conscientiousness and agreeableness, which have been linked to productivity at the country level (e.g., Freeman, Coyle, & Baggio, 2016; Stolarski, Zajenkowski, & Meisenberg, 2013) and may mediate or moderate nonlinear effects of cognitive ability. For example, only countries with high levels of conscientiousness may invest the resources (e.g., research and education) needed to produce the nonlinear effects of ability. Alternatively, only countries with high levels of agreeableness may have the levels of cooperation and trust needed to produce the nonlinear effects of ability (cf. Freeman et al., 2016). In sum, the current study is the first to show that the effects of country-level cognitive ability on economic productivity increase nonlinearly at higher ability levels. The results replicated for both intellectual (95th percentile) and average (50th percentile) classes, and for all productivity measures. Future research should examine whether the nonlinear effects of ability are moderated by other factors (e.g., personality traits), and whether the effects replicate for noneconomic factors (e.g., happiness and well-being). Acknowledgments This research was supported by a grant from the National Science Foundation’s Interdisciplinary Behavioral and Social Science Research competition (Award: 1620457). Portions of the research were presented at the 2014 and 2015 conventions of the Association for Psychological Science. Electronic Supplementary Material The electronic supplementary material is available with the online version of the article at https://doi.org/10.1027/ 1614-0001/a000247 ESM 1. Tables S1 and S2 (docx). The tables report the data used in the analyses and the correlations among the variables. Ó 2018 Hogrefe Publishing


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Journal of Individual Differences (2018), 39(1), 39–47


Original Article

Adults’ Sex Difference in a Dynamic Mental Rotation Task Validating Infant Results Martin Heil,1 Markus Krüger,2 Horst Krist,2 Scott P. Johnson,3 and David S. Moore4 1

Institute of Experimental Psychology, Heinrich-Heine-University, Düsseldorf, Germany

2

Institute of Psychology, Ernst-Moritz-Arndt-Universität Greifswald, Germany Department of Psychology, University of California Los Angeles, CA, USA

3 4

Pitzer College and Claremont Graduate University, Claremont, CA, USA

Abstract: With the Mental Rotation Test (MRT), large and reliable sex differences are found. Used with children younger than about 9 or 10 years, MRT performance is at chance level. Simpler tasks used with younger children have revealed inconclusive results. Moore and Johnson (2008, 2011) observed sex differences in infants using a habituation task with 3D cube figures rotating back and forth in depth through a 240° angle. Thereafter, female infants treated similarly the original figure and a mirror-image cube figure presented revolving through the previously unseen 120° angle, whereas male infants behaved as if they recognized the familiar object. In the present study, 256 adults participated in the MRT as well as in a modified two-alternative forced-choice dynamic version of the infants’ task. Sex differences were present for both tasks. More importantly, there was a positive correlation in performance across both tasks for both women and men. Since the new task turned out to be simpler, it might be suitable also for children. We present the first, although indirect, evidence that the sex effects reported by Moore and Johnson might indeed reflect early sex differences in mental rotation. Keywords: sex difference, visual-spatial cognition, mental rotation, infant cognition

The cognitive process of imagining an object rotating in space is called mental rotation, first demonstrated in the seminal work of Shepard and Metzler (1971). Participants in that study were presented with pairs of perspective drawings of 3D cube figures and were asked to decide whether these two objects were identical or not. The authors found a linear relationship between response time (RT) and angular disparity, suggesting that the representation of the object was mentally rotated with a constant speed. Similar results were also obtained with much simpler 2D stimuli (e.g., Shepard & Cooper, 1982). Vandenberg and Kuse (1978; see Peters et al., 1995, for a modern version) used these block drawings to produce the paper-pencil Mental Rotation Test (MRT), a non-chronometric task in which participants were presented 24 items, each consisting of a 3D target block figure and four choice figures. Two of these were identical to the target figure but were rotated in depth, while the other two could not be matched by rotation. In this task, too, participants are able to provide evidence of mental rotation.

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Although the cause(s) are still far from being understood (e.g., Levine, Foley, Lourenco, Ehrlich, & Ratliff, 2016), it seems to be widely accepted that men outperform women on mental rotation tasks. However, a closer look at the data reveals that the empirical reality is much more complex. With the MRT, the sex difference indeed amounts to one standard deviation (see the meta-analysis of Voyer, Voyer, & Bryden, 1995). Sex differences turned out to be significantly larger when the test was administered with some time constraints compared to when such constraints were absent (Voyer, 2011). Tests with simpler stimuli like the 2D Card Rotation Test (CRT; Ekstrom, French, & Harman, 1976), for example, yield a substantially smaller effect size of d = 0.3, indicating the importance of the stimulus material used. Moreover, RT effects in chronometric approaches usually (e.g., Jansen-Osmann & Heil, 2007. But see Voyer et al., 2006) reveal no sex effect at all. Peters (2005), for example, preselected a sample to establish substantial and reliable sex differences in the MRT that amounted to d = 1.5. With these participants, no sex differences in RT or error rates were found for the chronometric,

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M. Heil et al., Adults’ Sex Difference in Dynamic Mental Rotation

