Personal goals and personality traits among young adults: Genetic and environmental effects

Journal of Research in Personality 46 (2012) 248–257

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Personal goals and personality traits among young adults: Genetic and environmental effects Katariina Salmela-Aro a,⇑, Sanna Read a, Jari-Erik Nurmi b, Eero Vuoksimaa a, Mari Siltala a, Danielle M. Dick c, Lea Pulkkinen b, Jaakko Kaprio a, Richard J. Rose d a

University of Helsinki, Finland University of Jyväskylä, Finland Virginia Commonwealth University, USA d Indiana University, USA b c

a r t i c l e

i n f o

Article history: Available online 6 February 2012 Keywords: Personal goals Personality Genetic Twin Young adulthood

a b s t r a c t To assess genetic and environmental contributions to personal goals, 1279 twins aged 20–26 filled in Personal Project Analysis and NEO-FFI inventories. Personal goals relating to education, the respondent’s own family, friends, property, travel and self showed primarily genetic and unique environmental effects, whereas goals related to parents and relatives showed both shared and unique environmental effects. The variation in goals related to health, work, hobbies and life philosophy was attributable to non-shared environmental effects. Openness to experience and personal goals related to family, education and property shared a significant amount of genetic influence. The same was true for extraversion and self-related goals, and agreeableness and goals related to property. Ó 2012 Elsevier Inc. All rights reserved.

1. Introduction Personal goals and personality traits represent different levels of personality (Little, 1999; McAdams & Pals, 2006; Roberts, O’Donnell & Robins, 2004). Dispositional personality traits operate on an upper level (emotional, cognitive and behavioral tendencies) and provide a dispositional outline of psychological individuality (Little, 1999; McAdams & Pals, 2006; Sheldon, 2004; Singer, 2005). In turn, personal goals function as a middle-level construct (characteristic adaptation) and fill in the motivational and sociocognitive details (Winter, John, Stewart, Klohnen, & Duncan, 1998). Although genetic and environmental influences on personality traits have attracted considerable attention in the recent literature (Krueger & Johnson, 2008), there is a lack of behavioral research on personal goals from a behavior-genetic perspective. This is surprising, given that the kinds of things that appeal to people have been shown to be partly attributable to genetic factors (Nigg & Goldsmith, 1998). To our knowledge, only two previous studies have been conducted on the genetic background of personal goals. Salmela-Aro et al. (2009) investigated genetic influences on the contents of personal goals among elderly women and found that such factors accounted for from 44% to 53% of the variation in goals related to ⇑ Corresponding author. Address: University of Helsinki, Helsinki Collegium for Advanced Studies, PO Box 4, 10014 University of Helsinki, Finland. E-mail address: katariina.salmela-aro@helsinki.fi (K. Salmela-Aro). 0092-6566/$ - see front matter Ó 2012 Elsevier Inc. All rights reserved. doi:10.1016/j.jrp.2012.01.007

health and functioning, independence, and close relations. Bleidorn et al. (2010), in turn, studied the genetic background of agency and communion life goals in an adult twin sample. They found that the proportion of variance attributable to additive genetic factors varied between 25% and 36%. Given the evidence of low to moderate associations between personality traits and personal goals (Lüdtke, Trautwein, & Husemann, 2009; Roberts, O’Donnell, & Robins, 2004; Roberts & Robins, 2000; Romero, Villar, Luengo, & Gomez-Fraguela, 2009), it is also possible that they share the same genetic components (McCrae & Costa, 2008). However, only one study has so far investigated this issue: Bleidorn et al. (2010) found that personality traits and both agency and communion life goals shared from one third to two thirds of their genetic background. The present study aimed to broaden our understanding of genetic and environmental influences on idiographic personal goals and personality traits among Finnish twins aged 20–26. 2. Personal goals Personal goals could be conceived of as future-oriented representations of what individuals strive for in various life domains (Austin & Vancouver, 1996; Karniol & Ross, 1996). They have been conceptualized in a variety of ways in the literature, such as personal strivings (Emmons, 1986), life tasks (Cantor, Norem, Niedenthal, Langston, & Brower, 1987), developmental goals (Heckhausen, 1999), personal projects (Little, 1983) and personal goals (Nurmi, 1992; Salmela-Aro & Nurmi, 1997). One way to investigate them

K. Salmela-Aro et al. / Journal of Research in Personality 46 (2012) 248–257

is to ask respondents to generate a list of goals, which are then analyzed according to their content (e.g., education, occupation, leisure, identity and human relationships; Little, 1983; Nurmi, 1992). Alternatively, respondents can be asked to rate the importance of different kinds of goals (Lüdtke et al., 2009; Bleidorn et al., 2010). Personal goals simultaneously reflect the personality of the individual and the features of his or her culturally defined life contexts (Little, 1983; McCrae & Costa, 2008; Nurmi, Salmela-Aro, & Aunola, 2009). On the one hand, goals are internal representations of desired states (Miller, Galanter, & Pribram, 1960) that originate in individual characteristics, such as motives and values (Nuttin, 1984) and personality traits (McCrae & Costa, 2008). For instance, McCrae and Costa (2008) distinguish between ‘‘basic tendencies’’ and ‘‘characteristic adaptations,’’ the former referring to stable, endogenous personality traits and the latter to how these traits adapt to different environments, characterized by personal goals, attitudes, interests, plans, beliefs and expectations. On the other hand, personal goals refer to specific objectives and tasks in an individual’s life context, which are assumed to satisfy the original motivation (Nuttin, 1984). Many of these objectives and tasks are evidenced in goal contents (Nurmi, 1992; Nuttin, 1984; SalmelaAro, 1992). Previous research has shown that the age-graded challenges, developmental tasks and constraints that people face during a particular stage of their lives channel the kinds of personal goals they construct (Cross & Markus, 1991; Nurmi, 1991; Salmela-Aro et al., 2009).

