Search

Awaiting news of uncertain outcomes is distressing because the news might be disappointing. To prevent such disappointments, people often "brace for the worst," pessimistically lowering expectations before news arrives to decrease the possibility of surprising disappointment (a negative prediction error , or PE). Computational decision-making research commonly assumes that expectations do not drift within trials, yet it is unclear whether expectations pessimistically drift in real-world, high-stakes settings, what factors influence expectation drift, and whether it effectively buffers emotional responses to goal-relevant outcomes. Moreover, individuals learn from PEs to accurately anticipate future outcomes, but it is unknown whether expectation drift also impedes PE-based learning. In a sample of students awaiting exam grades ( N = 625), we found that expectations often drift and tend to drift pessimistically. We demonstrate that bracing is preferentially modulated by uncertainty; it transiently buffers the initial emotional impact of negative PEs but impairs PE-based learning, counterintuitively sustaining uncertainty into the future.

Increasing daily exploration is linked to improvements in affective well-being. However, COVID-19 elevated uncertainty when leaving the home, altering the risk-reward of balance of geospatial novelty. To this end, we simultaneously collected real-world geospatial tracking and experience sampling of emotion, prior to and during the first year of the pandemic in 630 individuals. COVID-19 reduced exploration and subjective well-being. Yet, despite the health risks of exploring during the pandemic, the days of highest affective well-being were those when individuals explored the most. However, this was not true for everyone: during the first months of the pandemic, at the height of the uncertainty surrounding the transmissibility and prognosis of a COVID-19 infection, more anxious individuals experienced no affective benefit to leaving home. Taken together, real-world exploration improved well-being regardless of the presence of real-world threat, but anxiety mitigated these benefits. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

The present study expands on the growing body of research on the effects of cognitive behavioral therapy (CBT) on positive affect. More specifically, we explore how CBT may promote increases in the Joviality subscale of the Positive and Negative Affect Schedule-Expanded Form (PANAS-X), a measure of self-rated affect that captures positive emotions, including joy and excitement, and how change in joviality may be associated with concurrent symptom change. We utilized data from a randomized equivalence trial comparing the efficacy of the unified protocol (UP) for transdiagnostic treatment of emotional disorders, a transdiagnostic CBT, against various well-established single disorder protocols (SDP) and waitlist control. First, we generated affect profiles for patients receiving CBT (either UP or SDP) or waitlist control, based on their baseline and posttreatment positive affect (PA) and negative affect (NA), compared with a clinical reference sample. We found that the affect profile for most patients receiving CBT shifted from high NA/low PA to low NA/high PA. Further, participants receiving CBT were more likely than individuals in the waitlist control to achieve this outcome. We then examined the PANAS-X Joviality subscale, which has been subject to very limited previous research. Change in joviality was associated with improvement in symptoms of both anxiety ( B = -0.81, p = .00) and depression ( B = -0.94, p = .00). Joviality increased more rapidly in individuals with more severe anxiety but not severe depression. We discuss the possible clinical implications of these preliminary results, including the role of treatment innovations incorporating a focus on increasing positive affect, particularly the emotions associated with joviality, while simultaneously decreasing negative affect. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Cognitive risk factors are key in the vulnerability for internalizing disorders. Cognitive risk factors modulate the way individuals process information from the environment which in turn impacts the day-to-day affective experience. In 296 young adults, we assessed two transdiagnostic, general risk factors-repetitive negative thinking (RNT) and anxiety sensitivity in a high-RNT subsample ( N = 119). We also assessed disorderand content-specific risk factors including worry, rumination, and three facets of anxiety sensitivity (cognitive, social, physical). To determine the day-to-day affective experience, we used cell-phone-based ecological momentary assessment to assess the mean and variability of positive and negative affect (PA; NA) over 3-4 months. Two multilevel multivariate Bayesian models were used to predict PA and NA mean and variability from (1) general and (2) specific cognitive risk factors. Mean NA was a nonspecific correlate of cognitive risk across both models, while mean PA was most strongly related to RNT and rumination. NA variability was most strongly related to RNT, rumination, and the physiological facet of anxiety sensitivity. PA variability was a specific correlate of RNT. Results highlight that cognitive risk factors for internalizing disorders manifest in unique patterns of day-to-day emotional experience. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Organisms learn from prediction errors (PEs) to predict the future. Laboratory studies using small financial outcomes find that humans use PEs to update expectations and link individual differences in PE-based learning to internalizing disorders. Because of the low-stakes outcomes in most tasks, it is unclear whether PE learning emerges in naturalistic, high-stakes contexts and whether individual differences in PE learning predict psychopathology risk. Using experience sampling to assess 625 college students' expected exam grades, we found evidence of PE-based learning and a general tendency to discount negative PEs, an "optimism bias." However, individuals with elevated negative emotionality, a personality trait linked to the development of anxiety disorders, displayed a global pessimism and learning differences that impeded accurate expectations and predicted future anxiety symptoms. A sensitivity to PEs combined with an aversion to negative PEs may result in a pessimistic and inaccurate model of the world, leading to anxiety.