Shepard-Metzler-like version of mental rotation with 3D cube figures used in the MRT (i.e., when pairs of perspective drawings of 3D cube figures were presented). To make things even more complicated, when the usual MRT is reduced in complexity to a paper-pencil version with pairwise presentation of the cube figures, the size of the sex effect is not affected (Titze, Heil, & Jansen, 2010). Thus, sex differences in mental rotation are unreliable when tested with protocols other than the standard MRT administered with time constraints. With the MRT, however, the situation is relatively straightforward: The sex difference is large, reliable, probably independent of participants’ cultural background (Peters, Lehmann, Takahira, Takeuchi, & Jordan, 2006), and stable over the past several decades (for meta-analyses, see e.g., Voyer, 2011; Voyer et al., 1995). Moreover, the sex difference can be found as long as the participants can complete the task, that is, it is observed with elderly people aged 60–70 years (Jansen & Heil, 2010) and also with children aged 9 or 10 years (Titze, Jansen, & Heil, 2010). Identifying the age of the onset of the sex difference is difficult, however, although this knowledge might give clues with respect to its cause(s). Unfortunately, if children are younger than 10 years, performance in the MRT approaches chance level and as a consequence no reliable sex differences can be observed (Titze, Jansen, et al., 2010). When simpler stimuli and 2D tasks are used instead of the MRT, empirical results are ambiguous. Sometimes behavioral sex differences are observed in preschoolers that are absent in other studies (e.g., Hahn, Jansen, & Heil, 2010a, 2010b; Neuburger, Jansen, Heil, & Quaiser-Pohl, 2011). These simpler 2D tasks, however, rarely yield sex differences with adults. Thus, it is unknown whether the fact that sex differences in young children are small (or even absent) is due to participants’ age or due to the type of task that was (and had to be) used. Moore and Johnson (2008; see also Quinn & Liben, 2008, 2014, for converging evidence based upon simpler 2D stimuli) observed sex differences in 5-month-old infants using a habituation task with 3D cube figures (although conflicting results exist; for a review, see Levine et al., 2016). The infants were habituated to a cube figure repeatedly revolving in depth through a 240° angle. In the test trials, the original or a mirror-image cube figure was presented revolving through the previously unseen 120° angle, thus being a new percept in either case. Whereas female 5-month-olds treated the two test forms similarly, male 5-month-olds provided evidence of recognizing the familiar object from the new perspective by looking longer at the mirror-image test object than at the familiar object. The sex difference in this novelty preference amounted to d = 0.66. Next, Moore and Johnson (2011) replicated the

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experiment with 3-month-old infants, and again female infants in the test trials treated the familiar and the mirror-image cube figures similarly. In contrast, 3-monthold male infants provided evidence of recognizing the familiar object from the new perspective, but at this age, they looked longer at the familiar test object than at the mirror-image test object. The sex difference in the younger infants’ familiarity preference amounted to d = 0.81. Moore and Johnson (2011) interpreted the familiarity preferences in younger male infants in the same way that they interpreted novelty preferences in older male infants: as evidence of mental rotation. Specifically, they argued that infants who recognized an object when it was viewed from a novel perspective must have been capable of rotating a mental representation of that object. They further argued that compared to older infants, younger infants should be expected to process habituation stimuli more slowly. Therefore, familiarity rather than novelty preferences were predictable in younger infants capable of mental rotation (in addition to seeing Moore & Johnson, 2011, for a detailed explanation of their similar interpretations of novelty and familiarity preferences, see Hunter, Ames, & Koopman, 1983, for a thorough consideration of the effects of age, stimulus complexity, and familiarization times on infants’ post-habituation novelty versus familiarity preferences). Based on these exciting results, many questions emerged, from self-evident ones like whether the sex effect observed by Moore and Johnson (2008, 2011) is reliable and robust, to far-reaching ones regarding the stability of the effect, that is, whether adults’ sex difference can be predicted by their looking behavior when they were infants, and the validity of the effect, that is, are male infants actually engaging in mental rotation during this task, questions that are very difficult to answer (see, e.g., Frick, Möhring, & Newcombe, 2014). In the present paper, we addressed three simpler but related questions: if the infants’ looking preference task is modified into an adults’ two-alternative forced choice task, (a) do we find a sex difference in behavior and (b) is that behavior related to MRT performance? If we could provide positive evidence for both possibilities, this would validate the new dynamic mental rotation task. It would open new research possibilities regarding the stability of the effect reported by Moore and Johnson (2008, 2011) since it would reduce differences between the tasks used with infants and with adults. Finally, it would also constitute first (although rather indirect) empirical evidence that the Moore and Johnson (2008, 2011) task might have measured the cognitive process of (male) infants’ mental rotation.

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Methods Participants Altogether, 256 adults (128 women and 128 men) participated. Their age ranged from 18 to 35 years (M = 23.2, SD = 3.3). Participants younger than 36 years were recruited on campus and needed to have general qualification for university entrance to be allowed to take part in this experiment. Participants studying Psychology were not allowed to take part because of the huge number of mental rotation experiments carried out in our Department. Furthermore, self-reported right-handedness was required, because handedness is correlated with mental rotation performance (see, e.g., Somers, Shields, Boks, Kahn, & Sommer, 2015). Participants were paid €3 for their participation.

Material and Procedure For this study we created a modified two-alternative forced choice adult version (called the 2AFC dynamic task) of the infant habituation task developed by Moore and Johnson (2008, 2011), which used the original videos (see Moore & Johnson, 2008) that presented a simplified block figure constructed of seven cubes. One figure was arbitrarily called the L-object whereas its mirror image was called the R-object. Two familiarization and two test videos were used. The former ones (length = 10.67 s) presented the L- or the R-object rotating back and forth at 45°/s around the vertical axis through a 240° arc, that is, after reaching its maximum extent of rotation, the object rotated back to its starting point. The test videos of the L- and R-object continued the rotation with the same speed through the previously unseen 120° of arc, continuously rotating back and forth until a response was given. Each trial consisted of two videos, a familiarization video followed after a 10 s interval by a test video. Twenty trials were presented. Ten familiarization videos used the L-object (five followed by the L- and five followed by the R-test video) and 10 used the R-object, that is, in 50% of the cases, the familiarization and test videos presented the same object successively. Participants responded “same” by pressing the left mouse button and “different” by pressing the right one. Additionally, the MRT (redrawn version of Peters et al., 1995), a paper-and-pencil test of mental rotation ability, was used. The MRT consists of two 12-item sections, each with a 3-min time limit, separated by a 3-min break. Each item consists of a row of one standard cube figure and four comparison cubes. Two comparison cube figures are correct matches rotated in depth; the remaining two are incorrect matches.

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The individual test sessions, which lasted about 30 min, took place in a laboratory at the Heinrich-Heine-University of Düsseldorf. Half of the participants (with an equal number of women and men) worked on the MRT first, the other half started with the 2AFC dynamic task. Since sequence of task had no effect (either as a main effect or in an interaction term), results are presented collapsed across this factor.

Statistical Analysis The design of the study involved “sex” (male, female) as the independent variable and “2AFC dynamic task performance” and “MRT performance,” respectively, as dependent variables. The dependent variable for the 2AFC dynamic task was the number of “same” responses to same trials minus the number of “same” responses to different trials. Thus, a score of “10” reflects perfect performance whereas guessing at the chance level is reflected by a score of “0.” The dependent variable for the MRT was the number of correct answers. An answer was correct when both correct figures were correctly selected. No point was given if only one line drawing was selected correctly. Thus, a score of “24” reflects perfect performance whereas guessing at the chance level is reflected by a score of “6.” Given a total sample size of N = 256 and a desired alpha level of α = .05 (one-tailed), effects of size d = 0.2, that is, even small sex effects as defined by Cohen (1977) could be detected with a probability of 1 β = .95. The power calculation reported was conducted using the G*Power program (Faul, Erdfelder, Lang, & Buchner, 2007).

