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Jang OJ, Lee H, Choi KY, Lee JH, Kim E, Jeong N, Il Ryu J, Park SC. How the network structures of depressive symptoms are differently estimated across the levels of depression severity?: Findings from the Korea National Health & Nutrition Examination Survey. Asian J Psychiatr 2024; 93:103909. [PMID: 38241805 DOI: 10.1016/j.ajp.2024.103909] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/24/2023] [Accepted: 12/31/2023] [Indexed: 01/21/2024]
Affiliation(s)
- Ok-Jin Jang
- Department of Psychiatry, Haeundae Paik Hospital, Inje University College of Medicine, Busan, the Republic of Korea
| | - Hyangjn Lee
- Hanyang University Medical Center, Seoul, the Republic of Korea
| | - Kwang-Yeon Choi
- Department of Psychiatry, College of Medicine, Chungnam National University, Daejeon, the Republic of Korea
| | - Jae-Hon Lee
- Department of Psychiatry, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
| | - Eunkyung Kim
- Department of Premedicine, Hanyang University College of Medicine, Seoul, the Republic of Korea; Department of Psychiatry, Hanyang University Guri Hospital, Guri, the Republic of Korea
| | - Narae Jeong
- Department of Clinical Psychology, Yong-In Mental Hospital, Yongin, the Republic of Korea
| | - Je Il Ryu
- Department of Neurosurgery, Hanyang University College of Medicine, Seoul, the Republic of Korea; Department of Neurosurgery, Hanyang University Guri Hospital, Guri, the Republic of Korea.
| | - Seon-Cheol Park
- Department of Psychiatry, Hanyang University College of Medicine, Seoul, the Republic of Korea; Department of Psychiatry, Hanyang University Guri Hospital, Guri, the Republic of Korea.
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Iida H, Okada T, Nemoto K, Hasegawa N, Numata S, Ogasawara K, Miura K, Matsumoto J, Hori H, Iga J, Ichihashi K, Hashimoto N, Yamada H, Ohi K, Yasui‐Furukori N, Fukumoto K, Tsuboi T, Usami M, Furihata R, Takaesu Y, Hishimoto A, Muraoka H, Katsumoto E, Nagasawa T, Ochi S, Komatsu H, Kikuchi S, Takeshima M, Onitsuka T, Tamai S, Kubota C, Inada K, Watanabe K, Kawasaki H, Hashimoto R. Satisfaction with web-based courses on clinical practice guidelines for psychiatrists: Findings from the "Effectiveness of Guidelines for Dissemination and Education in Psychiatric Treatment (EGUIDE)" project. Neuropsychopharmacol Rep 2023; 43:23-32. [PMID: 36444167 PMCID: PMC10009432 DOI: 10.1002/npr2.12300] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Revised: 10/27/2022] [Accepted: 11/01/2022] [Indexed: 12/03/2022] Open
Abstract
To disseminate, educate, and validate psychiatric clinical practice guidelines, the Effectiveness of Guidelines for Dissemination and Education in Psychiatric Treatment (EGUIDE) project was launched in 2016. In this study, we investigated whether the web-based courses offered by this project would be as effective as the face-to-face courses. We analyzed and compared survey answers about overall participant satisfaction with the course and answers regarding clinical knowledge of schizophrenia and major depressive disorder between 170 participants who took the web-based courses in 2020 and 689 participants who took the face-to-face courses from 2016 to 2019. The web-based course participants completed the survey questions about satisfaction with the web-based courses. The web-based courses were conducted using a combination of web services to make it as similar as possible to the face-to-face courses. The degree of satisfaction assessed by the general evaluation of the web-based courses was higher than what was expected from the face-to-face courses. The degree of satisfaction was similar for the courses on schizophrenia and major depressive disorder. In addition, there were no significant differences in overall satisfaction and clinical knowledge between web-based and face-to-face courses. In conclusion, the web-based courses on clinical practice guidelines provided by the EGUIDE project were rated as more satisfying than the face-to-face course that the participants expected to take and no differences in the effectiveness of either course. The results suggest that, after the COVID-19 pandemic, it would be possible to disseminate this educational material more widely by adopting web-based courses additionally face-to-face courses.
