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Wang Q, Sui A, Gong L, Chattun MR, Han R, Cao Q, Shen D, Zhang Y, Zhao P. Personality traits influence the effectiveness of hypomania checklist-32 in screening for bipolar disorder. Front Psychiatry 2022; 13:919305. [PMID: 35911250 PMCID: PMC9337268 DOI: 10.3389/fpsyt.2022.919305] [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: 04/13/2022] [Accepted: 06/24/2022] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND It is clinically challenging to distinguish bipolar disorder (BD) from major depressive disorder (MDD) in the early stages. While the hypomania checklist-32 (HCL-32) is a proper auxiliary tool that is useful to differentiate between BD and MDD, there is currently no standard cut-off value. The variations in HCL-32 cut-off values could potentially be influenced by personality traits. Therefore, the aim of this study is to explore the effect of personality traits on the screening performance of HCL-32. METHODS In this retrospective cross-sectional study, 168 patients with BD or MDD were evaluated with the Eysenck Personality Questionnaire (EPQ) and HCL-32. The associations between demographic data, diagnosis and clinical rating scales were analyzed. RESULTS Diagnosis was not associated with extraversion but was related to neuroticism. HCL-32 scores in typical extraverted patients were higher in contrast to atypical extraverted patients. The best cut-off value for BD recognition of typical and atypical extraversion groups were 15 and 12.5, respectively. In patients with MDD, HCL-32 score of typical neuroticism was higher than the atypical type, but there was no difference in patients with BD. In typical neuroticism, there was no difference in HCL-32 scores between patients with MDD and BD. But among atypical neurotic patients, HCL-32 scores of BD were higher compared to MDD, with a cut-off value of 14.5. LIMITATIONS This study had a small sample size. CONCLUSION HCL-32 scores were affected by personality traits, with higher scores for typical extraversion and neuroticism. Clinicians should also consider the patients' personality traits when referring to HCL-32 scores, so as to increase the recognition rate of BD and eliminate false positives.
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Affiliation(s)
- Qiang Wang
- Department of Medical Psychology, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, China
| | - Aiping Sui
- Jinling Institute of Technology, Nanjing, China
| | - Lin Gong
- Department of Psychology, The Air Force Hospital from Eastern Theater of People's Liberation Army (PLA), Nanjing, China
| | - Mohammad Ridwan Chattun
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Ruichen Han
- Nanjing Drum Tower Hospital, Clinical College of Jiangsu University, Nanjing, China
| | - Qiuyun Cao
- Department of Medical Psychology, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, China
| | - Diwen Shen
- Department of Medical Psychology, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, China
| | - Yuzhe Zhang
- Department of Medical Psychology, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, China
| | - Peng Zhao
- Department of Medical Psychology, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, China
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Hypomanic symptoms in early pregnancy: prevalence and associated factors. Arch Womens Ment Health 2021; 24:463-471. [PMID: 33094351 DOI: 10.1007/s00737-020-01078-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/16/2020] [Accepted: 10/12/2020] [Indexed: 10/23/2022]
Abstract
Given that the perinatal period is a time of increased risk for pregnant women to manifest mental health problems, the identification of antenatal hypomanic symptoms is particularly important. However, data on antenatal hypomanic symptoms is lacking. The present study was aimed at filling this research gap by investigating the prevalence of hypomanic symptoms, including the "active-elated" and "irritable/risk-taking" sides of hypomanic symptoms at the first trimester, and examining their associations with anxiety and depressive symptoms at the following time points: the first trimester, the second trimester, and up to 6-week postpartum. A prospective longitudinal design with a quantitative approach was adopted. A consecutive sample of 229 pregnant Chinese women in Hong Kong was assessed. Hypomanic symptoms were assessed with the Hypomania Checklist-32 (HCL-32). Of the sample, 43.6% had elevated levels of hypomanic symptoms in the first trimester. Multiple regression analysis showed that after adjusting for potential confounding factors, irritable/risk-taking symptoms were independently associated with higher anxiety symptoms in the first and second trimesters and in the 6-week postpartum period. Primary healthcare practitioners should be made aware of antenatal hypomanic symptoms in pregnant women to facilitate early identification and intervention for anxiety and depression to improve the well-being of both mothers and infants.
