Introduction to Abnormal Child and Adolescent Psychology. Robert Weis
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study, researchers specify the direction of the relationship between variables by measuring them at different times. In a prospective longitudinal study, researchers measure a hypothesized predictor variable at Time 1 and measure its expected outcome at Time 2. For example, Humphreys and colleagues (2013) conducted a second, prospective longitudinal study examining children’s ADHD symptoms in early childhood and depressive symptoms in early adulthood. They found a significant, positive correlation between early attention problems and later depression. Because children’s ADHD and depressive symptoms were assessed at different points in time, the researchers concluded that children’s attention problems emerged before their depressive symptoms (Markon & Markon, 2018).
Figure 3.2 ■ Correlations Do Not Imply Causality
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Note: (A) Children’s behavior problems can increase parenting stress; (B) parenting stress can increase behavior problems; or (C) other factors, such as divorce, can increase both behavior problems and parenting stress.
Prospective longitudinal studies are difficult to conduct because researchers must wait a long time to test their hypotheses and participants often drop out of studies before completion. Consequently, some researchers use other methods. In a retrospective longitudinal study, researchers recruit individuals with a known disorder and ask them (or their parents) to recall events in the past that might have predicted its emergence. For example, researchers might recruit a large sample of young adults with depression. Then, they might ask their parents to recall symptoms of ADHD that these adults showed as children. The chief limitation of retrospective longitudinal studies is that people may not accurately recall past events.
In a follow-back longitudinal study, researchers recruit individuals with a known disorder and examine their medical records, school reports, or other objective data for events in the past that might have predicted its emergence. For example, researchers might ask young adults with depression for permission to review their childhood medical records. The researchers could then determine if participants were ever diagnosed with ADHD or prescribed medication to treat attention problems when they were children. Follow-back studies do not rely on people’s memories of past events. However, obtaining high-quality records is often difficult (Wright & Markon, 2018).
Mediators and Moderators
Considerable research has established a link between ADHD symptoms in childhood and depression later in life. Although this correlation exists, it does not tell us how the two variables are related or why some children with ADHD develop depression and others do not. To answer more complex and interesting questions like these, researchers look for mediators and moderators (Baron & Kenny, 1986).
A mediator is a variable that can help explain how two variables are related. Mediator variables explain the mechanism by which one variable predicts another variable. Mediators tend to be continuous variables—that is, they range from low to high and everywhere in between (Figure 3.3).
Figure 3.3 ■ Mediation and Moderation
Note: Mediators explain how two variables are related. Parenting a child with ADHD can cause stress and conflict in the home; the more stress and conflict, the higher children’s likelihood of depression (Humphreys et al., 2017).
Note: Moderators affect the direction or strength of the relationship between two variables. Children’s likelihood of depression depends on whether they are rejected by peers (Humphreys et al., 2017).
For example, parenting stress may mediate the relationship between ADHD in childhood and depression later in life. Children’s ADHD symptoms can increase parenting stress, prompting parents to lose their temper, blame their children for their inattention or hyperactivity, or discipline their children in harsh or punitive ways. Over time, these problematic parenting behaviors can cause children to feel depressed (Humphreys, Galán, Tottenham, & Lee, 2017).
A moderator is a variable that affects the direction or strength of the relationship between two other variables. Moderator variables help identify the conditions under which one variable predicts another variable. Moderators tend to be categorical variables such as gender (i.e., boy, girl), age (e.g., child, adolescent), ethnicity (e.g., White, non-White), family income (e.g., low income, middle class), and diagnostic status (e.g., ADHD, non-ADHD).
For example, peer rejection may moderate the relationship between ADHD in childhood and depression later in life. Children with ADHD who are rejected by their classmates and who have few friends are at increased risk for depression and other mood problems. In contrast, children with ADHD who are able to make friends and sustain relationships with classmates are less likely to become depressed (Humphreys et al., 2017).
Mediators and moderators are important because they can suggest ways to prevent or to treat childhood problems. For example, one way to prevent depression in children with ADHD is to help their parents manage their stress levels and avoid negative interactions with their children. A second strategy is to help children build friendships and avoid rejection by their classmates (Evans, Owens, Wymbs, & Ray, 2019).
Review
Correlational studies allow researchers to explore relationships between variables. The correlation coefficient (r) shows the strength and direction of the linear relationship between two variables. A correlation means that the two variables are associated with each other; it does not imply that one variable causes or affects the other.
Cross-sectional studies examine correlations between variables at the same point in time. Longitudinal studies examine correlations between variables at different points in time.
Mediators explain how two variables are related. They are usually continuous variables. Moderators explain the conditions under which two variables are related. They are usually categorical variables.
How Do Psychologists Explain Behavior?
Experiments
Researchers are usually not satisfied with knowing that variables correlate. They also want to determine whether a change in one variable causes a corresponding change in another variable. The best way to establish causality is to conduct an experiment. In an experiment, researchers randomly assign participants to two or more groups. They manipulate one variable (i.e., the independent variable) and hold all other factors constant. Then, they examine the effects of their manipulation on a second variable (i.e., the dependent variable). Experiments allow causal inferences because researchers randomly assign participants to different groups at the onset of the study and treat groups identically throughout the duration of the study. If groups differ at the end of the study, the researchers can conclude that their manipulation of the independent variable caused this difference (Kazdin, 2017).
Random assignment is essential for experimental research. Random assignment implies that each participant has an equal chance of being assigned to each of the groups. By randomly assigning participants, researchers decrease the likelihood that groups differ in meaningful ways before the study. Without random assignment, differences between the groups that emerge at the end of the study might be attributable to differences that existed at its beginning, rather than to the manipulation of the independent variable itself.
A randomized controlled trial is a special type of experiment used to test the efficacy of treatment. Typically, researchers recruit participants with the same disorder from mental health clinics, hospitals, or the community. Then, researchers randomly assign participants to at least two groups: a treatment group that receives