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Affiliation(s)
- Hitoshi Iida
- Department of Psychiatry, Faculty of MedicineFukuoka UniversityFukuokaJapan
| | - Tsuyoshi Okada
- Department of PsychiatryJichi Medical UniversityTochigiJapan
| | - Kiyotaka Nemoto
- Department of Psychiatry, Faculty of MedicineUniversity of TsukubaIbarakiJapan
| | - Naomi Hasegawa
- Department of Pathology of Mental Diseases, National Center of Neurology and PsychiatryNational Institute of Mental HealthTokyoJapan
| | - Shusuke Numata
- Department of PsychiatryGraduate School of Biomedical Science, Tokushima UniversityTokushimaJapan
| | - Kazuyoshi Ogasawara
- Center for Postgraduate Clinical Training and Career DevelopmentNagoya University HospitalNagoyaJapan
| | - Kenichiro Miura
- Department of Pathology of Mental Diseases, National Center of Neurology and PsychiatryNational Institute of Mental HealthTokyoJapan
| | - Junya Matsumoto
- Department of Pathology of Mental Diseases, National Center of Neurology and PsychiatryNational Institute of Mental HealthTokyoJapan
| | - Hikaru Hori
- Department of Psychiatry, Faculty of MedicineFukuoka UniversityFukuokaJapan
| | - Jun‐ichi Iga
- Department of Neuropsychiatry, Molecules and FunctionEhime University Graduate School of MedicineMatsuyamaEhimeJapan
| | - Kayo Ichihashi
- Department of NeuropsychiatryUniversity of Tokyo HospitalTokyoJapan
| | - Naoki Hashimoto
- Department of PsychiatryHokkaido University Graduate School of MedicineSapporoJapan
| | - Hisashi Yamada
- Department of Pathology of Mental Diseases, National Center of Neurology and PsychiatryNational Institute of Mental HealthTokyoJapan
- Department of NeuropsychiatryHyogo College of MedicineNishinomiyaHyogoJapan
| | - Kazutaka Ohi
- Department of PsychiatryGifu University Graduate School of MedicineGifuJapan
| | - Norio Yasui‐Furukori
- Department of PsychiatryDokkyo Medical University School of MedicineTochigiJapan
| | - Kentaro Fukumoto
- Department of NeuropsychiatryIwate Medical University School of MedicineIwateJapan
| | - Takashi Tsuboi
- Department of NeuropsychiatryKyorin University School of MedicineTokyoJapan
| | - Masahide Usami
- Department of Child and Adolescent Psychiatry, National Center for Global Health and MedicineKohnodai HospitalChibaJapan
| | | | - Yoshikazu Takaesu
- Department of NeuropsychiatryGraduate School of Medicine, University of the RyukyusOkinawaJapan
| | - Akitoyo Hishimoto
- Department of PsychiatryYokohama City University Graduate School of MedicineYokohamaKanagawaJapan
| | - Hiroyuki Muraoka
- Department of PsychiatryKitasato University School of MedicineSagamiharaKanagawaJapan
| | | | - Tatsuya Nagasawa
- Department of NeuroPsychiatryKanazawa Medical UniversityUchinadaIshikawaJapan
| | - Shinichiro Ochi
- Department of Neuropsychiatry, Molecules and FunctionEhime University Graduate School of MedicineMatsuyamaEhimeJapan
| | - Hiroshi Komatsu
- Department of PsychiatryTohoku University HospitalSendaiMiyagiJapan
| | - Saya Kikuchi
- Department of PsychiatryTohoku University HospitalSendaiMiyagiJapan
| | - Masahiro Takeshima
- Department of NeuropsychiatryAkita University Graduate School of MedicineAkitaJapan
| | - Toshiaki Onitsuka
- Department of Neuroimaging PsychiatryGraduate School of Medical Sciences, Kyushu UniversityFukuokaJapan
| | - Shinichiro Tamai
- Department of NeuropsychiatryTokyo Metropolitan Tama Medical CenterTokyoJapan
| | - Chika Kubota
- National Center of Neurology and PsychiatryTokyoJapan
| | - Ken Inada
- Department of PsychiatryKitasato University School of MedicineSagamiharaKanagawaJapan
| | - Koichiro Watanabe
- Department of NeuropsychiatryKyorin University School of MedicineTokyoJapan
| | - Hiroaki Kawasaki
- Department of Psychiatry, Faculty of MedicineFukuoka UniversityFukuokaJapan
| | - Ryota Hashimoto
- Department of Pathology of Mental Diseases, National Center of Neurology and PsychiatryNational Institute of Mental HealthTokyoJapan
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Park SC. Commentary: How Can We Detect and Manage COVID-19 Worry and Related Factors? ALPHA PSYCHIATRY 2022; 23:284-285. [PMID: 36628384 PMCID: PMC9797723 DOI: 10.5152/alphapsychiatry.2022.09112022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Affiliation(s)
- Seon-Cheol Park
- Department of Psychiatry, Hanyang University College of Medicine, Seoul, Republic of Korea,Department of Psychiatry, Hanyang University Guri Hospital, Guri, Republic of Korea,Corresponding author:Seon-Cheol Park✉
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Li W, Zhang Q, Tang Y, Park SC, Park Y, Yang SY, Chen LY, Lin SK, Najoan E, Kallivayalil RA, Viboonma K, Jamaluddin R, Javed A, Thi Quynh Hoa D, Iida H, Sim K, Swe T, He YL, Ahmed HU, De Alwis A, Chiu HFK, Sartorius N, Tan CH, Chong MY, Shinfuku N, Avasthi A, Grover S, Ungvari GS, Ng CH, Xiang YT. Network analysis of psychiatric symptoms in schizophrenia: Findings from the Research on Asian Psychotropic Prescription Patterns for Antipsychotics (REAP-AP). Asian J Psychiatr 2022; 75:103200. [PMID: 35850062 DOI: 10.1016/j.ajp.2022.103200] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/06/2022] [Revised: 06/22/2022] [Accepted: 07/01/2022] [Indexed: 11/02/2022]
Abstract
