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Zhong S, Ma C, Huang Y, Zhang T, Hou X, Tai TC, Yan J, Yu Y, Xu X, Wang Z, Xu Y, Li T, Xu G, Xu X, Wang L, Yan Y, Xiao S, Li L, Liu Z, Zhou L. Patterns, delays, and associated factors of help-seeking behaviour for lifetime mood disorders and anxiety disorders: A national representative survey. J Affect Disord 2025; 372:386-393. [PMID: 39638063 DOI: 10.1016/j.jad.2024.12.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/17/2024] [Revised: 08/29/2024] [Accepted: 12/02/2024] [Indexed: 12/07/2024]
Abstract
BACKGROUND Utilisation of health services is low and delayed among individuals with mood mental disorders and anxiety disorders, despite high disease burdens and available effective treatments. This study aims to examine patterns and delays in help-seeking and associated factors among individuals with lifetime disorder of mood disorders and/or anxiety disorders. METHODS We used data from the China Mental Health Survey (CMHS), a nationally representative multistage clustered-area probability sample study across 31 provinces. We assessed lifetime mental disorders and help-seeking behaviour using the Composite International Diagnostic Interview (CIDI). Logistic regression analyses were used to examine sociodemographic and clinical correlates of delay to seek health care. RESULTS Among 32,552 participants, we identified 3075 patients with lifetime mood and/or anxiety disorders; 486 (15.5 % [95 % CI: 13.6-17.5 %]) have sought health care. Of these, 163 (4.8 % [95 % CI: 3.7-6.3]) ever sought specialized mental health services. The delays to initial health care were 1.0 (IQR: 0-7.1), 1.9 (0-10.0), and 10.0 (1.0-22.1) years for depressive, bipolar, and anxiety disorders. Patients with comorbidities, later age of onset, and living in urban areas showed a higher propensity for help-seeking (all p < 0.05). Older cohort was associated with longer delays in seeking health care, while a later age of onset was associated with shorter delays (all p < 0.05). LIMITATIONS The cross-sectional retrospective design and self-assessment approach may add bias. CONCLUSIONS Failure and delays in help-seeking are common in China. National strategies are needed to promote health care utilisation.
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Affiliation(s)
- Shaoling Zhong
- The Affiliated Brain Hospital, Key Laboratory of Neurogenetics and Channelopathies of Guangdong Province and the Ministry of Education of China, Guangzhou Medical University, Guangzhou 510370, China
| | - Chao Ma
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health, Peking University, National Clinical Research Center for Mental Disorders, Peking University Sixth Hospital, Beijing 100191, China
| | - Yueqin Huang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health, Peking University, National Clinical Research Center for Mental Disorders, Peking University Sixth Hospital, Beijing 100191, China
| | - Tingting Zhang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health, Peking University, National Clinical Research Center for Mental Disorders, Peking University Sixth Hospital, Beijing 100191, China
| | - Xiaofei Hou
- Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, Tianjin 300222, China
| | - Tak Ching Tai
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health, Peking University, National Clinical Research Center for Mental Disorders, Peking University Sixth Hospital, Beijing 100191, China
| | - Jie Yan
- Institute of Social Science Survey, Peking University, Beijing 100871, China
| | - Yaqin Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, Changchun 130021, Jilin, China
| | - Xiufeng Xu
- Department of Psychiatry, The First Affiliated Hospital of Kunming Medical University, Kunming 650032, Yunnan, China
| | - Zhizhong Wang
- Department of Epidemiology and Statistics, School of Public Health and Management, Ningxia Medical University, Yinchuan 750004, Ningxia, China
| | - Yifeng Xu
- Shanghai Mental Health Center, School of Medicine, Shanghai Jiao Tong University, Shanghai 200030, China
| | - Tao Li
- Mental Health Centre of West China Hospital, Sichuan University, Chengdu 610041, Sichuan, China
| | - Guangming Xu
- Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, Tianjin 300222, China
| | - Xiangdong Xu
- The Fourth People's Hospital in Urumqi, Urumqi 830002, China
| | - Limin Wang
- National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China
| | - Yongping Yan
- Department of Epidemiology, Ministry of Education Key Lab of Hazard Assessment and Control in Special Operational Environment, School of Public Health, Fourth Military Medical University, Xi'an 710032, China
| | - Shuiyuan Xiao
- Department of Social Medicine and Health Management, School of Public Health, Central South University, Changsha 410078, Hunan, China
| | - Lingjiang Li
- Mental Health Institute, the Second Xiangya Hospital, Central-south University, Changsha 410011, Hunan, China
| | - Zhaorui Liu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health, Peking University, National Clinical Research Center for Mental Disorders, Peking University Sixth Hospital, Beijing 100191, China.
