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F119. MULTILEVEL ANALYSIS IMPROVES THE MODEL FIT OF THE DIMENSIONAL STRUCTURE OF THE PANSS IN PATIENTS WITH SCHIZOPHRENIA

BACKGROUND: Principal component analyses (PCA) studies show that schizophrenia symptoms are usually grouped into five domains. However, to infer a latent dimensional structure, confirmatory factor analysis (CFA) is more appropriate than PCA. Most CFA studies addressing the five-factor model yielded...

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Autores principales: Higuchi, Cinthia, Cogo-Moreira, Hugo, Bertolucci, Bruno, Correll, Christoph U, Noto, Cristiano, Cordeiro, Quirino, Freitas, Rosana, Elkis, Hélio, Belangero, Sintia I, Bressan, Rodrigo A, Gadelha, Ary
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5888240/
http://dx.doi.org/10.1093/schbul/sby017.650
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author Higuchi, Cinthia
Cogo-Moreira, Hugo
Bertolucci, Bruno
Correll, Christoph U
Noto, Cristiano
Cordeiro, Quirino
Freitas, Rosana
Elkis, Hélio
Belangero, Sintia I
Bressan, Rodrigo A
Gadelha, Ary
author_facet Higuchi, Cinthia
Cogo-Moreira, Hugo
Bertolucci, Bruno
Correll, Christoph U
Noto, Cristiano
Cordeiro, Quirino
Freitas, Rosana
Elkis, Hélio
Belangero, Sintia I
Bressan, Rodrigo A
Gadelha, Ary
author_sort Higuchi, Cinthia
collection PubMed
description BACKGROUND: Principal component analyses (PCA) studies show that schizophrenia symptoms are usually grouped into five domains. However, to infer a latent dimensional structure, confirmatory factor analysis (CFA) is more appropriate than PCA. Most CFA studies addressing the five-factor model yielded poor fit indices. One single study achieved a good fit using a multilevel CFA structure with the interviewers as level. Other possible reasons for sample heterogeneity and subsequent poor model adjustments, such as differences in patients’ clinical profiles across clinical units and clinical staging, were not measured in this study. We aimed to replicate the effect of the CFA multilevel analyses and evaluate the possible influence of other heterogeneity sources as levels, i.e., clinical staging, on the Positive and Negative Syndrome Scale (PANSS) five-factor structure. METHODS: 700 patients with schizophrenia at four different centers had their PANSS analyzed. A Confirmatory Factor Analysis (CFA) was conducted using the following fit index: Comparative Fit Index (CFI) and Non-Normed Fit Index (NNFI) >0.95, the Root Mean Square Errors of Approximation (RMSEA) <0.06, and Weighted Root Mean Square Residual (WRMR) <1.0. Thereafter, we performed multilevel analyses considering the following levels: i) centers, ii) interviewers and iii) clinical staging for schizophrenia (first episode, treatment-resistant schizophrenia and non-treatment resistant schizophrenia). RESULTS: The mean (SD) age was 34.9 (10.3) years, mean age of onset was 21.7 (7.5), mean duration of illness means was 13.2 (9.7) years, and 64.3% of the sample was male. The CFA model without multilevel analyses yielded poor fit indices: RMSEA = 0.102 (90% CI: 0.097 – 0.107; Cfit was <0.001), CFI = 0.921 and NNFI = 0.906 and WRMR = 1.952. When the multilevel analysis was applied, all models reached an acceptable fit: i) centers: RMSEA = 0.044 (90% CI: 0.038 – 0.049; CFit = 0.964), CFI = 0.981, NNFI = 0.977, and WRMR = 1.860; ii) interviewers: RMSEA = 0.047 (90% CI: 0.041 – 0.053; CFit = 0.765), CFI = 0.947, NNFI = 0.938, and WRMR = 1.531; iii) clinical stage: RMSEA = 0.052 (90% CI: 0.046 – 0.058; CFit = 0.274), CFI = 0.988, NNFI = 0.985, and WRMR = 2.433. DISCUSSION: Good CFA model fits were only achieved when the multilevel structure was applied. Besides the bias generated by data collection (i.e., local of data collection and raters), the clinical staging is a potential source of variability to consider in schizophrenia dimensional structure. As dimensional approaches gain relevance to reduce heterogeneity in schizophrenia and to investigate their biological substrates, reliable methods to address latent dimensions are required.
