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Indicators to facilitate the early identification of patients with major depressive disorder in need of highly specialized care: A concept mapping study
Author(s) -
Krugten F. C. W.,
Goorden M.,
Balkom A. J. L. M.,
Spijker J.,
Brouwer W. B. F.,
Hakkaartvan Roijen L.
Publication year - 2018
Publication title -
depression and anxiety
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.634
H-Index - 129
eISSN - 1520-6394
pISSN - 1091-4269
DOI - 10.1002/da.22741
Subject(s) - psychosocial , psychology , conceptualization , comorbidity , major depressive disorder , clinical psychology , concept map , psychiatry , mood , mathematics education , artificial intelligence , computer science
Background Early identification of the subgroup of patients with major depressive disorder (MDD) in need of highly specialized care could enhance personalized intervention. This, in turn, may reduce the number of treatment steps needed to achieve and sustain an adequate treatment response. The aim of this study was to identify patient‐related indicators that could facilitate the early identification of the subgroup of patients with MDD in need of highly specialized care. Methods Initial patient indicators were derived from a systematic review. Subsequently, a structured conceptualization methodology known as concept mapping was employed to complement the initial list of indicators by clinical expertise and develop a consensus‐based conceptual framework. Subject‐matter experts were invited to participate in the subsequent steps (brainstorming, sorting, and rating) of the concept mapping process. A final concept map solution was generated using nonmetric multidimensional scaling and agglomerative hierarchical cluster analyses. Results In total, 67 subject‐matter experts participated in the concept mapping process. The final concept map revealed the following 10 major clusters of indicators: 1‐depression severity, 2‐onset and (treatment) course, 3‐comorbid personality disorder, 4‐comorbid substance use disorder, 5‐other psychiatric comorbidity, 6‐somatic comorbidity, 7‐maladaptive coping, 8‐childhood trauma, 9‐social factors, and 10‐psychosocial dysfunction. Conclusions The study findings highlight the need for a comprehensive assessment of patient indicators in determining the need for highly specialized care, and suggest that the treatment allocation of patients with MDD to highly specialized mental healthcare settings should be guided by the assessment of clinical and nonclinical patient factors.