| | - Liang Zhou
- The Affiliated Brain Hospital, Key Laboratory of Neurogenetics and Channelopathies of Guangdong Province and the Ministry of Education of China, Guangzhou Medical University, Guangzhou 510370, China.
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Xu P, Liu Z, Xu Y, Li T, Xu G, Xu X, Wang L, Yan Y, Xiao S, Li L, Zhang T, Yan J, Yu Y, Xu X, Wang Z, Wang B, Guo W, Huang Y. The prevalence and profiles of adverse childhood experiences and their associations with adult mental health outcomes in China: a cross-sectional study. THE LANCET REGIONAL HEALTH. WESTERN PACIFIC 2024; 53:101253. [PMID: 39717023 PMCID: PMC11665606 DOI: 10.1016/j.lanwpc.2024.101253] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/20/2024] [Revised: 11/04/2024] [Accepted: 11/19/2024] [Indexed: 12/25/2024]
Abstract
Background Adverse childhood experiences (ACEs) are common and associated with mental disorders. However, the prevalence and co-occurrence of ACEs and their association with mental health outcomes among Chinese adults have not been well demonstrated. Methods China Mental Health Survey, a cross-sectional nationally representative survey consisting of 28,140 adults, was conducted from July 2013 to March 2015. Twelve ACEs and mental health outcomes, including mood disorder, anxiety disorder, substance-use disorder, and suicide were measured using the Composite International Diagnostic Interview (CIDI) 3.0 in a weighted representative subsample of 9378 respondents. Latent class analysis was used to identify the co-occurrence profiles of ACEs, and logistic regression was applied to examine the association between ACEs and mental health outcomes. Population-attributable fractions (PAFs) were calculated to quantify the attribution of ACEs to these outcomes. Findings Among the 9378 respondents, the weighted count (proportion) of females was 4642 (49.5%), with a weighted mean (SD) age of 43.0 (15.8) years. In this study, 27.1% of respondents showed at least one ACE, with multiple ACEs common (37.6%) among those affected. Neglect was the most prevalent ACE (11.3%), followed by physical abuse (9.1%). Latent class analysis identified four co-occurrence profiles: low risk of ACEs, maltreatment, caregiver's maladjustment and parental loss. The strongest association with mental health outcomes was found in the caregiver's maladjustment group (OR, 4.9; 95% CI, 3.2-7.6). Estimates of PAFs indicated that all ACEs together explained 39.4% (95% CI, 31.3%-47.4%) of observed mental health outcomes. Gender differences were noted in prevalence and associations with outcomes. Interpretation ACEs are highly prevalent and interrelated in China, attributing to over one-third of the mental disorder burden. In resource-limited settings, prioritizing the reduction of the most prevalent and impactful ACEs through education and policy can more effectively alleviate the disease burden. Funding The National Twelfth Five-Year Plan for Science and Technology Support from the Chinese Ministry of Science and Technology (grant numbers 2012BAI01B01 & 2015BAI13B00), and the National Key R&D Program of China (grant numbers 2017YFC0907800 and 2017YFC0907801).
