Genetic and Environmental Influences on Human Psychological Differences, Thomas J. Bouchard, Jr., Matt McGue.
Selon Jergen, le facteur g reflète certaines propriété du cerveau humain, compte tenu du fait qu’il est étroitement lié à la taille du cerveau, au taux métabolique, à la vitesse de conduction nerveuse, et la latence des potentiels évoqués électriques. Pour comprendre l’importance pratique du facteur g dans la vie quotidienne (voir Gottfredson).
La figure 3, représentée à partir des données de nombreuses études, de Burks à Segal, montre que les influences environnementales partagées sur le QI deviennent insignifiantes à l’âge adulte, suggérant l’importance de la prise en compte de l’âge.
In fact, and as shown in Figure 3, a major contributor to the heterogeneity in the adoptive sibling correlation is the age of the sample. The childhood data are from Burks (1928), Freeman et al. (1928), Leahy (1935), Skodak (1950), Scarr and Weinberg (1977), and Horn et al. (1979). The adult data are from Scarr and Weinberg (1978), Teasdale and Owen (1984), Scarr et al. (1993), Loehlin et al. (1997), and Segal (2000).
The adoptive siblings assessed in childhood or adolescence, when they were presumably still living together, had an average IQ correlation of .26, suggesting that common rearing accounts for 26% of IQ variance. The adoptive sibling pairs assessed in adulthood, however, had an average IQ correlation of only .04, suggesting that common rearing effects do not endure once the siblings no longer live together.
La figure 4 (Wilson, 1978) indique le changement dans les contributions génétiques et environnementales sur le QI avec l’âge. Les corrélations constatées entre les jumeaux monozygotes et dizygotes deviennent de plus en plus disparates, illustrant une fois de plus l’influence environnementale (partagée) qui diminue avec l’âge.
Twin studies also suggest that genetic and environmental contributions to IQ vary with age. Wilson (1978) was one of the first to explore changes in kinship correlations for IQ in a longitudinal study, and his findings are shown in Figure 4.
Prior to age 2, the phenotypic assessments used in this study are best characterized as indicies of mental development, and not IQ. The content of these mental development assessments is quite different from the, primarily verbal, content of the IQ tests used in the later years. In any case, if we use the Falconer formula 2(r mz – r dz) as an estimate of genetic influence we see that in the early months there is minimal genetic influence but that by the age of 1 genetic factors begin to express themselves and they get much larger from 4 years of age and on. The same influences are expressing themselves in the sib-twin and midparent-offspring correlations. These longitudinal data thus suggest that with age, genetic factors increase while environmental factors decrease in importance.
Building on the work by Wilson, McGue et al. (1993) plotted twin IQ correlations by age. The IQ variance estimates derived from comparing the age-specific MZ and DZ correlations are shown in Figure 5.
La figure 6 résume les recherches de Plomin (1997). Avec l’âge, le QI de l’enfant ressemble de plus en plus à celui de ses parents biologiques, et de moins en moins à celui des parents adoptifs. On note que les corrélations parents-enfants divergent significativement après l’âge de 5 ans entre les deux groupes.
Recent longitudinal family and adoption data from the Texas Adoption Project (TAP) and Colorado Adoption Project (CAP) confirm these findings. In the TAP, researchers reported that estimates of IQ heritability increased (from .38 to .78) while estimates of shared environmental influence decreased (from .19 to .00) as the adopted children in the families aged from adolescence to young adulthood (Loehlin et al., 1997). A notable feature of TAP is that test reliability was incorporated into the model so that parameter estimates refer to true score rather than observed score variance. In CAP (Plomin et al., 1997), parent-offspring IQ correlations (weighted average for mothers and fathers) for adoptive and control (matched biological) families were assessed at 1, 2, 3, 4, 7, 12, and 16 years of age. These findings are shown in Figure 6.