3. Sources of individual differences in personal goals One major source of individual differences in personal goals constitutes dispositional characteristics such as personality traits (McCrae & Costa, 2008). Previous findings indicate a moderate phenotypic association between personality traits and personal goals. Costa and McCrae (1988) found, for example, that extraversion was associated with the need for social contact, attention and fun, and neuroticism with worries about other people’s opinions, defensive and guarded needs, and the need for care and sympathy. Agreeableness was related to non-domineering and argumentative needs, and the need to help other people. Conscientiousness was associated with organization and accomplishment, persistence and carefulness. Openness to experience was related to the need for variety, intellectual stimulation and esthetic experiences. In more recent work, Denissen and Penke (2008) found that extraversion was associated with a high reward value of social interaction, agreeableness with the ability to cooperate, conscientiousness with tenacity in pursuing goals in the face of distracting circumstances, neuroticism with sensitivity to signs of social exclusion and openness to experience with a high reward value of cognitively challenging activity. Roberts, O’Donnell, and Robins (2004), in turn, found that extraversion was related to hedonistic and relationship goals, agreeableness to social and relationship goals, conscientiousness to relationship goals, and openness to esthetic and social goals. Neuroticism was negatively related to all of these. As personal goals originate partly from genetically based personality traits (Bleidorn et al., 2010; McCrae & Costa, 2008), and variation in both personality traits (Krueger & Johnson, 2008) and personal goals (Bleidorn et al., 2010; Salmela-Aro et al., 2009) stems, in part, from genetic sources, there are thus good reasons to assume that some of this genetic impact may be shared. However, only one study so far has focused on this issue. Bleidorn et al. (2010) studied the associations between personality traits and two major life goals, agency and communion, in a 5-year period among 217 identical and 112 fraternal twin pairs from the Bielefeld Longitudinal Study of Adult twins. The associations between

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personality traits and two major life goals, agency and communion, suggested a shared genetic background of between one and two thirds. However, this study focused only on middleaged adults and used a questionnaire that is primarily limited to measuring goals in their work and community. To broaden our understanding of the topic, we investigated whether the genetic and environmental effects on personal goals and personality traits are attributable to the same genetic and enviromental components in young adults using a broader range of goals. 4. Aims The present study addressed the following three research questions: (1) To what extent do genetic and environmental effects contribute to the contents of personal goals? On the basis of previous studies, we expected (Hypothesis 1) personal goals to be moderately heritable and non-shared environmental effects to be the largest source of variation (Bleidorn et al., 2010; Salmela-Aro et al., 2009). (2) To what extent are the contents of personal goals and the five personality traits associated? We expected (Hypothesis 2a) that openness to experience would be associated positively with educational and social goals, and negatively with property-related goals (see Costa & McCrae, 1988; Roberts, O’Donnell, & Robins, 2004; Roberts & Robins, 2000). Given that self-related goals are characterized by preoccupation with one’s social standing and negative affects (SalmelaAro, Pennanen & Nurmi, 2001b), we assumed (Hypothesis 2b) that such goals correlate positively with neuroticism and negatively with extraversion. Further, because selfrelated goals may reflect the intention to broaden one’s awareness and enhance self-understanding, we expected (Hypothesis 2c) them to be associated with openness to experience (Lüdtke et al., 2009). Further, we hypothesized (Hypothesis 2d) that agreeableness would be associated positively with social goals and negatively with propertyrelated goals (Costa & McCrae, 1988; Roberts, O’Donnell, & Robins, 2004; Roberts & Robins, 2000). Finally, we expected (Hypothesis 2e) conscientiousness to be positively associated with work-related goals (Roberts, O’Donnell, & Robins, 2004; Roberts & Robins, 2000). (3) To what extent do the contents of personal goals and the five personality traits share the same genetic and environmental effects? Given previous research evidence that about half of any additive genetic effect on personal goals (agency and communion goals) is shared with personality traits (Bleidorn et al., 2010), we expected (Hypothesis 3a) to find about the same amount of shared genetic impact between goal contents and personality traits. Furthermore, because the contents of personal goals are also influenced by changes in age-graded developmental tasks and normative constraints (Nurmi, 1991, 1992), whereas this is not the case for personality traits, we assumed (Hypothesis 3b) that the non-shared environmental impact would the higher for goal contents than personality traits. 5. Methods 5.1. Sample We used data from the population-based longitudinal FinnTwin12 study, which consists of five consecutive twin cohorts born between 1983 and 1987. At the initial stage, baseline

