Relationships between autism spectrum disorder and intolerance of uncertainty

Vasa, Roma A.; Kreiser, Nicole L.; Keefer, Amy; Singh, Vini; Mostofsky, Stewart H.

doi:10.1002/aur.1916

Cited by 77 publications

(63 citation statements)

References 61 publications

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“…This is because there is often a discrepancy between self-reported and proxy-reported data in relation to autistic individuals (e.g. Vasa et al, 2018) and that individuals are often better-informants of their IoU (Comer et al, 2009). This parallels the approach taken by Osmanağaoğlu et al (2018).…”

Section: The Current Reviewmentioning

confidence: 99%

The relationship between intolerance of uncertainty and anxiety in autism: A systematic literature review and meta-analysis

Jenkinson

Milne

Thompson

2020

Autism

103

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The association between intolerance of uncertainty and anxiety has proved robust in neurotypical populations and has led to effective interventions targeting intolerance of uncertainty. The aim of this systematic review and meta-analysis was to investigate this association in autistic people, given the high prevalence of anxiety in this population and the limited effectiveness of therapies used currently to treat anxiety in autism. A protocol was published on the Prospero database (CRD42019125315), and electronic databases were searched using terms related to intolerance of uncertainty, anxiety and autism. Included in the systematic review were 12 studies, of which 10 were included in a meta-analysis. Results showed that anxiety and intolerance of uncertainty were consistently elevated in autistic participants. Examining the correlation between these two constructs, the meta-analysis revealed a large sample-weighted effect size, r = 0.62, 95% confidence interval = [0.52, 0.71], p < 0.001. The strength of this association was comparable to meta-analyses conducted on neurotypical populations, and therefore, it was concluded intolerance of uncertainty may be an appropriate target for intervention for autistic individuals. However, conclusions were limited due to the small number of relevant studies that were available and due to issues with methodological quality. Lay abstract People who find it especially hard to cope with the unexpected or unknown are said to have an intolerance of uncertainty. Autistic individuals often report a preference for certainty and experience levels of anxiety that can interfere with their daily life. Understanding more about the link between the intolerance of uncertainty and anxiety in autistic people might lead to better treatments for anxiety being developed. Therefore, this work aimed to review previous research in order to explore this link. Twelve studies were found and their results were compared and contrasted. The autistic people who participated in the studies completed questionnaires that suggested a large number of them experienced very high levels of anxiety and intolerance of uncertainty. Of 10 studies that used relevant statistics, nine found a statistically significant link between anxiety and the intolerance of uncertainty. In general, the strength of the link was about the same as previous research found in people who did not have a diagnosis of autism. This might mean that interventions that aim to help people who are intolerant of uncertainty could be effective for autistic individuals.

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Section: The Current Reviewmentioning

confidence: 99%

The relationship between intolerance of uncertainty and anxiety in autism: A systematic literature review and meta-analysis

Jenkinson

Milne

Thompson

2020

Autism

103

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“…A need for predictability and routine is a key dimension of “intolerance of uncertainty,” which has been identified within a meta‐analysis as a transdiagnostic factor for the development and maintenance of anxiety (Osmanagaoglu, Creswell, & Dodd, 2018) as well as other mental health conditions (Gentes & Ruscio, 2011; Hong & Cheung, 2014). The relationship between intolerance of uncertainty and anxiety in individuals on the spectrum has been explored using quantitative (e.g., Cai, Richdale, Dissanayake, & Uljarevic, 2018; Vasa, Kreiser, Keefer, Singh, & Mostofsky, 2018) and qualitative methods (e.g., Hodgson, Freeston, Honey, & Rodgers, 2017). Although there is clearly a strong relationship between intolerance of uncertainty and anxiety, there is a complex interplay with the sensory sensitivities (Neil, Olsson, & Pellicano, 2016) and emotional dysregulation (Vasa et al, 2018).…”

Section: Discussionmentioning

confidence: 99%

“…The relationship between intolerance of uncertainty and anxiety in individuals on the spectrum has been explored using quantitative (e.g., Cai, Richdale, Dissanayake, & Uljarevic, 2018; Vasa, Kreiser, Keefer, Singh, & Mostofsky, 2018) and qualitative methods (e.g., Hodgson, Freeston, Honey, & Rodgers, 2017). Although there is clearly a strong relationship between intolerance of uncertainty and anxiety, there is a complex interplay with the sensory sensitivities (Neil, Olsson, & Pellicano, 2016) and emotional dysregulation (Vasa et al, 2018). As parents in the current study identified self‐regulation and sensory difficulties as a barrier to children managing their own anxiety in the community, these areas and their interplay with the autism and anxiety profile warrant further consideration and exploration.…”

Section: Discussionmentioning

confidence: 99%

Parent perspectives of what helps and hinders their child on the autism spectrum to manage their anxiety