The correlations are modest and in about the same range for both types of families until about age 5, after which they diverge dramatically, with the adoptive family correlations reaching an asymptote of zero at age 12. Model fitting to the data yielded a heritability estimate of .56, an environmental transmission value of .01, an assortative mating value of .21, and a genotype-environment correlation of .01. A very similar trend, of adopted children becoming more similar to their biological than their adoptive parents over time, was reported by Honzik (1957).
La figure 7 (Boomsma, 1999) indique là encore l’importance de l’héritabilité du QI à l’âge adulte, même s’il a été trouvé que l’héritabilité du QI tend à diminuer chez les personnes âgées, sans augmentation néanmoins de la variance du QI attribuée aux facteurs environnementaux partagés.
Boomsma et al. (1999) have recently published estimates of heritability and shared environmental influence for IQ by age (5, 7, 10, 16, 18, 27 years of age) from a sample of Dutch twins. To these estimates we add data extending the Dutch sample to age 50 that were kindly provided to us by Prof. Boomsma (see also Posthuma et al., 2002a, Figure 12.1). The results are shown in Figure 7.
Interestingly, the heritability of general cognitive ability may decline in late life. McClearn et al. (1997) reported estimates of heritability and shared environmental influence in a sample of 117 twins age 80 years or older. For the first principal component of the seven cognitive tests, an index of g, heritability was estimated at .62 (95% CI, .29–.73), and shared environment was estimated at .11 (95% CI, .00–.47). If a short form of the Weschler Adult Intelligence Scale was used to estimate g, heritability was estimated at .55 (95% CI, .19–.76), and shared environment was estimated at .20 (95% CI, .00–.47). The influence of shared environment could have been dropped from the model in both instances as indicated by the confidence intervals. McGue and Christensen (2001) recently replicated McClearn et al.’s findings by reporting a heritability estimate of .54 (95% CI, .27–.63) for a general cognitive ability measure, in a sample of Danish twins 75 years and older. These heritability estimates are a bit lower than in younger adult data (Plomin et al., 1994), and suggest that heritability decreases in older cohorts. This conclusion is also supported by longitudinal studies of older twins (Finkel et al., 1995, 1998).
La table 2 confirme l’importance des influences génétiques en ce qui concerne les capacités verbales, les capacités spatiales, la rapidité de perception, et la mémoire. Les influences environnementales partagées sont généralement proches de 0,0 et de 0,1. Chacune des quatre catégories démontre l’accroissement des facteurs génétiques entre l’adolescence et l’âge adulte. L’héritabilité des capacités verbales et spatiales diminue chez les personnes âgées alors même que les influences environnementales partagées restent tout aussi insignifiantes, ce qui suggère que les influences environnementales non partagées doivent augmenter à un âge avancé.
While the bulk of behavioral genetic research on human cognitive ability has focused on general cognitive ability, research on specific mental abilities (i.e., abilities at one level below the general factor in the hierarchical model) also implicates the importance of genetic influences. The CAP has reported parent-offspring correlations by age for Verbal Ability, Spatial Ability, Speed of Processing, and Memory. The results are similar to those in Figure 6 in that the adoptive correlations hover about zero and the biological correlations climb with age, although for the specific mental abilities (SMA) they are not as high.
Table 2 illustrates much the same age effect on heritability (increasing through middle age until it begins to drop in old age) as we showed for g, except for memory. These results are not a surprise as these mental abilities are highly intercorrelated and constitute the vehicles with which we derive a measure of g.
It is possible to fit what is known as a common pathway model, shown in Figure 8, to such data and estimate the percentage of genetic and variance contributed by g and by each specific test. As the figure shows, genetic (G), shared (C), and nonshared (E) sources of variance are estimated for the cognitive factor (g), which is made up of the variance common to the SMAs, and then separately estimated for the remaining variance that is not shared.
The solution for the Minnesota Twin Study of Adult Development and Aging is shown in Table 3. The total heritability (under Total) is now divided into that which is shared with g (General) and that which is specific to each test. The same is true for the nonshared environmental variance, which is largely specific to the tests. Note that the model allows for shared environmental variance at both the general and specific level. None is necessary at the general level to fit the data. The heritability of the general factor g for this data set is .81.
