Variables that are not intentionally studied in any research are called extraneous variables and could pose a threat to the findings of the research in that they interfere with the internal validity of the results. In studies that deal with quantitative experimental designs, particularly the experimental ones, steps must be taken to control these extraneous variables so as not to become confounding variables. In the event that these extraneous variables change systematically with the variables being studied, then the variables are called confounding variables. These variables are known as confounding because they provide alternative explanations to the results of the study.
This study draws its arguments from the following hypothesis:
Adults in their old age who exhibit symptoms of depression but get Cognitive Behavioral Therapy (CBT) are more prone than those who are given psychoanalysis to illustrate an improvement in depressive symptoms.
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From this case, the symptoms of depression are the dependent variables while old age is the independent variable. From this argument, it is prudent to postulate that psychoanalysis is more responsive in adults who suffer from depression as opposed to the normal CBT when it comes to susceptibility to the condition. The confounding factors in this case are the causative factors of the effects suffered by the elderly and the consequence of the outcome or response.
As such, old age is a powerful confounding variable since it associates with both depression and low physical activity. This is in the sense that old age or aging is a strong predisposing factor for the individuals in this age gap to suffer from depression. The other confounding factor in this experimental design is gender. With many studies pointing out to the high numbers of depressed females with greater pulse rate compared to their non-depressant counterparts, the opposite does not apply to the case with men and this variability may be attributed to different symptoms shown by the depression (Chambers &Allen, 2007). These adults may have some other factors which may include their drinking or eating habits, something that this hypothesis seems to have given a wide berth.
Medication use and psychiatric comorbidities are also some of the possible and potential confounding factors as medication can react differently on the individuals based on their body systems. The effects of depression can induce in someone different depressive consequences which may include rumination or preservative cognition.
Control
Confounding can best be controlled through statistical means. That is, it can be adjusted through the use of statistical models. This can be achieved through multivariate and stratification methods. Stratification is one of the strategies that can be used in fixing the levels of confounders so as not to vary in any given survey.
The other strategy that can be used in controlling the confounding factors include multivariate models. These models are useful in the sense that they can handle large numbers of confounders (covariates) at a time. This is where such applications as covariance analysis and regression analysis are employed.
Reference
Ingram, R. E. (2009). The international encyclopedia of depression . New York: Springer.
