Socializing social sampling models: The limits of explaining norm perceptions and biases with sampling from social circles.

People often overestimate the prevalence of unfavorable behavior. To explain these misperceptions, social sampling models propose that individuals infer the social norm from the behavior of their own social circle. We investigated this idea by asking a friendship network of college freshmen to report their own behavior and norm perceptions across eight domains at two timepoints (N = 104). Assessing this complete social network allows to directly test if sampling from the social circle shapes norm perception. Replicating previous findings, freshmen systematically misperceived the average social norm within their cohort. Yet, these misperceptions persisted even when individuals judged their own social circle, indicating that sampling from social circles does not fully explain normative biases. Moreover, cognitive modelling of norm perceptions suggested that individuals unlikely limited their search to their own social circle.

The relation between memory and decision-making in multiple sclerosis patients.

BACKGROUND: Impairments in long-term and working memory are widespread in Multiple Sclerosis (MS), setting on in early disease stages. These memory impairments may limit patients' ability to take informed and competent medical decisions, too. In healthy populations, memory abilities predict decision quality across a wide range of tasks. These studies suggest that higher working memory capacity supports decisions in cognitively taxing tasks, whereas better semantic memory facilitates decisions in tasks requiring knowledge retrieval. In individuals with MS, previous studies have linked less accurate decisions to memory deficits and reduced executive functioning, too. However, these studies focussed on decisions under risk and did not broadly assess decision making skills. We aimed to fill this gap in a cross-sectional study. METHODS: Hundred thirty-seven participants with MS were recruited during their stay in an MS specialized rehabilitation centre. In a first test session, participants completed a standardized test battery for working memory and semantic memory, the inventory for memory diagnostics. In a second test session, participants filled out the Adult Decision Making Competence battery (A-DMC). This version of the A-DMC measured decision making competence on five subscales: Resistance to Framing Effects, Under/Overconfidence, Applying Decision Rules, Consistency in Risk Perception, and Resistance to Sunk Cost Effects. In addition, participants were screened for depression and cognitive fatigue. RESULTS: Working memory was impaired in most participants, whereas semantic memory was not impaired. To understand which memory abilities underlie distinct components of decision making in people with MS, we used structural equation modelling. Replicating previous findings in a healthy sample, working memory capacity was associated with the ability to recall semantic knowledge. Participants with lower working memory capacity were less resistant to framing effects and adhered to decision rules less. In contrast, participants with worse semantic memory assessed their own knowledge less accurately, perceived risks less consistently, and made more errors in applying decision rules. Cognitive fatigue and depression unlikely explain these relationships. CONCLUSIONS: Taken together, our study suggests that the memory problems, frequently reported in MS patients, may reach out to higher-order cognitive functions, such as decision making skills. Supporting shared decision-making and patient autonomy within MS thus requires to take memory impairments into account and to match the information provided to the patient's memory abilities.

Competitive retrieval strategy causes multimodal response distributions in multiple-cue judgments.

Research on quantitative judgments from multiple cues suggests that judgments are simultaneously influenced by previously abstracted knowledge about cue-criterion relations and memories of past instances (or exemplars). Yet extant judgment theories leave 2 questions unanswered: (a) How are past exemplars and abstracted cue knowledge combined to form a judgment? (b) Are all past exemplars retrieved from memory to form the judgment (integrative retrieval) or is the judgment based on one exemplar (competitive retrieval)? To address these questions we propose and test a new model, CX-COM (combining Cue abstraction with eXemplar memory assuming COMpetitive memory retrieval). In a first step, CX-COM recalls only a single exemplar from memory. In a second step, the initially retrieved judgment is adjusted based on abstracted cue knowledge. Qualitatively, we show that CX-COM naturally captures judgment patterns that have been previously attributed to multiple strategies. Next, we tested CX-COM quantitatively in 2 experiments and found that it accounts well for people's judgment behavior. In the second experiment we additionally tested 2 qualitative predictions of CX-COM: The existence of multimodal response distributions within participants and systematic variability in judgments depending on the distance between similar exemplars in memory. The empirical results confirm CX-COM's assumptions. In sum, the evidence suggests that CX-COM is a viable new model for quantitative judgments and shows the importance of considering judgment variability in addition to average responses in judgment research. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Tracing the path of forgetting in rule abstraction and exemplar retrieval.

