Frontiers in psychology · 2026
AI-powered cognitive remediation for schizophrenia: a psychologist's lens on evidence and scalability in India.
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Gehlot Drishti, Musale Sheetal
Аннотация
BACKGROUND: Schizophrenia spectrum disorders (SSDs) are marked by cognitive deficits, functional impairment, and notable treatment gap in India, with lifetime prevalence of 1.41%, current prevalence as 0.42%, and the gap of 72%, added by a severe workforce gap, that is, 0.75 psychiatrists per 100,000 and 0.29 clinical psychologists per 100,000. Scalable tools are required by the psychologists that can fill the substantial urban-rural gap.
AIM: To evaluate how effective, feasible, and clinically applicable AI-powered cognitive remediation is, emphasizing India/LMIC contexts.
METHODS: PRISMA-guided umbrella review with narrative synthesis of records published between 2020-2026, identified 48 studies (14 randomized controlled trials (RCTs), 22 reviews, 8 pilots, and 4 bibliometric studies) across PubMed, Scopus, Web of Science. Cognition, functioning, and feasibility, retention, and usability were included as outcome measures.
RESULTS: AI-based AI-powered cognitive remediation showed generally favorable effects. Reported effect sizes ranged from moderate to large across different interventions and outcomes. VR-based social-cognition training showed largest benefits and smartphone-based programs showed promise for working memory and engagement. Hybrid or monitored formats showed generally better retention and usability than fully self-directed interventions. However, the evidence remained heterogeneous, and many findings came from small studies, feasibility work, or reviews of mixed quality.
CONCLUSION: AI-powered CRT appears to be a promising model for schizophrenia rehabilitation when delivered through psychologist-monitored hybrid models. Such approaches may improve access, support rural and semi-rural service delivery, and help reduce the treatment gap through scalable, culturally adaptable, and technology-enabled care, especially in rural India.
AIM: To evaluate how effective, feasible, and clinically applicable AI-powered cognitive remediation is, emphasizing India/LMIC contexts.
METHODS: PRISMA-guided umbrella review with narrative synthesis of records published between 2020-2026, identified 48 studies (14 randomized controlled trials (RCTs), 22 reviews, 8 pilots, and 4 bibliometric studies) across PubMed, Scopus, Web of Science. Cognition, functioning, and feasibility, retention, and usability were included as outcome measures.
RESULTS: AI-based AI-powered cognitive remediation showed generally favorable effects. Reported effect sizes ranged from moderate to large across different interventions and outcomes. VR-based social-cognition training showed largest benefits and smartphone-based programs showed promise for working memory and engagement. Hybrid or monitored formats showed generally better retention and usability than fully self-directed interventions. However, the evidence remained heterogeneous, and many findings came from small studies, feasibility work, or reviews of mixed quality.
CONCLUSION: AI-powered CRT appears to be a promising model for schizophrenia rehabilitation when delivered through psychologist-monitored hybrid models. Such approaches may improve access, support rural and semi-rural service delivery, and help reduce the treatment gap through scalable, culturally adaptable, and technology-enabled care, especially in rural India.