Le QI n’est pas le seul trait à montrer une forte héritabilité. Les études sur les traits de personnalité racontent la même histoire. La table 5 rapporte les niveaux d’héritabilité pour chaque trait de personnalité composant le Big Five.
Early meta-analyses of twin studies of personality can be found in Nichols (1978), Eaves et al. (1989), and Bouchard (1997). In addition to these, Bouchard and Loehlin (2001) organized findings from four recent large studies of adult twins according to the Big Five model and compared these results to a synthesis of twin, adoption, and family studies conducted by Loehlin (1992), as well as to Bouchard’s (1997) reanalysis of the Nichols (1978) data. A summary of this comparison, given in terms of estimates of broad heritability, is given in Table 5. The Jang et al. (1996) and Reimann et al. (1997) studies used versions of the NEO (Costa and McCrae, 1992), a widely used self-report measure of the Big Five. Findings from both the Waller (1999) and Loehlin (1998) studies used different instruments, but the findings could be organized according to the Big Five (1998). In all of these studies shared environmental influence was estimated as zero or near zero.
Analyses based solely on twin samples (i.e., the four individual studies and the Bouchard review) consistently yield higher estimates of personality heritability than analyses based on twin, adoption, and family data (i.e., the Loehlin review). The difference may be due to nonadditive genetic effects (which contribute to the similarity of MZ twins but not to parent-offspring pairings; Plomin et al., 1998), although a variety of methodological and measurement problems (age at measurement, comparability of measures, sampling, etc.) cannot be ruled out. Combined model fitting of multiple kinships using the same instrument can help determine whether nonadditive genetic factors are operative.
La table 6 montre les héritabilités indiquées pour les items du Multidimensional Personality Questionnaire. Le fait que les niveaux d’héritabilité des jumeaux monozygotes élevés ensemble (MZT) et séparément (MZA) soient extrêmement proches indiquent la preuve de l’absence des influences environnementales partagées, et donc, de l’éducation parentale.
Finkel and McGue (1997) fit models to MPQ [Multidimensional Personality Questionnaire] data gathered from 12 sets of kinships (male-male, female-female, and male-female MZ and DZ twins and sibling pairs, and the four gender-specific parent-offspring pairings) totaling 4298 pairs. The participants were aged 17 years or older and drawn from the Minnesota Twin Family Registry (Lykken et al., 1990). A variety of sources of variance were tested for, including sex-limitation. The results are presented in Table 6 by sex, and nonadditive variance (d²) is estimated for each trait. […] No significant shared environmental variance was detected for any scale and there was no evidence to suggest that different genetic factors influenced personality in males and females. There was, however, evidence for sex differences in heritability for three specific scales, Alienation, Control, and Absorption (shown in bold), but for none of the higher-order factors. For most of the specific and higher-order scales, estimates of nonadditive genetic effects were considerable (typically accounting for from 10 to 20% of the variance) and statistically significant.
La table 7 illustre à quel point il est difficile d’estimer avec précision la variance génétique non-additive. Même si les différentes études s’accordent sur la contribution globale des facteurs génétiques, il existe de nettes différences dans la proportion de la variance génétique accordée aux effets non additifs. Les auteurs ajoutent :
The 95% confidence intervals for nonadditive genetic variance based on the very large combined sample do not include the estimates from the Virginia 30,000 sample (which makes up about half the sample from which the estimates are derived) nor those from the Minnesota male sample, and they barely include the estimate from the Minnesota female sample. Notice also that parental environmental and G-E covariance effects, which can be estimated with these large kinships, are estimated to be very small. Combined data on the Extraversion factor have not been published. Turning finally to Constraint (Table 6), the third MPQ factor, we see that the heritability estimate is close to the MZT correlation, which, when compared to the MZA correlation, suggests no shared environmental influence, a result consistent with the model fitting. We do not believe that a direct comparison of Constraint with either Psychoticism or Conscientiousness is appropriate.