Results Mental Rotation Test performance replicated the wellknown sex effect: Men (M = 12.30, SD = 4.63) outperformed women (M = 8.52, SD = 3.75), F(1, 254) = 51.50, p < .001. The effect size was large, d = 0.90 (95% CI = 0.64 < d < 1.15). Forty-three women (i.e., 33.6%) scored 6 points or lower (i.e., at chance level) in the MRT with no woman reaching the maximum score of 24 points. Fourteen men (i.e., 10.9%) scored 6 points or lower (i.e., at chance level) in the MRT with two men (i.e., 1.6%) reaching the maximum score of 24 points. More importantly, in the modified two-alternative forced choice (2AFC) dynamic adult version of the infant habituation task, men (M = 7.94, SD = 2.22) also outperformed women (M = 6.75, SD = 2.95), F(1, 254) = 13.21, p < .001. The effect size was medium, d = 0.46 (95% CI = 0.21 < d < 0.70). Seven women (i.e., 4.7%) scored 0 points or

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lower (i.e., at chance level) in this task with 20 women (15.6%) reaching the maximum score of 10 points. One man (i.e., 0.8%) scored 0 points or lower (i.e., at chance level) in this task with 34 men (i.e., 26.6%) reaching the maximum score of 10 points. Finally, MRT performance was significantly correlated with 2AFC-adult performance in the full sample, r = .40, and also when calculated separately both for men (r = .34) and for women (r = .38), all ps < .001. Based on a gratefully acknowledged suggestion by an anonymous reviewer, we also analyzed the data in an analysis of variance (ANOVA) based on a 2 (MRT vs. 2AFC test) by 2 (sex) by 2 (order of presentation) design after applying a z standardization separately for the two tests. In addition to a main effect of sex, F(1, 252) = 42.02, p < .01, an interaction of sex by test, F(1, 252) = 7.79, p < .01, reflected the larger sex effect size for the MRT in comparison to the 2AFC. No other main effect or interaction turned out to be significant.

Discussion Adults’ sex difference in the MRT has proven to be reliable, stable, and substantial with an effect size of about d = 1.0 when the test was administered with time constraints. With children, reliable and substantial sex differences based on the MRT have been observed when performance was above chance level, that is, when children were at least 9 or 10 years of age. With younger children, simpler tests have usually revealed ambiguous results that could either be attributed to the simpler tests or to reliable sex differences only emerging at around the age of 10 years (see e.g., Titze, Jansen, et al, 2010). Interestingly, Moore and Johnson (2008, 2011) reported sex differences in infants using a habituation-dishabituation task with dynamic 3D block figures. Obviously, many questions emerged from that (Frick et al., 2014), and the goals of the present study were to find out whether a sex difference in adults’ behavior would be found with the modified 2AFC dynamic task, and whether that behavior would be related to MRT performance. The present study replicated the large effect sizes (see Cohen, 1977) of about d = 0.90 previously reported in the MRT, indicating a fundamental sex difference comparable to the effect sizes reported in the meta-analysis by Voyer and colleagues (1995). A medium-sized sex effect was observed for our 2AFC adult version of the infant task, which was slightly smaller than the effect sizes reported by Moore and Johnson (2008, 2011). This might be due to the relatively large number of (male) adult participants with perfect performance. Ó 2018 Hogrefe Publishing

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Moreover, performance in the new task was correlated moderately with MRT performance across the entire sample and for women and men when analyzed separately. One might speculate that the correlation would have been even higher with no ceiling or floor effects in the 2AFC task or in the MRT, respectively. The new task obviously turned out to be substantially easier than the MRT and might even be slightly too easy for adults, probably due to the fact that the rotation is dynamically visible in the new task but has to be completely imagined in the MRT. Thus, it might be that the new task could be well suited even for children younger than 10 years, for whom the MRT is definitely too difficult to be used. Thus, empirical data are needed for the new task with (elementary) school children given that the new task might be suitable for a wider age range than the MRT. Our data are consistent with the hypothesis that the modified 2AFC dynamic adult version of the infant looking time task indeed involves the cognitive process of mental rotation. That does, of course, not constitute direct evidence that infants indeed used the cognitive process of mental rotation in the Moore and Johnson (2008, 2011) task; instead, the evidence for the validity of the infants’ results remains indirect. Nevertheless, the present data constitute the first indirect evidence that (male) infants might use mental rotation when choosing to preferentially fixate a mirror-image test object or a familiar test object seen from a novel perspective. More research is needed to verify this possibility, but our results suggest that it will be worth the effort. Acknowledgments We thank Michael Peters for his friendly permission to use the Mental Rotations Test (MRT) in our study. We gratefully acknowledge the helpful suggestions of two anonymous reviewers.

References Cohen, J. (1977). Statistical power analysis for the behavioral sciences. Hillsdale, NJ: Erlbaum. Ekstrom, R., French, J. W., & Harman, H. (1976). Manual for kit of factor-referenced cognitive tests. Princeton, NJ: Educational Testing Service. Faul, F., Erdfelder, E., Lang, A.-G., & Buchner, A. (2007). G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behavior Research Methods, 39, 175–191. https://doi.org/10.3758/BF03193146 Frick, A., Möhring, W., & Newcombe, N. S. (2014). Development of mental transformation abilities. Trends in Cognitive Sciences, 18, 536–542. https://doi.org/10.1016/j.tics.2014.05.011 Hahn, N., Jansen, P., & Heil, M. (2010a). Preschoolers’ mental rotation: Sex differences in hemispheric asymmetry. Journal of Cognitive Neuroscience, 22, 1244–1250. https://doi.org/10.1162/ jocn.2009.21236

