Negative Emotion Differentiation Predicts Psychotherapy Outcome: Preliminary Findings

Abstract

Emotion differentiation (ED), the extent to which same-valenced emotions are experienced as distinct, is considered a valuable ability in various contexts owing to the essential affect-related information it provides. This information can help individuals understand and regulate their emotional and motivational states. In this study, we sought to examine the extent to which ED can be beneficial in psychotherapy context and specifically for predicting treatment response. Thirty-two prospective patients with mood and anxiety disorders completed four daily assessments of negative and positive emotions for 30 days before receiving cognitive-behavioral treatment. Depression, stress, and anxiety symptoms severity were assessed pre- and post-treatment using self-reports and clinical interviews. We conducted a series of hierarchical regression models in which symptoms change scores were predicted by ED while adjusting for the mean and variability. We found that negative ED was associated with greater self-reported treatment response (except for anxiety) when negative emotional variability (EV) was included in the models. Probing negative ED and EV’s interactive effects suggested that negative ED was associated with greater treatment response (except for anxiety) for individuals with lower EV levels. Results were obtained while controlling for mean negative affect. Our findings suggest that negative ED can benefit psychotherapy patients whose negative emotions are relatively less variable. We discuss the meaning of suppression and interactive effects between affect dynamics and consider possible clinical implications.

Valence in the eyes: An emotion decoding profile of adults with major depressive disorder and a history of childhood maltreatment

“…Especially, emotion decoding abilities may be clinically meaningful to target in the treatment of MDD. A study by Lazarus and Fisher (2021) found that individuals who displayed good emotion decoding abilities generally had better outcomes of psychotherapy. Thus, improving the identified emotion decoding problems in MDD patients with childhood maltreatment may potentially benefit their treatment outcomes.…”

Within-Person Changes in Aversive Reactivity Predict Session-to-Session Reductions in Anxiety and Depression in the Unified Protocol

“…Further, by applying both HLM and RI-CLPM to these data, these results can function as a second empirical replication of Falkenström et al's (2022) results. By testing both lag-1 and contemporaneous effects, we hope to help future researchers specify the timescale at which these theorized processes occur (Fisher & Bosley, 2020;Lazarus & Fisher, 2021), since these are currently unknown. Both anxiety (OASIS), B = -.30, SE = .07, p < .01, 95% CI [-.43, -.17], d = .53, and depression (ODSIS), B = -.42, SE = .08, p < .01, 95% CI [-.59, -.26], d = .65, significantly decreased across the first seven sessions/weeks (see Table 1 for means and standard deviations at each session).…”

The promise of affective language for identifying and intervening on psychopathology

“…Differentiation scores are computed by reverse-scoring the intraclass correlation of these ratings: High correlations between these ratings indicate that people essentially use all of these emotion words identically, whereas low correlations indicate that they think of each as a unique emotional experience. Emotion differentiation scores have now been widely associated with healthy emotion regulation (Barrett et al, 2001;Kalokerinos et al, 2019), mental health in both youth and adults (Demiralp et al, 2012;Nook, 2021;Nook, Flournoy, et al, 2021;O'Toole et al, 2020;Seah & Coifman, 2022), and even treatement response (Lazarus & Fisher, 2021). However, unlike our other constructs reviewed here, emotion differentiation does not currently have a purely linguistic measure.…”