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questionnaires were sent to all twins and their parents late in the year when the twins reached their 11th birthday. A total of 2724 families returned the questionnaires (participation rate 87%). Of these, 1035 families were invited to participate in a more intensive study protocol when the twins were 14 (Kaprio, Pulkkinen, & Rose, 2002). The third wave of data collection was a questionnaire study conducted when the twins were 17 years old. The invitation to participate in the fourth wave of data collection in 2005–2009 was sent to all the twins who participated in the intensive study protocol at age 14. The analyses for the present study concern all the twins who participated in the fourth wave of data collection and provided data on personal goals and personality traits. A total of 1854 individuals, aged 20–26 years, were eligible. Of these, 353 individuals could not be contacted, i.e. no phone number was available, phone calls were not answered, or no address was available. Of those contacted, 154 individuals did not participate. Moreover, 68 individuals provided incomplete data for the purposes of this study. Accordingly, the realized study sample comprised 1279 individuals. A more detailed description of the FinnTwin12 study is to be found in Kaprio et al. (2002). A validated questionnaire on physical similarity (Sarna, Kaprio, Sistonen, & Koskenvuo, 1978), with added questions (e.g., eye and hair color) for younger twins, was used to determine zygosity (Goldsmith, 1991). DNA from venous blood or saliva samples was used to confirm the zygosity of 397 same-sex pairs, which is 95% of the cases. The total sample in the present study comprised 141 monozygotic female twin pairs (MZF), 104 monozygotic male twin pairs (MZM), 98 dizygotic female twin pairs (DZF), 77 dizygotic male twin pairs (DZM) and 153 dizygotic opposite-sex twin pairs (DZOS). In addition, there were 133 individual twins whose co-twin did not participate. In these cases the individual twin contributed to the calculation of the means and variances/prevalences, but not to the intraclass correlations or covariance matrix between the members of twin pairs. 5.2. Measures A revised version of Little’s (1983) Personal Project Analysis inventory (PPA) was used to measure personal goals. The participants were asked to describe four of their current personal projects in response to the following instruction: ‘‘People have many kinds of things that they think about, hope for and hope to accomplish. Think about the kinds of personal goals/projects you have in your life at the moment. The goals/ projects may be related to any life domain, such as hobbies, work, family, friends or yourself.’’ Each project that the participants mentioned was first classified independently by two trained assessors into one of sixteen categories on the basis of content. The categories were similar to those used most frequently in earlier studies (Little, 1983): education (‘‘finish my Master’s degree’’), work (‘‘find a good job’’), their own family (‘‘find a partner and have children’’), parents and relatives (‘‘keep a close relationship with my parents’’), friends (‘‘find new friends’’), property and financial issues (‘‘buy a house’’), hobbies (‘‘learn to play the guitar’’), daily routines (‘‘water the plants), health (‘‘take care of my health’’), self and personality (‘‘grow as a person’’), travel (‘‘travel abroad’’), politics and society (‘‘participate in political life’’), life philosophy (‘‘live a happy life’’), change of residence (‘‘move to a new city’’), the army (‘‘military service’’), and tobacco, alcohol and drugs (‘‘quit smoking’’). The content analysis reliability measured by Cohen’s kappa between the two independent assessors was 0.89. Each project content was coded for further analysis on a dichotomous scale: 0 = no projects mentioned and 1 = at least one project mentioned in the particular category. The Finnish version of the 67-item NEO Five Factor Inventory (NEO-FFI) was used to assess five personality traits: extraversion, neuroticism, openness, agreeableness and conscientiousness. The

NEO-FFI is based on the longer 180-item Personality Inventory (Pulver, Allik, Pulkkinen, & Hämäläinen, 1995), which is an authorized adaptation of the NEO Personality Inventory (NEO-PI) (Costa & McCrae, 1985). Our 67-item NEO-FFI (Rantanen, Metsäpelto, Feldt, Pulkkinen, & Kokko, 2007) corresponds to the original NEO-FFI (Costa & McCrae, 1989). We added seven extra items to more broadly cover the excitement-seeking facet of the extraversion factor. If a single item was missing for a trait score, the mean value for the trait was calculated using the items that were available for the individual concerned. Those with more than one item missing (less than 1% of the sample) were excluded from the analysis. The internal consistency for the five personality scores was adequate (Cronbach’s alpha was 0.80 for extraversion, 0.89 for neuroticism, 0.73 for openness, 0.69 for agreeableness, and 0.83 for conscientiousness). Because the estimates of genetic and environmental factors may be influenced by the twins’ shared age, gender and contacts, and as personal goals may be affected by life circumstances such as having a partner, having a higher degree qualification and currently studying, we used these factors as covariates in the models. The covariates included gender and age in years and dichotomous measures for having a partner (0 = no partner, 1 = having a partner), qualifications (0 = below the matriculation level, 1 = above the matriculation level) and the current study status (0 = not studying, 1 = studying full time or part-time). We assessed the frequency of contact between the twins from reports from both members of the respective pairs. If one or both of them reported daily contact (meeting in person, phoning, emailing), the frequency of contact was coded 1; if it was less than daily, it was coded 0. 5.3. Analysis strategy We used the structural equation modeling framework in Mplus (version 5.21; Muthén & Muthén, 2007; Prescott, 2004) for the analyses. The individual variation in the traits was decomposed into additive genetic (A), common environment (C) and unique environment (E) effects. The genetic effects of A represent the total independent additive effect of multiple genes from different loci. The environmental effects of C comprise common, or shared environmental factors that are shared by family members and thus contribute to twin similarity irrespective of zygosity. C acts to make twins similar, regardless of whether the actual environmental input is the same. E represents a non-shared, or unique, environment that contributes to twin dissimilarity, including random error variance. These variance components can be teased out by comparing the similarity of the members of monozygotic and dizygotic twin pairs. Given that monozygotic twins share all genes and dizygotic twins on average half of their segregating genes (in the absence of assortative mating for the trait, i.e., random mating), the correlation for genetic effects between twins was constrained to be 1 for MZ twin pairs and 0.5 for DZ twin pairs. Further, because the twin siblings were raised together, common environment was constrained to be 1 for both MZ and DZ twins. The models also assume the absence of gene-by-environment interactions on the traits in question. The assumptions regarding assortative mating, equal environments for MZ and DZ twins, and no gene-environment interaction are likely to be violated to some extent. We calculated the within-trait cross-twin correlations for the MZ female and male pairs, DZ female and male pairs, and opposite-sex DZ pairs. In order to ensure enough cases in the dichotomous variables, we included personal goals with a frequency of 5% or more in the genetic analyses. Tetrachoric correlations were calculated for the dichotomous personal-goal measures, and Pearson correlations for the personality-trait scores. The within-trait cross-twin correlations could then be used for inspecting the patterns for further modeling. An MZ correlation twice the value of

