Yannick Boddez’s research while affiliated with Ghent University and other places

Human behavior can sometimes cause harm to the behaving individual, other organisms, or their environment. Psychological science plays a crucial role in understanding and addressing these harmful behaviors by providing direction to behavior change interventions. However, the field of psychology encompasses numerous theories, and translating these theories into effective practices can be challenging. In this paper, we introduce the Goal-Directed Predictive Processing (GDPP) framework—an integrative approach that combines key principles from predictive processing and goal-directed theories. The GDPP framework bridges recent theoretical advancements with practical application, offering a user-friendly model to assist practitioners across various domains. It emphasizes assessing inference chains that underlie harmful behaviors in risk situations, mapping out alternative inferential processes in relation to expected surprise, and designing targeted interventions to influence these processes. We illustrate the application of this framework in the context of harmful alcohol consumption and depressive behavior.

Whereas traditional behavior therapy is grounded in learning principles, cognitive therapy often focuses on meaning. Within cognitive behavioral therapy, attempts were made to reconcile these two approaches by analyzing meaning in terms of learning principles, more specifically classical conditioning. In doing so, classical conditioning has often been conceptualized as the process of the formation of associations in semantic memory. We argue that this conceptualization is not only problematic but also unnecessary. We propose two alternative ways of reconciling learning principles with a focus on meaning: (1) by treating learning principles like classical conditioning as effects rather than mental processes and (2) by conceptualizing meaning analyses in terms of Relational Frame Theory. Research on classical conditioning remains an important source of inspiration also from these alternative perspectives. [Paper in Dutch]

People sometimes emit frequently practiced responses that were previously effective in achieving desired outcomes but are no longer appropriate in the current context. While dual-process theories attribute these action slips to goal-independent, associative processes, we propose that errors in the expectancies about action outcomes contribute to their occurrence. To investigate this, we first replicated an influential study by Hardwick et al. (2019), demonstrating the occurrence of action slips following extensive stimulus–response training when individuals are required to respond rapidly. Building on this foundation, we conducted two additional experiments using a similar procedure, incorporating a measure of outcome expectancies under time pressure. Our findings provide compelling evidence for errors not just in selected responses but also in expected outcomes of these responses, particularly in early time intervals. These results highlight the possible role of goal-directed processes in action slips under time pressure, advancing our understanding of the cognitive mechanisms underlying suboptimal behavior.

Many researchers have tackled the question of how behavior is influenced by its outcomes. Some have adopted a non-mechanistic (functional) perspective that aims to describe the impact of outcomes on behavior. Others have adopted a mechanistic (cognitive) perspective that aims to explain the impact of outcomes on behavior. Orthogonal to this distinction, some have focused on the impact of outcomes that a behavior had in the past whereas others take into account also the impact of outcomes that a behavior might have in the future. In the current paper, we relate these different perspectives with the aim of reducing misunderstandings and fostering collaborations between researchers who adopt different perspectives on the common question of how behavior is influenced by its outcomes.

In this introduction to the special collection of papers on the relation between learning and personality research, we provide a functional-cognitive framework that can guide interactions between learning and personality researchers. It highlights that learning researchers can treat personality variables as potential (first or second order) moderators of learning effects. They can also examine whether the effects of personality on learning itself depend on other moderators. Personality researchers can benefit from looking for stable individual differences in known learning effects. Together with learning researchers, they can analyze personality as learned and thus malleable behavior. We end by summarizing the papers of the special collection and by situating them within our framework.

Numerous studies have demonstrated a link between neuroticism and negative biases. Although some studies suggest that people with high neuroticism give more weight to negative information, others suggest that they respond more strongly to both positive and negative information. We investigated whether neuroticism is related to the evaluation of conditioned stimuli (CSs) in evaluative conditioning procedures that involve ambiguous learning conditions. We created ambiguous situations where CSs were paired with unconditioned stimuli (USs) consisting of both positive and negative pictures (Experiment 1) or paired alternatingly with positive and negative USs (Experiment 2). In addition to CSs consistently paired with positive and negative USs, we introduced neutral USs as a control condition. Our findings revealed that neurotic individuals negatively evaluated the CSs from ambiguous conditions relative to neutral conditions. In addition, participants with high neuroticism scores generally rated CSs more negatively. Theoretical and clinical implications of these results are discussed.