AIMS Schizophrenia is a major mental disorder with a wide range of psychiatric symptoms. This study explored the structure of psychiatric symptoms of schizophrenia using network analysis in a large representative Asian sample based on a survey of clinical features and treatment used in schizophrenia patients across 15 countries/territories in Asia. METHODS Data on the demographic characteristics and psychiatric symptoms in schizophrenia patients were extracted from the dataset of the fourth Research on Asia Psychotropic Prescription for Antipsychotics (REAP-AP) project. The presence of the following psychiatric symptoms including delusions, hallucinations, disorganized speech, grossly disorganized or catatonic behavior, negative symptoms, social/occupational dysfunction, verbal aggression, physical aggression, and affective symptoms were analyzed. RESULTS A total of 3681 patients were included. The network analysis revealed that verbal aggression, hallucinations, and social/occupational dysfunction were the most central symptoms, while the connections between social/occupational dysfunction and verbal aggression, and between hallucinations and disorganized speech were the two strongest edges. There were significant gender differences in the network structure based on the network structure invariance test (M=0.74, P = 0.03) and invariant edge strength test. The positive correlation between verbal aggression and hallucinations was significantly stronger in the female network than that in the male network (P = 0.03), while a negative correlation between affective symptoms and negative symptoms was found in the female, but not the male network (P < 0.01). CONCLUSION Central symptoms including verbal aggression, hallucinations, and socio-occupational dysfunction should be addressed in developing targeted treatment strategy for schizophrenia patients.
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Affiliation(s)
- Wen Li
- Shanghai Key Laboratory of Forensic Medicine, Key Laboratory of Forensic Science, Ministry of Justice, China, Shanghai Forensic Service Platform, Academy of Forensic Science, Shanghai, China
| | - Qinge Zhang
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital & the Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Yilang Tang
- Department of Psychiatry and Behavioral Sciences, Emory University, Atlanta, GA, USA; Atlanta Veterans Affairs Medical Center, Decatur, GA, USA
| | - Seon-Cheol Park
- Department of Psychiatry, Hanyang University College of Medicine, Seoul, the Republic of Korea
| | - Yongchon Park
- Department of Psychiatry, Hanyang University, Seoul, the Republic of Korea
| | - Shu-Yu Yang
- Department of Pharmacy, Taipei City Hospital, Taipei, Taiwan
| | - Lian-Yu Chen
- Kunming Prevention and Control Center, Taipei City Hospital; Institute of Epidemiology and Preventive Medicine, National Taiwan University, Taiwan
| | - Shih-Ku Lin
- Kunming Prevention and Control Center, Taipei City Hospital; Institute of Epidemiology and Preventive Medicine, National Taiwan University, Taiwan; Department of Psychiatry, Chang Gung Memorial Hospital, Linkou, Taoyuan, Taiwan
| | | | | | | | - Ruzita Jamaluddin
- Department of Psychiatry & Mental Health, Hospital Tuanku Fauziah, Kangar, Perlis, Malaysia
| | - Afzal Javed
- Pakistan Psychiatric Research Centre, Fountain House, Lahore, Pakistan
| | | | - Hitoshi Iida
- Department of Psychiatry, Faculty of Medicine, Fukuoka University, Fukuoka, Japan
| | - Kang Sim
- Institute of Mental Health, Buangkok Green Medical Park, Singapore
| | - Thiha Swe
- Department of Mental Health, University of Medicine, Magway, Myanmar
| | - Yan-Ling He
- Department of Psychiatric Epidemiology, Shanghai Mental Health Center, Shanghai, China
| | | | | | - Helen F K Chiu
- Department of Psychiatry, Chinese University of Hong Kong, Hong Kong, China
| | - Norman Sartorius
- Association for the Improvement of Mental Health Programs, Geneva, Switzerland
| | - Chay-Hoon Tan
- Department of Pharmacology, National University of Singapore, Singapore
| | - Mian-Yoon Chong
- Department of Psychiatry, Kaohsiung Chang Gung Memorial Hospital, Kaohsiung & Chang Gung University School of Medicine, Taoyuan, Taiwan
| | - Naotaka Shinfuku
- International Center for Medical Research, Kobe University School of Medicine, Kobe, Japan
| | - Ajit Avasthi
- Department of Psychiatry, Postgraduate Institute of Medical Education and Research (PGIMER), Chandigarh, India
| | - Sandeep Grover
- Department of Psychiatry, Postgraduate Institute of Medical Education and Research (PGIMER), Chandigarh, India
| | - Gabor S Ungvari
- University of Notre Dame Australia, Fremantle, Australia; Division of Psychiatry, Medical School, University of Western Australia, Perth, Australia
| | - Chee H Ng
- Department of Psychiatry, The Melbourne Clinic and St Vincent's Hospital, University of Melbourne, Richmond, Victoria, Australia.
| | - Yu-Tao Xiang
- Unit of Psychiatry, Department of Public Health and Medicinal Administration, & Institute of Translational Medicine, Faculty of Health Sciences, University of Macau, Macao; Centre for Cognitive and Brain Sciences, University of Macau, Macao; Institute of Advanced Studies in Humanities and Social Sciences, University of Macau, Macao.