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the DZ correlation indicates an additive genetic influence on the trait. If the difference in correlation is smaller, it is likely to indicate a shared environmental effect. The next step was to fit univariate models, including the genetic and environmental components, to the personal goals, using the raw data on all individuals. Because personal goals were categorical variables, we used liability-threshold models (Neale & Cardon, 1992) with the logit link function and maximum likelihood estimation. In these models, it is assumed that normally distributed liabilities underlie the categorical outcomes. We fixed the means of the latent variables at zero and held the variances to be equal across the members of a twin pair. Age was included as a covariate in the models. We tested for gender differences by comparing the groups of MZ and DZ males and females. The full model comprised A, C and E components. Total variance (Vtotal) is the sum of all components in the model (Vtotal = A + C + E). To assess the contribution of each parameter to the total variance (Vtotal), the unstandardized coefficients were squared (x  x = A, y  y = C and z  z = E), and their proportion of the total was calculated, i.e., standardized A = A/ (A + C + E). The correlation between the additive genetic effects on opposite-sex DZ twins was fixed to .50 (assuming the same genes for males and females), and the prevalences of personal goals were estimated freely for men and women. The restricted models tested the following: whether the prevalences for personal goals were equal for men and women, and whether the parameter estimates for A, C and E could be set to be equal for men and women. The difference between the full models and the restricted models (the difference in 2ln L) was distributed as v2, the degrees of freedom being the difference in the number of parameters that are estimated. A significant v2 difference indicates that the reduction in the model significantly reduces its fit to the data. We also compared the models according to Akaike’s (1987) Information Criteria (AIC): a smaller value indicates a better fit. We assessed genetic and environmental influences on personality traits by means of univariate analysis, testing the equality of the variances and means between the MZ and DZ twins in a saturated model. Personality scores were used as continuous variables. We tested the full model, including separate estimates of the A, C and E components for men and women, against more restricted models where these components were equal for men and women, and from which the C component was dropped. To test the associations between personal goals and personality traits, we calculated the biserial correlations both within the individuals (cross-trait within-twin correlations for assessing the phenotypic correlations) and between the members of the twin pair (cross-trait cross-twin correlations for assessing the genetic and environmental correlations between the traits). The cross-trait within-twin correlations were pooled for the MZ and DZ twin groups, and the twin pairs were treated as clusters to take into account the dependency between them. The difference between the MZ and DZ groups in cross-trait cross-twin correlations can be interpreted in similar ways as the univariate within-trait crosstwin correlations described above. We analyzed the traits that exhibited possible shared genetic and environmental effects by means of Cholesky decomposition. Cholesky decomposition assesses the genetic and environmental factors that are specific to each phenotype as well as the genetic and environmental effects that are shared between the traits. Personality traits were treated as continuous and personal goals as categorical variables. Comparison of the full and restricted Cholesky decompositions makes it possible to test whether the genetic and/or environmental correlation between the traits is significant. We tested for differences between the full models and the nested models in a similar way as in the univariate models described above. Because the frequency of social contacts between co-twins may influence twin correlations, we controlled for frequency of contact.

Moreover, given that educational level and employment and study status as well as having a partner may influence the results, we added each of these separately to the models. They did affect the mean levels, but they had very little influence on the genetic and environmental estimates. Because of these negligible effects and the fact that adding a large number of covariates would have decreased the power in the models, we chose not to control these in the final analyses.

