Lowering costs for large-scale screening in psychosis: a systematic review and meta-analysis of performance and value of information for speech-based psychiatric evaluation

• Autor(a) principal: Argolo,Felipe
• Data de Publicação: 2020
• Outros Autores: Magnavita,Guilherme, Mota,Natalia Bezerra, Ziebold,Carolina, Mabunda,Dirceu, Pan,Pedro M., Zugman,André, Gadelha,Ary, Corcoran,Cheryl, Bressan,Rodrigo A.
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Brazilian Journal of Psychiatry (São Paulo. 1999. Online)
• Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1516-44462020000600673
• topic: Psychosis; automated speech analysis; speech analysis; verbal behavior; schizophrenia

Objective: Obstacles for computational tools in psychiatry include gathering robust evidence and keeping implementation costs reasonable. We report a systematic review of automated speech evaluation for the psychosis spectrum and analyze the value of information for a screening program in a healthcare system with a limited number of psychiatrists (Maputo, Mozambique). Methods: Original studies on speech analysis for forecasting of conversion in individuals at clinical high risk (CHR) for psychosis, diagnosis of manifested psychotic disorder, and first-episode psychosis (FEP) were included in this review. Studies addressing non-verbal components of speech (e.g., pitch, tone) were excluded. Results: Of 168 works identified, 28 original studies were included. Valuable speech features included direct measures (e.g., relative word counting) and mathematical embeddings (e.g.: word-to-vector, graphs). Accuracy estimates reported for schizophrenia diagnosis and CHR conversion ranged from 71 to 100% across studies. Studies used structured interviews, directed tasks, or prompted free speech. Directed-task protocols were faster while seemingly maintaining performance. The expected value of perfect information is USD 9.34 million. Imperfect tests would nevertheless yield high value. Conclusion: Accuracy for screening and diagnosis was high. Larger studies are needed to enhance precision of classificatory estimates. Automated analysis presents itself as a feasible, low-cost method which should be especially useful for regions in which the physician pool is insufficient to meet demand.