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spelling pubmed-58882402018-04-11 F119. MULTILEVEL ANALYSIS IMPROVES THE MODEL FIT OF THE DIMENSIONAL STRUCTURE OF THE PANSS IN PATIENTS WITH SCHIZOPHRENIA Higuchi, Cinthia Cogo-Moreira, Hugo Bertolucci, Bruno Correll, Christoph U Noto, Cristiano Cordeiro, Quirino Freitas, Rosana Elkis, Hélio Belangero, Sintia I Bressan, Rodrigo A Gadelha, Ary Schizophr Bull Abstracts BACKGROUND: Principal component analyses (PCA) studies show that schizophrenia symptoms are usually grouped into five domains. However, to infer a latent dimensional structure, confirmatory factor analysis (CFA) is more appropriate than PCA. Most CFA studies addressing the five-factor model yielded poor fit indices. One single study achieved a good fit using a multilevel CFA structure with the interviewers as level. Other possible reasons for sample heterogeneity and subsequent poor model adjustments, such as differences in patients’ clinical profiles across clinical units and clinical staging, were not measured in this study. We aimed to replicate the effect of the CFA multilevel analyses and evaluate the possible influence of other heterogeneity sources as levels, i.e., clinical staging, on the Positive and Negative Syndrome Scale (PANSS) five-factor structure. METHODS: 700 patients with schizophrenia at four different centers had their PANSS analyzed. A Confirmatory Factor Analysis (CFA) was conducted using the following fit index: Comparative Fit Index (CFI) and Non-Normed Fit Index (NNFI) >0.95, the Root Mean Square Errors of Approximation (RMSEA) <0.06, and Weighted Root Mean Square Residual (WRMR) <1.0. Thereafter, we performed multilevel analyses considering the following levels: i) centers, ii) interviewers and iii) clinical staging for schizophrenia (first episode, treatment-resistant schizophrenia and non-treatment resistant schizophrenia). RESULTS: The mean (SD) age was 34.9 (10.3) years, mean age of onset was 21.7 (7.5), mean duration of illness means was 13.2 (9.7) years, and 64.3% of the sample was male. The CFA model without multilevel analyses yielded poor fit indices: RMSEA = 0.102 (90% CI: 0.097 – 0.107; Cfit was <0.001), CFI = 0.921 and NNFI = 0.906 and WRMR = 1.952. When the multilevel analysis was applied, all models reached an acceptable fit: i) centers: RMSEA = 0.044 (90% CI: 0.038 – 0.049; CFit = 0.964), CFI = 0.981, NNFI = 0.977, and WRMR = 1.860; ii) interviewers: RMSEA = 0.047 (90% CI: 0.041 – 0.053; CFit = 0.765), CFI = 0.947, NNFI = 0.938, and WRMR = 1.531; iii) clinical stage: RMSEA = 0.052 (90% CI: 0.046 – 0.058; CFit = 0.274), CFI = 0.988, NNFI = 0.985, and WRMR = 2.433. DISCUSSION: Good CFA model fits were only achieved when the multilevel structure was applied. Besides the bias generated by data collection (i.e., local of data collection and raters), the clinical staging is a potential source of variability to consider in schizophrenia dimensional structure. As dimensional approaches gain relevance to reduce heterogeneity in schizophrenia and to investigate their biological substrates, reliable methods to address latent dimensions are required. Oxford University Press 2018-04 2018-04-01 /pmc/articles/PMC5888240/ http://dx.doi.org/10.1093/schbul/sby017.650 Text en © Maryland Psychiatric Research Center 2018. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Abstracts
Higuchi, Cinthia
Cogo-Moreira, Hugo
Bertolucci, Bruno
Correll, Christoph U
Noto, Cristiano
Cordeiro, Quirino
Freitas, Rosana
Elkis, Hélio
Belangero, Sintia I
Bressan, Rodrigo A
Gadelha, Ary
F119. MULTILEVEL ANALYSIS IMPROVES THE MODEL FIT OF THE DIMENSIONAL STRUCTURE OF THE PANSS IN PATIENTS WITH SCHIZOPHRENIA
title F119. MULTILEVEL ANALYSIS IMPROVES THE MODEL FIT OF THE DIMENSIONAL STRUCTURE OF THE PANSS IN PATIENTS WITH SCHIZOPHRENIA
title_full F119. MULTILEVEL ANALYSIS IMPROVES THE MODEL FIT OF THE DIMENSIONAL STRUCTURE OF THE PANSS IN PATIENTS WITH SCHIZOPHRENIA
title_fullStr F119. MULTILEVEL ANALYSIS IMPROVES THE MODEL FIT OF THE DIMENSIONAL STRUCTURE OF THE PANSS IN PATIENTS WITH SCHIZOPHRENIA
title_full_unstemmed F119. MULTILEVEL ANALYSIS IMPROVES THE MODEL FIT OF THE DIMENSIONAL STRUCTURE OF THE PANSS IN PATIENTS WITH SCHIZOPHRENIA
title_short F119. MULTILEVEL ANALYSIS IMPROVES THE MODEL FIT OF THE DIMENSIONAL STRUCTURE OF THE PANSS IN PATIENTS WITH SCHIZOPHRENIA
title_sort f119. multilevel analysis improves the model fit of the dimensional structure of the panss in patients with schizophrenia
topic Abstracts
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5888240/
http://dx.doi.org/10.1093/schbul/sby017.650
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