Objectives: Melancholic features of depression (MFD) seem to be a unidimensional group of signs and symptoms. However, little importance has been given to the evaluation of what features are related to a more severe disorder. That is, what are the MFD that appear only in the most depressed patients. We aim to demonstrate how each MFD is related to the severity of the major depressive disorder.
Methods: We evaluated both the Hamilton depression rating scale (HDRS-17) and its 6-item melancholic subscale (HAM-D6) in 291 depressed inpatients using Rasch analysis, which computes the severity of each MFD. Overall measures of model fit were mean (±SD) of items and persons residual = 0 (±1); low χ2 value; p>0.01.
Results: For the HDRS-17 model fit, mean (±SD) of item residuals = 0.35 (±1.4); mean (±SD) of person residuals = -0.15 (±1.09); χ2 = 309.74; p<0.00001. For the HAM-D6 model fit, mean (±SD) of item residuals = 0.5 (±0.86); mean (±SD) of person residuals = 0.15 (±0.91); χ2 = 56.13; p = 0.196. MFD ordered by crescent severity were depressed mood, work and activities, somatic symptoms, psychic anxiety, guilt feelings, and psychomotor retardation.
Conclusions: Depressed mood is less severe, while guilt feelings and psychomotor retardation are more severe MFD in a psychiatric hospitalization. Understanding depression as a continuum of symptoms can improve the understanding of the disorder and may improve its perspective of treatment.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5256939 | PMC |
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0170000 | PLOS |
J Clin Psychol
January 2025
Department of Clinical Psychology and Psychobiology, The Institute of Neurosciences, Universitat de Barcelona, Barcelona, Spain.
Based on the repertory grid technique, we developed Explore Your Meanings (EYME), a digital platform that helps patients explore identity values and internal conflicts using virtual reality (VR). EYME was part of a research project treating depression in young adults, including 10 weekly, 1-h sessions aimed at changing personal constructs-cognitive schemas that shape how individuals interpret reality. We present the case of Mary, a 21-year-old woman diagnosed with persistent major depressive disorder and social phobia.
View Article and Find Full Text PDFNeuroradiology
January 2025
Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China.
Introduction: Bipolar disorder (BD) and major depressive disorder (MDD) have overlapping clinical presentations which may make it difficult for clinicians to distinguish them potentially resulting in misdiagnosis. This study combined structural MRI and machine learning techniques to determine whether regional morphological differences could distinguish patients with BD and MDD.
Methods: A total of 123 participants, including BD (n = 31), MDD (n = 48), and healthy controls (HC, n = 44), underwent high-resolution 3D T1-weighted imaging.
Nord J Psychiatry
January 2025
Mental Health Services, Psychiatry East, Copenhagen University Hospital, Region Zealand, Denmark.
Purpose: To describe the prevalence of self-reported depression in a socioeconomically deprived area in Denmark and the association to socioeconomic position (SEP) defined by education, occupation, and being in financial strain.
Method: 13,955 adults completing the Major Depression Inventory (MDI) in the Lolland-Falster Health Study questionnaire were included.Multivariate logistic regression on symptoms of depression based on MDI sum score and ICD-10 scores, associated to education, occupation, and financial strain - unadjusted and adjusted for sex and age group.
BMC Psychiatry
January 2025
Department of Neurology, Shenzhen People's Hospital (The Second Clinical Medical College, Jinan University; The First Affiliated Hospital, Southern University of Science and Technology), Shenzhen, Guangdong, China.
Background: The neurasthenia-depression controversy has lasted for several decades. It is challenging to solve the argument by symptoms alone for syndrome-based disease classification. Our aim was to identify objective electroencephalography (EEG) measures that can differentiate neurasthenia from major depressive disorder (MDD).
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!