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Sultan P, Ando K, Sultan E, Hawkins J, Blake L, Barwick F, Kawai M, Carvalho B. A systematic review of patient-reported outcome measures used to assess sleep in postpartum women using Consensus Based Standards for the Selection of Health Measurement Instruments (COSMIN) guidelines. Sleep 2021; 44:6278483. [PMID: 34013345 DOI: 10.1093/sleep/zsab128] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2021] [Revised: 04/02/2021] [Indexed: 12/12/2022] Open
Abstract
STUDY OBJECTIVES We performed a systematic review to identify the best patient-reported outcome measure (PROM) of postpartum sleep in women. METHODS We searched 4 databases for validated PROMs used to assess postpartum sleep. Studies were considered if they evaluated at least 1 psychometric measurement property of a PROM. An overall rating was assigned for each psychometric measurement property of each PROM based upon COSMIN criteria. A modified GRADE approach was used to assess the level of evidence and recommendations were then made for each PROM. RESULTS We identified 15 validation studies of 8 PROMs, in 9,070 postpartum women. An adequate number of sleep domains was assessed by 5 PROMs: Bergen Insomnia Scale (BIS), Pittsburgh Sleep Quality Index (PSQI), General Sleep Disturbance Scale (GSDS), Athens Insomnia Scale (AIS) and the Sleep Symptom Checklist (SSC). BIS and GSDS were the only PROMs to demonstrate adequate content validity and at least a low level of evidence of sufficient internal consistency, resulting in Class A recommendations. The BIS was the only PROM, which is easily accessible and free to use for non-commercial research, that achieved a Class A recommendation. CONCLUSION The BIS is the best currently available PROM of postpartum sleep. However, this PROM fails to assess several important domains such as sleep duration (and efficiency), chronotype, sleep-disordered breathing and medication usage. Future studies should focus on evaluating the psychometric measurement properties of BIS in the North American setting and in different cultural groups, or to develop a more specific PROM of postpartum sleep.
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Affiliation(s)
- P Sultan
- Associate Professor. Department of Anesthesiology, Perioperative and Pain Medicine. Stanford University School of Medicine, Stanford, CA, USA
| | - K Ando
- Assistant Professor. Department of Anesthesiology, Perioperative and Pain Medicine. Stanford University School of Medicine, Stanford, CA, USA
| | - E Sultan
- Clinical Instructor. Department of Anesthesiology, Perioperative and Pain Medicine. Stanford University School of Medicine, Stanford, CA, USA
| | - J Hawkins
- Medical Student. Stanford University School of Medicine, Stanford, CA, USA
| | - L Blake
- Associate Professor. UAMS Medical Library, UAMS, Little Rock, AR, USA SCIENC ES
| | - F Barwick
- Clinical Associate Professor, Division of Sleep Medicine, Department of Psychiatry and Behavioral Sciences, Stanford University, School of Medicine
| | - M Kawai
- Clinical Associate Professor, Division of Sleep Medicine, Department of Psychiatry and Behavioral Sciences, Stanford University, School of Medicine
| | - B Carvalho
- Professor. Department of Anesthesiology, Perioperative and Pain Medicine. Stanford University School of Medicine, Stanford, CA, USA
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Zhang L, Li YH, Bu YG, Yang FF, Chen YH, Liao PP, Mu TY, Zhang CL. Evaluation of the clinical application of the Postpartum Depression Predictors Inventory-Revised for postpartum women in China. Jpn J Nurs Sci 2021; 18:e12405. [PMID: 34002484 DOI: 10.1111/jjns.12405] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2020] [Revised: 11/05/2020] [Accepted: 12/10/2020] [Indexed: 11/29/2022]
Abstract
AIM This study was designed to assess the clinical applicability of the Postpartum Depression Predictors Inventory-Revised (PDPI-R) during the 1st month following delivery among women in China and to survey the prevalence of postpartum depression (PPD)-related risk factors included in the PDPI-R in this population. METHODS This was a cross-sectional study which recruited 447 women from the People's Liberation Army Hospital in Hefei of Anhui province. All participants completed the Chinese version of the PDPI-R (PDPI-R-C) and the Chinese version of the Edinburgh Postnatal Depression Scale (C-EPDS) within 1 month of delivery. The predictive ability of the PDPI-R was then evaluated through receiver operating characteristic (ROC) curve analyses. RESULTS The PDPI-R-C was able to accurately predict 73.2% of PPD cases (area under the ROC curve = 0.732; 95% CI 0.69-0.78) using a cut-off score of 5.5, as defined by a C-EPDS score of ≥10 (sensitivity = 62.8%; specificity = 73.5%; positive predictive value = 74.5%; negative predictive value = 61.5%). All 13 risk factors in the PDPI-R-C other than socioeconomic status and marital status were associated with the risk of PPD. CONCLUSIONS The PDPI-R-C was found to be an effective and easy-to-implement tool that has promise as a means of screening for PPD in Chinese populations.
