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Dimensional analysis of depressive, anxious and somatic symptoms presented by primary care patients and their relationship with ICD-11 PHC proposed diagnoses

Published online by Cambridge University Press:  04 June 2018

Carolina Ziebold
Affiliation:
Universidade Federal de São Paulo, São Paulo, Brazil
David P. Goldberg
Affiliation:
Institute of Psychiatry, King's College London, London, UK
Geoffrey M. Reed
Affiliation:
World Health Organization, Geneva, Switzerland Global Mental Health Program, Columbia University Medical Center, New York, NY, USA
Fareed Minhas
Affiliation:
Institute of Psychiatry, Rawalpindi, Pakistan
Bushra Razzaque
Affiliation:
Institute of Psychiatry, Rawalpindi, Pakistan
Sandra Fortes
Affiliation:
Rio de Janeiro State University, Rio de Janeiro, Brazil
Rebeca Robles
Affiliation:
National Institute of Psychiatry Ramón de la Fuente Muñiz, Mexico, DF, Mexico
Tai Pong Lam
Affiliation:
University of Hong Kong, Hong Kong, People's Republic of China
Julio Bobes
Affiliation:
University of Oviedo, CIBERSAM, Asturias, Spain
Celso Iglesias
Affiliation:
University of Oviedo, CIBERSAM, Asturias, Spain Hospital Valle del Nalon, Langreo, Spain
Hugo Cogo-Moreira
Affiliation:
Universidade Federal de São Paulo, São Paulo, Brazil
José Ángel García
Affiliation:
National Institute of Psychiatry Ramón de la Fuente Muñiz, Mexico, DF, Mexico
Jair J. Mari*
Affiliation:
Universidade Federal de São Paulo, São Paulo, Brazil
*
Author for correspondence: Jair J. Mari, E-mail: jamari17@gmail.com
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Abstract

Background

A study conducted as part of the development of the Eleventh International Classification of Mental Disorders for Primary Health Care (ICD-11 PHC) provided an opportunity to test the relationships among depressive, anxious and somatic symptoms in PHC.

Method

Primary care physicians participating in the ICD-11 PHC field studies in five countries selected patients who presented with somatic symptoms not explained by known physical pathology by applying a 29-item screening on somatic complaints that were under study for bodily stress disorder. Patients were interviewed using the Clinical Interview Schedule-Revised and assessed using two five-item scales that measure depressive and anxious symptoms. Structural models of anxious-depressive symptoms and somatic complaints were tested using a bi-factor approach.

Results

A total of 797 patients completed the study procedures. Two bi-factor models fit the data well: Model 1 had all symptoms loaded on a general factor, along with one of three specific depression, anxiety and somatic factors [x2 (627) = 741.016, p < 0.0011, RMSEA = 0.015, CFI = 0.911, TLI = 0.9]. Model 2 had a general factor and two specific anxious depression and somatic factors [x2 (627) = 663.065, p = 0.1543, RMSEA = 0.008, CFI = 0.954, TLI = 0.948].

Conclusions

These data along with those of previous studies suggest that depressive, anxious and somatic symptoms are largely different presentations of a common latent phenomenon. This study provides support for the ICD-11 PHC conceptualization of mood disturbance, especially anxious depression, as central among patients who present multiple somatic symptoms.

Information

Type
Original Articles
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - SA
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike licence (http://creativecommons.org/licenses/by-nc-sa/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the same Creative Commons licence is included and the original work is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use.
Copyright
Copyright © Cambridge University Press 2018
Figure 0

Fig. 1. Diagrams representing the bi-factor models structure underlying the depressive, anxiety and somatic symptoms in PHC patients.

Figure 1

Table 1. Rates, general and specific factors loadings of each symptom and reliability indices of the models.