شخصیت و بهزیستن ذهنی: یک مدل غفلت از شخصیت و دو جنبه فراموش شده از بهزیستن ذهنی

Abstract Previous research on the relations between personality and subjective well-being (SWB) often overlooked the distinction between the affective and cognitive components of SWB. The main aim of this study was to investigate the role of personality traits in predicting separately affective well-being and satisfaction with life. We used Zuckerman’s Alternative Five Factor Model of Personality, which is rarely used as a framework to operationalize personality traits in the field of SWB. Results of this research clearly show that personality traits have different predictive power in explaining individual differences in affective well-being and satisfaction with life. None of the personality traits had a unique contribution in explaining satisfaction with life, showing that they do not have a direct effect on the cognitive aspect of well-being. On the other hand, Neuroticism-Anxiety and Activity proved to have a direct effect on the affective component of SWB. Theoretical and practical implications of the results were discussed.

1. Introduction Subjective well-being (SWB) is one of the most attractive fields in modern psychology. A sudden increase of interest for studying this phenomenon has especially been expressed in the last 10 years, from establishing positive psychology as a scientific discipline (Seligman and Csikszentmihalyi, 2000 and Snyder and Lopez, 2002) and recognizing the significance of SWB on the level of an individual and the society as a whole (e.g. Diener and Seligman, 2004 and Veenhoven, 2004). Instant popularisation of the research into SWB made it a potentially risky field that could descend into chaos. According to our opinion, in the domain of SWB, there are at least two mutually related inconsistencies: terminological and conceptual, that create quite a confusion in this field. Firstly, among the researchers there is no uniform use of the terms when it comes to the phenomena that refer to SWB. Some of the most famous researchers in this field use the term happiness as a synonym for SWB (e.g. Lyubomirsky, Sheldon, & Schkade, 2005). On the other hand, there are authors who use the term happiness in a more specific meaning – either in the sense of positive affect or in the sense of satisfaction with life (e.g. Steel, Schmidt, & Shultz, 2008). Inconsistent and non-universal use of the terms is particularly problematic in the context of investigating individual differences in SWB, since it limits the generalizability of the results obtained. Despite considerable terminological chaos, researchers have a unique opinion on what the SWB structure consists of. Summarizing previous research, Diener (1984) has defined SWB as a construct, which consists of three components: satisfaction with life, positive affect and a low level of negative affect. Satisfaction with life represents the cognitive aspect of SWB and it refers to global evaluation of a person on how his/her life looks like (Diener, Suh, & Oishi, 1997). Positive affect implies frequent experiences of pleasant emotions, and low level of negative affect implies a relative absence of unpleasant emotional states. Such a tripartite structure of SWB was confirmed in a number of studies (e.g. Arthaud-Day et al., 2005 and Lucas et al., 1996). Therefore, the essential theoretical conceptualization of SWB is represented by a distinction between the affective and cognitive components of this construct (Diener, Suh, Lucas, & Smith, 1999), which are related but still can be distinguished on several levels (Schimmack, 2008). However, previous research on the relations between personality and subjective well-being (SWB) often overlooked this distinction. There are a number of research reports on personality traits as predictors of SWB, but, it is not specified to which aspect the prediction refers – affective or cognitive (e.g. Hills & Argyle, 2001). In addition, in different researches there are various instruments used that capture either the affective or the cognitive evaluation only and hence, the authors determine them as the general measures of SWB or happiness (e.g. Cheng & Furnham, 2003). An additional problem is the fact that SWB is often operationalized through a global measure obtained when a negative affect is subtracted from the sum of positive affect and satisfaction with life (e.g. Sheldon and Hoon, 2007 and Vittersø, 2001). Few studies have addressed relations between personality and separately the affective and cognitive components of SWB. One of them is a study conducted by Schimmack, Schupp, and