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Affiliation(s)
- Liu Zhang
- School of Nursing, Anhui Medical University, Hefei, China
| | - Yu-Hong Li
- School of Nursing, Anhui Medical University, Hefei, China
| | - Yang-Gao Bu
- Department of Obstetrics and Gynecology, The 901 Hospital of Chinese People's Liberation Army Joint Service Support Unit, Hefei, China
| | - Fang-Fang Yang
- Department of Obstetrics and Gynecology, The 901 Hospital of Chinese People's Liberation Army Joint Service Support Unit, Hefei, China
| | - Yue-Hua Chen
- Department of Obstetrics and Gynecology, The 901 Hospital of Chinese People's Liberation Army Joint Service Support Unit, Hefei, China
| | - Pei-Pei Liao
- School of Nursing, Anhui Medical University, Hefei, China
| | - Ting-Yu Mu
- School of Nursing, Anhui Medical University, Hefei, China
| | - Cheng-Lu Zhang
- School of Nursing, Anhui Medical University, Hefei, China
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Duan Z, Wang Y, Jiang P, Wilson A, Guo Y, Lv Y, Yang X, Yu R, Wang S, Wu Z, Xia M, Wang G, Tao Y, Xiaohong L, Ma L, Shen H, Sun J, Deng W, Yang Y, Chen R. Postpartum depression in mothers and fathers: a structural equation model. BMC Pregnancy Childbirth 2020; 20:537. [PMID: 32933502 PMCID: PMC7493423 DOI: 10.1186/s12884-020-03228-9] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2019] [Accepted: 09/01/2020] [Indexed: 02/08/2023] Open
Abstract
BACKGROUND Post-partum depression (PPD) is a growing mental health concern worldwide. There is little evidence in the Chinese context of the relationship between paternal PPD and maternal PPD. Given the growing global concerns this relationship requires further exploration. METHODS A survey was conducted with 950 total couples from March 2017 to December 2018. The study was conducted using a standardized questionnaire that included basic demographic information, information on the relationship between the mother-in-law and daughter-in-law, marital satisfaction (both maternal and paternal), and PPD symptoms. Structural Equation Modelling (SEM) analysis was used to explore the underlying mechanism for PPD symptoms in mothers and fathers. RESULTS In 4.4% of the couples both the wife and the husband showed depressive symptoms. Maternal marital satisfaction showed a significant mediating effect on paternal PPD (B = -0.114, p < 0.01), and there was a direct effect of maternal PPD on paternal PPD (B = 0.31, p < 0.001). CONCLUSIONS This is the first study to investigate the possible correlation between maternal PPD, mother-in-law and daughter-in-law relationship satisfaction, maternal marital satisfaction, paternal marital satisfaction, and paternal PPD. It is important for future PPD interventions to target both maternal and paternal mental health, as well as the mechanisms identified that can lead to PPD.