6. Results 6.1. Descriptive results Table 1 shows the percentages of personal goals among women and men. The most often mentioned categories were work, their own family, property and health. The means and standard deviations for the personality traits are presented in Table 2. Equality of prevalence in personal goals and personality-trait means were calculated for men and women. The women expressed goals related to education, parents and relatives, and traveling more frequently than men, and these differences were taken into account in the further analyses (the prevalences were allowed to differ for men and women). In terms of personality traits, women achieved higher scores for neuroticism and openness and lower scores for extraversion than men, thus the means for men and women were allowed to differ in the univariate models. Given these gender differences in prevalences and means, and the restriction involved in testing gender differences in the model estimates due to the moderate sample size and dichotomous outcome variable, we took possible gender differences into account by using gender as a covariate in the models. Age and the frequency of contact between the twins were also added as covariates. However, their effects were small. There were no differences in the means and variances between the MZ and DZ twins. Table 3 shows the within-trait cross-twin correlations that were calculated for personal goals and personality traits. The pattern of the correlations implied genetic influence on goals related to edu-

Table 1 Percentages of men and women who expressed personal goals. Personal goal

Men (n = 584)

Women (n = 695)

Education Work Own family Parents and relatives Friends Property Hobbies Travel Health Life philosophy Self Change of residence Army Daily chores Tobacco, alcohol, drugs

28.1 54.9 52.8 3.9 15.9 44.0 20.8 15.7 44.7 17.3 9.4 2.8 1.1 0.4 2.1

32.6 56.0 56.0 7.1 19.8 41.5 22.1 19.7 41.5 15.6 13.1 5.5 0.3 1.0 2.0

Table 2 Means (SD) of personality traits. Personality trait

Men (n = 584)

Women (n = 695)

Extraversion Neuroticism Openness Agreeableness Conscientiousness

3.52 2.36 2.97 3.56 3.58

3.40 2.87 3.11 3.61 3.64

(0.44) (0.64) (0.53) (0.59) (0.43)

(0.39) (0.70) (0.49) (0.59) (0.49)

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Table 3 Within-trait cross-twin correlations (r) and 95% confidence interval (95%CI) for personal goals and personality (NEO-FFI). MZ

DZ-SS

r

(95%CI)

r

n of pairs = 245

DZ-OS (95%CI)

n of pairs = 175

r

(95%CI)

n of pairs = 153

Personal goals Education Work Own family Parents and relatives Friends Property Hobbies Travel Health Self Life philosophy

0.43 0.20 0.42 0.46 0.62 0.47 0.29 0.38 0.11 0.39 0.26

(0.25–0.61) (0.01–0.39) (0.25–0.59) (0.09–0.83) (0.45–0.80) (0.31–0.64) (0.07–0.51) (0.15–0.60) ( 0.09–0.30) (0.12–0.65) (0.00–0.52)

0.20 0.09 0.11 0.39 0.26 0.32 0.25 0.08 0.28 0.34 0.47

( 0.04–0.44) ( 0.15–0.32) ( 0.12–0.34) ( 0.05–0.83) ( 0.05–0.54) (0.11–0.54) ( 0.03–0.54) ( 0.21–0.38) (0.06–0.50) (0.02–0.65) (0.23–0.71)

0.16 0.10 0.10 0.45 0.22 0.20 0.14 0.05 0.15 0.15 0.37

( 0.11–0.42) ( 0.15–0.35) ( 0.14–0.36) (0.00–0.89) ( 0.09–0.53) ( 0.08–0.53) ( 0.10–0.43) ( 0.20–0.30) ( 0.10–0.40) ( 0.11–0.43) (0.15–0.60)

Personality (NEO-PI) Extraversion Neuroticism Openness Agreeableness Conscientiousness

0.63 0.62 0.69 0.46 0.55

(0.55–0.70) (0.54–0.70) (0.59–0.76) (0.36–0.56) (0.45–0.63)

0.20 0.27 0.35 0.14 0.18

(0.05–0.34) (0.13–0.41) (0.21–0.48) (0.00–0.29) (0.04–0.32)

0.27 0.18 0.23 0.19 0.09

(0.13–0.42) (0.02–0.33) (0.07–0.37) (0.04–0.34) ( 0.06–0.25)

MZ = Monozygotic twins, DZ = Dizygotic twins, SS = Same sex, OS = opposite sex.

cation, the respondent’s own family, friends, property, travel and self. The correlations for goals related to parents and relatives, health, work, hobbies and life philosophy suggested mainly environmental effects. In terms of personality traits, the correlations indicated genetic effects. All the MZ correlations were far less than unity, indicating a substantial non-shared environmental effect on personal goals and personality traits. The correlations for the opposite and same-sex DZ twin pairs were similar. Hence in the univariate and multivariate models, the DZ groups were merged, and the gender effects on means adjusted. 6.2. Univariate models In terms of personal goals, the estimates for men and women could be set to be equal. The estimates for genetic and environTable 4 Genetic and environmental estimates for the personal goals. Personal goal

Education Work Own family Parents and relatives Friends Property Hobbies Travel Health Self Life philosophy

Parameter estimates (95% CI) A

C

E

0.41 (0.14–0.55) 0.17 (0–0.34) 0.27 (0.08–0.43) 0.00 (0–0.16) 0.57 (0.29–0.72) 0.47 (0.13–0.62) 0.21 (0–0.40) 0.29 (0–0.49) 0.00 (0–0.31) 0.32 (0.03–45) 0.24 (0–0.45)

0.00 (0–0.26) 0.01 (0–0.23) 0.00 (0–0.11) 0.38 (0.04–0.58) 0.00 (0–0.27) 0.01 (0–0.34) 0.00 (0–0.20) 0.00 (0–0.23) 0.12 (0–0.24) 0 (0–29) 0 (0–0.29)

