The experimental approach permits for concluding causal relationship between independent variables (IVs) and dependent variables (DVs) by observing change in DVs resulting from manipulating IVs in a controlled environment (Cozby & Bates, 2015). Mogilner (2010) exemplifies an experimental study using a factorial design to test the impact of time- and money-related words on expected engaging in work- or leisure-related activities.
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Another example of a study using a factorial design (2×2) is Dunn, Trivedi, Kampert, Clark, & Chambliss (2005), which assessed the impact of aerobic exercise treatment on reducing mild to moderate major depressive disorder (MDD). The IVs were: total energy expenditure (7.0 kcal/kg/week or 17.5 kcal/kg/week) and exercise frequency (3 or 5 times/week); there also was an exercise placebo control group (thrice per week, flexibility exercise). The DV was the level of depression measured using Hamilton Rating Scale for Depression.
Dunn et al. (2005) exemplifies experimental research because it applied different treatments (reflected in 2 IVs) to participants and compared the changes in the IVs using ANCOVA, thus assessing the impact of manipulating IVs on the DV.
The fact that the participants, who were randomly attributed to treatments or placebo, were sedentary and received no treatment from depression apart from the experimental treatment allowed for ruling out the effect of other than the experimental treatment possible major impacts on the DV, therefore permitting for concluding that it was the type of treatment that affected the outcome. Using the control group was also a major safeguard against threats to validity.
Thus, the experimental design allowed for concluding that it was the IVs that primarily affected the outcome depression scores. The control group permitted for ruling out the possibility that the depression scores would drop “on their own,” and for assessing the impact of treatments when compared to a situation with practically no treatment. ANCOVA allowed for statistically controlling for pre-intervention levels of depression, taking the baseline into account.
The article contributes to the literature review by showing that depression could be reduced using the exercise with 17.5 kcal/kg/week energy expenditures, and that frequency of such exercise (3 or 5 times/week) did not matter. This means that when assessing the impact of self-esteem on depression, exercise done by participants should be controlled for. It is important to the field of psychology because it shows how physical exercise can affect mental states.
I learned that, strictly speaking, experiment is the only type of research design that allows for concluding causal relationship, and that is uses specific methods (such as controlled environment and direct observation of changes in the DV resulting from changes in the IV) for doing so. However, I am not confident about the construct of construct validity, which comprises several aspects such as concurrent or convergent validity (Cozby & Bates, 2015, p. 106). It is possible to ask about the possibility of assessing construct validity as a whole, and whether it would make sense to do such an assessment.
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The research about the relationship between depression and self-esteem has been mainly descriptive or correlational (Orth, Robins, Widaman, & Conger, 2014; Steiger, Allemand, Robins, & Fend, 2014); also, secondary, meta-analytic studies were conducted (Orth & Robins, 2013; Sowislo & Orth, 2013). Thus, the experimental design has apparently contributed little to this research topic as of today. It is probable that experiments have rarely been used to explore this topic because the nature and, importantly, the direction of the relationship between self-esteem and depression was not clear (Orth & Robins, 2013), so there were little grounds which would permit for ensuring that an experiment is constructed appropriately. In addition, influencing one’s self-esteem and assessing the longitudinal impact of it on the risk of depression is a difficult task, probably requiring much time and resources.
Experimental research on the relationship between self-esteem and depression may advance the knowledge base in psychology because it would allow for assessing the impact of one psychological phenomenon on another. In such studies, variables reflecting the levels of self-esteem and of depression in individuals should be investigated.
Cozby, P. C., & Bates, S. C. (2015). Methods in behavioral research (12th ed.). New York, NY: McGraw-Hill Education.
Dunn, A. L., Trivedi, M. H., Kampert, J. B., Clark, C. G., & Chambliss, H. O. (2005). Exercise treatment for depression: Efficacy and dose response. American Journal of Preventive Medicine, 28(1), 1-8. Web.
Mogilner, C. (2010). The pursuit of happiness: Time, money, and social connection. Psychological Science, 21(9), 1348-1354. Web.
Orth, U., & Robins, R. W. (2013). Understanding the link between low self-esteem and depression. Current Directions in Psychological Science, 22(6), 455-460. Web.
Orth, U., Robins, R. W., Widaman, K. F., & Conger, R. D. (2014). Is low self-esteem a risk factor for depression? Findings from a longitudinal study of Mexican-origin youth. Developmental Psychology, 50(2), 622-633. Web.
Sowislo, J. F., & Orth, U. (2013). Does low self-esteem predict depression and anxiety? A meta-analysis of longitudinal studies. Psychological Bulletin, 139(1), 213-240. Web.
Steiger, A. E., Allemand, M., Robins, R. W., & Fend, H. A. (2014). Low and decreasing self-esteem during adolescence predict adult depression two decades later. Journal of Personality and Social Psychology, 106(2), 325-338. Web.