A systematic review of implicit statistical learning in schizophrenia spectrum disorders
Year: 2026
Type: preprint
Abstract: This systematic review examined current findings on implicit statistical learning (ISL) in schizophrenia spectrum disorders and the factors that influence performance. We aimed to update and expand the existing literature by including various ISL tasks, such as serial reaction time, artificial grammar learning, or transitional probabilities. We also considered several ISL moderators related to the characteristics of these tasks, as well as a host of potential clinical and cognitive correlates. We searched PubMed, Scopus, PsycINFO, and MEDLINE Complete for original studies published in English involving adults diagnosed with schizophrenia spectrum disorders. Twenty-one studies published between 1992 and 2025 met the inclusion criteria. We extracted relevant data including study information and design, sample characteristics, ISL task type and characteristics, and main outcomes. Study quality was assessed using the Newcastle–Ottawa Assessment Scale. Findings were heterogeneous, with studies reporting both intact and impaired ISL. The most frequently reported outcome with the largest aggregate patient sample showed that ISL was preserved in comparison to healthy controls. Seven studies reported ISL deficits, and the rest reported mixed or condition-specific findings. The most promising moderators included task and stimulus type. Disorganized symptomatology and working memory span consistently correlated with ISL performance. In contrast, antipsychotic dosage, overall symptomatology, illness duration, or explicit memory did not show consistent associations with ISL.
Source: PsyArXiv (OSF Preprints)
Language: English
Subfield: Psychiatry and Mental health
Field: Medicine
Domain: Health Sciences
Open Access status: green
OpenAlex ID: W7225611338
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