Summary
In this article, the authors, Nadler, Rabi, and Minda (2010) sought to explore the idea that cognitive tasks relying on behaviors, including rule selection and hypothesis testing are likely to benefit from positive moods using the category-learning framework. The study was experimental because the researchers induced different changes, specifically positive, neutral, and negative moods in the participants and monitored the resulting effects. The independent variables were positive, negative, and neutral moods, while the dependent variable was cognitive flexibility based on category learning. The independent variables were manipulated throughout the study by inducing different moods in the subjects. Operationally, the researchers defined the dependent variable by arguing that various studies have shown that category learning has been positively associated with cognitive flexibility.
In research, the independent variable is the one that could be manipulated or altered to determine its effects on what is being studied. On the other hand, the dependent variable is the one being tested. In this article, these different variables are clearly defined operationally by discussing how the two are related. The authors argue that positive mood increases “cognitive flexibility and this effect enhances the explicit category-learning system” (Nadler et al., 2010, p. 1770), and this statement underscores the operational definition of both dependent and independent variables in this study.
The participants in this study were required to perform category-learning tasks on a computer after being induced to positive, neutral, or positive moods. 87 university students were randomly selected as participants and they were assigned to one of the mood induction conditions. Data was collected in person based on how the participants scored in the category learning sets. The findings of this study showed that a positive mood improves the performance of the explicit system or cognitive flexibility. On the other hand, both negative and neutral moods did not have any effect on cognitive flexibility.
Critique
In my opinion, some confounding variables in the study could have affected the results. First, the argument that the positive-mood subjects “experienced increased cognitive flexibility, which allowed them to find the optimal verbal rule faster than negative-mood subjects and neutral mood subjects did” (Nadler et al., 2010, p. 1774), is not based on facts but assumptions. The researchers did not control for other factors that contribute to increased cognitive flexibility apart from positive moods. Second, as the authors indicate in the article, the failure to notice any cognitive flexibility in negative mood participants is that such mood was not sustained long enough to affect performance, which is a major confounding factor. The sample used in the study is not appropriate. While it was randomized, a sample size of 87 students is not large enough for the generalization of the results in other setups.
In addition, the study was restricted to university students and the results might thus be inapplicable in other population cohorts. Another major problem with this study is that it does not mention whether the students gave written consent. Given that the participants were expected to undergo mood induction, they should have at least assented to the procedure through written consent before taking part in the study. Additionally, an institutional review board (IRB) should have approved the study, but the authors did not indicate whether this important ethical regulation was met.
Nevertheless, despite the shortcomings of this study, the authors correctly interpreted their findings based on the data that they collected and analyzed. Similarly, the dependent variable was measured in a valid way. For instance, one each trial, “a Gabor patch appeared in the center of the screen, and subjects pressed the “A” or the “B” key to classify the stimulus” (Nadler et al., 2010, p. 1772). In the process of testing verbal optimal rule, “Subjects who viewed the RD category set had to find a single-dimensional rule to correctly classify the stimuli on the basis of the frequency of the grating while ignoring the more salient dimension of orientation” (Nadler et al., 2010, p. 1772). In other words, this process could identify the subjects’ cognitive flexibility. Therefore, it suffices to argue that the dependent variable was measured in a valid way because the data collected represent the phenomenon that the authors sought to measure in this study.
Brief Summary
The authors of this article wanted to investigate the effects of mood on cognitive flexibility with a specific focus on the category-learning framework. To achieve this objective, positive, neutral, and negative moods were induced in the research participants, as the independent variables, while the dependent variable was cognitive flexibility based on category learning. The authors defined both the independent and dependent variables by clearly indicating their association based on the available literature on the subject. The study was designed in a way that the 87 randomly selected university students could be randomly assigned the different mood induction processes and the learning categories and the resulting data collected in person based on how each subject performed. The results showed that positive moods are associated with improved cognitive flexibility. However, negative or neutral moods do not have any observable effects on the dependent variable.
Reference
Nadler, R. T., Rabi, R., & Minda, J. P. (2010). Better mood and better performance: Learning rule-described categories is enhanced by positive mood. Psychological Science, 21(12), 1770-1776.