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.
© iStockphoto.com/YinYang
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 study to determine an effect. Effect size is an important measure of the effects of a treatment on a mental disorder. One could compare two different types of psychotherapy, for example, or even a psychotherapy combined with a particular medication.
Replication and Meta-Analysis
Although researchers seek to design studies to rule out alternative hypotheses, they cannot consider every possibility. When a study is performed in different laboratories with different participants, a process referred to as replication, we can have more certainty that the results found reflect the true nature of what we are studying. Thus, scientists seek to find a number of different studies from different laboratories that answer the same research question. For example, various studies from around the world have shown structural brain differences in individuals with schizophrenia including enlarged ventricles in the brain (Faludi & Mirnics, 2011). A number of journals, such as Clinical Psychology Review and Psychological Bulletin, are designed to publish reviews of research in the field.
replication: the process whereby a study is performed in different laboratories with different participants and obtains the same results
Once the literature in a particular area has been reviewed, it is possible to examine statistically the results of all the studies taken together. This technique is referred to as meta-analysis. Meta-analysis is a statistical technique for combining a number of studies to improve the reliability of the results. For example, a large number of studies have examined depression and how it can be treated with cognitive behavioral therapy (Butler, Chapman, Forman, & Beck, 2006). With a meta-analysis, it can be asked, what if we consider all of these studies to be one study. Then we could calculate the common effect size of all of the available studies. A similar meta-analysis was performed to examine the effectiveness of interpersonal psychotherapy for depression (Cuijpers et al., 2011). While the use of meta-analysis is often invaluable, the LENS below points to a potentially complicating factor when undertaking such a review of previously published studies.
meta-analysis: statistical examination of the results of studies taken together and treated as one study
Lens
Treatment and Clinical Perspectives:
