Cognitive and Clinical Predictors of Camouflaging and Autistic Burnout Severity in Autistic Adults: A Structural Equation Modeling Approach

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Abstract

Autistic burnout is a debilitating condition characterized by exhaustion, loss of skills, and reduced tolerance to stimuli, yet its cognitive and clinical predictors remain poorly understood. This study examined whether autistic traits, executive dysfunction, and mental health predict camouflaging, and whether camouflaging mediates their relationship with autistic burnout severity.A sample of 115 autistic French-speaking adults reporting varying degrees of autistic burnout severity completed validated self-report measures. Structural relationships were tested using Partial Least Squares Structural Equation Modeling (PLS-SEM).The model explained 21.3% of variance in camouflaging and 36.9% in burnout severity, with approximate model fit (SRMR = 0.094). Executive functioning difficulties and autistic trait severity significantly predicted camouflaging, while mental health did not meet the pre-specified significance criterion as a direct predictor of camouflaging. Camouflaging emerged as the strongest predictor of burnout severity, followed by a direct effect of mental health. Significant indirect effects on burnout via camouflaging were found for both executive functioning and autistic traits, consistent with a partial mediating role for camouflaging.These findings provide initial quantitative evidence consistent with camouflaging as a central pathway through which individual cognitive and clinical characteristics relate to burnout severity, and underscore the importance of examining structural and psychosocial contributors.

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