Revision, Reclassification, and Refrigerators

Current debates about cultural change question how and how often change in personal culture happens. Is personal culture stable, or under constant revision through interaction with the environment? While recent empirical work finds attitudes are remarkably stable, this paper argues that typifications—how material tokens are classified as a particular mental type by individuals—are more open to transformation as a result of the fundamentally fuzzy nature of classifying. Specifically, this paper investigates the social conditions that lead people to reclassify. How do we move people to see the same thing differently over time? Paying attention to type-token dynamics provides mechanisms for why and under what circumstances personal culture may change. To assess reclassification, the paper analyzes an online survey experiment that asked people to classify refrigerators as owned by “Trump” or “Biden” voters. Those participants who received definitive feedback about the correct answer were more likely to reclassify than are those receiving normative feedback about how “most people” classified the images. Implications for cultural change and persuasion are discussed.

Using Anchor-Based Methods to Determine the Smallest Effect Size of Interest

Effect sizes are an important outcome of quantitative research, but few guidelines exist that explain how researchers can determine which effect sizes are meaningful. Psychologists often want to study effects that are large enough to make a difference to people’s subjective experience. Thus, subjective experience is one way to gauge meaningfulness of an effect. We illustrate how to quantify the minimum subjectively experienced difference—the smallest change in an outcome measure that individuals consider to be meaningful enough in their subjective experience such that they are willing to rate themselves as feeling different—using an anchor-based method with a global rating of change question applied to the positive and negative affect scale. For researchers interested in people’s subjective experiences, this anchor-based method provides one way to specify a smallest effect size of interest, which allows researchers to interpret observed results in terms of their theoretical and practical significance.

Minimal clinically important difference on the Beck Depression Inventory - II according to the patient's perspective

BackgroundThe Beck Depression Inventory, 2nd edition (BDI-II) is widely used in research on depression. However, the minimal clinically important difference (MCID) is unknown. MCID can be estimated in several ways. Here we take a patient-centred approach, anchoring the change on the BDI-II to the patient's global report of improvement.MethodWe used data collected (n = 1039) from three randomized controlled trials for the management of depression. Improvement on a ‘global rating of change’ question was compared with changes in BDI-II scores using general linear modelling to explore baseline dependency, assessing whether MCID is best measured in absolute terms (i.e. difference) or as percent reduction in scores from baseline (i.e. ratio), and receiver operator characteristics (ROC) to estimate MCID according to the optimal threshold above which individuals report feeling ‘better’.ResultsImprovement in BDI-II scores associated with reporting feeling ‘better’ depended on initial depression severity, and statistical modelling indicated that MCID is best measured on a ratio scale as a percentage reduction of score. We estimated a MCID of a 17.5% reduction in scores from baseline from ROC analyses. The corresponding estimate for individuals with longer duration depression who had not responded to antidepressants was higher at 32%.ConclusionsMCID on the BDI-II is dependent on baseline severity, is best measured on a ratio scale, and the MCID for treatment-resistant depression is larger than that for more typical depression. This has important implications for clinical trials and practice.