Wagner (2008). The results of this research have shown that extraversion and neuroticism are the strongest predictors of affective and neuroticism of cognitive components of SWB, but that effect is lost when the affective component is introduced in a regression equation as a predictor. The conclusion of the authors is that affective and cognitive components represent different aspects of SWB and that the research should take that distinction into consideration, because the results obtained by examining affective well-being cannot be generalized on satisfaction with life and vice versa. In accordance with this view, in this research we define SWB as a phenomenon that includes two components: cognitive well-being (CWB) and affective well-being (AWB). CWB is defined as satisfaction with one’s life, and AWB as a balance of positive and negative emotions. When examining relations between personality traits and SWB, previous research mostly leaned on the Five Factor Model (FFM), as a dominant one in personality psychology (Larsen & Buss, 2008), and showed that neuroticism and extraversion were the strongest correlates of SWB (e.g. DeNeve and Cooper, 1998 and Steel et al., 2008). In the present research, we have used Zuckerman‘s Alternative Five Factor Model of Personality (AFFM) (Zuckerman, 2005), which has attracted little or no attention with regard to SWB, although it had undergone extensive testing, especially in the field of psychopathology (Zuckerman, 1999). The relationships between the AFFM and positive aspects of functioning are still largely unknown. This research aimed to fill this gap and represents a first step to understanding the usefulness of the AFFM in the prediction of SWB. The AFFM postulates five biologically based dimensions of personality: Activity (Act) covering the need for general activity and preference for challenging and hard work, Sociability (Sy) involving interacting with many people and intolerance for social isolation, Aggression-Hostility (Agg-Host) including antisocial behaviors, Impulsive Sensation Seeking (ImpSS) relating to the tendency to act impulsively, the seeking of exciting experiences and the willingness to take risks and Neuroticism-Anxiety (N-Anx) involving a disposition to feel upset and anxious. Several studies compared the AFFM and the FFM and concluded that there was a high convergence between the two models (e.g. Zuckerman, Kuhlman, Teta, Joireman, & Kraft, 1993). Comparing the AFFM and the FFM, Aluja, Garcia, and Garcia (2002) found that N-Anx was strongly related to Neuroticism (r = .81) and Sy correlated positively with Extraversion (r = .66), but that the Activity scale is poorly represented in the NEO-PI-R. It seems that the main difference between the two models is the presence of a single dimension in each model (Openness to Experience and Activity) that has no equivalent in the other ( Joireman & Kuhlman, 2004). In our opinion, the AFFM can be useful for understanding the role of extraversion in SWB, because it does not integrate sociability and activity into a single trait (extraversion) as do most personality models, but it postulates them as two separate basic personality dimensions. According to the AFFM, sociability and activity should be associated with positive affect, since they share a common neurobiological basis in the form of dopamine (Zuckerman, 2005). In the context of SWB, a particularly interesting component of the AFFM is the ImpSS dimension. ImpSS is found to be significantly negatively correlated (r = −.53) with the NEO-PI-R Conscientiousness dimension ( Aluja et al., 2002), which is an important predictor of SWB ( Hayes & Joseph, 2003). Most research has dealt with examining the dimension of sensation seeking as the predictor of behaviors that compromise health and impair psycho-social functioning (e.g. Kalichman, Simbayi, Jooste, Cain, & Cherry, 2006). A number of researches have shown that sensation seeking is related to maladaptive behavior patterns such as risky sexual behavior ( Hoyle, Fejfar, & Miller, 2000) and drug abuse ( Pedersen, 1991). However, as far as we know, there is no research that has focused on the relations between sensation seeking and positive aspects of functioning. Hence, due to the limitations of the previous research, two main objectives of this research were established: First, examining the distinctiveness of the affective and cognitive components of SWB, concerning their relations with personality traits. Second, examining the predictive power of personality traits according to the AFFM