With the emerging ubiquity of cell phones, ecological momentary assessment (EMA) as a set of methods enable researchers to study momentary social, psychological, and affective responses to everyday life. Additionally, EMA enables researchers to acquire longitudinal data without the need for multiple lab visits. As the use of EMA in research increases, so too does the necessity of determining what constitutes valid or careless individual EMA responses to ensure validity and replicability of findings. Currently, EMA studies solely consider the response rate of a participant for exclusion. Yet, other features of an assessment can help to determine whether a response is careless or implausible. Here, we examined over 18,000 EMA text message responses of individual affect items to derive a data-driven model of what constitutes a "careless response." Results from this study indicate that an overly fast time to complete items (≤ 1 s), an overly narrow within assessment response variance ( SD ≤ 5), and the percentage of items that fall at the mode (≥ 60%) are independent and reliable indicators of a careless response. Excluding careless responses such as these remove implausible positive correlations among psychometric antonyms (e.g., relaxed and anxious). Further, by identifying and removing careless responses, we also identify careless responders, participants who could be removed from group analyses. We use these results to develop and introduce an R package, EMAeval, so EMA researchers may similarly identify careless responses and responders either online during data collection or posthoc, after data collection has completed. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Background: Ketamine induces rapid and robust antidepressant effects, and many patients also describe dissociation, which is associated with antidepressant response. This follow-up study investigated whether antidepressant efficacy is uniquely related to dissociative symptom clusters., Methods: Treatment-resistant patients with major depressive disorder (MDD) or bipolar disorder (BD) (n = 126) drawn from three studies received a single subanesthetic (0.5 mg/kg) ketamine infusion. Dissociative effects were measured using the Clinician-Administered Dissociative States Scale (CADSS). Antidepressant response was measured using the 17-item Hamilton Depression Rating Scale (HAM-D). A confirmatory factor analysis established the validity of CADSS subscales (derealization, depersonalization, amnesia), and a general linear model with repeated measures was fitted to test whether subscale scores were associated with antidepressant response., Results: Factor validity was supported, with a root mean square error of approximation of .06, a comparative fit index of .97, and a Tucker-Lewis index of .96. Across all studies and timepoints, the depersonalization subscale was positively related to HAM-D percent change. A significant effect of derealization on HAM-D percent change was observed at one timepoint (Day 7) in one study. The amnesia subscale was unrelated to HAM-D percent change., Limitations: Possible inadequate blinding; combined MDD/BD datasets might have underrepresented ketamine's antidepressant efficacy; the possibility of Type I errors in secondary analyses., Conclusions: From a psychometric perspective, researchers may elect to administer only the CADSS depersonalization subscale, given that it was most closely related to antidepressant response. From a neurobiological perspective, mechanistic similarities may exist between ketamine-induced depersonalization and antidepressant response, although off-target effects cannot be excluded., (Published by Elsevier B.V.)

Current pharmacotherapies for major depressive disorder (MDD) have a distinct lag of onset that can prolong distress and impairment for patients, and realworld effectiveness trials further suggest that antidepressant efficacy is limited in many patients. All currently approved antidepressant medications for MDD act primarily through monoaminergic mechanisms, e.g., receptor/reuptake agonists or antagonists with varying affinities for serotonin, norepinephrine, or dopamine. Glutamate is the major excitatory neurotransmitter in the central nervous system, and glutamate and its cognate receptors are implicated in the pathophysiology of MDD, as well as in the development of novel therapeutics for this disorder. Since the rapid and robust antidepressant effects of the N-methyl-D-aspartate (NMDA) antagonist ketamine were first observed in 2000, other NMDA receptor antagonists have been studied in MDD. These have been associated with relatively modest antidepressant effects compared to ketamine, but some have shown more favorable characteristics with increased potential in clinical practice (for instance, oral administration, decreased dissociative and/or psychotomimetic effects, and reduced abuse/diversion liability). This article reviews the clinical evidence supporting the use of glutamate receptor modulators with direct affinity for cognate receptors: 1) non-competitive NMDA receptor antagonists (ketamine, memantine, dextromethorphan, AZD6765); 2) subunit (NR2B)-specific NMDA receptor antagonists (CP- 101,606/traxoprodil, MK-0657); 3) NMDA receptor glycine-site partial agonists (D-cycloserine, GLYX- 13); and 4) metabotropic glutamate receptor (mGluR) modulators (AZD2066, RO4917523/basimglurant). Several other theoretical glutamate receptor targets with preclinical antidepressant-like efficacy, but that have yet to be studied clinically, are also briefly discussed; these include α-amino-3-hydroxyl-5-methyl-4- isoxazoleproprionic acid (AMPA) agonists, mGluR2/3 negative allosteric modulators, and mGluR7 agonists.