Quantitative or qualitative development in decision making?

A key question in the developmental sciences is whether developmental differences are quantitative or qualitative. For example, does age increase the speed in processing a task (quantitative differences) or does age affect the way a task is processed (qualitative differences)? Until now, findings in the domain of decision making have been based on the assumption that developmental differences are either quantitative or qualitative. In the current study, we took a different approach in which we tested whether development is best described as being quantitative or qualitative. We administered a judgment version and a choice version of a decision-making task to a developmental sample (njudgment = 109 and nchoice = 137; Mage = 12.5 years, age range = 9–18). The task, the so-called Gambling Machine Task, required decisions between two options characterized by constant gains and probabilistic losses; these characteristics were known beforehand and thus did not need to be learned from experience. Data were analyzed by comparing the fit of quantitative and qualitative latent variable models, so-called multiple indicator multiple cause (MIMIC) models. Results indicated that individual differences in both judgment and choice tasks were quantitative and pertained to individual differences in “consideration of gains,” that is, to what extent decisions were guided by gains. These differences were affected by age in the judgment version, but not in the choice version, of the task. We discuss implications for theories of decision making and discuss potential limitations and extensions. We also argue that the MIMIC approach is useful in other domains, for example, to test quantitative versus qualitative development of categorization, reasoning, math, and memory

Investigating latent decision constructs using computational modeling of behavioral and brain data

The current dissertation is aimed at the study of a variety of latent decision-making constructs, that is, constructs reasoned to underlie variability in decision-making behavior but which cannot be directly observed (e.g., decision strategies). This is achieved via computational modeling, the use of mathematical models to describe, understand, and test hypotheses concerning complex phenomena. The models applied in these studies take into account, or focusses specifically on, individual differences in decision making in either behavioral or combined behavioral and neuroimaging data. The dissertation consists of five separate research articles, split into two parts. Part I focusses on the MIMIC model approach, a structural equation model allowing to empirically test whether individual differences in decision making are quantitative (i.e., or qualitative (i.e., categorical) in nature. In chapter 2, the method is introduced, tested, and illustrated in combined behavioral and neuroimaging data. In chapter 3, the method is applied to demographic and behavioral data of a gambling machine task. Part II focusses on the study of individual differences in decision strategies, qualitatively distinct latent mechanisms that describe how available information is used to reach decisions. Chapter 4 involved the study of individual differences and age effects in decision strategies in perceptual decision making including advice from others. In chapter 5, we investigate if individuals with ADHD utilize less complex decision strategies due to a reduced need for cognition. In chapter 6, we test if individual differences in the framing effect relate to differences in decision strategy and brain activity

Modulation of genes involved in inflammation and cell death in atherosclerosis-susceptible mice

In this thesis we focus on atherosclerosis as the main cause of cardiovascular disease. Since inflammation and cell death are important processes in the onset and progression of atherosclerosis, we investigate the role of several genes involved in inflammation and cell death in the vessel wall and their effect on atherosclerosis. We use several ways to modulate gene expression. Examples from different chapters are whole body deletion of TNF (2), local gene targeting of Fas Ligand to the cap of the plaque (3), conditional gene targeting of mdm2, thereby upregulating p53 (4), and beta-galactosidase (5), and pharmacological targeting of PPARs (6). In this thesis we use various mouse models of atherosclerosis, such as the apoE deficient mouse, the "humanized" apoE3*Leiden mouse and accelerated atherosclerosis induced by collar placement.TNO-Quality of life, The Gaubius Laboratory, Netherlands Organization of Scientific Research(NWO/ZonMW), Astra Zeneca, Sweden, Leids Universitair Fonds (LUF)UBL - phd migration 201

Formal Models of Differential Framing Effects in Decision Making Under Risk

An intriguing finding in the decision-making literature is that, when people have to choose between sure and risky options of equal expected value, they typically take more risks when decisions are framed as losses instead of gains (Tversky &amp; Kahneman, 1981). This framing effect is robust and has important implications for health, finance, and politics. However, theoretical debate exists on the origins of this effect. Moreover, pronounced task-related, individual, and developmental differences exist in the magnitude of the effect. These two issues—theoretical debate and differential framing effects— can be solved together, as an adequate theory of the framing effect should both describe the effect itself and describe differences therein. Therefore, we compare four theories on their capacity to describe differential framing effects: cumulative prospect theory (CPT), fuzzy trace theory (FTT), dual process theory, and a hybrid theory (HT) incorporating elements from lexicographic theory and fuzzy trace theory. First, in a theoretical analysis and empirical review, we build on recent advances in the fields of decision making, brain– behavior relationships, and cognitive development. Second, in an empirical study, we directly compare these theories by using a new experimental task and new analytic approach in which we use hierarchical Bayesian model-based mixture analysis of theories. Taken together, results indicate that differential framing effects are best described by the notion that the majority of decision makers decide according to the hybrid theory, and a sizable minority according to cumulative prospect theory and fuzzy trace theory. We discuss implications of these results for our understanding of the framing effect, and for decision making in general.</p

Susceptibility to peer influence in adolescents with mild-to-borderline intellectual disability: Investigating links with inhibition, Theory of Mind and negative interpretation bias

Background: This preregistered study compares adolescents with mild-to-borderline intellectual disability (MBID) and typically developing (TD) adolescents on their susceptibility to peer influence. To understand why adolescents with MBID are susceptible to peer influence, links with inhibition, Theory of Mind (ToM) and negative interpretation bias are investigated. Method: We assessed 163 adolescents (111 MBID, 52 TD 14–19 years; 63% boys) using experimental tasks and self- and/or teacher-reports. Results: Adolescents with MBID and TD adolescents did not differ in their susceptibility to peer influence, inhibition, and negative interpretations. On two ToM instruments, adolescents with MBID performed weaker than TD adolescents. In a structural equation model, tested in the MBID group, inhibition, ToM and negative interpretation bias were not related to susceptibility to peer influence. Conclusions: This study revealed new insights by strong methods such as the multimethod approach, a full theoretical model testing relations between all constructs simultaneously, and the large sample