ReviewCurrent topics in behavioral neurosciences2025
Using Inhibitory Learning Theories to Optimise Treatment for Children with Anxiety Disorders.
Review in Current topics in behavioral neurosciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Anxiety disorders in children lead to substantial impairment in functioning and development. Even the most effective gold standard treatments for childhood anxiety have 50% remission rates, suggesting a critical need to improve current treatments. Optimising exposure, the key component of anxiety treatments, represents a promising way to do so. This chapter explains how to optimise exposure outcomes for childhood anxiety through inhibitory learning theory. This chapter describes the background of inhibitory learning, including its different components and the empirical evidence supporting it. We then discuss how to improve the formation of inhibitory associations through enhancing expectancy violation, the proposed mechanism underlying inhibitory learning. Strategies to enhance inhibitory learning for child anxiety treatment are provided. These include strategies to enhance the formation of inhibitory associations, such as psychoeducation, eliminating safety signals, deepened extinction, occasional reinforced extinction, and affect-based strategies. Additionally, strategies to enhance retrieval include variability, multiple contexts, and retrieval cues. Suggestions are made on how to adapt these strategies to child populations. Further, a clinical guide for using inhibitory learning strategies in child anxiety treatment is included as an appendix. This details how clinicians can utilise these strategies to enhance current treatments, including examples of case studies and scripts.
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