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An attempt to construct a 7-item short version of the temperament and character inventory to predict the treatment response of patients with depression; a validation study

BACKGROUND: The Temperament and Character Inventory (TCI) is a psychological test that is frequently used to assess personality traits. Many studies have shown the potential of the inventory to predict the treatment response of patients with major depressive disorder (MDD). Previously, we showed the...

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Detalles Bibliográficos
Autores principales: Tomita, Tetsu, Yasui-Furukori, Norio, Kaneda, Ayako, Ishioka, Masamichi, Sugawara, Norio, Nakagami, Taku, Nakamura, Kazuhiko
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4983023/
https://www.ncbi.nlm.nih.gov/pubmed/27520460
http://dx.doi.org/10.1186/s12888-016-0997-0
Descripción
Sumario:BACKGROUND: The Temperament and Character Inventory (TCI) is a psychological test that is frequently used to assess personality traits. Many studies have shown the potential of the inventory to predict the treatment response of patients with major depressive disorder (MDD). Previously, we showed the association between 10 items of the TCI and the treatment response. In the present study, we reanalyzed the 10 items and aimed to provide cut-off values. METHODS: This work is a secondary analysis of previously published work. Seventy-three patients were enrolled in the previously done study. Participants were treated with 10–40 mg/day of paroxetine for six weeks, and then the participants completed the TCI. The Montgomery-Asberg Depression Rating Scale (MADRS) was used to evaluate depression. The participants were divided into two groups (responders and non-responders). Using chi-squared tests, we reanalyzed the 10 items that had the strongest association with the treatment response in the previous study. We rated the answers to each item associated with the treatment response as a “1”, and the answers associated with a non-response were rated as a “0”. We calculated predictive scores using 10 models. Each model consisted of 1–10 scores of the best 1–10 items. We defined cut-off values for predicting treatment responses using a receiver operating characteristic (ROC) curve analysis. RESULTS: Ranked by the strength of the association with the treatment response, items 174, 137, 70, 237, 106, 191, 34, 232, 161, and 215 of the TCI significantly predicted treatment responses. All predictive scores from models 1 to 10 significantly predicted treatment responses. The predictive score threshold of model 7 was 3/4, with an area under the curve of 0.825, and this model showed the highest odds and likelihood ratios (19.3 and 8.86, respectively). CONCLUSIONS: We might predict the treatment response of patients with MDD using TCI predictive scoring, including items 174, 137, 70, 237, 106, 191, and 34 and a cut-off value of 3/4. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12888-016-0997-0) contains supplementary material, which is available to authorized users.