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Hahn, N., Jansen, P., & Heil, M. (2010b). Preschoolers’ mental rotation of letters: Sex differences in hemispheric asymmetry. Cognitive Neuroscience, 1, 261–267. https://doi.org/10.1080/ 17588928.2010.485248 Hunter, M. A., Ames, E. W., & Koopman, R. (1983). Effects of stimulus complexity and familiarization time on infant preferences for novel and familiar stimuli. Developmental Psychology, 19, 338–352. https://doi.org/10.1037/0012-1649.19.3.338 Jansen, P., & Heil, M. (2010). Gender differences in mental rotation across adulthood. Experimental Aging Research, 36, 94–104. https://doi.org/10.1080/03610730903422762 Jansen-Osmann, P., & Heil, M. (2007). Suitable stimuli to obtain (no) gender differences in the speed of cognitive processes involved in mental rotation. Brain and Cognition, 64, 217–227. https://doi.org/10.1016/j.bandc.2007.03.002 Levine, S. C., Foley, A., Lourenco, S., Ehrlich, S., & Ratliff, K. (2016). Sex differences in spatial cognition: Advancing the conversation. Wiley Interdisciplinary Reviews – Cognitive Science, 7, 127–155. https://doi.org/10.1002/wcs.1380 Moore, D. S., & Johnson, S. P. (2008). Mental rotation in human infants: A sex difference. Psychological Science, 19, 1063–1066. https://doi.org/10.1111/j.1467-9280.2008.02200.x Moore, D. S., & Johnson, S. P. (2011). Mental rotation of dynamic, three-dimensional stimuli by 3-month-old infants. Infancy, 16, 435–445. https://doi.org/10.1111/j.1532-7078.2010.00058.x Neuburger, S., Jansen, P., Heil, M., & Quaiser-Pohl, C. (2011). Gender differences in pre-adolescent’s mental rotation performance: Do they depend on grade und stimuli? Personality and Individual Differences, 50, 1238–1242. https://doi.org/10.1016/ j.paid.2011.02.017 Peters, M. (2005). Sex differences and the factor of time in solving Vandenberg and Kuse mental rotation problems. Brain and Cognition, 57, 176–184. https://doi.org/10.1016/j.bandc.2004. 08.052 Peters, M., Laeng, B., Latham, K., Jackson, M., Zaiyouna, R., & Richardson, C. (1995). A redrawn Vandenberg and Kuse mental rotations test: Different versions and factors that affect performance. Brain and Cognition, 28, 39–58. https://doi.org/ 10.1006/brcg.1995.1032 Peters, M., Lehmann, W., Takahira, S., Takeuchi, Y., & Jordan, K. (2006). Mental rotation test performance in four crosscultural samples (n = 3367): Overall sex differences and the role of academic program in performance. Cortex, 42, 1005–1014. https://doi.org/10.1016/S0010-9452(08)70206-5 Quinn, P. C., & Liben, L. S. (2008). A sex difference in mental rotation in young infants. Psychological Science, 19, 1067–1070. https://doi.org/10.1111/j.1467-9280.2008.02201.x Quinn, P. C., & Liben, L. S. (2014). A sex difference in mental rotation in infants: Convergent evidence. Infancy, 19, 103–116. https://doi.org/10.1111/infa.12033

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Shepard, R. N., & Cooper, L. A. (1982). Mental images and their transformations. Cambridge, MA: MIT Press. Shepard, R. N., & Metzler, J. (1971). Mental rotation of threedimensional objects. Science, 171, 701–703. https://doi.org/ 10.1126/science.171.3972.701 Somers, M., Shields, L. S., Boks, M. P., Kahn, R. S., & Sommer, I. E. (2015). Cognitive benefits of right-handedness: A metaanalysis. Neuroscience and Biobehavioral Reviews, 51, 48–63. https://doi.org/10.1016/j.neubiorev.2015.01.003 Titze, C., Heil, M., & Jansen, P. (2010). Pairwise presentation of cube figures does not reduce gender differences in mental rotation performance. Journal of Individual Differences, 31, 101–105. https://doi.org/10.1027/1614-0001/a000018 Titze, C., Jansen, P., & Heil, M. (2010). Mental rotations performance and the effect of gender in fourth graders and adults. European Journal of Developmental Psychology, 7, 432–444. https://doi.org/10.1080/17405620802548214 Vandenberg, S. G., & Kuse, A. R. (1978). Mental rotations, a group test of three-dimensional spatial visualization. Perceptual and Motor Skills, 47, 599–604. https://doi.org/10.2466/pms.1978. 47.2.599 Voyer, D. (2011). Time limits and gender differences on paper-andpencil tests of mental rotation: A meta-analysis. Psychonomic Bulletin & Review, 18, 267–277. https://doi.org/10.3758/ s13423-010-0042-0 Voyer, D., Butler, T., Cordero, J., Brake, B., Silbersweig, D., Stern, E., & Imperato-McGinley, J. (2006). The relation between computerized and paper-and-pencil mental rotation tasks: A validation study. Journal of Clinical and Experimental Neuropsychology, 28, 928–939. https://doi.org/10.1080/ 13803390591004310 Voyer, D., Voyer, S., & Bryden, M. P. (1995). Magnitude of sex differences in spatial abilities: A meta-analysis and consideration of critical variables. Psychological Bulletin, 117, 250–270. https://doi.org/10.1037/0033-2909.117.2.250 Received February 28, 2017 Revision received May 29, 2017 Accepted June 15, 2017 Published online January 12, 2018 Martin Heil Institute of Experimental Psychology Heinrich-Heine-University Universitätsstr. 1 40225 Düsseldorf Germany martin.heil@hhu.de

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Original Article

CHC Model According to Weiss Evidence From the WAIS-IV Administration to Italian Adults and Elders Lina Pezzuti,1 Margherita Lang,2,3 Serena Rossetti,1 and Clara Michelotti3 1

Department of Dynamic and Clinical Psychology, Sapienza University of Rome, Italy

2

Department of Psychology, Milano-Bicocca University, Milan, Italy

3

Association for Research in Clinical Psychology (ARP), Milan, Italy Abstract: The Italian version of the Wechsler Adult Intelligence Scale – Fourth Edition (WAIS-IV) – was standardized using a sample of 2,174 participants, aged between 16 and 90 years. The WAIS-IV consists of 10 core subtests and 5 supplemental subtests. While the 70–90 yr group is usually excluded from three of the five supplemental subtests (Letter-Number Sequencing, Figure Weights, and Cancellation), we administered all 15 subtests both to adults and elderly people. The aim of the present study was to investigate the factorial invariance of the Weiss and colleagues’ hierarchical five-factor CHC (Cattell-Horn-Carroll) model in Italian adults and elders. The overall results of this study generally support both the configural and factorial invariance of the WAIS-IV, and hence the five-factor CHC model of Weiss is equivalent in adults and elderly people. However, for the elderly sample we found higher loadings of WAIS-IV subtests on the second-order g factor. Keywords: CHC model, intelligence, WAIS-IV, multigroup confirmatory factor analysis