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Affiliation(s)
- Zhizhou Duan
- Institute of Mental Health, Suzhou Guangji Hospital, Affiliated Guangji Hospital of Soochow University, Soochow University, No. 11 Guangqian Road, Jiangsu Province, 215137, Suzhou, PR China
- School of Health Sciences, Wuhan university, 430072, Wuhan, Hubei Province, China
| | - Yuanyuan Wang
- National Clinical Research Center for Mental Disorders, Department of Psychiatry, and China National Technology Institute on Mental Disorders, The Second Xiangya Hospital of Central South University, 410011, Changsha, Hunan, China
- Division of Psychology, Faculty of Health and Life Sciences, De Montfort University, Leicester, UK
| | - Ping Jiang
- Institute of Mental Health, Suzhou Guangji Hospital, Affiliated Guangji Hospital of Soochow University, Soochow University, No. 11 Guangqian Road, Jiangsu Province, 215137, Suzhou, PR China
| | - Amanda Wilson
- Division of Psychology, Faculty of Health and Life Sciences, De Montfort University, Leicester, UK
| | - Yan Guo
- Institute of Mental Health, Suzhou Guangji Hospital, Affiliated Guangji Hospital of Soochow University, Soochow University, No. 11 Guangqian Road, Jiangsu Province, 215137, Suzhou, PR China
| | - Yongliang Lv
- Institute of Mental Health, Suzhou Guangji Hospital, Affiliated Guangji Hospital of Soochow University, Soochow University, No. 11 Guangqian Road, Jiangsu Province, 215137, Suzhou, PR China
| | - Xiaonan Yang
- Institute of Mental Health, Suzhou Guangji Hospital, Affiliated Guangji Hospital of Soochow University, Soochow University, No. 11 Guangqian Road, Jiangsu Province, 215137, Suzhou, PR China
| | - Renjie Yu
- Institute of Mental Health, Suzhou Guangji Hospital, Affiliated Guangji Hospital of Soochow University, Soochow University, No. 11 Guangqian Road, Jiangsu Province, 215137, Suzhou, PR China
| | - Shuilan Wang
- Institute of Mental Health, Suzhou Guangji Hospital, Affiliated Guangji Hospital of Soochow University, Soochow University, No. 11 Guangqian Road, Jiangsu Province, 215137, Suzhou, PR China
| | - Zhengyan Wu
- Institute of Mental Health, Suzhou Guangji Hospital, Affiliated Guangji Hospital of Soochow University, Soochow University, No. 11 Guangqian Road, Jiangsu Province, 215137, Suzhou, PR China
| | - Mengqing Xia
- Institute of Mental Health, Suzhou Guangji Hospital, Affiliated Guangji Hospital of Soochow University, Soochow University, No. 11 Guangqian Road, Jiangsu Province, 215137, Suzhou, PR China
| | - Guosheng Wang
- Institute of Mental Health, Suzhou Guangji Hospital, Affiliated Guangji Hospital of Soochow University, Soochow University, No. 11 Guangqian Road, Jiangsu Province, 215137, Suzhou, PR China
| | - Ye Tao
- Suzhou science & technology town hospital, Suzhou, China
| | - L Xiaohong
- Institute of Mental Health, Suzhou Guangji Hospital, Affiliated Guangji Hospital of Soochow University, Soochow University, No. 11 Guangqian Road, Jiangsu Province, 215137, Suzhou, PR China
| | - Ling Ma
- Suzhou science & technology town hospital, Suzhou, China
| | - Hong Shen
- Suzhou science & technology town hospital, Suzhou, China
| | - Jue Sun
- Gusu District Wumenqiao Street Canglang Xincheng Community Health Service Center, Suzhou, China
| | - Wei Deng
- Mental Health Center, West China Hospital of Sichuan University, Chengdu, PR China
| | - Yong Yang
- Institute of Mental Health, Suzhou Guangji Hospital, Affiliated Guangji Hospital of Soochow University, Soochow University, No. 11 Guangqian Road, Jiangsu Province, 215137, Suzhou, PR China.
