Treating intrusive memories after trauma in healthcare workers: a Bayesian adaptive randomised trial developing an imagery-competing task intervention.

Intensive care unit (ICU) staff continue to face recurrent work-related traumatic events throughout the COVID-19 pandemic. Intrusive memories (IMs) of such traumatic events comprise sensory image-based memories. Harnessing research on preventing IMs with a novel behavioural intervention on the day of trauma, here we take critical next steps in developing this approach as a treatment for ICU staff who are already experiencing IMs days, weeks, or months post-trauma. To address the urgent need to develop novel mental health interventions, we used Bayesian statistical approaches to optimise a brief imagery-competing task intervention to reduce the number of IMs. We evaluated a digitised version of the intervention for remote, scalable delivery. We conducted a two-arm, parallel-group, randomised, adaptive Bayesian optimisation trial. Eligible participants worked clinically in a UK NHS ICU during the pandemic, experienced at least one work-related traumatic event, and at least three IMs in the week prior to recruitment. Participants were randomised to receive immediate or delayed (after 4 weeks) access to the intervention. Primary outcome was the number of IMs of trauma during week 4, controlling for baseline week. Analyses were conducted on an intention-to-treat basis as a between-group comparison. Prior to final analysis, sequential Bayesian analyses were conducted (n = 20, 23, 29, 37, 41, 45) to inform early stopping of the trial prior to the planned maximum recruitment (n = 150). Final analysis (n = 75) showed strong evidence for a positive treatment effect (Bayes factor, BF = 1.25 × 106): the immediate arm reported fewer IMs (median = 1, IQR = 0-3) than the delayed arm (median = 10, IQR = 6-16.5). With further digital enhancements, the intervention (n = 28) also showed a positive treatment effect (BF = 7.31). Sequential Bayesian analyses provided evidence for reducing IMs of work-related trauma for healthcare workers. This methodology also allowed us to rule out negative effects early, reduced the planned maximum sample size, and allowed evaluation of enhancements. Trial Registration NCT04992390 ( www.clinicaltrials.gov ).

Fear and anxiety in the face of COVID-19: Negative dispositions towards risk and uncertainty as vulnerability factors.

In the face of the COVID-19 pandemic it is important to identify factors that make people particularly vulnerable of developing mental-health issues in order to provide case-specific treatments. In this article, we examine the roles of two psychological constructs - originally put forth in the behavioral decision sciences - in predicting interindividual differences in fear responses: general risk aversion (GRA) and intolerance of uncertainty (IU). We first provide a review of these constructs and illustrate why they may play important roles in shaping anxiety-related disorders. Thereafter we present an empirical study that collected survey data from 550 U.S. residents, comprising self-assessments of dispositions towards risk and uncertainty, anxiety- and depression levels, as well as demographic variables - to thus test the extent to which these psychological constructs are predictive of strong fear responses related to COVID-19 (i.e., mortal fear, racing heart). The results from Bayesian multi-model inference analyses showed that GRA and IU were more powerful predictors of fear responses than demographic variables. Moreover, the predictive power of these constructs was independent of general anxiety- and depression levels. Subsequent mediation analyses showed that the effects of GRA and IU were both direct and indirect via anxiety. We conclude by discussing possible treatment options, but also highlight that future research needs to further examine causal pathways and conceptual overlaps.

Cognitiva Speciebus: Towards a Linnaean Approach to Cognition.

Research points to the limitations of approaches to decision-making, that rest on general 'Newtonian principles' derived from unitary a priori conceptions of rationality. To understand how the mind exploits environments, we instead propose a process of more open-ended discovery and systematization in the mold of Linnaeus's famous taxonomy of plants.

Precise/not precise (PNP): A Brunswikian model that uses judgment error distributions to identify cognitive processes.

In 1956, Brunswik proposed a definition of what he called intuitive and analytic cognitive processes, not in terms of verbally specified properties, but operationally based on the observable error distributions. In the decades since, the diagnostic value of error distributions has generally been overlooked, arguably because of a long tradition to consider the error as exogenous (and irrelevant) to the process. Based on Brunswik's ideas, we develop the precise/not precise (PNP) model, using a mixture distribution to model the proportion of error-perturbed versus error-free executions of an algorithm, to determine if Brunswik's claims can be replicated and extended. In Experiment 1, we demonstrate that the PNP model recovers Brunswik's distinction between perceptual and conceptual tasks. In Experiment 2, we show that also in symbolic tasks that involve no perceptual noise, the PNP model identifies both types of processes based on the error distributions. In Experiment 3, we apply the PNP model to confirm the often-assumed "quasi-rational" nature of the rule-based processes involved in multiple-cue judgment. The results demonstrate that the PNP model reliably identifies the two cognitive processes proposed by Brunswik, and often recovers the parameters of the process more effectively than a standard regression model with homogeneous Gaussian error, suggesting that the standard Gaussian assumption incorrectly specifies the error distribution in many tasks. We discuss the untapped potentials of using error distributions to identify cognitive processes and how the PNP model relates to, and can enlighten, debates on intuition and analysis in dual-systems theories.