The Cattell-Horn-Carroll theory of cognitive abilities (CHC) is currently considered one of the most comprehensive models of cognitive functioning, as well as one of the most agreed with psychometric-based models of human cognitive abilities (Alfonso, Flanagan, & Radwan, 2005). In the late 1990s McGrew proposed an integration between the Gf-Gc Cattell and Horn model (Horn & Noll, 1997), and the three-stratum Carroll theory (1993). We must point out that many authors, including McGrew, have described the model’s evolution, which allows a different approach to the assessment of intelligence from a psychometric perspective. We refer the interested reader to McGrew (2009), Flanagan and Harrison (2012), McGrew, LaForte, and Schrank (2014). The integrated model has been presented in the Woodcock-Johnson (WJ) III Technical Manual (Woodcock, McGrew, & Mather, 2001a) and is described as “an amalgamation of two similar theories about the content and structure of human cognitive abilities” (Woodcock et al., 2001a, p. 9). The first version of the CHC model – in addition to the g factor – included both narrow and broad abilities. Broad abilities are: Crystallized Intelligence (Gc), Visual Processing (Gv), Quantitative Knowledge (Gq), Reading & Writing Ability (Grw), Short-Term Memory (Gsm), Fluid Reasoning (Gf), Processing Speed (Gs), Long-Term Storage and Ó 2018 Hogrefe Publishing

Retrieval (Glr), Auditory Processing (Ga), and Decision/ Reaction Time/Speed (Gt). Multiple narrow abilities underlie each broad ability (McGrew, 1997, 2014). The model was revised several times (Flanagan, McGrew, & Ortiz, 2000; McGrew & Flanagan, 1998; Schneider & McGrew, 2012) until 2014, when McGrew, LaForte, and Schrank proposed the CHC model v 2.5. They were inclined to an extension of the CHC taxonomy into new unexplored, or so far partially explored domains, for example, General (domain-specific) Knowledge (Gkn), Tactile abilities (Gh), Kinesthetic abilities (Gk; Danthiir, Roberts, Pallier, & Stankov, 2001; Stankov, 2000), and the three broad Processing Speed Abilities, (Processing speed [Gs], Decision/ Reaction time or speed [Gt], and Psychomotor speed [Gps]). Abilities are operationalized in line with Hempel’s claims (1965) at the American Psychopathological Association conference in 1959. Both a universal taxonomy of cognitive abilities and a single classification have been created for the first time: “The viability and success and ever-growing popularity of CHC theory is rooted largely in the fact that it has created a landscape that has enhanced theoretical and psychometric development by clearly delineating factors, tests that measure those factors, test that do not measure them, and language common to all that reduce confusion and ambiguity” (Ortiz, 2015, p. 224). Journal of Individual Differences (2018), 39(1), 53–59 https://doi.org/10.1027/1614-0001/a000249


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As can be deduced from the troubling issues concerning the connection between theories of intelligence and clinical measures, the critical point was to adapt old intelligence tests to new theories. Except the third and the fourth edition of the Woodcock-Johnson Battery (McGrew, LaForte, & Schrank, 2014; Woodcock, McGrew, & Mather, 2001a, 2001b), the majority of test for adults were not constructed to measure cognitive abilities described by the model. Although the Wechsler Adult Intelligence Scale – Fourth Edition (WAIS-IV) represents a significant revision of Wechsler Adult Intelligence Scale – Third Edition (WAIS-III), and it is more psychometrically and theoretically grounded (Lichtenberger & Kaufman, 2013), the scale still presents some important limitations, especially concerning the relation between test interpretation and contemporary theories of cognitive abilities. The American and Italian factorial analyses consistently highlighted a four-factor structure that leads to the identification – in addition to the IQ – of four partial composite scores: the Verbal Comprehension Index (VCI), the Visual-Perceptual Reasoning Index (PRI), the Working Memory Index (WMI), and the Processing Speed Index (PSI). Score interpretation is possible only if the values they consist of are homogeneous (Wechsler, 2008a; Orsini & Pezzuti, 2013a, 2013b; Orsini, Pezzuti, & Hulbert, 2015). Some studies showed that CHC-based models are equally or more adequate than the four-factor scoring structure of the US sample (Benson, Hulac, & Kranzler, 2010; Weiss, Keith, Zhu, & Chen, 2013). Weiss and colleagues suggested that the WAIS-IV subtest scores measure five CHC factors: Fluid Reasoning (Gf; Matrix Reasoning, Figure Weights), Comprehension-Knowledge (Gc; Vocabulary, Similarity, Information, Comprehension), Visual Processing (Gv; Block Design, Visual Puzzle), Short-term Memory (Gsm; Digit Span, Letter-Number Sequencing), and Processing Speed (Gs; Symbol Search, Coding). Weiss and colleagues’ analyses (2013) highlight two elements on which attention should be focused: (1) WAIS-IV properly measures five broad abilities of CHC model only if the clinician administrates three additional subtests: Letter-Number Sequencing, Figure Weights, and Cancellation. In the USA WAIS-IV edition, however, these three subtests are not expected to be administered to subjects aged over 69 years: therefore, it is not possible for the clinician to adequately measure the CHC broad abilities of Fluid Reasoning (Gf), Short-Term Memory (Gsm), and Processing Speed (Gs) in this population, by using WAIS-IV only. The decision to exclude Letter-Number Sequencing, Figure Weights, and Cancellation subtests for such populations is not adequately substantiated in