A comparison of the overall heritabilities, and the MZT and MZA correlations for the specific scales of the MPQ, is also informative. The fact that the MZT correlations very closely approximate the heritabilities flows directly from the failure to find shared environmental influence and is a consistent finding for most personality traits. The similarity between the MZT and MZA correlations independently confirms the lack of shared environmental influence and the broad heritability estimates. In the personality domain the MZT correlation alone provides an excellent approximation to the heritability of a trait.
Quant il s’agit de répondre à la question des influences environnementales non partagées sur la personnalité, le Nonshared Environment in Adolescent Development (NEAD) a enquêté le sujet. L’étude utilise un modèle sur la concordance des individus apparentés sur plusieurs traits de personnalité. L’héritabilité de ces six traits était de 0.68 et la contribution environnementale non partagée de 0.17. La fiabilité (reliability) moyenne de ces six mesures était de 0.81, ce qui suggère la possibilité que les erreurs de mesures pourraient expliquer la totalité de la variance environnementale non partagée. L’effet moyen associé aux facteurs environnementaux partagés était de 0.15 même si l’effet n’était large que pour deux des six traits (Bouchard & Loehlin, 2001, Table 6). Les questionnaires ayant été administrées plusieurs fois, ces mesures ont été aggrégées afin de réduire les erreurs de mesure spécifiques aux réponses des sujets aux questionnaires administrées à une certaine période donnée. Pour résumer, les auteurs notent :
Genetic influences account for approximately 40–55% of the variance in personality. Some of the genetic effects appear to be nonadditive genetic variance, although it is difficult to precisely estimate such effects. There appear to be sex differences in heritability, but they are infrequent and probably not large, and the same genes appear to operate on all traits in both sexes.
Le conservatisme (à savoir, la réticence au changement) montre lui aussi de forts niveaux d’héritabilité. Le contrôle du QI n’altère pas l’héritabilité du conservatisme.
Eysenck’s Public Opinion Inventory, which measures two factors, Radicalism versus Conservatism (R) and Toughmindedness versus Tendermindedness (T), and an 80-item personality inventory, were administered to 451 MZ and 257 DZ twin pairs (preponderantly females). R yielded a heritability of .65 and was entirely independent of the personality measures. T yielded a heritability of .54 and had a small correlation with the personality trait of Extraversion. This groundbreaking report was virtually ignored and had very little influence on the field. About the time of the Eaves and Eysenck report, Scarr and Weinberg (1978) were carrying out the adoption study cited earlier. These investigators included the California F-scale (F for Fascism) in their assessment of adoptive and biological families. The F-scale had been developed by a team of researchers interested in the rise of Nazism, who published their findings in a landmark book — The Authoritarian Personality (Adorno et al., 1950). The F-scale had been the focus of a very large body of research but eventually grew to be disfavored, primarily because of its very high negative correlation with IQ (Christie and Jahoda, 1954; Stone et al., 1993). In their adoption study, Scarr and Weinberg (1981) also found that individuals who were high in verbal ability tended to score low on the F-scale. When she adjusted statistically for the F-scale’s association with verbal ability, however, the heritability of the F-scale remained statistically significant, even if diminished. Remarkably and unexpectedly, heritable influences on authoritarianism could not be accounted for by heritable influences on cognitive ability.