0.59 (0.45–0.76) 0.82 (0.66–0.98) 0.73 (0.57–0.89) 0.62 (0.34–0.84) 0.43 (0.28–0.61) 0.51 (0.38–0.68) 0.79 (0.60–0.98) 0.71 (0.51–0.92) 0.88 (0.69–0.99) 0.68 (0.46–0.88) 0.76 (0.55–0.98)

Note: The prevalences were allowed to vary between men and women; A = Additive genetic effects, C = Shared environmental effects, E = Non-shared environmental effects.

mental effects are shown in Table 4. According to the AIC values and the difference tests between the nested models (model steps not shown), the best models were the ones including the additive genetic component for education, the respondent’s own family, friends, property, travel and self-related goals, varying between 27% and 57%, and the rest of the variance was attributable to the non-shared environmental component. With regard to personal goals related to health, work, hobbies and life philosophy, the variation due to genetic or shared environmental factors was small and non-significant, indicating that the source of variation in these goals was primarily from the non-shared environment. For personality traits, the estimates for men and women could be set to be equal, and the component for shared environment could be dropped from the model across all traits (models not shown). The best fitting models for extraversion, neuroticism, openness, agreeableness and conscientiousness included additive genetic effects (60%, 51%, 58%, 42% and 42%, respectively), with the residual variation being attributable to non-shared environmental effects.

6.3. Associations between personal goals and personality traits Table 5 shows the phenotypic correlations between personal goals and personality traits (cross-trait within-twin), and the correlations between personal goals and personality traits and members of a twin pair (cross-trait, cross-twin). The values were quite low, indicating that personal goals and personality traits measure different aspects of the personality. However, there were significant phenotypic correlations of personal goals with personality traits of the other member of a twin pair related to education, the respondent’s own family, friends, property, travel and the self. The pattern of cross-trait cross-twin correlations showing that the MZ correlations were higher than the DZ correlations implies that the genetic components of openness and goals related to education, family and property are correlated. There were also phenotypic correlations between agreeableness and friends and property, of which the association between agreeableness and property may be partly attributable to genetic factors. Conscientiousness correlated with goals related to the respondent’s own family and the self, but the cross-trait cross-twin correlations did not indicate any genetic associations between the traits.

K. Salmela-Aro et al. / Journal of Research in Personality 46 (2012) 248–257 Table 5 Cross-trait within-twin and cross-trait cross-twin correlations for personal goals and personality traits in monozygotic (MZ, n of pairs = 245) and dizygotic (DZ, n of pairs = 328) twins. Cross-trait within-twin correlations

Cross-trait cross-twin correlations MZ

DZ

Education with Neuroticism Extraversion Openness Conscientiousness Agreeableness

0.11* 0.02 0.15** 0.08 0.03

0.01 0.01 0.22** 0.06 0.12

0.10 0.01 0.10 0.08 0.03

Own family with Neuroticism Extraversion Openness Conscientiousness Agreeableness

0.02 0.06 0.10* 0.09* 0.03

0.09 0.03 0.16* 0.02 0.04

0.03 0.07 0.02 0.06 0.05

Friends with Neuroticism Extraversion Openness Conscientiousness Agreeableness

0.05 0.06 0.14** 0.08 0.15**

0.04 0.01 0.13 0.09 0.12

0.16* 0.12 0.12 0.15 0.18*

Property with Neuroticism Extraversion Openness Conscientiousness Agreeableness

0.02 0.04 0.21*** 0.03 0.10*

0.01 0.03 0.18** 0.05 0.16**

0.08 0.06 0.02 0.01 0.04

Travel with Neuroticism Extraversion Openness Conscientiousness Agreeableness

0.12* 0.11* 0.14** 0.02 0.03

0.13 0.05 0.14 0.00 0.03

0.03 0.13 0.13 0.06 0.16

Self with Neuroticism Extraversion Openness Conscientiousness Agreeableness

0.21*** 0.20*** 0.29*** 0.17*** 0.04

0.13 0.18** 0.22** 0.11 0.07

0.02 0.09 0.21** 0.14 0.19*

*** ** *

p < 0.001. p < 0.01. p < 0.05.

253

extraversion and goals related to self suggested a genetic association between extraversion and self-related goals. Neuroticism correlated with goals related to education, travel and the self. However, the pattern of these cross-trait cross-twin correlations did not indicate any genetic association between neuroticism and goals, as evident in the lack of differences between cross-trait cross-twin correlations. In accordance with the association patterns described above, Cholesky decomposition was carried out for openness and goals related to education; openness and goals related to the respondent’s own family; openness, agreeableness and goals related to property; and extraversion and goals related to self. Given that the shared environmental components were not significant in the univariate models, we tested the multivariate models only for additive genetic and non-shared environmental effects. The genetic and environmental effects between goals and traits are shown in Figs. 1–4. The genetic effects between the traits and goals were significant. Except for the association between openness and educational goals, the associations were negative, reflecting the direction of the phenotypic association between these traits and goals. Environmental effects between the traits and goals were non-significant. Genetic effects shared with openness to experience accounted for 19% (CI 95% = 14–25) of the total variance in educational goals (Fig. 1). In the model for openness and family-related goals (Fig. 2), 10% (CI 95% = 4–15) of the total variance of family-related goals was due to the genetic correlation. In the model between openness to experience, agreeableness and property-related goals (Fig. 3), the genetic correlation between openness and property-related goals accounted for 9% (CI 95% = 3–16) and the genetic correlation between agreeableness and property-related goals accounted for 7% (CI 95% = 1–14) of the total variance in property-related goals. In the model between extraversion and self-related goals (Fig. 4), 19% (CI 95% 15–24) of the total variance of self-related goals was due to the genetic correlation. These results suggest that the moderate phenotypic correlation between these personality traits and personal goals are almost entirely attributable to the shared genetic basis. It appears from the comparison of the full and restricted models that the environmental association (the correlated E component) between personality traits and personal goals could be removed without worsening the model fit (results not shown). 7. Discussion