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the Technical and Interpretive Manual of WAIS-IV (Wechsler, 2008b) and in scale Wechsler literature (Pezzuti & Rossetti, 2017). In the WAIS-IV analysis, if an older adult spoils a subtest from the WMI or from the PSI, the Index score cannot be calculated. The choice to administer these three subtests to the Italian sample allows the Italian clinician to resort to additional subtests for all age groups whenever this may be clinically useful or when a core subtest is invalidated (Pezzuti & Rossetti, 2017). The administration of all 15 subtests to the Italian elderly did not prove to be particularly tiring for them, given the rule of interrupting the subtest after a number of errors (which in the elderly take place before the adults) and the possibility of administering the WAIS-IV in two separate and neartime sessions. It must be said, however, that there is a paper of Niileksela, Reynolds, and Kaufman (2013) which showed a CHC five-factor solution could be obtained in older adults without administering supplementary subtests by splitting Digit Span Forward and Backward into separate subtests. But their results show that the alternative CHC model fits the data with a partial strict measurement invariance across the life span (similarities showed non-invariance). We believe that administering the three additional subtests LetterNumber Sequencing, Figure Weights, and Cancellation to the elderly can also make the five CHC factors stronger as well grown for adults by Weiss et al. (2013). (2) Subtests included in the Perceptual Reasoning Index measure two different CHC broad abilities: Block Design and Visual Puzzle measure the Visual Processing (Gv) ability, Matrix Reasoning and Figure Weights – which is an additional PRI subtest – measure the Fluid Reasoning (Gf) ability. The application of the CHC model to WAIS-IV can assist clinicians in interpreting results, because it allows to separately measure Fluid Reasoning (Gf) and Visual Processing (Gv). By doing so, clinicians can better identify a subject’s cognitive strengths and weaknesses. Moreover, it is particularly useful to separately assess these two CHC broad abilities when PRI is not interpretable because of the extreme variability of the subtests that compose it (Orsini et al., 2015). Benefits that can derive from the use of the CHC model in the interpretation of the WAIS-IV results led us: (1) to replicate the factorial analysis on the Italian standardization sample to verify the presence of a five-factor structure, and (2) to test the measurement invariance between adults and elders on the hierarchical five-factor CHC model of the Weiss and colleagues (2013), using all 15 subtests of WAIS-IV, by means of a multigroup confirmatory factor

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L. Pezzuti et al., CHC Model in Italian Adults and Elders

analysis. This assessment was achieved because, unlike Weiss and colleagues (2013), the authors of the Italian version administered Letter-Number Sequencing, Figure Weights, and Cancellation supplementary subtests also to subjects aged between 70 and 90 years (Pezzuti & Rossetti, 2017). Nowadays a number of contemporary neuropsychological and intellectual functioning measures have normative data through approximately age 90, but until years 1990 normative data were extended only to age 74 at most. Since the age of the elderly population is moving far above the age of 70, the extended normative data are of obvious clinical utility and it is important to encourage older people to perform to their maximal level, without forgetting that the evaluation of the elderly involves specific cautions (Woodard, 2010).

Method Participants The Italian standardization sample of the Wechsler Adult Intelligence Scale – Fourth Edition (WAIS-IV) included 2,174 volunteer, normal healthy participants from 16 to 90 years (1,072 males and 1,102 females). In particular, 1,424 subjects were subdivided into nine age groups ranging from 16 to 69 years old (Orsini & Pezzuti, 2013b), and 750 subjects were subdivided into four age groups ranging from 70 to 90 years old (Orsini & Pezzuti, 2015). For both Italian WAIS-IV standardization samples all 15 subtests were administered.

Statistical Analyses Age standardized scores (or weighted scores) were used as input for data analysis. Using confirmatory factor analysis (CFA) we tested a hierarchical model with one general factor (g), five broad first-order factors (VCI-Gc, POI-Gv, FRI-Gf, WMI-Gsm, and PSI-Gs), and one narrow factor (RQ). To study the factorial invariance between adults and elder samples all analyses are consistent with the steps in testing for string factorial invariance: all procedures were based on the analyses of MACS within the framework of CFA modeling. According to Chen, Sousa, and West (2005) procedure, we tested the invariance of the factorial pattern (configural invariance), of factor loadings (metric invariance), of intercepts (scalar invariance), and of residual variance (strict factorial invariance). Partial measurement invariance tests the configural, metric, scalar, and strict factorial invariance when some parameters vary between groups. Successively, we indicated the loadings of Ó 2018 Hogrefe Publishing

55

WAIS-IV subtest on the second-order g factor. The EQS 6.1 (Bentler, 2005) program were used for all analyses.

Results In order to study the factorial invariance between adult and elderly sample, skewness, kurtosis, and KolmogorovSmirnov tests for each subtest by age were computed and they are presented in Table 1. Skewness ranged from 0.01 to 0.02 for adults and from 0.27 to 1.95 for elders; kurtosis ranged from 0.24 to 0.14 for adults and from 0.27 to 1.65 for elders. These skewness and kurtosis values are pretty negligible, and are statistically significant at the Kolmogorov-Smirnov test primarily because of the large N. Indeed, one rule of thumb is skewness < 2 and kurtosis < 7 is fine in SEM (West, Finch, & Curran, 1995). However, we have decided to not only report w2 but also use a robust statistic (e.g., Satorra-Bentler scaled chi-square statistic, S-Bw2; see Yuan & Bentler, 2000). Table 2 shows the goodness-of-fit indexes of model used to test measurement invariance across two age groups: seven multigroup models were tested across adults and elders. We can see that all the seven models present an excellent fit to the data with resulting ΔCFI values (the use of ΔCFI is supported by Cheung & Rensvold, 2002) never exceeding .01 and ΔMcDonald’s values exceeding .02 only for invariance of intercepts of first-order factor and for invariance of residual variance of observed variables. From these results, we concluded that the hierarchical CHC five-factor model of Weiss et al. (2013), as portrayed in Figure 1, that has an excellent good fit to the data, was operating equivalently across the adults and elders. For this model, subtest loadings on g are shown in Table 3. According to results of Weiss et al. (2013) Cancellation subtest had the lowest loading on g for adults’ sample. On the contrary for the elderly sample, all subtests showed higher loading on g factor.