Martin et al. (1986) administered the 50-item version of the Wilson-Paterson Conservatism scale (WPCS) to a large sample of MZ, like-sex DZ, and unlike-sex DZ twins from the Australian twin registry. The WPC scale uses a “catch phrase” format, whereby respondents are asked to indicate whether they agree with various topics (e.g., death penalty, X-rated movies, women’s liberation, foreign aid, abortion, etc.) by simply circling YES, ?, or NO. The heritability of the WPC scale was estimated at .62 in a model-fitting analysis that took into account assortative mating as estimated in a separate husband-wife sample. Perhaps even more remarkable than the estimate of significant heritable influences was the finding that shared environmental factors exerted no influence on social attitudes once the effects of assortative mating had been taken into account. Unfortunately, because these investigators did not include measures of personality and ability in their assessment battery, they could not determine the extent to which heritable influences on social attitudes were independent of heritable influences in these other domains. Nonetheless, their findings led them to the strong prediction that the conservatism scores of reared-apart MZ twins would be correlated .62. Martin et al.’s conclusion that social attitudes are moderately to strongly heritable has been supported in several subsequent investigations. In the MISTRA, the intraclass correlation for a 28-item version of the WPCS was .59 for MZA (n = 54 pairs) and .21 for DZA (n = 46 pairs) twins. The spouse (n = 93 pairs) correlation was .60. Model-fitting analyses yielded a highly significant heritability estimate of .56 (95% confidence interval .38–.70). This heritability is quite close to the value of .62 reported by Martin et al. (1986) using a longer and therefore more reliable version of the WPCS. Interestingly, statistical refinement of the WPCS measure in the MISTRA sample (dropping a few items that did not load on the first principal component) yields an MZA correlation of .62, a DZA correlation of .29, and a spouse correlation of .60 (heritability estimate of .60–95%, confidence interval of .43–.73; Bouchard, 2002). Eaves et al. (1999) also replicated the Australian twin study findings in a model-fitting analysis of data from the Virginia 30,000 (using 80 kinships of twins and their relatives). They reported an average heritability of .55 (.65 for males, .45 for females) for the same 28-item version of the WPCS used by Bouchard et al. (2002).
A study by McCourt et al. (1999) that assessed Right Wing Authoritarianism (RWA) in both a sample of reared-apart twins from the MISTRA and a sample of reared-together twins from the Minnesota Twin Registry provided an opportunity to test Martin et al.’s conclusions concerning both the existence of heritable and the lack of shared environmental influences on a social attitude measure other than the WPCS. The twin correlations from this study are given in Table 8. Because RWA was correlated .37 with IQ in the MISTRA sample (IQ was not assessed in the reared-together twin sample), the reared-apart twin correlations were adjusted for IQ. This adjustment had only a modest effect on the MZA and DZA correlations.
Il y a peu de différences dans les corrélations MZA, ou monozygotes élevés séparément, et MZT, ou monozygotes élevés ensemble, ce qui indique une faible influence environnementale partagée. Deux modèles ont été prouvés être adaptés aux données : un modèle posant que la similarité des jumeaux est due à des facteurs génétiques (h² = 0.64) et un modèle posant l’existence à la fois des facteurs génétique (h² = 0.50) et environnementaux partagés (c² = 0.16), ce qui tend à confirmer les tendances notées initialement par Martin et ses collègues.
Truett (1993), figure 9, trouve une relation négative entre les scores du conservatisme et le niveau d’éducation. Néanmoins, les scores du conservatisme augmentent avec l’âge, indépendamment du niveau d’éducation. La même chose est vraie en ce qui concerne l’héritabilité du conservatisme.
Beginning after age 30, mean WPC scores increase independently of educational level. In a large twin study, Eaves et al. (1997) investigated the implication of age changes in the WPC for estimates of genetic and shared environmental influences. Their findings are summarized in Figure 10. This figure illustrates two important points. First, genetic factors have little influence on WPC scores prior to age 20, but substantial influence after age 20. Second, there is considerable variation in the size of the differences between the MZ and DZ twins from point to point, reflecting both the effect of varying sample sizes and chance differences in the populations sampled.
La religiosité est un trait tout aussi héréditaire. Koenig et al. avaient démontré que l’héritabilité de la religiosité augmente avec l’âge. La théorie communément invoquée serait que les parents ont moins de contrôle sur le comportement de leurs enfants à mesure qu’ils grandissent, à plus forte raison lorsqu’ils quittent le foyer familial. L’affiliation religieuse, en revanche, n’est pas médiée par des facteurs génétiques.
