Full Answer Section

• Dependent Variable (DV): This is the variable that the researcher measures to see if it is affected by the manipulation of the independent variable. It is considered the presumed effect. In the teaching method example, student test scores would be the dependent variable, as researchers would measure these scores to see if they differ between the groups exposed to different teaching methods.

• Extraneous Variables (EVs): These are any variables other than the independent variable that could potentially influence the dependent variable. If not controlled, extraneous variables can provide alternative explanations for the observed results, making it difficult to determine if the independent variable truly had an effect. For instance, in the teaching method study, students’ prior knowledge, motivation levels, home environment, or the teacher’s experience could all be extraneous variables that might affect test scores alongside or instead of the teaching method itself.

In essence, the researcher manipulates the independent variable, measures the dependent variable, and attempts to control the extraneous variables to isolate the relationship between the IV and DV.

Controlling Extraneous Variables

Researchers employ various techniques to minimize the influence of extraneous variables and increase the internal validity of their studies (the extent to which the study demonstrates a true cause-and-effect relationship). Two common methods include:

1. Random Assignment: This involves assigning participants to different levels or conditions of the independent variable randomly. Random assignment aims to distribute extraneous variables equally across the groups. For example, in our teaching method study, if students are randomly assigned to either the new teaching method group or the traditional method group, pre-existing differences in prior knowledge or motivation are likely to be distributed relatively evenly between the two groups. This reduces the likelihood that these pre-existing differences, rather than the teaching method, are responsible for any observed differences in test scores. Randomization helps to control for unknown extraneous variables as well.

2. Holding Variables Constant: This involves keeping specific potential extraneous variables the same across all conditions of the study. For instance, in the teaching method study, researchers might ensure that all students are taught by the same teacher, in the same classroom, at the same time of day, and using the same materials (except for the teaching method itself). By holding these factors constant, researchers eliminate them as potential confounding variables that could explain any differences in test scores. This method is particularly effective for controlling for known and easily identifiable extraneous variables.

Example from Peer-Reviewed Research

Let’s consider the peer-reviewed, primary research article: “The impact of mindfulness-based interventions on anxiety symptoms in adolescents: A systematic review and meta-analysis” by Dunning et al. (2019), published in Developmental Psychology. While this article is a meta-analysis (synthesizing findings from multiple primary studies), many of the primary studies it reviewed would have employed control strategies.

Imagine one hypothetical primary study included in this meta-analysis aimed to investigate the effect of a 8-week mindfulness-based intervention (the independent variable, with two levels: intervention group and control group receiving no intervention) on self-reported anxiety symptoms (the dependent variable) in adolescents.

Application of Control Strategies:

1. Random Assignment: Researchers in this hypothetical study would likely have used random assignment to allocate adolescent participants who met the study criteria to either the mindfulness intervention group or the control group. This would help to ensure that pre-existing differences in anxiety levels, coping mechanisms, family support, or other potential extraneous variables were roughly equally distributed between the two groups at the start of the study. If the intervention group showed a significant reduction in anxiety compared to the control group after the 8 weeks, researchers could be more confident that the mindfulness intervention (IV) was the likely cause, rather than pre-existing differences.

2. Holding Variables Constant: To further control for extraneous variables, the researchers might have implemented the mindfulness intervention in a standardized way. For example, they might have:

   • Used the same curriculum and trained the facilitators to deliver the intervention with a high degree of fidelity across all intervention groups. This would hold the intervention delivery method constant.
   • Conducted the intervention sessions in the same setting (e.g., a quiet classroom in the school) and at the same time of day for all participants in the intervention group, controlling for potential environmental influences.
   • Used the same standardized questionnaire to measure anxiety symptoms at the beginning and end of the 8-week period for both the intervention and control groups, ensuring consistency in the measurement tool.

By using random assignment and holding key procedural variables constant, the researchers in this hypothetical primary study (and, by extension, the primary studies reviewed in Dunning et al.’s meta-analysis) would have aimed to minimize the influence of extraneous variables, thereby strengthening the evidence for a causal relationship between the mindfulness-based intervention and changes in anxiety symptoms.