An Investigation of the “Jumping to Conclusions” Data-Gathering Bias and Paranoid Thoughts in Asperger Syndrome

Paranoia and Data-Gathering Biases in Autism

Previous research has identified contradictory patterns in autism upon probabilistic reasoning tasks, and high levels of self-report paranoia symptoms have also been reported. To explore this relationship, the present study assessed 64 non-autistic and 39 autistic adults on two variants of a probabilistic reasoning task which examined the amount of evidence required before making a decision and 'jumping to conclusions' (a neutral beads task and an emotionally-salient words variant). The autism group was found to require significantly more evidence before making a decision and to have significantly less jumping to conclusions than the non-autistic group. For those with relatively low levels of paranoia, the emotionally-salient variant impacted on the non-autistic group, but not the autism group.

Thinking, fast and slow on the autism spectrum

What is already known about the topicDaniel Kahneman wrote a highly influential book titled 'thinking, fast and slow'. He proposes that people usually think in a rapid, automatic, intuitive style. When people realise their intuitive thinking may be wrong, a slower, effortful, deliberative style of thinking takes over. It has recently been proposed that thinking in autistic individuals can be characterised as usually thinking in the deliberative style (rather than the intuitive style that non-autistic people usually think in).What this paper addsAs intuitive thinking is fast and deliberative thinking is slow, this research manipulated the time available to complete a series of reasoning questions. These questions have been developed to have intuitive answers (which are incorrect) and deliberative answers (which are correct). For the first time, a fast time manipulation (you must answer quickly) and slow (you must think about your answer before responding) was undertaken with autistic individuals. Autistic participants did produce more deliberative answers than the non-autistic participants. However, both groups produced comparably more intuitive answers and less deliberative answers in the fast condition. This shows that while autistic people tend not to use their intuition, autistic people can be encouraged to use their intuition.Implications for practice, research or policyUsing rapid intuition can be useful in fast-changing contexts, such as some social situations. Future research can explore how to support autistic individuals to use their intuition when the need arises. In addition, the propensity for deliberation resulting in unbiased, correct responses reflects a strengths-based account of autism. This requires more mental effort and is less susceptible to bias and errors. This is called 'Dual Process Theory'.

Decision-making in autism: A narrative review

LAY SUMMARY

Many autistic people report difficulties with real-life decision-making. However, when doing decision-making tests in laboratory experiments, autistic people often perform as well or better than non-autistic people. We review previously published studies on autistic people's decision-making, across different types of tests, to understand what type of decision-making is more challenging. To do this, we searched four databases of research papers. We found 104 studies that tested, in total, 2712 autistic and 3189 comparison participants on different decision-making tasks. We found that there were four categories of decision-making tests that were used in these experiments: perceptual (e.g. deciding which image has the most dots); reward learning (e.g. learning which deck of cards gives the best reward); metacognition (e.g. knowing how well you perform or what you want); and value-based (e.g. making a decision based on a choice between two outcomes that differ in value to you). Overall, these studies suggest that autistic and comparison participants tend to perform similarly well at perceptual and reward-learning decisions. However, autistic participants tended to decide differently from comparison participants on metacognition and value-based paradigms. This suggests that autistic people might differ from typically developing controls in how they evaluate their own performance and in how they make decisions based on weighing up the subjective value of two different options. We suggest these reflect more general differences in metacognition, thinking about thinking, in autism.

The effect of autism on information sampling during decision-making: An eye-tracking study

Recent research has highlighted a tendency for more rational and deliberative decision-making in individuals with autism. We tested this hypothesis by using eye-tracking to investigate the information processing strategies that underpin multi-attribute choice in a sample of adults diagnosed with autism spectrum condition. We found that, as the number of attributes defining each option increased, autistic decision-makers were speedier, examined less of the available information, and spent a greater proportion of their time examining the option they eventually chose. Rather than indicating a more deliberative style, our results are consistent with a tendency for individuals with autism to narrow down the decision-space more quickly than does the neurotypical population.

Overestimation of volatility in schizophrenia and autism? A comparative study using a probabilistic reasoning task

BACKGROUND AND OBJECTIVES

A plethora of studies has investigated and compared social cognition in autism and schizophrenia ever since both conditions were first described in conjunction more than a century ago. Recent computational theories have proposed similar mechanistic explanations for various symptoms beyond social cognition. They are grounded in the idea of a general misestimation of uncertainty but so far, almost no studies have directly compared both conditions regarding uncertainty processing. The current study aimed to do so with a particular focus on estimation of volatility, i.e. the probability for the environment to change.

METHODS

A probabilistic decision-making task and a visual working (meta-)memory task were administered to a sample of 86 participants (19 with a diagnosis of high-functioning autism, 21 with a diagnosis of schizophrenia, and 46 neurotypically developing individuals).

RESULTS

While persons with schizophrenia showed lower visual working memory accuracy than neurotypical individuals, no significant group differences were found for metamemory or any of the probabilistic decision-making task variables. Nevertheless, exploratory analyses suggest that there may be an overestimation of volatility in subgroups of participants with autism and schizophrenia. Correlations revealed relationships between different variables reflecting (mis)estimation of uncertainty, visual working memory accuracy and metamemory.

LIMITATIONS

Limitations include the comparably small sample sizes of the autism and the schizophrenia group as well as the lack of cognitive ability and clinical symptom measures.