Clark

Adams

2020

Clinical Psychologist

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Objectives Although anxiety is recognised as one of the most common co‐occurring conditions to affect school‐aged children with an autism spectrum disorder, little research has explored the strategies that children on the autism spectrum use to manage their own anxiety. Methods Seventy‐two parents of children on the spectrum aged 5 to 17 years identified things that supported their child to manage their anxiety (enablers) and things that hindered their child's management of anxiety (barriers) across the home, school, and community. Using content analysis, parents' open‐ended responses were coded into a series of subcategories for each setting. Results At home, “routine, modifications, and adaptations” was the most frequently reported enabler while “social, communication, and personal challenges” was the most frequently reported barrier to managing anxiety. “Supports and strategies (at school/in the community)” was the most commonly identified enabler that supported children to manage their anxiety in both the school and community environments. “Overstimulation, unpredictability, and demands (at school/in the community)” was the most commonly identified barrier hindering children's management of anxiety in both the school and community settings. Conclusions Given the wide range of barriers and enablers identified, working with children and families to identify the barriers and enablers for each child in managing their anxiety may be a useful process during therapy. Targeting interventions to align with the identified barriers and enablers may assist children on the autism spectrum to develop strategies for the management of their own anxiety across settings.

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“…In addition to restricted inhibitory tone in ASD, there is evidence for a general intolerance of uncertainty (Boulter et al 2014;Fujino et al 2017;Vasa et al 2018), and altered performance with environmental uncertainty (Milne et al 2002;Spencer et al 2000). Furthermore, differences have been found in multiattribute decision tasks (Foxe et al 2015;Zaidel, Goin-Kochel, and Angelaki 2015).…”

Section: Choice Patterns Of Those With Autism Will Differ From Neurotmentioning

confidence: 99%

“…Additionally, environmental uncertainty offers an entry-point to understanding neuropsychiatric conditions, such as autism spectrum disorder (ASD). A myriad of findings suggest that the diagnostic signs of behavioral rigidity and sensory abnormalities (American Psychiatric Association 2013) may be related to an intolerance of environmental uncertainty (Foss-Feig et al 2017;Fujino et al 2017;Boulter et al 2014; Van de Cruys et al 2014;Vasa et al 2018). A mechanistic understanding of how hierarchical neural systems handle environmental uncertainty when making decisions can not only provide knowledge as to how the brain functions, but also may produce hypotheses as to the etiology of ASD.…”

mentioning

confidence: 99%

Hierarchical Network Model Excitatory-Inhibitory Tone Shapes Alternative Strategies for Different Degrees of Uncertainty in Multi-Attribute Decisions

Pettine

Louie

Murray

et al. 2020

Preprint

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We investigated two-attribute, two-alternative decision-making in a hierarchical neural network with three layers: an input layer encoding choice alternative attribute values; an intermediate layer of modules processing separate attributes; and a choice layer producing the decision. Depending on intermediate layer excitatory-inhibitory (E/I) tone, the network displays three distinct regimes characterized by linear (I), convex (II) or concave (III) choice indifference curves. In regimes I and II, each option's attribute information is additively integrated. To maximize reward at low environmental uncertainty, the system should operate in regime I. At high environmental uncertainty, reward maximization is achieved in regime III, with each attribute module selecting a favored alternative, and the ultimate decision based upon comparison between outputs of attribute processing modules. We then use these principles to examine multi-attribute decisions with autism-related deficits in E/I balance, leading to predictions of different choice patterns and overall performance between autism and neurotypicals. IntroductionWe are constantly faced with decisions between alternatives defined by multiple attributes. The true value of each attribute is at times clear, and other times uncertain. For example, on Friday one might choose between main courses at a restaurant where the flavor or healthiness attributes of all the dishes are familiar.The following Wednesday might be at a restaurant with an unknown cuisine, where one is highly uncertain as to different items' flavor or healthiness. To ensure the best meal, the brain must be able to optimize choice in both environments.Systems neuroscientists have, for many years, been studying the specific circuits engaged in this kind of multi-attribute decision-making. Based on a robust set of electrophysiology and imaging findings (Xie and Padoa-Schioppa 2016; Raghuraman and Padoa-Schioppa 2014; Padoa-Schioppa and Assad 2006; O'Neill and Schultz 2018; Morrison and Salzman 2009; Conen and Padoa-Schioppa 2015; Chib et al. 2009; Pastor-Bernier, Stasiak, and Schultz 2019), many hold that all attribute signals are available in brain areas proximal to the final decision (Levy and Glimcher 2012; Padoa-Schioppa and Conen 2017). Indeed, when attribute values are clear, multi-attribute choice theoretically is simple: linearly weight and combine all attributes associated with a choice alternative, then select the one with the larger value. Though the subjective value of an attribute might be non-linearly related to the quantity offered, when the final choice is made in an environment without uncertainty, a weighted linear combination of attributes optimizes the choice between options (Nicholson and Snyder 2007).

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Relationships between autism spectrum disorder and intolerance of uncertainty

Abstract: Youth with ASD without co-occurring intellectual disability experience high levels of intolerance of uncertainty (IU), which is related to anxiety. This study found that IU may also have a relationship with certain aspects of ASD, particularly emotion dysregulation.

Cited by 77 publications

References 61 publications

The relationship between intolerance of uncertainty and anxiety in autism: A systematic literature review and meta-analysis

The relationship between intolerance of uncertainty and anxiety in autism: A systematic literature review and meta-analysis

Parent perspectives of what helps and hinders their child on the autism spectrum to manage their anxiety

Hierarchical Network Model Excitatory-Inhibitory Tone Shapes Alternative Strategies for Different Degrees of Uncertainty in Multi-Attribute Decisions

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