Twin studies of religious affiliation (e.g., Christian, Jewish, Muslim) have shown that variance in this trait is nearly completely environmental in origin, thus demonstrating that model-fitting is not intrinsically biased and can indeed show no genetic effects when that is the case (Eaves et al., 1990). Alternatively, frequency of church attendance, an aspect of religiousness, appears to be genetically influenced. Using the Virginia 30,000 sample (Americans representing 80 distinct kinship pairings), Maes et al. (1999) reported that 25 to 42% of the variance (depending on sex) in religious attendance was heritable, while 14 to 34% of the variance was associated with shared environmental effects.
D’Onofrio et al. (1999) have summarized much of the behavioral genetic literature on adult religiousness through 1998. After updating reports for MISTRA based on our recent results, we have reproduced their findings for strictly religious measures in Table 9. The Martin et al. (1986) assessment of religiousness is based on single items. Items are known to be less reliable than scales composed of multiple inter-related items. Despite limitations in the assessment of religiousness, Martin et al. (1986) still found, on average, significant genetic (.28) and shared environmental (.25) influence. The MISTRA scales all suggest a moderate heritability for religiousness (mean = .47).
Participants in MISTRA are asked to complete a number of “environmental measures”, one of which is the Moral Religious Emphasis (MRE) scale of the Family Environment Scales (Moos and Moos, 1994). This instrument requires a retrospective report of family/parental behavior while the respondent was growing up (Hur and Bouchard, 1995). For study participants who were reared by their biological parents (mostly spouses of the twins) the correlation between MRE and Intrinsic Religiousness is .53. For adopted individuals the correlation is only .10. This comparison is supportive of strong genetic and weak environmental influence on the trait. Although there was a tendency for MZA twins to be placed in rearing homes with similar levels of MRE (r = .32), this placement effect contributes only .003 to the MZA correlation because of the weak correlation between the MRE and Intrinsic Religiousness in adoptive families. The focus in the previous section has been on adult religiousness. As with social attitudes, genetic influence on religiousness is attenuated in younger samples. Winter et al. (1999), using the MMPI Religious Fundamentalism scale, reported heritabilities of .11 and .22 and shared environmental effects of .60 and .45 for Finnish adolescent girls and boys (16 years olds), respectively. Boomsma et al. (1999) also reported little genetic influence on three measures of religion [Religious Upbringing (no/yes), Religious Affiliation, Participation in Religious Activities (none, am religious but do not participate, am an active member of the church)] in a sample of adolescent (18 year old) twins. These measures do not directly address religiousness as a trait, but the last one should have at least a modest correlation with direct measures, and these results with adolescents stand in clear contrast with findings on adults. It will be interesting to see what happens when direct measures of religiousness are gathered on these individuals in adulthood.
La plus récente étude de jumeaux (MZ = 195 pairs, DZ = 141 pairs) concernant l’influence génétique sur les attitudes, de Olson (2001), utilise 30 items hétérogènes (non sélectionnés pour mesurer un ou plusieurs facteurs sous-jacents). Une moyenne d’héritabilité de h² = 0.32 a été trouvée, dont 26 de ces items montrèrent de forte influences génétiques.
Une analyse factorielle de ces items a produit 9 facteurs. Trois facteurs avaient une héritabilité de zéro. Les 6 autres avaient une héritabilité moyenne de 0.50 et une influence environnementale partagée de 0.04. L’item “Organized Religion” avait une héritabilité de 0.45 et une influence environnementale partagée de 0.00. Peu de ces héritabilités étaient médiées par des facteurs de personnalité, comme il a été possible de démontrer que certaines attitudes et mesures de personnalité partagent des variances génétiques.
Les intérêts professionnels sont tout aussi héréditaires. La théorie du choix vocationnel (Holland, 1997) distingue six catégories d’intérêts professionnels (réaliste, investigateur, artistique, social, entreprenant, conventionnel).
Many psychologists, as well as most lay people, believe that vocational interests are no more than a manifestation of personality traits. To make matters worse the major theorist in this domain calls his theory a “Theory of Vocational Personalities” (Holland, 1997).
