Determining optimal parameters of the Self Referent Encoding Task: A large-scale examination of self-referent cognition and depression

Abstract

This is a post-print of a manuscript which has been published in Psychological Assessment.Although the Self-Referent Encoding Task (SRET) is commonly used to measure self-referent cognition in depression, many different SRET metrics can be obtained. The current study used best subsets regression with cross-validation and independent test samples to identify the SRET metrics most reliably associated with depression symptoms in three large samples: a college student sample (n = 572), a sample of adults from Amazon Mechanical Turk (n = 293), and an adolescent sample from a school field study (n = 270). Across all three samples, SRET metrics associated most strongly with depression severity included number of words endorsed as selfdescriptive and rate of accumulation of information required to decide whether adjectives were self-descriptive (i.e., drift rate). These metrics had strong intra-task and split-half reliability and high test-retest reliability across a 1-week period. Recall of SRET stimuli and traditional reaction time metrics were not robustly associated with depression severity.

Positive imagery training increases positive self-referent cognition in depression

“…The primary behavioral outcome from the SRET is the probability of endorsing positive vs. negative words, which we have demonstrated to be strongly linked to depression (Dainer-Best et al, 2018). Additionally, including an extra subset of words at each time-point allowed us to distinguish between responses that varied due to repetition and those that varied putatively due to changes in self-referential processing.…”

“…The relationship between negative self-schema and the maintenance of depression is sometimes viewed in causal terms, with stronger negative self-schemas thought to produce a more protracted episode of depression (Beck, 1967). It is clear that both positive and negative schema are strongly correlated with depressive symptoms (Phillips et al, 2010; Dainer-Best et al, 2018), and can predict worsening of symptoms (Disner et al, 2016); however, such studies are correlational and thus vulnerable to third variable explanations that account for the association between self-referent processing and depression.…”

Determining optimal parameters of the self-referent encoding task: A large-scale examination of self-referent cognition and depression.

“… Data are located on the Texas Data Repository, https://doi.org/10.18738/T8/XK5PXX (Dainer-Best et al, 2017) and additional information on Github, https://jdbest.github.io/sretmodels/. An interactive Shiny interface to explore the relationships between these variables can be viewed online at https://jdbest.shinyapps.io/shiny-comparisons/ …”

Negative Self-Referent Cognition Predicts Future Depression Symptom Change: An Intensive Sampling Approach

“…Although there are no previously published studies examining the prediction of day-to-day fluctuations in depression by the SRET, prior cross-sectional work suggests a strong association between endorsements of negative adjectives on the SRET and depression severity (rs ranged from .65 to .70-a large effect size; Dainer-Best, Lee, et al, 2018). Based on this evidence, we reasoned that large effects may also be observed in the current study.…”

“…Many cross-sectional studies provide evidence of an association between negative self-referent thinking and depression. For instance, depressed people are more likely than non-depressed individuals to endorse negative adjectives (e.g., defective, worthless, dumb) as self-descriptive (Dainer-Best, Lee, et al, 2018;Dalgleish et al, 2004;Sarsam et al, 2013). A recent meta-analysis found that depressed individuals endorsed more negative adjectives as self-descriptive than non-depressed individuals.…”