Discussion and Conclusion The Cattell-Horn-Carroll theory of cognitive abilities (CHC) is currently considered one of the most comprehensive models of cognitive functioning, but it “need not to be seen as the final word on the matter” (Ortiz, 2015, p. 225). It is considered a model that is continuously reorganized and restructured on the base of current research (Flanagan & Dixon, 2013). The model’s relevance in clinical and psychometric settings is also highlighted by the numerous studies conducted, analyzing it in relation to gender, ethnic and Journal of Individual Differences (2018), 39(1), 53–59


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Table 1. Normality of 15 core and supplemental subtests in the Wechsler Adult Intelligence Scale – Forth Edition Adult sample (N = 1,424)

Elderly sample (N = 750)

Indices

Subtest

Sk

Ku

K-S’ d

Sk

Ku

Verbal Comprehension Index (VCI)

Similarity

0.01

0.19

.07*

0.03

0.34

.09*

Vocabulary

0.01

0.14

.07*

0.62

0.26

.14*

Comprehension

0.01

0.13

.07*

0.77

0.17

.15*

a

0.01

0.23

.09*

1.09

0.18

.25*

Block design

0.01

0.22

.07*

0.36

0.22

.09*

Matrix reasoning

0.00

0.21

.08*

0.82

0.88

.14*

Visual puzzle

0.00

0.20

.08*

1.95

1.65

.18*

Figure weightsa

0.01

0.23

.09*

0.62

0.74

.15*

Picture completiona

0.01

0.17

.08*

0.74

0.35

.17*

Digit span

0.02

0.19

.09*

0.52

0.34

.13*

Arithmetic

0.01

0.24

.09*

0.44

0.29

.09*

Letter-number sequencesa

0.02

0.15

.08*

0.27

0.27

.11*

Symbol search

0.02

0.16

.07*

0.62

0.61

.12*

Coding search

0.00

0.14

.07*

0.90

0.84

.15*

Cancellationa

0.00

0.16

.07*

0.52

0.77

.12*

Information Perceptual Reasoning Index (PRI)

Working Memory Index (WMI)

Processing Speed Index (PSI)

K-S’ d

Note. aSupplemental subtests; Sk = skewness; Ku = kurtosis; K-S’ d = Kolmogorov-Smirnov test for normality. *p < .01 (two-tailed).

Table 2. Tests of invariance of WISC-IV (15 core and supplemental subtests) hierarchical structure between adults and elders Model fit

Model fit comparison

w2

S-Bw2

df

*CFI

RMSEA

RMSEA 90% CI

McDonald’s fit Index

1. Configural invariance

832.143

777.615

162

.951

.059

[.055, .063]

.868

2. Invariance of first-order factor loadings 3. Invariance of first- and second-order factor loadings 4. Invariance of intercepts of measured variables 5. Invariance of intercepts of first-order factors 6. Invariance of residual variances of first-order factors 7. Invariance of residual variance of observed variables

887.068

828.519

174

.948

.059

[.055, .063]

.860

2 vs. 1

.003

.008

949.445

881.675

180

.944

.060

[.056, .064]

.851

3 vs. 2

.004

.009

952.279

889.349

195

.944

.060

[.056, .064]

.850

4 vs. 3

.000

.001

1,070.222

998.665

202

.935

.065

[.061, .069]

.829

5 vs. 4

.009

.021

1,176.406

1,103.494

208

.927

.067

[.063, .071]

.811

6 vs. 5

.008

.018

1,249.202

1,244.095

223

.919

.070

[.066, .073]

.786

7 vs. 6

.008

.025

Model

Model comparison

ΔCFI –

ΔMcDonald –

Notes. w2 = Chi-square statistic; S-Bw2 = Satorra-Bentler scaled chi-square statistic; *CFI = robust comparative factor index; RMSEA = robust root mean square error of approximation; ΔCFI  .01 (in absolute terms) indicates that the null hypothesis of invariance should not be rejected; ΔMcDonald  .02 (in absolute terms) indicates that the null hypothesis of invariance should not be rejected. ΔCFI < .01 (in absolute terms) and ΔMcDonald < .02 (in absolute terms) are in bold characters.

cultural groups, and the different stages of life of participants (e.g., Bickley, Keith, & Wolfe, 1995; Carroll, 1993; Gustafsson & Balke, 1993; Keith, 1997, 1999; Woodcock et al., 2001a, 2001b). The aim of our study was to investigate the factorial invariance of the Weiss and colleagues’ hierarchical five-factor CHC model (2013) in Italian adults and elders using all 15 subtests of WAIS-IV, by means of a multigroup confirmatory factor analysis. Since the authors of the Italian version administered Letter-Number Sequencing, Figure Weights, and Cancellation supplementary subtests also to subjects

Journal of Individual Differences (2018), 39(1), 53–59

aged between 70 and 90 years (Pezzuti & Rossetti, 2017), it has been possible, using all 15 subtests of WAIS-IV, to verify the CHC model for subjects aged over 69 years. Three conclusions can be deduced from the results of the analyses: (1) our results indicate a measurement invariance across two considered age groups (16–69 and 70–90 years) concluding that the hierarchical CHC five-factor model of Weiss et al. (2013) has an excellent fit to the data and was operating equivalently across the adults and elders. This is important because some

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Figure 1. Final standardized estimations of adults and elders (in parenthesis) performance on the 15 core and supplemental subtest of WAIS-IV. VCI = Verbal Comprehension Index; Gc = Crystallized Intelligence; POI = Perceptual Organization Index; Gv = Visual Processing; FRI = Fluid reasoning Index; Gf = Fluid Intelligence; WMI = Working Memory Index; Gsm = Short-Term Memory; PSI = Processing Speed Index; Gs = Processing Speed; g = General Intelligence. For adults: S-Bw2 (Satorra-Bentler scaled chi square statistic) = 414.99, df = 81; CFI (robust comparative factor index) = .96; SRMR (standardized root mean square residual) = .04; RMSEA (robust root mean square error of approximation) = .05; RMSEA 90% CI [.049, .059]. For elders: S-Bw2 = 358.30, df = 81; CFI = .95; SRMR = .04; RMSEA = .07; RMSEA 90% CI [.060, .075].