Pairing a cue (e.g., an image of a geometrical figure) with an outcome (e.g., an image with aversive content) can result in the cue eliciting thoughts of that outcome (i.e., thought conditioning). Previous research suggests an advantage of counterconditioning over extinction in reducing thoughts of (aversive) outcomes. However, it is unclear how robust this effect is. This study aimed to (1) replicate the previously observed advantage of counterconditioning over extinction and (2) test whether counterconditioning leads to less reinstatement of thoughts of an aversive outcome relative to extinction. Participants (N = 118) underwent a differential conditioning procedure and were then assigned to one of three conditions: extinction (i.e., the aversive outcome was no longer presented), no extinction (i.e., the aversive outcome continued to be presented) and counterconditioning (i.e., the aversive outcome was replaced with positive images). After three unsignaled outcome presentations, participants indicated in a return of fear test the extent to which they thought of the aversive outcome. As predicted, counterconditioning was more successful in reducing thinking of the aversive outcome than extinction. Yet, there were no differences in return of thoughts of the aversive outcome between the two conditions. Future research should consider other return of fear procedures.

Biases in fear conditioning and interpretation biases have both been linked to the onset, maintenance, and treatment of anxiety. This chapter starts with summarizing empirical evidence on the link between fear conditioning biases and pathological anxiety. We discuss how biased interpretational processing might mediate biased behavior in fear conditioning tasks. In particular, stimuli might become ambiguous as a result of fear conditioning procedures (e.g., generalization and extinction). A tendency to interpret these ambiguous stimuli as threatening might result in increased fear responding in anxiety-prone individuals. We make a distinction between biases as observable behaviors (e.g., in experimental tasks) and biases as underlying (latent) cognitive processes or deficits. A mediation model is proposed that explains how a combination of genetic factors and learning experiences can give rise to observable biases and how this association can be (partially) driven by biases as a latent cognitive process (including interpretation biases). Finally, we discuss the role of (fear conditioning) biases in interventions for anxiety. Remediating biases might enhance the efficacy of cognitive-behavioral treatment and exposure interventions. However, it is predicted that biased individuals might be less sensitive to corrective experiences (e.g., due to a stagnated error reduction process).KeywordsFear conditioningAnxietyInterpretation biasExposureExtinctionGeneralization

Background and objectives: Models are omnipresent in science. We introduce a novel framework to achieve more effective modelling practices in general psychology and experimental psychopathology. Method: We analyze three types of models that are common in psychology: laboratory models, computational models, and cognitive models. We then evaluate two common ways to assess the translational value of models (phenomenological similarity and deep similarity) as well as an arguably underappreciated way (functional similarity). Functional similarity is based on an assessment of whether variables (e.g., the administration of a pharmacological substance) have a similar effect (a) in the model (e.g., in a fear conditioning procedure) and (b) on the real-life target phenomenon (e.g., on real-life anxiety complaints). Conclusions: We argue that the assessment of functional similarity is a powerful tool to assess the translational value of models in the field of experimental psychopathology and beyond.

Background: Learning tasks have been used to predict why some, and not others, develop posttraumatic stress disorder (PTSD) after exposure to a traumatic event. There is some evidence from prospective studies in high risk profession samples that reduced extinction learning might represent a marker or even a vulnerability factor for PTSD development. Objective: Since the evidence is scarce, the aim of this study was to perform a conceptual replication of an earlier prospective study, testing whether pretrauma extinction learning predicts later PTSD symptom severity. Method: A sample of 529 fire fighters performed a conditioning task at baseline and filled out questionnaires to assess PTSD symptom severity and neuroticism. At six and 12 months follow-up, exposure to stressful events and PTSD symptom severity were measured. Results: Results indicate that previous findings were not replicated: although reduced extinction learning was associated with higher PTSD symptom severity at baseline, extinction learning did not predict PTSD symptom severity at follow-up. Only PTSD symptom severity at baseline and stressor severity predicted PTSD symptom severity at follow-up. Conclusions: Since earlier findings on the predictive value of pre-trauma extinction learning on PTSD symptom severity were not replicated, extinction learning might not be a general risk factor PTSD for all individuals. More prospective studies including multiple factors seem needed to unravel the complex relationships of these factors influencing PTSD development. Highlights: Reduced extinction learning correlated with higher PTSD symptom severity at baseline.Reduced extinction learning did not predict PTSD symptom severity at follow-up.The predictive effect of pre-trauma extinction learning on PTSD was not replicated.