Beyond verbal fluency in the verbal fluency task: semantic clustering as a predictor of remission in individuals at clinical high risk for psychosis

Abstract

Background: There have been conflicting reports on whether conventional verbal fluency measures can predict the prognosis of individuals at clinical high risk (CHR) for psychosis. We aimed to investigate whether verbal fluency task measures that represent semantic processing more directly than conventional measures could be more reliable predictors of later remission in CHR individuals.

Methods: We recruited CHR individuals and healthy controls to participate in a baseline verbal fluency assessment. We identified semantic clusters within the verbal fluency task responses based on cosine similarity between consecutive words, calculated from the word embedding model. Binomial logistic regression was performed to test whether average semantic cluster size and number of words produced could be predictors of remission in CHR individuals.

Results: Our study sample included 96 CHR individuals and 178 healthy controls. According to clinical assessment at the last follow-up, 23 CHR individuals were classified as remitters and 73 as nonremitters, including 29 individuals who converted to psychosis. The CHR remitters showed larger average and maximum semantic cluster sizes than CHR nonremitters and healthy controls. Average semantic cluster size, but not the number of words, was a significant predictor of later remission in CHR individuals.

Limitations: Our sample included only native Korean speakers.

Conclusion: A verbal fluency task measure that more specifically represents semantic processing may be a better neurocognitive predictive marker for remission in CHR individuals than conventional verbal fluency measures. Our results provide an explanation for heterogeneous reports on whether verbal fluency can predict prognosis in CHR individuals and suggest that semantic processing is a putative cognitive predictor of their prognosis.