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A Machine-Learning-Algorithm-Based Prediction Model for Psychotic Symptoms in Patients with Depressive Disorder. J Pers Med 2022; 12:jpm12081218. [PMID: 35893312 PMCID: PMC9394314 DOI: 10.3390/jpm12081218] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2022] [Revised: 07/19/2022] [Accepted: 07/24/2022] [Indexed: 11/17/2022] Open
Abstract
Psychotic symptoms are rarely concurrent with the clinical manifestations of depression. Additionally, whether psychotic major depression is a subtype of major depression or a clinical syndrome distinct from non-psychotic major depression remains controversial. Using data from the Research on Asian Psychotropic Prescription Patterns for Antidepressants, we developed a machine-learning-algorithm-based prediction model for concurrent psychotic symptoms in patients with depressive disorders. The advantages of machine learning algorithms include the easy identification of trends and patterns, handling of multi-dimensional and multi-faceted data, and wide application. Among 1171 patients with depressive disorders, those with psychotic symptoms were characterized by significantly higher rates of depressed mood, loss of interest and enjoyment, reduced energy and diminished activity, reduced self-esteem and self-confidence, ideas of guilt and unworthiness, psychomotor agitation or retardation, disturbed sleep, diminished appetite, and greater proportions of moderate and severe degrees of depression compared to patients without psychotic symptoms. The area under the curve was 0.823. The overall accuracy was 0.931 (95% confidence interval: 0.897–0.956). Severe depression (degree of depression) was the most important variable in the prediction model, followed by diminished appetite, subthreshold (degree of depression), ideas or acts of self-harm or suicide, outpatient status, age, psychomotor retardation or agitation, and others. In conclusion, the machine-learning-based model predicted concurrent psychotic symptoms in patients with major depression in connection with the “severity psychosis” hypothesis.
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Yamada H, Motoyama M, Hasegawa N, Miura K, Matsumoto J, Ohi K, Yasui-Furukori N, Numata S, Takeshima M, Sugiyama N, Nagasawa T, Kubota C, Atake K, Tsuboi T, Ichihashi K, Hashimoto N, Inagaki T, Takaesu Y, Iga JI, Hori H, Onitsuka T, Komatsu H, Hishimoto A, Fukumoto K, Fujimoto M, Nakamura T, Nemoto K, Furihata R, Yamamura S, Yamagata H, Ogasawara K, Katsumoto E, Murata A, Iida H, Ochi S, Makinodan M, Kido M, Kishimoto T, Yasuda Y, Usami M, Suwa T, Inada K, Watanabe K, Hashimoto R. A dissemination and education programme to improve the clinical behaviours of psychiatrists in accordance with treatment guidelines for schizophrenia and major depressive disorders: the Effectiveness of Guidelines for Dissemination and Education in Psychiatric Treatment (EGUIDE) project. BJPsych Open 2022; 8:e83. [PMID: 35446248 PMCID: PMC9059732 DOI: 10.1192/bjo.2022.44] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/07/2021] [Revised: 02/02/2022] [Accepted: 03/04/2022] [Indexed: 12/20/2022] Open
Abstract
BACKGROUND Clinical practice guidelines for schizophrenia and major depressive disorder have been published. However, these have not had sufficient penetration in clinical settings. We developed the Effectiveness of Guidelines for Dissemination and Education in Psychiatric Treatment (EGUIDE) project as a dissemination and education programme for psychiatrists. AIMS The aim of this study is to assess the effectiveness of the EGUIDE project on the subjective clinical behaviour of psychiatrists in accordance with clinical practice guidelines before and 1 and 2 years after participation in the programmes. METHOD A total of 607 psychiatrists participated in this study during October 2016 and March 2019. They attended both 1-day educational programmes based on the clinical practice guidelines for schizophrenia and major depressive disorder, and answered web questionnaires about their clinical behaviours before and 1 and 2 years after attending the programmes. We evaluated the changes in clinical behaviours in accordance with the clinical practice guidelines between before and 2 years after the programme. RESULTS All of the scores for clinical behaviours in accordance with clinical practice guidelines were significantly improved after 1 and 2 years compared with before attending the programmes. There were no significant changes in any of the scores between 1 and 2 years after attending. CONCLUSIONS All clinical behaviours in accordance with clinical practice guidelines improved after attending the EGUIDE programme, and were maintained for at least 2 years. The EGUIDE project could contribute to improved guideline-based clinical behaviour among psychiatrists.