In simple terms, Holland’s theory purports that there are six major general interest factors (often called Themes), and the correlations between the various types are “inversely proportional to the theoretical relationships between them” (Holland, 1985, p. 5).
Nichols grouped interest measures in a manner that is quite similar to the Holland themes (Practical Realistic, Science = Investigative, Business = Enterprising, Clerical = Conventional, Helping = Social). The mean intraclass correlation is .48 for MZT twins and .30 for DZT twins. The associated mean Falconer heritability estimate [i.e., 2(rMZ – rDZ)] is .36 (Falconer, 1960).
The Minnesota Twin Registry (1990) includes in its assessment battery the Minnesota Occupational Interest Inventory and the Minnesota Leisure Time Inventory. The two inventories yield 17 occupational interest scales and 18 leisure interest scales that are highly inter-related (Lykken et al., 1993; Waller et al., 1995, Table 3). Waller et al. (1995) have reported boxplots of intraclass correlations for both instruments, for both MZ and DZ twins by sex. They are shown in Figure 12. The results are remarkably similar to those reported by Nichols, although the DZ correlations are a little lower, implying somewhat higher heritabilities (between .40 and .50).
Betsworth et al. ont étudié l’héritabilité de ces six catégories d’intérêts professionnels avec d’autres méthodes, incluant les familles biologiques et adoptives, ainsi que des jumeaux élevés ensemble et séparément. La table 11 indique des niveaux d’héritabilité assez disparates entre les jumeaux élevés ensemble et séparément. À première vue, on pourrait suggérer que ce résultat indique aussi la preuve d’une influence environnementale partagée. Néanmoins, les échantillons sous étude comprenaient des sujets encore très jeunes. Les intérêts professionnels ne sont pas encore complètement cristallisés à cet âge, d’où l’importance de mesurer l’héritabilité de ces traits jusqu’à l’âge adulte.
Betsworth et al. (1994) combined data from multiple twin, adoption, and family studies, and scored and analyzed the common interest scales. The twin and family correlations from their analyses are given in Table 11. Their model-fitting results are given in Table 12. The sample of twins reared together (from the National Merit Scholarship Twin Study) dominates the data set in terms of sample size. The sample of reared-apart twins has the smallest sample sizes (particularly the DZA sample).
Nevertheless, on average the MZA twin correlation (.32), which reflects both additive and nonadditive genetic variance (broad heritability), comes close to the overall mean estimate of .36 for the broad-sense heritability. The twins reared together, if taken alone, however, suggests a mean heritability of .47, additive genetic effects only, and no shared environmental effects. The apparent discrepancy between the results from the reared-together and reared-apart twins is due to two factors: there is consistent evidence for shared environmental effects (i.e., reared-apart twins are less similar than reared-together twins and adopted relatives have similar, albeit modestly similar, interest patterns); and once these shared environmental effects have been taken into account, there is evidence for nonadditive genetic effects (e.g., MZA twins are more than twice as similar as DZA twins).
… the offspring in the various adoption and family studies reviewed above were still teenagers at the time of their interest assessment. Interests have not fully crystallized by that age, and it may be that the heritability of interests, like the heritability of IQ, increases with age.
Arvey et al. rapportent une étude sur la satisfaction intrinsèque et extrinsèque du travail. Conformément à leur théorie, l’héritabilité mesurée est plus élevée en ce qui concerne la satisfaction intrinsèque.
