RESEARCH ARTICLE
The Factor Structure of the Mood Disorder Questionnaire in Tunisian Patients
Uta Ouali1, 2, *, Lamia Jouini3, Yosra Zgueb1, 2, Rabaa Jomli1, 2, Adel Omrani4, Fethi Nacef1, 2, Antonio Preti5, Mauro Giovanni Carta5
Article Information
Identifiers and Pagination:
Year: 2020Volume: 16
Issue: Suppl-1, M3
First Page: 82
Last Page: 92
Publisher ID: CPEMH-16-82
DOI: 10.2174/1745017902016010082
Article History:
Received Date: 18/02/2019Revision Received Date: 02/05/2019
Acceptance Date: 08/05/2019
Electronic publication date: 30/07/2020
Collection year: 2020
open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: (https://creativecommons.org/licenses/by/4.0/legalcode). This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Abstract
Background:
The Mood Disorder Questionnaire (MDQ) is a frequently used screening tool for the early detection of Bipolar Disorder (BD), which is often unrecognized or misdiagnosed at its onset. In this study, data from Tunisia has been used to evaluate the psychometric properties of the Arabic MDQ.
Methods:
The sample included 151 patients with a current major depressive episode. The Arabic adapted version of the Structured Clinical Interview for DSM-IV-TR was used to formulate a diagnosis, yielding 62 patients with BD and 89 with unipolar Major Depressive Disorder (MDD). Principal component analysis with parallel analysis was used to establish the spontaneous distribution of the 13 core items of the MDQ. Confirmatory Factor Analysis (CFA) was used to check the available factor models. Receiver Operating Characteristic (ROC) analysis was used to assess the capacity of the MDQ to distinguish patients with BD from those with MDD.
Results:
Cronbach’s α in the sample was 0.80 (95%CI: 0.75 to 0.85). Ordinal α was 0.88. Parallel analysis suggested two main components, which explained 59% of variance in the data. CFA found a good fit for the existing unidimensional, the two-factor, and the three-factor models. ROC analysis showed that at a threshold of 7, the MDQ was able to distinguish patients with BD from those with MDD with extraordinary negative predictive value (0.92) and a positive diagnostic likelihood ratio of 3.8.
Conclusion:
The Arabic version of the MDQ showed good measurement properties in terms of reliability, factorial validity and discriminative properties.