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Affiliation(s)
- Hisashi Yamada
- Department of Neuropsychiatry, Hyogo College of Medicine, Japan; and Department of Pathology of Mental Diseases, National Institute of Mental Health, National Center of Neurology and Psychiatry, Japan
| | - Mikuni Motoyama
- Department of Neuropsychiatry, Hyogo College of Medicine, Japan
| | - Naomi Hasegawa
- Department of Pathology of Mental Diseases, National Institute of Mental Health, National Center of Neurology and Psychiatry, Japan
| | - Kenichiro Miura
- Department of Pathology of Mental Diseases, National Institute of Mental Health, National Center of Neurology and Psychiatry, Japan
| | - Junya Matsumoto
- Department of Pathology of Mental Diseases, National Institute of Mental Health, National Center of Neurology and Psychiatry, Japan
| | - Kazutaka Ohi
- Department of Psychiatry, Gifu University Graduate School of Medicine, Japan
| | | | - Shusuke Numata
- Department of Psychiatry, Graduate School of Biomedical Science, Tokushima University, Japan
| | - Masahiro Takeshima
- Department of Neuropsychiatry Section of Neuro and Locomotor Science, Akita University Graduate School of Medicine, Japan
| | - Nobuhiro Sugiyama
- Department of Psychiatry, Shinshu University School of Medicine, Japan; and Department of Applied Occupational Therapy, Shinshu University School of Health Sciences, Japan
| | - Tatsuya Nagasawa
- Department of Neuropsychiatry, Kanazawa Medical University, Japan
| | - Chika Kubota
- Department of Pathology of Mental Diseases, National Institute of Mental Health, National Center of Neurology and Psychiatry, Japan
| | - Kiyokazu Atake
- Kyushu Health Administration Center, Nippon Telegraph and Telephone West Corporation, Japan
| | - Takashi Tsuboi
- Department of Neuropsychiatry, Kyorin University School of Medicine, Japan
| | - Kayo Ichihashi
- Department of Neuropsychiatry, University of Tokyo Hospital, Japan
| | - Naoki Hashimoto
- Department of Psychiatry, Hokkaido University Graduate School of Medicine, Japan
| | - Takahiko Inagaki
- Adolescent Mental Health Service, Biwako Hospital, Japan; and Department of Psychiatry, Shiga University of Medical Science, Japan
| | - Yoshikazu Takaesu
- Department of Neuropsychiatry, Graduate School of Medicine, University of the Ryukyus, Japan
| | - Jun-ichi Iga
- Department of Neuropsychiatry, Molecules and Function, Ehime University Graduate School of Medicine, Japan
| | - Hikaru Hori
- Department of Psychiatry, Faculty of Medicine, Fukuoka University, Japan
| | - Toshiaki Onitsuka
- Department of Neuroimaging Psychiatry, Graduate School of Medical Sciences, Kyushu University, Japan
| | | | - Akitoyo Hishimoto
- Department of Psychiatry, Yokohama City University Graduate School of Medicine, Japan
| | - Kentaro Fukumoto
- Department of Neuropsychiatry, Iwate Medical University School of Medicine, Japan
| | - Michiko Fujimoto
- Department of Pathology of Mental Diseases, National Institute of Mental Health, National Center of Neurology and Psychiatry, Japan; and Department of Psychiatry, Osaka University Graduate School of Medicine, Japan
| | | | - Kiyotaka Nemoto
- Department of Psychiatry, Faculty of Medicine, University of Tsukuba, Japan
| | | | | | - Hirotaka Yamagata
- Division of Neuropsychiatry, Department of Neuroscience, Yamaguchi University School of Medicine, Japan
| | - Kazuyoshi Ogasawara
- Center for Postgraduate Clinical Training and Career Development, Nagoya University Hospital, Japan
| | | | - Atsunobu Murata
- Department of Pathology of Mental Diseases, National Institute of Mental Health, National Center of Neurology and Psychiatry, Japan
| | - Hitoshi Iida
- Department of Psychiatry, Faculty of Medicine, Fukuoka University, Japan
| | - Shinichiro Ochi
- Department of Neuropsychiatry, Molecules and Function, Ehime University Graduate School of Medicine, Japan
| | - Manabu Makinodan
- Department of Psychiatry, Faculty of Medicine, Nara Medical University, Japan
| | - Mikio Kido
- Department of Psychiatry, Toyama City Hospital, Japan; and Department of Neuropsychiatry, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, Japan
| | - Taishiro Kishimoto
- Department of Neuropsychiatry, Keio University School of Medicine, Japan
| | - Yuka Yasuda
- Department of Pathology of Mental Diseases, National Institute of Mental Health, National Center of Neurology and Psychiatry, Japan; and Life Grow Brilliant Mental Clinic, Medical Corporation Foster, Japan
| | - Masahide Usami
- Department of Child and Adolescent Psychiatry, Kohnodai Hospital, National Center for Global Health and Medicine, Japan
| | - Taro Suwa
- Department of Psychiatry, Graduate School of Medicine, Kyoto University, Japan
| | - Ken Inada
- Department of Psychiatry, Tokyo Women's Medical University, Japan
| | - Koichiro Watanabe
- Department of Neuropsychiatry, Kyorin University School of Medicine, Japan