Extraversion correlated with goals related to travel and the self. The pattern of cross-trait cross-twin correlations showing that the MZ correlations were higher than the DZ correlations between

Although it has been assumed that personal goals originate in the characteristics of individuals and are partly attributable to ge-

Fig. 1. Bivariate additive genetic (A) and non-shared environmental (E) effects in openness and education-related goals in the men and women. The figure shows unstandardized estimates and standard errors (in parentheses).

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Fig. 2. Bivariate additive genetic (A) and non-shared environmental (E) effects in openness and family-related goals in the men and women. The figure shows unstandardized estimates and standard errors (in parentheses).

Fig. 3. Trivariate additive genetic (A) and non-shared environmental (E) effects in openness, agreeableness and property-related goals in the men and women. The figure shows unstandardized estimates and standard errors (in parentheses).

Fig. 4. Bivariate additive genetic (A) and non-shared environmental (E) effects in extraversion and self-related goals in the men and women. The figure shows unstandardized estimates and standard errors (in parentheses).

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netic differences in motivation and personality traits, as reported in, for example, McCrae & Costa, 2008, and Nuttin, 1984, little research has been carried out on the role of genetic factors in personal goals. The aim of the present study involving a sample of Finnish twins aged 20–26 was thus to increase our understanding of genetic and environmental effects on personal goals and personality traits, and to evaluate whether these effects are due to the same genetic and environmental components. The results of our analyses showed that personal goals related to education, the respondent’s own family, friends, property, travel and the self showed primarily genetic and unique environmental effects, whereas goals related to parents and relatives showed shared and unique environmental effects. The variation in goals related to health, work, hobbies and life philosophy was attributable to non-shared environmental effects. The association between openness to experience and personal goals related to the respondent’s own family, education and property was partly due to genetic influence. The same was true for extraversion and goals related to the self, and agreeableness and goals related to property, although the correlation was negative. Our first research question concerned the extent to which genetic and environmental effects contribute to the contents of personal goals. According to the results, variation in education (41%), the respondent’s own family (27%), friends (57%), property (49%), travel (22%) and self-related goals (32%) reflect moderate genetic effects. The significance of these findings lies in the implication that research on personal goals should take one additional determinant into account, namely genetic variation, that explains a substantial amount of the variation in individual differences. It is assumed in the majority of studies conducted thus far that environmental determinants, such as age-graded normative tasks and contextual demands, and the ways these are dealt with, contribute to goal contents (Heckhausen, 1999; Nurmi, 1992; Salmela-Aro & Nurmi, 1997). It seems from the findings of the present study that personal goals are influenced not only by the normative demands of the current life stage (Nurmi, 1991; Wurf & Markus, 1991) and the individual’s life history in terms of previous success in goal aspiration (Heckhausen, 1999; Salmela-Aro et al., 2009; SalmelaAro et al., 2009), but also by genetic factors that affect the kinds of objectives and events that people find appealing at certain stages of their lives. There is thus an evident need to conduct longitudinal behavioral-genetic studies to further examine the dynamics between genetic influence and the role that environmental demands and constraints play in goal construction. Only two previous studies have examined the role of genes in personal goals. Salmela-Aro et al. (2009) identified an additive genetic effect in goals concerning health and functioning, independent living, and close relationships among elderly women, and a moderate common environmental effect in goals concerning physical exercise and care of others. There are similarities in the results of this and the current study. For example, in both cases the genetic effects were strong in close relationships, but shared environmental effects were detected in helping others. However, some of the findings differed. For instance, health and functioning showed genetic effects among older women in the 2009 study but not in the present study among younger adults. These differences may be attributable to age and different developmental stages and the fact that only women were included in the earlier study. Bleidorn et al. (2010) found recently that goals related to agency and communion showed moderate genetic effects (between 26% and 36%). The genetic estimates were somewhat higher in the present study, but on the other hand, the confidence intervals were quite wide. It is worth pointing out that Bleidorn et al. (2010) used a very different method of collecting their data. All the participants rated the same list of goals, which were later recoded into two very large entities representing agency and communion. This may have