| | - Runsen Chen
- National Clinical Research Center for Mental Disorders, Department of Psychiatry, and China National Technology Institute on Mental Disorders, The Second Xiangya Hospital of Central South University, 410011, Changsha, Hunan, China
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Sharma V, Sharma P, Sharma S. Managing bipolar disorder during pregnancy and the postpartum period: a critical review of current practice. Expert Rev Neurother 2020; 20:373-383. [PMID: 32172610 DOI: 10.1080/14737175.2020.1743684] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
Abstract
Introduction: Despite increased interest in the pharmacotherapy of bipolar disorder during pregnancy and the postpartum period, management of the disorder during these critical periods in a woman's life remains challenging.Areas covered: The authors review the effect of pregnancy and the postpartum period on the course of bipolar disorder, describe adverse pregnancy and birth outcomes, and discuss the pharmacotherapy of bipolar disorder during and after pregnancy.Expert opinion: When treating women with bipolar disorder of childbearing age, clinicians should consider the possibility of pregnancy. Pre-conception counseling should be an integral part of the overall plan to manage bipolar disorder during and after pregnancy. Peripartum management of bipolar disorder is challenging and requires balancing of risks associated with the use of drugs and the potentially deleterious effects of untreated bipolar disorder on the fetus/child. Formulation of personalized treatment requires knowledge of both current (episode type, symptom severity, psychiatric comorbidity, and safety concerns) and historical (episode frequency, response to drugs and psychotherapy, and the effect of reproductive events including pregnancy and postpartum period) factors. Close monitoring is essential for early detection and management of mood episodes. Routine safety assessments are necessary to identify women at risk of harming themselves or the newborn.
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Affiliation(s)
- Verinder Sharma
- Departments of Psychiatry and Obstetrics & Gynecology, University of Western Ontario, London, Canada.,Parkwood Institute Mental Health, London, Canada
| | - Priya Sharma
- Department of Psychiatry, Schulich School of Medicine and Dentistry, London, Canada
| | - Sapna Sharma
- Department of Obstetrics & Gynecology, McMaster University, Hamilton, Canada
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Lu L, Duan Z, Wang Y, Wilson A, Yang Y, Zhu L, Guo Y, Lv Y, Yang X, Yu R, Wang S, Wu Z, Jiang P, Xia M, Wang G, Wang X, Tao Y, Li X, Ma L, Huang L, Dong Q, Shen H, Sun J, Li S, Deng W, Chen R. Mental health outcomes among Chinese prenatal and postpartum women after the implementation of universal two-child policy. J Affect Disord 2020; 264:187-192. [PMID: 32056749 DOI: 10.1016/j.jad.2019.12.011] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/16/2019] [Revised: 11/26/2019] [Accepted: 12/05/2019] [Indexed: 02/05/2023]
Abstract
BACKGROUND Poor mental health status among both pregnant and postpartum women is commonly reported worldwide. The associations between mental health outcomes and giving birth to the second child since the implementation of China's universal two-child policy have not been identified. METHODS A large-scale based mental health survey was conducted between March 2017 and December 2018 in Suzhou, China. The survey evaluated the symptoms of anxiety, hypomania, depression and poor sleep quality among both pregnant and postpartum women. RESULTS A total of 3113 questionnaires were collected, the prevalence of anxiety, hypomanic and depressive symptoms and poor sleep quality in our sample were 3.2% (95%CI: 2.6%-3.9%), 51.7% (95%CI: 49.9%-53.4%), 12.4% (95%CI: 11.3%-13.6%) and 37.8% (95%CI: 36.0%-39.5%), respectively. Logistic regression showed that giving birth to the second child was positively associated with women's age, and was negatively correlated with higher educational level and living in rented housing. Women with the second pregnancy or child were positively associated with anxiety symptoms in the whole sample (OR = 1.75, 95%CI: 1.11-2.75) and among prenatal women (OR = 2.11, 95%CI: 1.16-3.83), while it was inversely correlated with depressive symptoms among postpartum women (OR = 0.63, 95%CI: 0.41-0.99). CONCLUSIONS Women giving birth a second time were more prone to have anxiety symptoms among the prenatal women and the whole sample, and less likely to have depressive symptoms among the postpartum women. Efficacious measures and interventions are essential to improve maternal mental health.