| | - Ryota Hashimoto
- Department of Pathology of Mental Diseases, National Institute of Mental Health, National Center of Neurology and Psychiatry, Japan
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Machine Learning-Based Definition of Symptom Clusters and Selection of Antidepressants for Depressive Syndrome. Diagnostics (Basel) 2021; 11:diagnostics11091631. [PMID: 34573974 PMCID: PMC8468112 DOI: 10.3390/diagnostics11091631] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2021] [Revised: 09/03/2021] [Accepted: 09/03/2021] [Indexed: 12/30/2022] Open
Abstract
The current polythetic and operational criteria for major depression inevitably contribute to the heterogeneity of depressive syndromes. The heterogeneity of depressive syndrome has been criticized using the concept of language game in Wittgensteinian philosophy. Moreover, “a symptom- or endophenotype-based approach, rather than a diagnosis-based approach, has been proposed” as the “next-generation treatment for mental disorders” by Thomas Insel. Understanding the heterogeneity renders promise for personalized medicine to treat cases of depressive syndrome, in terms of both defining symptom clusters and selecting antidepressants. Machine learning algorithms have emerged as a tool for personalized medicine by handling clinical big data that can be used as predictors for subtype classification and treatment outcome prediction. The large clinical cohort data from the Sequenced Treatment Alternatives to Relieve Depression (STAR*D), Combining Medications to Enhance Depression Outcome (CO-MED), and the German Research Network on Depression (GRND) have recently began to be acknowledged as useful sources for machine learning-based depression research with regard to cost effectiveness and generalizability. In addition, noninvasive biological tools such as functional and resting state magnetic resonance imaging techniques are widely combined with machine learning methods to detect intrinsic endophenotypes of depression. This review highlights recent studies that have used clinical cohort or brain imaging data and have addressed machine learning-based approaches to defining symptom clusters and selecting antidepressants. Potentially applicable suggestions to realize machine learning-based personalized medicine for depressive syndrome are also provided herein.
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Hossain R, Al-Khafaji K, Khan RA, Sarkar C, Islam MS, Dey D, Jain D, Faria F, Akbor R, Atolani O, Oliveira SMR, Siyadatpanah A, Pereira MDL, Islam MT. Quercetin and/or Ascorbic Acid Modulatory Effect on Phenobarbital-Induced Sleeping Mice Possibly through GABA A and GABA B Receptor Interaction Pathway. Pharmaceuticals (Basel) 2021; 14:ph14080721. [PMID: 34451819 PMCID: PMC8398796 DOI: 10.3390/ph14080721] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2021] [Revised: 07/22/2021] [Accepted: 07/23/2021] [Indexed: 12/28/2022] Open
Abstract
Depressive disorder is a recurrent illness that affects large numbers of the general population worldwide. In recent years, the goal of depression treatment has moved from symptomatic response to that of full remission. However, treatment-resistant depression is a major challenge in the treatment of depression or depression-related disorders. Consensus opinion, therefore, suggests that effective combined aggressive initial treatment is the most appropriate strategy. This study aimed to evaluate the effects of quercetin (QUR) and/or ascorbic acid (AA) on Phenobarbital-induced sleeping mice. QUR (50 mg/kg) and/or AA (25 mg/kg) with or without intraperitoneally pre-treated with GABA receptor agonist (diazepam: 2 mg/kg, i.p.) or antagonist (Flumazenil: 2.5 mg/kg, i.p.) to underscore the effects, as well as the possible involvement of the GABA receptor in the modulatory action of QUR and AA in sleeping mice. Additionally, an in silico study was undertaken to predict the involvement of GABA receptors in the sleep mechanism. Findings suggest that the pretreatment of QUR and AA modulated the onset and duration of action of the standard drugs in experimental animals. The acute administration of QUR and/or AA significantly (p < 0.05) reversed the DZP-mediated onset of action and slightly reversed the duration of sleep time in comparison to the vehicle (control) group. A further combination of QUR or AA with the FLU resulted in an enhancement of the onset of action while reducing the duration of action, suggesting a FLU-like effect on the test animals. In in silico studies, AA and QUR showed good to moderate binding affinities with GABAA and GABAB receptors. Both QUR and AA produced a stimulatory-like effect on mice, possibly through the GABAA and GABAB receptor interaction pathways. Further studies are necessary to verify this activity and clarify the exact mechanism of action(s) involved.
