TY - JOUR
T1 - Transdiagnostic comparisons of intellectual abilities and work outcome in patients with mental disorders
T2 - Multicentre study
AU - Sumiyoshi, Chika
AU - Ohi, Kazutaka
AU - Fujino, Haruo
AU - Yamamori, Hidenaga
AU - Fujimoto, Michiko
AU - Yasuda, Yuka
AU - Uno, Yota
AU - Takahashi, Junichi
AU - Morita, Kentaro
AU - Katsuki, Asuka
AU - Yamamoto, Maeri
AU - Okahisa, Yuko
AU - Sata, Ayumi
AU - Katsumoto, Eiichi
AU - Koeda, Michihiko
AU - Hirano, Yoji
AU - Nakataki, Masahito
AU - Matsumoto, Junya
AU - Miura, Kenichiro
AU - Hashimoto, Naoki
AU - Makinodan, Manabu
AU - Takahashi, Tsutomu
AU - Nemoto, Kiyotaka
AU - Kishimoto, Toshifumi
AU - Suzuki, Michio
AU - Sumiyoshi, Tomiki
AU - Hashimoto, Ryota
N1 - Publisher Copyright:
Copyright © The Author(s), 2022. Published by Cambridge University Press on behalf of the Royal College of Psychiatrists.
PY - 2022/7/3
Y1 - 2022/7/3
N2 - Background Cognitive impairment is common in people with mental disorders, leading to transdiagnostic classification based on cognitive characteristics. However, few studies have used this approach for intellectual abilities and functional outcomes. Aims The present study aimed to classify people with mental disorders based on intellectual abilities and functional outcomes in a data-driven manner. Method Seven hundred and forty-nine patients diagnosed with schizophrenia, bipolar disorder, major depression disorder or autism spectrum disorder and 1030 healthy control subjects were recruited from facilities in various regions of Japan. Two independent k-means cluster analyses were performed. First, intelligence variables (current estimated IQ, premorbid IQ, and IQ discrepancy) were included. Second, number of work hours per week was included instead of premorbid IQ. Results Four clusters were identified in the two analyses. These clusters were specifically characterised in terms of IQ discrepancy in the first cluster analysis, whereas the work variable was the most salient feature in the second cluster analysis. Distributions of clinical diagnoses in the two cluster analyses showed that all diagnoses were unevenly represented across the clusters. Conclusions Intellectual abilities and work outcomes are effective classifiers in transdiagnostic approaches. The results of our study also suggest the importance of diagnosis-specific strategies to support functional recovery in people with mental disorders.
AB - Background Cognitive impairment is common in people with mental disorders, leading to transdiagnostic classification based on cognitive characteristics. However, few studies have used this approach for intellectual abilities and functional outcomes. Aims The present study aimed to classify people with mental disorders based on intellectual abilities and functional outcomes in a data-driven manner. Method Seven hundred and forty-nine patients diagnosed with schizophrenia, bipolar disorder, major depression disorder or autism spectrum disorder and 1030 healthy control subjects were recruited from facilities in various regions of Japan. Two independent k-means cluster analyses were performed. First, intelligence variables (current estimated IQ, premorbid IQ, and IQ discrepancy) were included. Second, number of work hours per week was included instead of premorbid IQ. Results Four clusters were identified in the two analyses. These clusters were specifically characterised in terms of IQ discrepancy in the first cluster analysis, whereas the work variable was the most salient feature in the second cluster analysis. Distributions of clinical diagnoses in the two cluster analyses showed that all diagnoses were unevenly represented across the clusters. Conclusions Intellectual abilities and work outcomes are effective classifiers in transdiagnostic approaches. The results of our study also suggest the importance of diagnosis-specific strategies to support functional recovery in people with mental disorders.
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U2 - 10.1192/bjo.2022.50
DO - 10.1192/bjo.2022.50
M3 - Article
AN - SCOPUS:85131553868
SN - 2056-4724
VL - 8
JO - BJPsych Open
JF - BJPsych Open
IS - 4
M1 - e98
ER -