CONCLUSIONS

The results of the current study provide partial support for the notion of a general uncertainty misestimation account of autism and schizophrenia.

Jumping to conclusions in autism: integration of contextual information and confidence in decision-making processes

Individuals with Autism spectrum condition (ASC) present cognitive biases and a difficulty to integrate emotional responses in decision-making, which is necessary for adequate social functioning. Thus, understanding the underlying mechanisms of the altered decision-making in individuals with ASC may eventually have a positive impact on their social functioning. The Picture decision task was employed to observe the effect of new information (fragments of an incomplete picture), interpretative context (verbal cues), and the level of confidence on decision-making processes. Our study administered the task to 49 children with ASC and 37 children with Typical Development (TD). Children with TD showed a higher probability of success when an interpretative context was given. Conversely, children with ASC had an equal probability of success regardless of whether an interpretative context was provided or not. In addition, unlike children with TD, the level of confidence did not allow predicting the probability of successful decisions in children with ASC. Finally, children with ASC had more probability of jumping to conclusions, a decision made quickly with only one fragment of the picture while being completely sure of it. These results are discussed in light of current cognitive and emotional theories on ASC.

Autism Spectrum Disorder and Schizophrenia Are Better Differentiated by Positive Symptoms Than Negative Symptoms

Autism spectrum disorder (ASD) and schizophrenia (SZ) are heterogenous neurodevelopmental disorders that overlap in symptom presentation. The purpose of this study was to specify overlapping symptom domains and to identify symptoms that can reliably differentiate adults with ASD (n = 53), SZ (n = 39), and typical development (TD; n = 40). All participants regardless of diagnosis were administered gold-standard diagnostic assessments of ASD and SZ characteristics including the Autism Diagnostic Observation Schedule (ADOS-2) and the Positive and Negative Syndrome Scale (PANSS). Sensitivity and specificity of the ADOS were assessed using diagnostic cut-off scores. The degree of symptom overlap on these measures between participant groups was analyzed using Analyses of Variance (ANOVAs), Receiver Operating Characteristic (ROC) Curves, and Analyses of Covariance (ANCOVAs) to control for group differences in IQ and sex distributions. The ADOS reliably discriminated ASD and TD adults, but there was a high rate of "false positives" in SZ patients who did not meet the DSM-5 criteria for ASD. To identify the reasons for low specificity in the SZ sample, we categorized ASD and SZ symptoms into 'positive' (presence of atypical behaviors) and 'negative' (absence of typical behaviors) symptoms. ASD and SZ groups overlapped on negative symptoms largely related to the absence of typical social and communicative behaviors, whereas disorder-specific positive symptoms differentiated ASD and SZ. For example, those with ASD scored higher on restricted and repetitive behaviors and stereotyped language, whereas those with SZ scored higher on psychotic symptoms such as delusions and hallucinations. These results suggest that, when making a differential diagnosis between ASD and SZ, clinicians may benefit from focusing on the presence or absence of positive ASD and SZ symptoms. Standardized measures to classify ASD symptoms into positive and negative symptoms have not yet been developed but represent a potentially viable clinical tool.

Autistic traits influence the strategic diversity of information sampling: Insights from two-stage decision models

Information sampling can reduce uncertainty in future decisions but is often costly. To maximize reward, people need to balance sampling cost and information gain. Here we aimed to understand how autistic traits influence the optimality of information sampling and to identify the particularly affected cognitive processes. Healthy human adults with different levels of autistic traits performed a probabilistic inference task, where they could sequentially sample information to increase their likelihood of correct inference and may choose to stop at any moment. We manipulated the cost and evidence associated with each sample and compared participants’ performance to strategies that maximize expected gain. We found that participants were overall close to optimal but also showed autistic-trait-related differences. Participants with higher autistic traits had a higher efficiency of winning rewards when the sampling cost was zero but a lower efficiency when the cost was high and the evidence was more ambiguous. Computational modeling of participants’ sampling choices and decision times revealed a two-stage decision process, with the second stage being an optional second thought. Participants may consider cost in the first stage and evidence in the second stage, or in the reverse order. The probability of choosing to stop sampling at a specific stage increases with increasing cost or increasing evidence. Surprisingly, autistic traits did not influence the decision in either stage. However, participants with higher autistic traits inclined to consider cost first, while those with lower autistic traits considered cost or evidence first in a more balanced way. This would lead to the observed autistic-trait-related advantages or disadvantages in sampling optimality, depending on whether the optimal sampling strategy is determined only by cost or jointly by cost and evidence.

Children with autism can spend hours practicing lining up toys or learning all about cars or lighthouses. This kind of behaviors, we think, may reflect suboptimal information sampling strategies, that is, a failure to balance the gain of information with the cost (time, energy, or money) of information sampling. We hypothesized that suboptimal information sampling is a general characteristic of people with autism or high level of autistic traits. In our experiment, we tested how participants may adjust their sampling strategies with the change of sampling cost and information gain in the environment. Though all participants were healthy young adults who had similar IQs, higher autistic traits were associated with higher or lower efficiency of winning rewards under different conditions. Counterintuitively, participants with different levels of autistic traits did not differ in the general tendency of oversampling or undersampling, or in the decision they would reach when a specific set of sampling cost or information gain was considered. Instead, participants with higher autistic traits consistently considered sampling cost first and only weighed information gain during a second thought, while those with lower autistic traits had more diverse sampling strategies that consequently better balanced sampling cost and information gain.