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Affiliation(s)
- Rajib Hossain
- Department of Pharmacy, Life Science Faculty, Bangabandhu Sheikh Mujibur Rahman Science and Technology University, Gopalganj 8100, Bangladesh; (R.H.); (C.S.); (M.S.I.); (F.F.); (R.A.)
| | - Khattab Al-Khafaji
- Department of Chemistry, Faculty of Arts and Sciences, Gaziantep University, 27310 Gaziantep, Turkey;
| | - Rasel Ahmed Khan
- Pharmacy Discipline, Life Science School, Khulna University, Khulna 9280, Bangladesh;
| | - Chandan Sarkar
- Department of Pharmacy, Life Science Faculty, Bangabandhu Sheikh Mujibur Rahman Science and Technology University, Gopalganj 8100, Bangladesh; (R.H.); (C.S.); (M.S.I.); (F.F.); (R.A.)
| | - Md. Shahazul Islam
- Department of Pharmacy, Life Science Faculty, Bangabandhu Sheikh Mujibur Rahman Science and Technology University, Gopalganj 8100, Bangladesh; (R.H.); (C.S.); (M.S.I.); (F.F.); (R.A.)
| | - Dipta Dey
- Department of Biochemistry and Molecular Biology, Bangabandhu Sheikh Mujibur Rahman Science and Technology University, Gopalgonj 8100, Bangladesh;
| | - Divya Jain
- Department of Bioscience and Biotechnology, Banasthali Vidyapith, Vanasthali 304022, Rajasthan, India;
| | - Farhana Faria
- Department of Pharmacy, Life Science Faculty, Bangabandhu Sheikh Mujibur Rahman Science and Technology University, Gopalganj 8100, Bangladesh; (R.H.); (C.S.); (M.S.I.); (F.F.); (R.A.)
| | - Rukaya Akbor
- Department of Pharmacy, Life Science Faculty, Bangabandhu Sheikh Mujibur Rahman Science and Technology University, Gopalganj 8100, Bangladesh; (R.H.); (C.S.); (M.S.I.); (F.F.); (R.A.)
| | - Olubunmi Atolani
- Department of Chemistry, University of Ilorin, Ilorin P.M.B. 1515, Nigeria;
| | - Sónia M. R. Oliveira
- CICECO-Aveiro Institute of Materials & Department of Medical Sciences, University of Aveiro, 3810-193 Aveiro, Portugal;
- Hunter Medical Research Institute, New Lambton, NSW 2305, Australia
| | - Abolghasem Siyadatpanah
- Ferdows School of Paramedical and Health, Birjand University of Medical Sciences, Birjand 9717853577, Iran;
| | - Maria de Lourdes Pereira
- CICECO-Aveiro Institute of Materials & Department of Medical Sciences, University of Aveiro, 3810-193 Aveiro, Portugal;
- Department of Medical Sciences, University of Aveiro, 3810-193 Aveiro, Portugal
- Correspondence: (M.d.L.P.); (M.T.I.)
| | - Muhammad Torequl Islam
- Department of Pharmacy, Life Science Faculty, Bangabandhu Sheikh Mujibur Rahman Science and Technology University, Gopalganj 8100, Bangladesh; (R.H.); (C.S.); (M.S.I.); (F.F.); (R.A.)
- Correspondence: (M.d.L.P.); (M.T.I.)
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9
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An alternative approach to future diagnostic standards for major depressive disorder. Prog Neuropsychopharmacol Biol Psychiatry 2021; 105:110133. [PMID: 33049324 DOI: 10.1016/j.pnpbp.2020.110133] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/19/2020] [Accepted: 10/06/2020] [Indexed: 12/17/2022]
Abstract
During the period extending from 1780 to 1880, the conceptualization of melancholia changed from an intellectual to a mood model. The modern view of depression, based on Kraepelinian dualism, has reflected changes in opinion on psychiatric taxonomy of individual melancholia. From the point of view of an "operational revolution," the diagnostic criteria for major depressive disorder in the Diagnostic and Statistical Manual of Mental Disorders, 3rd edition (DSM-III) were based on a neoKraepelinian approach rooted in disease essentialism. In the revision process from the DSM-IV to the DSM-5, a combined dimensional and categorial approach was used. In the DSM-5, the diagnostic criteria for major depressive disorder are polythetic and operational in approach reflecting the heterogeneity of major depressive disorder. Although 227 different symptom combinations fulfilling the diagnostic criteria for major depressive disorder can be theoretically calculated, certain symptom combinations are more prevalent than others in real clinical situations. The heterogeneity of these operational criteria for major depressive disorder have been criticized in a manner informed by the Wittgensteinian analogy of the language game. Herein, our network analysis proposes a novel perspective on the psychopathology of major depressive disorder. The novel approach suggested here may lay the foundation for a redefinition of the traditional taxonomy of depression.