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resulted in a loss of detailed information as heterogeneous categories were merged. According to some genetic studies on personality, more detailed personality facets show different patterns of individual sources of variation than major personality traits (Jang, McCrae, Angleitner, Riemann, & Livesley, 1998; Kandler, Riemann, Spinath, & Angleitner, 2010). The same phenomenon seems to be true for personal goals as well. The relatively large non-shared environmental effect found in this and previous studies on goals may be partly due to measurement error included in the nonshared environmental component. The variation in the five personal goals related to parents and relatives, health, work, hobbies and life philosophy was mostly due to non-shared environmental effects. This result could reflect the high urgency of embarking on a career, forming ideological commitments and being vigorous and healthy (yet having a very low risk of serious health problems) in this cohort of young adults, which may override the possible genetic effects (Shanahan & Hofer, 2005). Goals related to work as well as health are likely to be closely tied to life events (e.g., getting a degree, being ill), which may be highly idiosyncratic. Similarly, goals related to parents and relatives, hobbies and life philosophy may result from uniquely individual experiences. Overall, the results of the present study are in line with previous findings on values and attitudes in the field of behavioral genetics (Plomin, DeFries, McClearn, & McGuffin, 2001). Our third research question concerned the extent to which the contents of personal goals and the five personality traits share the same genetic and environmental effects. According to our findings, openness to experience showed the most robust associations with personal goals, which reflects previous findings showing frequent and relatively strong associations with personal goals (Roberts & Robins, 2000; Roberts et al., 2004). As expected, we found a moderate amount of shared variation between openness to experience and personal goals related to education. Previous research has revealed an association between openness to experience and general intelligence, and also shared genetic effects (see Wainwright, Wright, Luciano, Geffen, & Martin, 2008). Given that intelligence is likely to contribute to success in education, which further increases the number of education-related goals, there is an evident need to investigate the role of intelligence in future genetic studies. In the present study, we controlled for the possible effects of the previous educational level. We also found that the association between openness to experience and the absence of personal goals related to establishing a family partly reflected genetic effects. One possible reason for this association is that family-related goals constitute an alternative set to career-oriented and educational goals (the correlation between education-related and family-related goals was 0.21, p < .001, and between educational level and family-related goals, 0.17, p < .001). This may apply to the present study in particular, in which the participants responded to open-ended questions and could choose to express the goals that were important to them. Limiting number of goals to four may restrict the combination of goals mentioned. Another possible explanation for this genetic correlation is that openness to experience may lead to a less conservative pattern of goals and values that do not give high importance to the question of a future family. A genetic correlation was also seen between openness to experience and the absence of personal goals related to property, again possibly due to the less conservative value pattern. Interestingly, agreeableness also shared a genetic effect with the absence of personal goals related to property, which indicates that non-selfish, altruistic interests and agreeableness may share some common genetic background. Previous phenotypic analyses suggest that both openness to experience and agreeableness are negatively associated with economic interests (Costa & McCrae, 1988; Roberts & Robins, 2000; Roberts et al., 2004). All in all, the results indicate

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that, although believed to be influenced largely by environmental factors, some materialistic goals are intertwined with personality characteristics and reflect some genetic foundation (Giddens, Schermer, & Vernon, 2009). Self-related goals showed the strongest phenotypic association with personality traits. The pattern of correlations suggested a genetic relationship with extraversion. Given that such goals have been described in terms of rumination in people who are concerned about their own self-development and about their negative features in particular, their association with low externality and the related lack of positive affiliation with other people is quite understandable. There is also evidence of an association between self-related goals and both depressive symptoms and a low level of well-being (Salmela-Aro, Nurmi, Saisto, & Halmesmäki, 2001a; Salmela-Aro et al., 2001b). Although, as expected, neuroticism and openness to experience were also associated with self-related goals, the pattern of the twin correlations suggests that this association is wholly attributable to environmental factors. Our results also showed that, although genetic effects contributed to the association between some personal goals and personality traits, in all cases the genetic variance specific to each trait and goal prevailed over the joint genetic variance. This is a significant finding because it indicates that, because personality traits and personal goals operate on two different personality levels, their genetic and environmental determinants are also somewhat independent. Bleidorn et al. (2010) reported a genetic association between personality traits and two major life goals, agency and communion, of approximately the same magnitude as found in the present study. However, the magnitude of the genetic variance specific to major life goals was higher in ours, leaving the proportion of correlated genetic effects considerably lower. The present study also has its limitations. First, our sample size was not large enough to allow the assessment of genetic and environmental effects on personal goals that have very low frequencies in young adults (such as daily chores and change of residence) or the division of goal categories into certain subgoals (related to different types of property or education, for example). Second, the positive and negative dimensions of goals were mixed, which may affect the variance decomposition. It has been suggested, for example, that positive traits may have more of a shared environmental influence and negative traits more of a genetic influence (Krueger, Hicks, & McGue, 2001). Third, given that estimates vary from one population to another and from one time point to another, the findings should be replicated using different populations. Fourth, our study on goals was cross-sectional, thus we were not able to investigate the role of genetic factors in changes in personal goals. There is, therefore, a need to extend the study of personal goals in a longitudinal direction. Finally, in the present study we used several independent statistical tests to investigate our research questions. As we did not correct the significance level due to the multiple testing, there is an evident need to replicate our results. In sum, it could be concluded from the present study that the goals that people have are influenced not only by the normative demands of the current life stage and by life history in terms of previous success in goal aspiration, but also by genetic factors that affect the objectives and events that individuals find appealing at certain stages of their lives. Moreover, part of the association between the contents of personal goals and personality traits was due to shared genetic effects.

Acknowledgments The data collection was supported by the National Institute of Alcohol Abuse and Alcoholism (Grants AA-12502, AA-00145, and AA-09203 to RJR), the Academy of Finland (Grants 100499,

205585 and 118555 to JK, Grants 134931 and 139168 to KSA), the Jacobs Foundation and the Academy of Finland Centre of Excellence in Complex Disease Genetics.

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