Arvey et al. (1989) reported a study of intrinsic (i.e., perceived benefits from a job) and extrinsic (i.e., objective benefits of employment) job satisfaction using MZA twins (n = 34). They predicted that because intrinsic satisfaction most likely reflects personal and internal factors it would show a higher heritability than extrinsic satisfaction, which is generally thought to be controlled by external factors. The correlation for intrinsic satisfaction was .32 and statistically significant, while the correlation for extrinsic satisfaction was .11 and not statistically significant, confirming the hypothesis. A follow-up study (Arvey et al., 1994) of 95 MZT and 80 DZT pairs yielded a broad heritability estimate of .23 for intrinsic satisfaction, while variance in extrinsic satisfaction could be explained entirely by environmental factors. Data previously gathered from the National Academy of Science and National Research Council (NAS-NRC) twin sample (MZT, n = 1152 pairs; DZT, n = 1055 pairs) included a single question (“How do you feel about the job you now have?”) scored on a five-point response format. We take this measure to assess general satisfaction. Model fitting to these data yielded a heritability estimate of .27. It seems reasonable to conclude that about 25% of the variance in measures of job satisfaction is due to genetic factors. While this may not seem like a great deal, we are not aware of any other single source of influence (e.g., compensation, benefits) that explains this much of the variance in job satisfaction.
Another study in this domain used small samples of MZA (n = 23 pairs) and DZA (n = 20 pairs) and the Minnesota Importance Questionnaire to measure the work values of Achievement, Comfort, Status, Altruism, Safety, and Autonomy. It yielded estimates of genetic influence of .56, .31, .43, .18, .41, and .34 respectively (mean = .37) (Keller et al., 1992). Finally, the NAS-NRC sample discussed above included 15 job importance items in addition to the job satisfaction item. The mean heritability estimate for these items was .34.
La table 13 indique que le niveau de concordance pour les différentes formes de psychopathologie est bien plus élevé chez les jumeaux monozygotes que chez les jumeaux dizygotes, ce qui démontre une nouvelle fois la prédominance des facteurs génétiques en ce qui concerne la psychopathologie.
Here, we report in Table 13 reared-together MZ and DZ twin concordance rates for various forms of psychopathology. … As is evident for the adult and childhood disorders listed, concordance rates are consistently higher among MZ than among DZ twins, consistent with the existence of genetic influences.
The heritability of liability has been estimated to be approximately 80% for schizophrenia (Gottesman, 2001), attention deficit/hyperactivity disorder (Sherman et al., 1997), autism (Smalley et al., 1988; Szatmari, 1999), and Tourette syndrome (Price et al., 1985), approximately 50–60% for alcoholism (McGue, 1991, 1995) and cannabis dependence (Lynskey et al., 2002), and approximately 40% for major depression (Kendler and Prescott, 1999). Genetic factors clearly exert a major and pervasive influence on risk of behavioral disorders.
As is the case with personality, for most forms of psychopathology the major source of nongenetic influence appears to be nonshared rather than shared environmental factors. Antisocial behavior appears, however, to be an exception to this general rule. Twin studies have generally found that approximately 30% of the variance in adolescent conduct disorder can be attributed to shared environmental effects (e.g., Gottesman and Goldsmith, 1994; Jacobson et al., 2000). Of some interest is whether these shared environmental effects persist into adulthood.
L’importance de la prise en compte de l’âge dans les études investigant l’héritabilité des traits psychologiques est justifiée une nouvelle fois compte tenu du fait que l’héritabilité de ces traits augmente avec l’âge. C’est le cas, par exemple, du comportement antisocial.
In a large twin study of U.S. male veterans who retrospectively reported their history of adolescent and adult antisocial behavior, Lyons et al. (1995) reported that the portion of variance in antisocial behavior attributable to shared environmental factors declined from 31% in adolescence to only 5% in adulthood. In contrast, the heritability of antisocial behavior increased from 7 to 43% over the same time period. A recent meta-analytic review of 51 twin and adoption studies of antisocial behavior confirmed the decrease in shared environmental effects with age, but failed to find the expected increase in genetic influences (Rhee and Waldman, 2002).
L’importance des facteurs génétiques en ce qui concerne un grand nombre de caractéristiques ne concorde pas avec la théorie du déterminisme culturel. Les facteurs environnementaux “non partagés” impliqués dérivent de l’expérience personnelle propre, et cela suggère qu’ils ne peuvent pas être manipulés aisément par les interventions gouvernementales.