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10
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Park SC, Kim Y, Kim K, Woo YS, Kim JB, Jang EY, Lee HY, Yim HW, Ham BJ, Kim JM, Park YC. Network Analysis of the Symptoms of Depressive Disorders Over the Course of Therapy: Changes in Centrality Measures. Psychiatry Investig 2021; 18:48-58. [PMID: 33460534 PMCID: PMC7897865 DOI: 10.30773/pi.2020.0367] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/06/2020] [Accepted: 12/07/2020] [Indexed: 11/27/2022] Open
Abstract
OBJECTIVE Network analysis can be used in terms of a novel psychopathological approach for depressive syndrome. We aimed to estimate the successive network structures of depressive symptoms in patients with depressive disorder using data from the Clinical Research Center for Depression study. METHODS We enrolled 1,152 South Korean adult patients with depressive disorders who were beginning treatment for first-onset or recurrent depressive episodes. We examined the network structure of the severities of the items on the Hamilton Depression Rating Scale (HAMD) at baseline and at weeks 2, 12, 25, and 52. The node strength centrality of all the HAMD items at baseline and at week 2, 12, 25, and 52 in terms of network analysis. RESULTS In the severity networks, the anxiety (psychic) item was the most centrally situated in the initial period (baseline and week 2), while loss of weight was the most centrally situated item in the later period (weeks 25 and 52). In addition, the number of strong edges (i.e., edges representing strong correlations) increased in the late period compared to the initial period. CONCLUSION Our findings support a period-specific and symptom-focused therapeutic approach that can provide complementary information to the unidimensional total HAMD score.
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Affiliation(s)
- Seon-Cheol Park
- Department of Psychiatry, Inje University Haeundae Paik Hospital, Busan, Republic of Korea
| | - Yaeseul Kim
- Department of Psychiatry, Hanyang University School of Medicine, Seoul, Republic of Korea
| | - Kiwon Kim
- Department of Psychiatry, Veteran Health Service Medical Center, Seoul, Republic of Korea
| | - Young Sup Woo
- Department of Psychiatry, The Catholic University of Korea, Yeouido St. Mary's Hospital, Seoul, Republic of Korea
| | - Jung-Bum Kim
- Department of Psychiatry, Keimyung University School of Medicine, Daegu, Republic of Korea
| | - Eun Young Jang
- Department of Counselling Psychology, Honam Unviersity College of Humanities and Social Sciences, Gwangju, Republic of Korea
| | - Hwa-Young Lee
- Department of Psychiatry, Soonchunhyang University Cheonan Hospital, Cheonan, Republic of Korea
| | - Hyeon-Woo Yim
- Department of Preventive Medicine, The Catholic University of Korea College of Medicine, Seoul, Republic of Korea
| | - Byung-Joo Ham
- Department of Psychiatry, Korea University Anam Hospital, Seoul, Republic of Korea
| | - Jae-Min Kim
- Department of Psychiatry, Chonnam National University School of Medicine, Gwangju, Republic of Korea
| | - Yong Chon Park
- Department of Neuropsychiatry, Hanyang University Guri Hospital, Guri, Republic of Korea
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11
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Wichers M, Riese H, Hodges TM, Snippe E, Bos FM. A Narrative Review of Network Studies in Depression: What Different Methodological Approaches Tell Us About Depression. Front Psychiatry 2021; 12:719490. [PMID: 34777038 PMCID: PMC8581034 DOI: 10.3389/fpsyt.2021.719490] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/02/2021] [Accepted: 09/30/2021] [Indexed: 11/13/2022] Open
Abstract
The network theory of psychopathology proposes that mental disorders arise from direct interactions between symptoms. This theory provides a promising framework to understand the development and maintenance of mental disorders such as depression. In this narrative review, we summarize the literature on network studies in the field of depression. Four methodological network approaches are distinguished: (i) studies focusing on symptoms at the macro-level vs. (ii) on momentary states at the micro-level, and (iii) studies based on cross-sectional vs. (iv) time-series (dynamic) data. Fifty-six studies were identified. We found that different methodological approaches to network theory yielded largely inconsistent findings on depression. Centrality is a notable exception: the majority of studies identified either positive affect or anhedonia as central nodes. To aid future research in this field, we outline a novel complementary network theory, the momentary affect dynamics (MAD) network theory, to understand the development of depression. Furthermore, we provide directions for future research and discuss if and how networks might be used in clinical practice. We conclude that more empirical network studies are needed to determine whether the network theory of psychopathology can indeed enhance our understanding of the underlying structure of depression and advance clinical treatment.
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Affiliation(s)
- Marieke Wichers
- University of Groningen, University Medical Center Groningen, Department of Psychiatry, Interdisciplinary Center Psychopathology and Emotion regulation, Groningen, Netherlands
| | - Harriëtte Riese
- University of Groningen, University Medical Center Groningen, Department of Psychiatry, Interdisciplinary Center Psychopathology and Emotion regulation, Groningen, Netherlands
| | - Taylor M Hodges
- University of Groningen, University Medical Center Groningen, Department of Psychiatry, Interdisciplinary Center Psychopathology and Emotion regulation, Groningen, Netherlands
| | - Evelien Snippe
- University of Groningen, University Medical Center Groningen, Department of Psychiatry, Interdisciplinary Center Psychopathology and Emotion regulation, Groningen, Netherlands
| | - Fionneke M Bos
- University of Groningen, University Medical Center Groningen, Department of Psychiatry, Interdisciplinary Center Psychopathology and Emotion regulation, Groningen, Netherlands.,University of Groningen, University Medical Center Groningen, Department of Psychiatry, Rob Giel Research Center, Groningen, Netherlands
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