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Insight differences between deficit and non-deficit schizophrenia: a systematic review and meta-analysis
Lucía Colmenero-Capote1, Álvaro López-Díaz2, Claudia Parás3
1Department of Psychiatry, School of Medicine, University of Seville, Seville, Spain.
Background:
Patients with deficit schizophrenia (DS) have been reported to have lower levels of insight than those with non-deficit schizophrenia (NDS). However, such an association remains poorly understood. This study aimed to systematically review and meta-analyse differences in insight between DS and NDS.
Methods:
A PRISMA-compliant systematic review and meta-analysis was conducted of studies published in PubMed, Scopus, and Web of Science up to January 2025. Eligible studies examined insight differences between DS and NDS. Any insight measure was considered. DS was categorised using validated methods. Risk of bias and the certainty of evidence were assessed using the JBI tools and GRADE. A narrative synthesis and a standardised mean difference (SMD) meta-analysis of available outcome data was conducted. The protocol was registered in Open Science Framework (https://osf.io/3D5PG).
Results:
Nine studies (N = 895 patients; n = 239 DS) were included. Narrative synthesis evidenced greater deficits in insight in the DS group, which was associated with the "expressive deficit" domain of negative symptoms and mediated by cognitive dysfunction and metacognitive impairments in "self-reflectiveness". Six studies contributed to the quantitative synthesis. The random-effects meta-analysis revealed a statistically significant poorer insight in DS vs. NDS (SMD = 0.99, 95 %CI:0.39-1.61, p = 0.009; I2 = 82.1 %).
Conclusions:
DS patients exhibit significantly poorer insight than NDS, which was linked to primary enduring negative symptoms and cognitive dysfunction, particularly metacognitive impairments in self-reflection. Rehabilitative interventions targeting these dysfunctions may improve insight and outcomes. Limitations of this study were heterogeneity of insight instruments, few meta-analysable datasets, and low-certainty evidence according to the GRADE assessment.
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