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Rezaei F, Rahmani K, Hemmati A, Komasi S. A head-to-head comparison of eight unique personality systems in predicting somatization phenomenon. BMC Psychiatry 2023; 23:912. [PMID: 38053166 PMCID: PMC10698954 DOI: 10.1186/s12888-023-05424-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/22/2023] [Accepted: 11/30/2023] [Indexed: 12/07/2023] Open
Abstract
BACKGROUND If somatization is an independent personality trait, it is not clear whether it is specific to the temperament or maladaptive spectrum of personality. We aimed at the head-to-head comparison of temperament and maladaptive systems and spectra of personality to predict both somatization and somatic symptom and related disorders (SSRD). METHODS The samples included 257 cases with SSRD (70.8% female) and 1007 non-SSRD (64.3% female) from Western Iran. The Personality Inventory for DSM-5 (PID-5), Personality Diagnostic Questionnaire-4 (PDQ-4), Temperament and Character Inventory (TCI), Temperament Evaluation of Memphis, Pisa, Paris, and San Diego-Autoquestionnaire (TEMPS-A), Affective and Emotional Composite Temperament Scale (AFECTS), and Positive Affect and Negative Affect Model (PANAS) was used to data collection. A somatization factor plus temperament and maladaptive spectra of personality were extracted using exploratory factor analysis. Several hierarchical linear and logistic regressions were used to test the predictive systems and spectra. RESULTS All personality systems jointly predict both somatization and SSRD with a slightly higher contribution for temperament systems. When the temperament and maladaptive spectra were compared, both spectra above each other significantly predicted both somatization (R2 = .407 versus .263) and SSRD (R2 = .280 versus .211). The temperament spectrum explained more variance beyond the maladaptive spectrum when predicting both the somatization factor (change in R2 = .156 versus .012) and SSRD (change in R2 = .079 versus .010). CONCLUSION All temperament and maladaptive frameworks of personality are complementary to predicting both somatization and SSRD. However, the somatization is more related to the temperament than the maladaptive spectrum of personality.
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Affiliation(s)
- Farzin Rezaei
- Department of Psychiatry, Roozbeh Hospital, Tehran University of Medical Sciences, Tehran, Iran
| | - Khaled Rahmani
- Liver and Digestive Research Center, Research Institute for Health Development, Kurdistan University of Medical Sciences, Sanandaj, Iran.
| | - Azad Hemmati
- Department of Psychology, University of Kurdistan, Sanandaj, Iran
| | - Saeid Komasi
- Neurosciences Research Center, Research Institute for Health Development, Kurdistan University of Medical Sciences, Sanandaj, Iran.
- Department of Neuroscience and Psychopathology Research, Mind GPS Institute, Kermanshah, Iran.
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Dong L, Liang HB, Du J, Wang Y, Zhou Q, Xin Z, Hu Y, Liu YS, Zhao R, Qiao Y, Zhou C, Liu JR, Du X. Microstructural Differences of the Cerebellum-Thalamus-Basal Ganglia-Limbic Cortex in Patients with Somatic Symptom Disorders: a Diffusion Kurtosis Imaging Study. CEREBELLUM (LONDON, ENGLAND) 2023; 22:840-851. [PMID: 35986875 DOI: 10.1007/s12311-022-01461-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 08/14/2022] [Indexed: 06/15/2023]
Abstract
Somatic symp tom disorders (SSDs) are a group of psychiatric disorders characterized by persistent disproportionate concern and obsessive behaviors regarding physical conditions. Currently, SSDs lack effective treatments and their pathophysiology is unclear. In this paper, we aimed to examine microstructural abnormalities in the brains of patients with SSD using diffusion kurtosis imaging (DKI) and to investigate the correlation between these abnormalities and clinical indicators. Diffusion kurtosis images were acquired from 30 patients with SSD and 30 healthy controls (HCs). Whole-brain maps of multiple diffusion measures, including fractional anisotropy (FA), axial diffusivity (AD), radial diffusivity (RD), mean diffusivity (MD), mean kurtosis (MK), radial kurtosis (RK), and axial kurtosis (AK), were calculated. To analyze differences between the two groups, nonparametric permutation testing with 10,000 randomized permutations and threshold-free cluster enhancement was used with family-wise error-corrected p values < 0.05 as the threshold for statistical significance. Then, the correlations between significant changes in these diffusion measures and clinical factors were examined. Compared to HCs, patients with SSD had significantly higher FA, MK, and RK and significantly lower MD and RD in the cerebellum, thalamus, basal ganglia, and limbic cortex. The FA in the left caudate and the pontine crossing tract were negatively correlated with disease duration; the MD and the RD in the genu of the corpus callosum were positively correlated with disease duration. Our findings highlight the role of the cerebellum-thalamus-basal ganglia-limbic cortex pathway, especially the cerebellum, in SSDs and enhance our understanding of the pathogenesis of SSDs.
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Affiliation(s)
- Liao Dong
- Department of Psychology, Shanghai University of Sport, Shanghai, 200438, China
- Shanghai Key Laboratory of Magnetic Resonance and Department of Physics, School of Physics and Electronic Science, East China Normal University, Shanghai, 200062, China
| | - Huai-Bin Liang
- Department of Neurology &Jiuyuan Municipal Stroke Center, Shanghai 9Th People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200011, China
- Clinical Research Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200011, China
| | - Jiaxin Du
- Centre for Advanced Imaging, The University of Queensland, St Lucia, QLD, 4072, Australia
| | - Yingying Wang
- Department of Psychology, Shanghai University of Sport, Shanghai, 200438, China
| | - Qichen Zhou
- Department of Psychology, Shanghai University of Sport, Shanghai, 200438, China
| | - Ziyue Xin
- Department of Psychology, Shanghai University of Sport, Shanghai, 200438, China
| | - Yue Hu
- Department of Neurology &Jiuyuan Municipal Stroke Center, Shanghai 9Th People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200011, China
- Clinical Research Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200011, China
| | - Yi-Sheng Liu
- Department of Neurology &Jiuyuan Municipal Stroke Center, Shanghai 9Th People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200011, China
| | - Rong Zhao
- Department of Neurology &Jiuyuan Municipal Stroke Center, Shanghai 9Th People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200011, China
- Clinical Research Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200011, China
| | - Yuan Qiao
- Department of Neurology &Jiuyuan Municipal Stroke Center, Shanghai 9Th People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200011, China
- Clinical Research Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200011, China
| | - Chenglin Zhou
- Department of Psychology, Shanghai University of Sport, Shanghai, 200438, China
| | - Jian-Ren Liu
- Department of Neurology &Jiuyuan Municipal Stroke Center, Shanghai 9Th People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200011, China.
- Clinical Research Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200011, China.
| | - Xiaoxia Du
- Department of Psychology, Shanghai University of Sport, Shanghai, 200438, China.
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