A signal-detection approach to individual differences in negative feeling

On the relationship between subjective decision criteria and paranoid ideations

Following the conjecture made by (Bliznashki and Hristova in Appetite 167:105645, 2021), we test the hypothesis that liberal subjective decision criteria exhibited during a task involving discrimination between random and systematically correlated patterns should be associated with elevated levels of paranoid ideations. Study 1 establishes the proposed association in the presence of several control measures while also demonstrating that the relationship in question is significantly moderated by subjects' working memory spans and tendencies to be overconfident in their judgments. Study 2 provides further evidence that these effects are indeed specific to tasks involving discrimination between random and systematic patterns and that the observed results are not due to some form of (anti) acquiescence bias or other general trends. Certain specifics of the correlation matrices involving cognitive measures significantly related to the paranoia continuum suggest that our results are consistent with the Entropic Brain Hypothesis. Finally, a simulation study employing a Neural Network demonstrates that increased entropy and liberal decision criteria might be connected to each other with said connection being amenable to an interpretation within the Bayesian paradigm.

Framing Subjective Emotion Reports as Dynamic Affective Decisions

Self-reports remain affective science's only direct measure of subjective affective experiences. Yet, little research has sought to understand the psychological process that transforms subjective experience into self-reports. Here, we propose that by framing these self-reports as dynamic affective decisions, affective scientists may leverage the computational tools of decision-making research, sequential sampling models specifically, to better disentangle affective experience from the noisy decision processes that constitute self-report. We further outline how such an approach could help affective scientists better probe the specific mechanisms that underlie important moderators of affective experience (e.g., contextual differences, individual differences, and emotion regulation) and discuss how adopting this decision-making framework could generate insight into affective processes more broadly and facilitate reciprocal collaborations between affective and decision scientists towards a more comprehensive and integrative psychological science.

The imputation of structure in random patterns as a cognitive factor predicting adult picky eating behavior

We raise the hypothesis that adult picky eating behavior may be related to subjects' tendency to impute structure in random stimuli. We test said hypothesis in an empirical study which operationalizes subjects' objective abilities and subjective decision criteria in discriminating between correlated and independent signals in terms of the classic Signal Detection Theory. A robust regularized Bayesian multiple regression analysis indicates that liberal subjective decision criteria which indicate a tendency to over-impute structure when trying to discriminate between random and correlated patterns are associated with elevated scores of picky eating while controlling for several other variables. The predictive power of our discriminating procedure appears comparable to that of related eating dispositions. Our results strongly suggest that cognitive factors might indeed have substantial and meaningful relationships with certain eating behaviors.