3. Results 3.1. Correlation analysis Table 1 shows correlations between scales of the ZKPQ, AWB, and CWB, with means and standard deviations. Table 1. Correlations, means and standard deviations among study variables. Act Sy Agg-Host ImpSS N-Anx AWB CWB Act – Sy .11 – Agg-Host .06 .18⁎⁎ – ImpSS .06 .16⁎ .39⁎⁎ – N-Anx .07 −.28⁎⁎ .12 .04 – AWB .35⁎⁎ .23⁎⁎ −.12 −.02 −.49⁎⁎ – CWB .22⁎⁎ .12 −.07 −.11 −.17⁎ .46⁎⁎ – M 4.99 6.67 4.51 6.12 3.70 15.94 24.30 SD 2.68 2.09 2.23 2.42 2.60 8.02 5.99 Note: Act = Activity; Sy = Sociability; Agg-Host = Aggression-Hostility; ImpSS = Impulsive Sensation-Seeking; N-Anx = Neuroticism-Anxiety; AWB = Affective well-being; CWB = Cognitive well-being. ⁎ p < .05. ⁎⁎ p < .01. Table options Correlation analysis revealed that AWB has the strongest relationship with Neuroticism-Anxiety (−.49). Regarding personality traits, CWB had the highest correlation with Activity (.22). Sociability was significantly associated with AWB (.23), but not with CWB. A moderate positive correlation between CWB and AWB was found (.46), suggesting that they are related, but distinct components of SWB. 3.2. Hierarchical regression analysis 3.2.1. Predicting CWB from personality and AWB A summary of the regression statistics, regarding CWB, is presented in Table 2. Inclusion of the set of personality traits in step 1 accounted for 9% of the variance [F (5, 220) = 4.44, p < .001], with Activity as the only significant predictor (β = .21, p < .001). The size of the beta coefficient for Neuroticism-Anxiety (β = −.13) and Impulsive Sensation Seeking (β = −.12) approached significance. Table 2. Hierarchical regression analysis. Predicting CWB from personality and AWB. Model R2 ΔR2 β sig sr2 1 .09 .09 .001⁎ Act .21 .001⁎ .04 Sy .08 .231 .00 Agg-Host −.01 .910 .00 ImpSS −.12 .084 .01 N-Anx −.13 .065 .01 2 .23 .14 .000⁎ Act .07 .276 .00 Sy .05 .486 .00 Agg-Host .02 .758 .00 ImpSS −.12 .071 .01 N-Anx .08 .274 .00 AWB .46 .000⁎ .14 Note: Act = Activity; Sy = Sociability; Agg-Host = Aggression-Hostility; ImpSS = Impulsive Sensation-Seeking; N-Anx = Neuroticism-Anxiety; AWB = Affective Well-Being; sr2 = squared part correlation indicating the unique contribution of each predictor to the total variance accounted for in the dependent variable. ⁎ p < .001. Table options Addition of the AWB in step 2 resulted in a significant increment in the explained variance of 14% [F (6, 219) = 10.91, p < .001]. After partialling out shared variance, only AWB remained significant unique predictors of CWB (β = .46, p < .001). The predictive power of Activity and Neuroticism-Anxiety was significantly reduced, suggesting that they influence CWB through their shared variance with affect. Impulsive Sensation Seeking was tending toward statistical significance (β = −.12, p = .071), even after eliminating shared variance with AWB. None of the personality traits had a unique contribution in explaining CWB, showing that they do not have a direct effect on the cognitive aspect of well-being. 3.3. Hierarchical regression analysis 3.3.1. Predicting AWB from personality and CWB In Table 3 the results of the hierarchical regression analysis for predicting AWB are shown. Personality traits entered into the equation in step 1, accounted for 35% of variance [F (5, 220) = 23.67, p < .001]. The strongest predictors were Neuroticism-Anxiety (β = −.44, p < .001) and Activity (β = .30, p < .001). Table 3. Hierarchical regression analysis. Predicting AWB from personality and CWB. Model R2 ΔR2 β sig sr2 1 .35 .35 .000⁎ Act .30 .000⁎ .09 Sy .08 .158 .01 Agg-Host −.06 .309 .00 ImpSS −.01 .877 .00 N-Anx −.44 .000⁎ .18 2 .45 .10 .000⁎ Act .24 .000⁎ .05 Sy .06 .307 .00 Agg-Host −.06 .292 .00 ImpSS .03 .574 .00 N-Anx −.40 .000⁎ .14 CWB .33 .000⁎ .10 Note: Act = Activity; Sy = Sociability; Agg-Host = Aggression-Hostility; Imp-SS = Impulsive Sensation-Seeking; N-Anx = Neuroticism-Anxiety; AWB = Affective well-being; CWB = Cognitive well-being; sr2 = squared part correlation indicating the unique contribution of each predictor to the total variance accounted for in the dependent variable. ⁎ p < .001. Table options In step 2, CWB was entered separately and significantly accounted (ΔR2 = .10) for additional variance [F (6, 219) = 29.74, p < .001]. After partialling out shared variance, the most significant predictor of AWB was Neuroticism-Anxiety (β = −.40, p < .001). Besides Neuroticism-Anxiety, significant predictors were CWB (β = .33, p < .001) and Activity (β = .24, p < .001). Neuroticism-Anxiety and Activity accounted respectively for 14% and 5% of the unique variance in AWB. Unlike CWB, these results suggest that some personality traits have direct effect on affective component of SWB.