People often forget acquired knowledge over time such as names of former classmates. Which knowledge people can access, however, may modify the judgement process and affect judgement accuracy. Specifically, we hypothesised that judgements based on retrieving past exemplars from long-term memory may be more vulnerable to forgetting than remembering rules that relate the cues to the criterion. Experiment 1 systematically tracked the individual course of forgetting from initial learning to later tests (immediate, 1 day, and 1 week) in a linear judgement task facilitating rule-based strategies and a multiplicative judgement task facilitating exemplar-based strategies. Practising the acquired judgement strategy in repeated tests helped participants to consistently apply the learnt judgement strategy and retain a high judgement accuracy even after a week. Yet, whereas a long retention interval did not affect judgements in the linear task, a long retention interval impaired judgements in the multiplicative task. If practice was restricted as in Experiment 2, judgement accuracy suffered in both tasks. In addition, after a week without practice, participants tried to reconstruct their judgements by applying rules in the multiplicative task. These results emphasise that the extent to which decision makers can still retrieve previously learned knowledge limits their ability to make accurate judgements and that the preferred strategies change over time if the opportunity for practice is limited.

Similar task features shape judgment and categorization processes.

The distinction between similarity-based and rule-based strategies has instigated a large body of research in categorization and judgment. Within both domains, the task characteristics guiding strategy shifts are increasingly well documented. Across domains, past research has observed shifts from rule-based strategies in judgment to similarity-based strategies in categorization, but limited these comparisons to 1 prototypical environment, a linear task structure, and a restricted set of strategies. To systematically compare the 2 domains, we considered several instantiations of rule-based and similarity-based strategies and examined strategy choice across different types of judgment and categorization tasks. Between participants, we varied task characteristics from a 1-dimensional linear to a multidimensional linear and to 2 multidimensional nonlinear tasks. Irrespective of domain, strategies considered, or model comparison technique used, we find that more participants relied on similarity-based strategies when the functional relationship between the cues and the criterion was nonlinear. Shifts from rule-based strategies in judgment to similarity-based strategies in categorization, however, were rare and most pronounced in 1-dimensional environments. These results support the hypothesis that the cognitive strategies people select to solve a judgment or categorization task depend less on the domain but more on the complexity of the task. (PsycINFO Database Record

Pillars of judgment: how memory abilities affect performance in rule-based and exemplar-based judgments.

Making accurate judgments is an essential skill in everyday life. Although how different memory abilities relate to categorization and judgment processes has been hotly debated, the question is far from resolved. We contribute to the solution by investigating how individual differences in memory abilities affect judgment performance in 2 tasks that induced rule-based or exemplar-based judgment strategies. In a study with 279 participants, we investigated how working memory and episodic memory affect judgment accuracy and strategy use. As predicted, participants switched strategies between tasks. Furthermore, structural equation modeling showed that the ability to solve rule-based tasks was predicted by working memory, whereas episodic memory predicted judgment accuracy in the exemplar-based task. Last, the probability of choosing an exemplar-based strategy was related to better episodic memory, but strategy selection was unrelated to working memory capacity. In sum, our results suggest that different memory abilities are essential for successfully adopting different judgment strategies.

Deliberation's blindsight: how cognitive load can improve judgments.

Multitasking poses a major challenge in modern work environments by putting the worker under cognitive load. Performance decrements often occur when people are under high cognitive load because they switch to less demanding--and often less accurate--cognitive strategies. Although cognitive load disturbs performance over a wide range of tasks, it may also carry benefits. In the experiments reported here, we showed that judgment performance can increase under cognitive load. Participants solved a multiple-cue judgment task in which high performance could be achieved by using a similarity-based judgment strategy but not by using a more demanding rule-based judgment strategy. Accordingly, cognitive load induced a shift to a similarity-based judgment strategy, which consequently led to more accurate judgments. By contrast, shifting to a similarity-based strategy harmed judgments in a task best solved by using a rule-based strategy. These results show how important it is to consider the cognitive strategies people rely on to understand how people perform in demanding work environments.