Causal learning through repeated decision making

Abstract Many decisions refer to actions that have a causal impact on other events. Such actions allow for mere learning of expected values, but also for causal learning about the structure of the decision context. Whereas most theories of decision making neglect causal knowledge, causal learning theories emphasize the importance of causal beliefs and assume that people represent decision problems in terms of their causal structure. In three studies we investigated the representations people acquire when repeatedly making decisions to maximize a certain payoff. Our results show that (i) initial causal hypotheses guide the interpretation of decision feedback, (ii) consequences of interventions are used to revise existing causal beliefs, (iii) decision makers use the experienced feedback to induce a causal model of the choice situation, which (iv) enables them to adapt their choices to changes of the decision problem

Causal selection – the linguistic take

Causal Selection is a widely discussed topic in philosophy and the cognitive sciences, concerned with characterizing the choice of "the cause" among the many individually necessary and jointly sufficient conditions on which any effect depends on. In this paper, we argue for an additional selection process underlying causal statements: Causative-Construction Selection, which pertains to the choice of linguistic constructions used to express causal relations. By exploring this phenomenon, we aim to answer the following question: given that a speaker wishes to describe the relation between one of the conditions and the effect, which linguistic constructions are available? We take CC-selection to be more crucial than causal selection, since the latter is in fact restricted by the linguistic options resulting from the former. Based on a series of experiments, we demonstrate that factors taken previously as contributing to causal selection should, in fact, be considered as the parameters that license the various linguistic constructions under given circumstances, based on previous knowledge about the causal structure of the world (the causal model). These factors are therefore part of the meaning of the causative expressions

Predecisional information distortion in physicians’ diagnostic judgments: Strengthening a leading hypothesis or weakening its competitor?

Decision makers have been found to bias their interpretation of incoming information to support an emerging judgment (predecisional information distortion). This is a robust finding in human judgment, and was recently also established and measured in physicians’ diagnostic judgments (Kostopoulou et al. 2012). The two studies reported here extend this work by addressing the constituent modes of distortion in physicians. Specifically, we studied whether and to what extent physicians distort information to strengthen their leading diagnosis and/or to weaken a competing diagnosis. We used the “stepwise evolution of preference” method with three clinical scenarios, and measured distortion on separate rating scales, one for each of the two competing diagnoses per scenario

The Nature and Perception of Fluctuations in Human Musical Rhythms

Although human musical performances represent one of the most valuable achievements of mankind, the best musicians perform imperfectly. Musical rhythms are not entirely accurate and thus inevitably deviate from the ideal beat pattern. Nevertheless, computer generated perfect beat patterns are frequently devalued by listeners due to a perceived lack of human touch. Professional audio editing software therefore offers a humanizing feature which artificially generates rhythmic fluctuations. However, the built-in humanizing units are essentially random number generators producing only simple uncorrelated fluctuations. Here, for the first time, we establish long-range fluctuations as an inevitable natural companion of both simple and complex human rhythmic performances. Moreover, we demonstrate that listeners strongly prefer long-range correlated fluctuations in musical rhythms. Thus, the favorable fluctuation type for humanizing interbeat intervals coincides with the one generically inherent in human musical performances

The tight coupling between category and causal learning

The main goal of the present research was to demonstrate the interaction between category and causal induction in causal model learning. We used a two-phase learning procedure in which learners were presented with learning input referring to two interconnected causal relations forming a causal chain (Experiment 1) or a common-cause model (Experiments 2a, b). One of the three events (i.e., the intermediate event of the chain, or the common cause) was presented as a set of uncategorized exemplars. Although participants were not provided with any feedback about category labels, they tended to induce categories in the first phase that maximized the predictability of their causes or effects. In the second causal learning phase, participants had the choice between transferring the newly learned categories from the first phase at the cost of suboptimal predictions, or they could induce a new set of optimally predictive categories for the second causal relation, but at the cost of proliferating different category schemes for the same set of events. It turned out that in all three experiments learners tended to transfer the categories entailed by the first causal relation to the second causal relation

Reference Values of the QOLIBRI from General Population Samples in the United Kingdom and The Netherlands

The Quality of Life after Traumatic Brain Injury (QOLIBRI) instrument is an internationally validated patient-reported outcome measure for assessing disease-specific health-related quality of life (HRQoL) in individuals after traumatic brain injury (TBI). However, no reference values for general populations are available yet for use in clinical practice and research in the field of TBI. The aim of the present study was, therefore, to establish these reference values for the United Kingdom (UK) and the Netherlands (NL). For this purpose, an online survey with a reworded version of the QOLIBRI for general populations was used to collect data on 4403 individuals in the UK and 3399 in the NL. This QOLIBRI version was validated by inspecting descriptive statistics, psychometric criteria, and comparability of the translations to the original version. In particular, measurement invariance (MI) was tested to examine whether the items of the instrument were understood in the same way by different individuals in the general population samples and in the TBI sample across the two countries, which is necessary in order to establish reference values. In the general population samples, the reworded QOLIBRI displayed good psychometric properties, including MI across countries and in the non-TBI and TBI samples. Therefore, differences in the QOLIBRI scores can be attributed to real differences in HRQoL. Individuals with and without a chronic health condition did differ significantly, with the latter reporting lower HRQoL. In conclusion, we provided reference values for healthy individuals and individuals with at least one chronic condition from general population samples in the UK and the NL. These can be used in the interpretation of disease-specific HRQoL assessments after TBI applying the QOLIBRI on the individual level in clinical as well as research contexts

Measurement invariance of six language versions of the post-traumatic stress disorder checklist for DSM-5 in civilians after traumatic brain injury

Publisher Copyright: © 2022, The Author(s).Traumatic brain injury (TBI) is frequently associated with neuropsychiatric impairments such as symptoms of post-traumatic stress disorder (PTSD), which can be screened using self-report instruments such as the Post-Traumatic Stress Disorder Checklist for DSM-5 (PCL-5). The current study aims to inspect the factorial validity and cross-linguistic equivalence of the PCL-5 in individuals after TBI with differential severity. Data for six language groups (n ≥ 200; Dutch, English, Finnish, Italian, Norwegian, Spanish) were extracted from the CENTER-TBI study database. Factorial validity of PTSD was evaluated using confirmatory factor analyses (CFA), and compared between four concurrent structural models. A multi-group CFA approach was utilized to investigate the measurement invariance (MI) of the PCL-5 across languages. All structural models showed satisfactory goodness-of-fit with small between-model variation. The original DSM-5 model for PTSD provided solid evidence of MI across the language groups. The current study underlines the validity of the clinical DSM-5 conceptualization of PTSD and demonstrates the comparability of PCL-5 symptom scores between language versions in individuals after TBI. Future studies should apply MI methods to other sociodemographic (e.g., age, gender) and injury-related (e.g., TBI severity) characteristics to improve the monitoring and clinical care of individuals suffering from PTSD symptoms after TBI.Peer reviewe