Reductions in Negative Automatic Thoughts in Students Attending Mindfulness Tutorials Predicts Increased Life Satisfaction

University education confronts students with stressful developmental challenges that can lead to mental health problems. Innovative programs must address an increasing prevalence of these problems but are impeded by the high costs involved. In this study, thirty-nine undergraduate students attended weekly one hour mindfulness meditation tutorials during a single (14 week) semester. Tutorials involved 40 minutes of guided meditation, followed by open-ended discussions on mindfulness and related scientific research. Multiple regression analysis tested associations between self-reported changes in mindfulness, in negative automatic thoughts and in satisfaction with life.Reductions in automatic thoughts accounted for a significant proportion of variance in life satisfaction and decreases in automatic thoughts were associated with an increased life satisfaction. This finding suggests guided meditation tutorials merit consideration in promoting student mental health on university campuses.

Negligible Interaction Test for Continuous Predictors

Behavioral science researchers are often interested in whether there is negligible interaction among continuous predictors of an outcome variable. For example, a researcher might be interested in demonstrating that the effect of perfectionism on depression is very consistent across age. In this case, the researcher is interested in assessing whether the interaction between the predictors is too small to be meaningful. Unfortunately, most researchers address the above research question using a traditional association-based null hypothesis test (e.g., regression) where their goal is to fail to reject the null hypothesis of no interaction. Common problems with traditional tests are their sensitivity to sample size and their opposite (and hence inappropriate) hypothesis setup for finding a negligible interaction effect. In this study, we investigated a method for testing for negligible interaction between continuous predictors using unstandardized and standardized regression-based models and equivalence testing. A Monte Carlo study provides evidence for the effectiveness of the equivalence-based test relative to traditional approaches