Introduction to Abnormal Child and Adolescent Psychology. Robert Weis

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      Nonequivalent Groups

      A nonequivalent groups study is a more sophisticated quasi-experimental study in which researchers compare participants in treatment and control groups, but participants are not randomly assigned to these groups. Because the researchers do not randomly assign participants to the two groups, the groups are nonequivalent—that is, they may differ in some way before treatment. Therefore, if the researchers notice differences between groups after treatment, they cannot definitively say that treatment caused those differences.

      For example, researchers wanted to see if medication for ADHD in childhood might reduce the likelihood of alcohol and drug use problems in adolescence. Ideally, the researchers would randomly assign children to either a treatment group that receives medication or to a control group that does not. Then, several years later, they could compare the prevalence of substance use problems among adolescents in the two groups.

      However, the researchers could not randomly assign children to treatment and control groups because it would be unethical to delay treatment to children with ADHD for so long. Instead, the researchers compared a group of adolescents with ADHD who took medication for this condition as children to another group of adolescents with ADHD who had no history of using medication to manage their symptoms. The researchers found that youths with ADHD who took medication were less likely to use alcohol and other drugs than youths with ADHD who never used medication (Hammerness, Petty, Faraone, & Biederman, 2017).

      Because their study included a control group, there are fewer threats to its internal validity. For example, it is unlikely that maturation explains differences in adolescents’ substance use because both groups of adolescents were assessed at the same point in their development. Similarly, the dropout rate of participants in both groups was roughly equal, ruling out attrition as a possible explanation for their findings. However, the use of nonequivalent groups can introduce a special threat to internal validity called selection bias.

      Selection bias refers to a systematic difference between the treatment and control groups that emerges when groups are not randomly assigned. Because their study lacked random assignment, youths in the treatment and control groups were nonequivalent at the beginning of the study. It is possible that subtle differences in demographic variables, family background, or attitudes toward medication existed between the two groups at the beginning of the study. Therefore, the differences in substance use seen at the end of the study might be explained by these subtle differences rather than the medication itself.

      Single Subject Studies

      A single subject study is a quasi-experimental study in which one participant’s behavior is assessed across time, usually with and without treatment. Single subject studies are frequently used when a therapist wants to assess the effectiveness of treatment with a particular client. Because single subject studies involve only one participant, they lack a control group and random assignment. However, the pattern of behavior shown by children when treatment is applied, compared to when it is absent or withdrawn, can suggest the effectiveness of the intervention.

      The simplest way to evaluate treatment effectiveness in a single subject study is to use an AB design. In this approach, we measure the frequency or severity of a child’s behavior before and after treatment. “A” refers to the level of behavior at baseline. “B” refers to the level of behavior when the intervention in applied. For example, a school psychologist might ask a teacher to estimate the percentage of time a student is attentive during math class each day for 2 weeks. The first week (A) serves as a baseline measure of the child’s attention. During the second week (B), the teacher uses a sticker chart to reinforce on-task behavior during class. She might praise the child and award a sticker for on-task behavior. Increased attention from phase A to phase B indicates that the treatment is effective (Gast & Baekey, 2016).

      A more sophisticated way to assess treatment effectiveness is to use a reversal (ABAB) design. The teacher rates behavior at baseline (A) and when the treatment is applied (B). Then, she temporarily withdraws treatment (i.e., stops using the sticker chart) and notices any change in the child’s behavior (the second A). If the treatment is responsible for improvement, then discontinuing the sticker chart should result in a temporary decrease in attention. Finally, the teacher would reinstate the treatment (the second B). If the sticker chart is effective, the child’s time on task should increase once again (Figure 3.5).

      Description

      Figure 3.5 ■ ABAB Reversal Design

      Note: This pattern of results indicates that the treatment is effective in increasing the child’s attention during math class. Based on Gast and Baekey (2015).

      A third strategy is to use a multiple baseline design. A multiple baseline design involves collecting baseline data on multiple behaviors or assessing the same behavior across multiple settings. The therapist targets each behavior or setting separately and notices the effect of treatment (Gast et al., 2016).

      For example, a teacher might collect baseline data about a student’s attention in two settings: math class (Baseline 1) and reading class (Baseline 2). For the first week, the teacher simply rates the student’s attention each day in each setting. For the second week, she uses a sticker chart to reinforce on-task behavior during math class and notices improvement in the student’s attention in that setting alone. During the third week, she also begins using the sticker chart to reinforce on-task behavior in reading class and notices subsequent improvement in that class, too. Because the child’s attention improved only when treatment was applied in that setting, we can be reasonably confident that the treatment was responsible for this improvement (Figure 3.6).

      Single subject studies that use treatment reversal or multiple baselines provide strong evidence that treatment is effective for a particular child. The chief limitation of all single subject designs is that causal inferences are based on data from only one individual. Consequently, it is often unclear whether the results of a single subject study are applicable to other people in other settings. The external validity of a study refers to the degree to which results generalize to other people and situations. To establish external validity, results must be replicated with other individuals, in other places, by other clinicians (Ledford, Wolery, & Gast, 2016).

      Description

      Figure 3.6 ■ A Multiple Baseline Design

      Note: Baseline data are collected in two different settings: math class and reading class. When treatment is applied in each class, behavior improves in that class only (Gast, Lloyd, & Ledford, 2016).

       Review

       Quasi-experimental studies often look like true experiments, but they lack random assignment. As a result, their internal validity is limited. We cannot say that one variable caused or affected another variable in a quasi-experimental study.

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