Detailed analysis of skin conductance responses during a gambling task: Decision, anticipation, and outcomes.

Physiological arousal is considered a key factor of gambling behavior. Hence, to understand gambling behavior it is important to study the arousal responses during gambling. Moreover, crucial mechanisms of action could be uncovered by detailing the situations that produce an arousal response. A gamble, or bet, can be partitioned into three distinct phases: (a) decision phase, during which the information concerning the gamble is presented, outcomes are appraised, and a decision is made on how to gamble; (b) anticipation phase, during which the result of the gamble is awaited; (c) outcome phase, during which the outcome of the gamble is presented. Previous research on arousal responses to gambling have mostly measured tonic changes in arousal, and when phasic responses have been measured, analyses have generally concentrated on one of the gamble phases. The aim of the present study was to map the arousal responses during gambling in more detail by measuring skin conductance responses (SCRs) during all three gamble phases of a simple card game. The anticipation phase was found to produce the largest arousal response, suggesting anticipation to be a major contributor to arousal during gambling behavior. Risk behavior during the gambling task was mirrored in self-reported risk taking in everyday life, and risk-takers displayed smaller SCRs compared to nonrisk-takers during decision making, suggesting this as a possible biomarker for risk-taking individuals.

Memory and decision making: Effects of sequential presentation of probabilities and outcomes in risky prospects.

The rationality of decision making under risk is of central concern in psychology and other behavioral sciences. In real-life, the information relevant to a decision often arrives sequentially or changes over time, implying nontrivial demands on memory. Yet, little is known about how this affects the ability to make rational decisions and a default assumption is rather that information about outcomes and probabilities are simultaneously available at the time of the decision. In 4 experiments, we show that participants receiving probability- and outcome information sequentially report substantially (29 to 83%) higher certainty equivalents than participants with simultaneous presentation. This holds also for monetary-incentivized participants with perfect recall of the information. Participants in the sequential conditions often violate stochastic dominance in the sense that they pay more for a lottery with low probability of an outcome than participants in the simultaneous condition pay for a high probability of the same outcome. Computational modeling demonstrates that Cumulative Prospect Theory (Tversky & Kahneman, 1992) fails to account for the effects of sequential presentation, but a model assuming anchoring-and adjustment constrained by memory can account for the data. By implication, established assumptions of rationality may need to be reconsidered to account for the effects of memory in many real-life tasks. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Disentangling the effects of serotonin on risk perception: S-carriers of 5-HTTLPR are primarily concerned with the magnitude of the outcomes, not the uncertainty.

Serotonin signaling is vital for reward processing, and hence, also for decision-making. The serotonin transporter gene linked polymorphic region (5-HTTLPR) has been connected to decision making, suggesting that short-allele carriers (s) are more risk averse than long-allele homozygotes (ll). However, previous research has not identified if this occurs because s-carriers (i) are more sensitive to the uncertainty of the outcomes or (ii) are more sensitive to the magnitude of the outcomes. This issue was disentangled using a willingness-to-pay task, where the participants evaluated prospects involving certain gains, uncertain gains, and ambiguous gains. The results clearly favored the hypothesis that s-carriers react more to the magnitude of the outcomes. Self-reported measures of everyday risk-taking behavior also favored this hypothesis. We discuss how these results are in line with recent research on the serotonergic impact on reward processing. (PsycINFO Database Record

Optimizing electricity consumption: A case of function learning.

A popular way to improve consumers' control over their electricity consumption is by providing outcome feedback on the cost with in-home displays. Research on function learning, however, suggests that outcome feedback may not always be ideal for learning, especially if the feedback signal is noisy. In this study, we relate research on function learning to in-home displays and use a laboratory task simulating a household to investigate the role of outcome feedback and function learning on electricity optimization. Three function training schemes (FTSs) are presented that convey specific properties of the functions that relate the electricity consumption to the utility and cost. In Experiment 1, we compared learning from outcome feedback with 3 FTSs, 1 of which allowed maximization of the utility while keeping the budget, despite no feedback about the total monthly cost. In Experiment 2, we explored the combination of this FTS and outcome feedback. The results suggested that electricity optimization may be facilitated if feedback learning is preceded by a brief period of function training.

Prospect evaluation as a function of numeracy and probability denominator.

This study examines how numeracy and probability denominator (a direct-ratio probability, a relative frequency with denominator 100, a relative frequency with denominator 10,000) affect the evaluation of prospects in an expected-value based pricing task. We expected that numeracy would affect the results due to differences in the linearity of number perception and the susceptibility to denominator neglect with different probability formats. An analysis with functional measurement verified that participants integrated value and probability into an expected value. However, a significant interaction between numeracy and probability format and subsequent analyses of the parameters of cumulative prospect theory showed that the manipulation of probability denominator changed participants' psychophysical response to probability and value. Standard methods in decision research may thus confound people's genuine risk attitude with their numerical capacities and the probability format used.