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Affiliation(s)
- Li Lu
- Suzhou Guangji Hospital, Affiliated Guangji Hospital of Soochow University, Soochow University, Suzhou, China; Team IETO, Bordeaux Population Health Research Center, UMR U1219, INSERM, Université de Bordeaux, Bordeaux, France
| | - Zhizhou Duan
- The National Clinical Research Center for Mental Disorders, Beijing Key Laboratory of Mental Disorders & Advanced Innovation Center for Human Brain Protection, Beijing Anding Hospital, Capital Medical University, Beijing, China; School of Health Sciences, Wuhan University, Wuhan, Hubei, China
| | - Yuanyuan Wang
- Division of Psychology, Faculty of Health and Life Sciences, De Montfort University, Leicester, UK
| | - Amanda Wilson
- Division of Psychology, Faculty of Health and Life Sciences, De Montfort University, Leicester, UK
| | - Yong Yang
- Suzhou Guangji Hospital, Affiliated Guangji Hospital of Soochow University, Soochow University, Suzhou, China.
| | - Longjun Zhu
- Suzhou Guangji Hospital, Affiliated Guangji Hospital of Soochow University, Soochow University, Suzhou, China
| | - Yan Guo
- Suzhou Guangji Hospital, Affiliated Guangji Hospital of Soochow University, Soochow University, Suzhou, China
| | - Yonglang Lv
- Suzhou Guangji Hospital, Affiliated Guangji Hospital of Soochow University, Soochow University, Suzhou, China
| | - Xiaonan Yang
- Suzhou Guangji Hospital, Affiliated Guangji Hospital of Soochow University, Soochow University, Suzhou, China
| | - Renjie Yu
- Suzhou Guangji Hospital, Affiliated Guangji Hospital of Soochow University, Soochow University, Suzhou, China
| | - Shuilan Wang
- Suzhou Guangji Hospital, Affiliated Guangji Hospital of Soochow University, Soochow University, Suzhou, China
| | - Zhengyan Wu
- Suzhou Guangji Hospital, Affiliated Guangji Hospital of Soochow University, Soochow University, Suzhou, China
| | - Ping Jiang
- Suzhou Guangji Hospital, Affiliated Guangji Hospital of Soochow University, Soochow University, Suzhou, China
| | - Mengqing Xia
- Suzhou Guangji Hospital, Affiliated Guangji Hospital of Soochow University, Soochow University, Suzhou, China
| | - Guosheng Wang
- Suzhou Guangji Hospital, Affiliated Guangji Hospital of Soochow University, Soochow University, Suzhou, China
| | - Xiuxia Wang
- Suzhou Guangji Hospital, Affiliated Guangji Hospital of Soochow University, Soochow University, Suzhou, China
| | - Ye Tao
- Suzhou Science and Technology Town Hospital, Suzhou, China
| | - Xiaohong Li
- Suzhou Science and Technology Town Hospital, Suzhou, China
| | - Ling Ma
- Suzhou Science and Technology Town Hospital, Suzhou, China
| | - Liming Huang
- Suzhou Science and Technology Town Hospital, Suzhou, China
| | - Qin Dong
- Suzhou Science and Technology Town Hospital, Suzhou, China
| | - Hong Shen
- Suzhou Science and Technology Town Hospital, Suzhou, China
| | - Jue Sun
- Gusu District Wumenqiao Street Canglang Xincheng Community Health Service Center, Suzhou, China
| | - Shun Li
- Gusu District Wumenqiao Street Canglang Xincheng Community Health Service Center, Suzhou, China
| | - Wei Deng
- Mental Health Center, West China Hospital of Sichuan University, Chengdu, China
| | - Runsen Chen
- The National Clinical Research Center for Mental Disorders, Beijing Key Laboratory of Mental Disorders & Advanced Innovation Center for Human Brain Protection, Beijing Anding Hospital, Capital Medical University, Beijing, China; Department of Psychiatry, University of Oxford, Oxford, UK.
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