Factors underlying the neurofunctional domains of the Addictions Neuroclinical Assessment assessed by a standardized neurocognitive battery

通过标准化的神经认知测试评估成瘾神经临床评估中神经功能领域的潜在因素

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Abstract

The Addictions Neuroclinical Assessment (ANA) is a neurobiologically-informed framework designed to understand the etiology and heterogeneity of Alcohol Use Disorder (AUD). Previous studies validated the three neurofunctional domains of ANA: Incentive Salience (IS), Negative Emotionality (NE) and Executive Function (EF) using secondary data. The present cross-sectional observational study assessed these domains in an independent, prospective clinical sample. Adults across the drinking spectrum (N = 300) completed the ANA battery, a standardized collection of behavioral tasks and self-report assessments. Factor analyses were used to identify latent factors underlying each domain. Associations between identified domain factors were evaluated using structural equation models. Receiver operating characteristics analyses were used to determine factors with the strongest ability to classify individuals with problematic drinking and AUD. We found (1) two factors underlie the IS domain: alcohol motivation and alcohol insensitivity. (2) Three factors were identified for the NE domain: internalizing, externalizing, and psychological strength. (3) Five factors were found for the EF domain: inhibitory control, working memory, rumination, interoception, and impulsivity. (4) These ten factors showed varying degrees of cross-correlations, with alcohol motivation, internalizing, and impulsivity exhibiting the strongest correlations. (5) Alcohol motivation, alcohol insensitivity, and impulsivity showed the greatest ability in classifying individuals with problematic drinking and AUD. Thus, the present study identified unique factors underlying each ANA domain assessed using a standardized assessment battery. These results revealed additional dimensionality to the ANA domains, bringing together different constructs from the field into a single cohesive framework and advancing the field of addiction phenotyping. Future work will focus on identifying neurobiological correlates and identifying AUD subtypes based on these factors.

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