Abnormal Psychology. William J. Ray

gene by environment correlation concerns how certain genotypes and certain environments occur together. For example, sensation seeking as a personality trait has been shown to be inherited. Those individuals who are sensation seekers are more likely to put themselves in high-risk environments such as mountain climbing or auto racing. In this example, it is more difficult to determine the amount of variance attributed to genetic influences and environmental influences as separate factors. Thus, it is possible for genetic and environmental factors to influence each other in subtle ways.

      gene by environment correlations: how certain genotypes and certain environments occur together

      twin studies: a major paradigm of behavioral genetics involving examination and understanding of critical factors related to genetic influences by studying twins

      monozygotic (MZ) twins: identical twins resulting from the zygote (fertilized egg) dividing during the first 2 weeks of gestation

      dizygotic (DZ) twins: twins who arise from the situation in which two different eggs are fertilized by two different spermatozoa; these are called fraternal twins since their shared genes are approximately 50%—the same as that between any two siblings

      adoption study: research into the phenomenon where dizygotic (DZ) and monozygotic (MZ) twins have been raised apart, providing insights into the environmental and genetic influences on human development and behavior

      One major paradigm of behavioral genetics involves twin studies. Twins offer an occurrence in nature that allows for understanding critical factors related to genetic influences. This is largely based on the fact that there are two types of twins. Monozygotic (MZ) twins are identical twins resulting from the zygote (fertilized egg) dividing during the first 2 weeks of gestation. Because they both come from the same egg, their genes are identical. Dizygotic (DZ) twins, on the other hand, arise from the situation in which two different eggs are fertilized by two different spermatozoa. These are called fraternal twins, since their shared genes are approximately 50%—the same as that between any two siblings. DZ twins can be either same sex or opposite sex, whereas MZ twins must always be the same sex. By comparing the psychological traits of MZ and DZ twins, it is possible to obtain an estimate of heritability.

      A classic research design is to compare the responses of MZ twins with DZ twins on particular behavioral traits such as intelligence or personality characteristics. Since it is assumed that both DZ and MZ twins would have had similar environmental influences in their family, any differences between MZ and DZ twins would be seen to be the result of genetic influences. For example, Gottesman (1991) has studied schizophrenia with this design. In these studies, a particular MZ twin was more likely (.50) to have schizophrenia if the other twin also did. In DZ twins, this was not the case.

      Statistically, researchers examine the degree to which twins are identical to each other as a function of genetic influences and environmental influences. To answer this question, researchers create correlation coefficients for MZ twins and DZ twins. This correlation reflects how similar each type of twin is on a particular trait. From this, it is possible to determine the percentage of contribution to the trait that comes from environmental influences and the percentage of contribution that comes from genetic influences. For example, personality factors such as extraversion have been shown to have a 50% contribution of genetic factors and a 50% contribution of environmental factors.

      Studies of identical twins have shown they share similarities in IQ, temperament, and leisure time interests, whether they are raised together or apart.

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      Another important type of behavioral genetics research is the adoption study. This is the situation where DZ and MZ twins have been raised apart. In the United States since 1979, a series of twins who were separated in infancy and reared apart have been studied by researchers at the University of Minnesota (Bouchard, Lykken, McGue, Segal, & Tellegen, 1990).

      In work with identical twins, researchers studying over 100 pairs of twins found that about 70% of the variance in IQ could be associated with genetic factors (Bouchard et al., 1990). Later studies have supported this finding. However, if the child’s family lived in poverty, the degree of association dropped drastically. Although it is not surprising to find IQ or temperament to have genetic associations, it was intriguing to see that the leisure time interests (e.g., sporting activities, hobbies, reading preferences, etc.) of each twin in the pair were similar whether the twins were reared together or reared apart.

      linkage analysis: an examination of generations of families that looks for the association between certain deoxyribonucleic acid (DNA) marker alleles and particular traits

      A third type of study is referred to as a linkage analysis. Linkage analysis examines generations of families and looks for the association between particular deoxyribonucleic acid (DNA) marker alleles and particular traits. This is commonly done for disorders that run in families. This approach is often used for studying psychological and physiological disorders such as depression or bipolar disorder. As part of this type of research, scientists may examine the manner in which traits associated with the disorder are also apparent in first- and second-degree relatives.

      Clinical and Statistical Significance

      When performing research studies, we use inferential statistics to determine whether the IV influences the DV. By using statistics, we ask, if we performed the same experiment 100 times, what is the probability we would obtain the results seen in the present study? Actually, with statistics, the convention is to ask the question in the other direction. That is, how many times would we expect the results not to be the same? If the answer is less than 5 in 100 times (p <.05), we say that the results of the study are statistically significant.

      statistically significant: the probability that the independent variable (IV) influences the dependent variable (DV) by chance alone

      clinically significant: the characterization of the results of a study when, beyond being statistically significant, the findings indicate clinically important outcomes

      When considering medical or psychological disorders, we also want to know if the results of the study are clinically significant. For example, if you did a study related to dieting and everyone in the experimental group lost .5 pounds, while everyone in the control group gained 2 pounds, the results would be statistically significant. However, clinically, you would not recommend a treatment that only resulted in weight loss of half a pound.

      Consider a study in which a researcher wants to determine whether performing exercise would reduce depression. In this study, the experimental group would receive the exercise training for 2 months and the control group would not. Assume that the exercise did indeed reduce the depression score on a particular measure of depression from 21 to 20, whereas the control group’s depression did not change. Statistics might show a significant relationship between the two sets of data. However, clinically, it would not be worth the effort of having participants exercise for 2 months to have depression change by only 1 unit. Thus, a distinction is often made in clinical work between results that are statistically significant and those that are also clinically significant.

      effect size: the measured magnitude indicating the influence that a treatment has on the dependent variable (DV)

      One way to measure the magnitude of effect that a treatment has on the DV is referred to as effect size. A common measure of effect is Cohen’s d. In essence, Cohen’s d reflects the difference in the mean scores of the control and experimental groups divided by the standard deviation of the measure from the two groups. Effect size measures are important to clinical researchers for two reasons. First, they describe in quantitative terms the influence of the treatment, and second, they aid a researcher in knowing how many participants need to be included in a research