Table 3. Loadings of WAIS-IV subtests on the second-Order g factor for adults and elders Loading on g Adult sample (N = 1,424)

Elderly sample (N = 750)

Similarity

.647

.751

Vocabulary

.716

.799

Comprehension

.670

.775

Subtest

Informationa

.619

.729

Block design

.594

.675

Matrix reasoning

.629

.778

Visual puzzle

.682

.702

Figure weightsa

.730

.713

Picture completiona

.537

.686

Digit span

.660

.735

Arithmetic

.692

.689

Letter-number sequencesa

.655

.785

Symbol search

.579

.743

Coding search

.525

.764

.347

.614

Cancellation

a

Note. aSupplemental subtests.

authors have not agreed that five-factor model was a better solution than four factors (e.g., Ward, Bergman, Ó 2018 Hogrefe Publishing

& Herbert, 2012). So, in light of the well-established structural validity of CHC model, external validity support for the various CHC constructs, derived through future research, can be used confidently to guide clinical interpretation of WAIS-IV performance on 15 subtests both with adults and elders. (2) About the elderly sample all subtests showed higher loading on g factor; this result could be interpreted as an effect of dedifferentiation hypothesis, which postulates that cognitive variables and abilities become less distinct (less differentiated) with increased age (e.g., de Frias, Lovden, Lindenberger, & Nilsson, 2007; Ghisletta & de Ribaupierre, 2005; Ghisletta & Lindenberger, 2003). The future research (also with longitudinal method) can deepen whether cognitive change with age operates primarily at the level of specific individual variables, the level of a first-order cognitive ability, or the level of a higher-order general (g) factor, and whether the relative influences on change from these levels vary as a function of age (Salthouse, 2012). (3) It has been possible for the Italian clinician, evaluating a subject aged over 69 years, to measure broad abilities of the CHC model – Fluid Reasoning (Gf) and Journal of Individual Differences (2018), 39(1), 53–59


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Short-Term Memory (Gsm) – by administering 9 core and 2 additional subtests, for a total of only 11 subtests instead of 10. Indeed, if the Italian clinician holds that it is important to assess Short-Term Memory (Gsm) and Fluid Reasoning in a subject from 70 to 90 years, he can replace the Arithmetic subtest with the Letter-Number Sequencing one – which is a better measure of the Short-Term Memory (Gsm) broad ability – and administer the Figure Weights subtest to assess Fluid Reasoning (Gf) properly.

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Structural equation modeling: Concepts, issues, and applications. Thousand Oaks, CA: Sage. Woodard, J. L. (2010). Geriatric neuropsychological assessment. In P. A. Lichtenberg (Ed.), Handbook of assessment in clinical gerontology (pp. 461–501). London, UK: Elsevier. Woodcock, R. W., McGrew, K. S., & Mather, N. (2001a). Woodcock Johnson III. Rolling Meadows, IL: Riverside. Woodcock, R. W., McGrew, K. S., & Mather, N. (2001b). WoodcockJohnson III tests of achievement. Rolling Meadows, IL: Riverside. Yuan, K. H., & Bentler, P. M. (2000). Three likelihood-based methods for mean and covariance structure analysis with nonnormal missing data. Sociological Methodology, 30, 165–200. Received January 10, 2017 Revision received May 26, 2017 Accepted June 14, 2017 Published online January 12, 2018

Lina Pezzuti Department of Dynamic and Clinical Psychology Sapienza University of Rome Via dei Marsi 78 00185 Rome Italy lina.pezzuti@uniroma1.it

Journal of Individual Differences (2018), 39(1), 53–59


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Integrative perspectives on motivation and volition “This is an excellent and valuable volume. It is a wonderful collection of pieces on motivation that serves as an apt tribute to an unusually creative and generous scholar.” Andrew J. Elliot, PhD, Professor of Psychology, Department of Clinical & Social Sciences in Psychology, University of Rochester, NY, USA

Nicola Baumann / Miguel Kazén / Markus R. Quirin / Sander L. Koole (Editors)

Why People Do the Things They Do Building on Julius Kuhl’s Contributions to the Psychology of Motivation and Volition 2018, xii + 434 pp. US $87.00 / € 69.95  ISBN 978-0-88937-540-6 Also available as eBook How can we motivate students, patients, employees, and athletes? What helps us achieve our goals, improve our well-being, and grow as human beings? These issues, which relate to motivation and volition, are familiar to everyone who faces the challenges of everyday life. This comprehensive book by leading international scholars provides integrative perspectives on motivation and volition that build on the work of German psychologist Julius Kuhl. The first part of the book examines the historical trail of the European and American research traditions of motivation and volition and their integration in Kuhl’s theory of personality systems interactions (PSI). The sec-

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ond part of the book considers what moves people to action – how needs, goals, and motives lead people to choose a course of action (motivation). The third part of the book explores how people, once they have committed themselves to a course of action, convert their goals and intentions into action (volition). The fourth part shows what an important role personality plays in our motivation and actions. Finally, the fifth part of the book discusses how integrative theories of motivation and volition may be applied in coaching, training, psychotherapy, and education. This book is essential reading for everyone who is interested in the science of motivating people.


Start using strengths today! “The GO-TO book for building character.” Martin E. P. Seligman, the founder of positive psychology

Ryan M. Niemiec

Character Strengths Interventions A Field Guide for Practitioners 2018, xx + 300 pp. US $59.00 / € 46.95 ISBN 978-0-88937-492-8 Also available as eBook This book is the epitome of positive psychology: it takes the “backbone” of positive psychology – character strengths – and builds a substantive bridge between the science and practice. Working with clients’ (and our own) character strengths boosts well-being, fosters resilience, improves relationships, and creates strong, supportive cultures in our practices, classrooms, and organizations. This unique guide brings together the vast experience of the author with the science and the practice of positive psychology in such a way that both new and experienced practitioners will benefit. New practitioners will learn about the core concepts of character and signature strengths and how to fine-tune their approach and troubleshoot. Experienced practitioners will deepen their knowledge about advanced topics such as strengths overuse and collisions, hot button issues, morality, and integrating strengths with savoring,

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flow, and mindfulness. Hands-on practitioner tips throughout the book provide valuable hints on how to take a truly strengths-based approach. The 24 summary sheets spotlighting each of the universal character strengths are an indispensable resource for client sessions, succinctly summarizing the core features of and research on each strength. 70 evidence-based step-by-step activity handouts can be given to clients to help them develop character strengths awareness and use, increase resilience, set and meet goals, develop positive relationships, and find meaning and engagement in their daily lives. No matter what kind of practitioner you are, this one-of-a-kind field guide is a goldmine in science-based applications. You’ll be able to immediately bring the science of well-being into action!

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Journal of Individual Differences 1/2018  

Journal of Individual Differences 1/2018