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Affiliation(s)
- Peilin Xu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing 100091, China
| | - Zhaorui Liu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing 100091, China
| | - Yifeng Xu
- Shanghai Mental Health Center, School of Medicine, Shanghai Jiao Tong University, Shanghai 200030, China
| | - Tao Li
- Affiliated Mental Health Center & Hangzhou Seventh People’s Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang 310058, China
- Mental Health Center, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Guangming Xu
- Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, Tianjin 300222, China
| | - Xiangdong Xu
- The Fourth People's Hospital in Urumqi, Urumqi 830002, China
| | - Limin Wang
- National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China
| | - Yongping Yan
- Department of Epidemiology, The Fourth Military Medical University, Xi’an, Shaanxi 710032, China
| | - Shuiyuan Xiao
- Department of Social Medicine and Health Management, School of Public Health, Central South University, Changsha, Hunan 410078, China
| | - Lingjiang Li
- Mental Health Institute, The Second Xiangya Hospital, Central-south University, Changsha, Hunan 410011, China
| | - Tingting Zhang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing 100091, China
| | - Jie Yan
- Institute of Social Science Survey, Peking University, Beijing 100871, China
| | - Yaqin Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, Changchun, Jilin 130021, China
| | - Xiufeng Xu
- Department of Psychiatry, The First Affiliated Hospital of Kunming Medical University, Kunming, Yunnan 650032, China
| | - Zhizhong Wang
- Department of Epidemiology and Statistics, School of Public Health and Management, Ningxia Medical University, Yinchuan, Ningxia 750004, China
| | - Bo Wang
- Department of Epidemiology, The Fourth Military Medical University, Xi’an, Shaanxi 710032, China
| | - Wanjun Guo
- Affiliated Mental Health Center & Hangzhou Seventh People’s Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang 310058, China
- Mental Health Center, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Yueqin Huang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing 100091, China
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Li J, Liu Z, Li M, Huang Y, Yin H, Xu G, Li L, Zhang T, Yan J, Yu Y, Xu X, Wang Z, Xu Y, Li T, Hou X, Xu X, Wang L, Yan Y, Xiao S, Du X, Li G. Associations of adverse childhood experiences with common psychiatric disorder in later life: results from the China mental health survey. BMC Geriatr 2023; 23:706. [PMID: 37907840 PMCID: PMC10619228 DOI: 10.1186/s12877-023-04421-z] [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: 03/15/2023] [Accepted: 10/19/2023] [Indexed: 11/02/2023] Open
Abstract
BACKGROUND Associations between adverse childhood experiences (ACEs) and common psychiatric disorders among older Chinese individuals have not been well reported. The objectives of this study are to examine the prevalence of ACEs and the associations of ACEs with common psychiatric disorders among older adults in China. METHODS The study used data from the China Mental Health Survey (CMHS), a nationally representative epidemiological survey, which used computer-assisted personal interviewing (CAPI), logistic regression models were used to examine community-based adult psychiatric disorders and associated risk factors. Finally, 2,317 individuals aged 60 years or over were included in the CMHS. The national prevalence of ACEs in older adults were estimated and logistic regression were used to analyse the association between ACEs and past-year psychiatric disorders. RESULTS Prevalence of ACEs among older adults in China was 18.1%. The three most common types of ACEs were neglect (11.6%), domestic violence (9.2%), and parental loss (9.1%). This study proved the association between ACEs and common past-year psychiatric disorders in older adults. ACEs increased the risk of past-year psychiatric disorders in older adults. After adjustment for age, sex, marital status, employment status, education, rural or urban residence, region, and physical diseases, the association between ACEs and past-year psychiatric disorders were still significant. CONCLUSIONS ACEs are linked to an increased risk for past-year psychiatric disorders in older adults. ACEs may have long-term effects on older adults' mental well-being. Preventing ACEs may help reduce possible adverse health outcomes in later life.
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Affiliation(s)
- Jinhao Li
- Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, Tianjin, China
| | - Zhaorui Liu
- National Clinical Research Center for Mental Disorders & Key Laboratory of Mental Health, Institute of Mental Health), Peking University Sixth Hospital, Ministry of Health (Peking University), Beijing, China
| | - Minghui Li
- Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, Tianjin, China
| | - Yueqin Huang
- National Clinical Research Center for Mental Disorders & Key Laboratory of Mental Health, Institute of Mental Health), Peking University Sixth Hospital, Ministry of Health (Peking University), Beijing, China
| | - Huifang Yin
- Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, Tianjin, China.
| | - Guangming Xu
- Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, Tianjin, China.
| | - Lingjiang Li
- Mental Health Institute, the Second Xiangya Hospital, Central-south University, Changsha, 410011, Hunan, China
| | - Tingting Zhang
- National Clinical Research Center for Mental Disorders & Key Laboratory of Mental Health, Institute of Mental Health), Peking University Sixth Hospital, Ministry of Health (Peking University), Beijing, China
| | - Jie Yan
- Institute of Social Science Survey, Peking University, Beijing, 100871, China
| | - Yaqin Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, Changchun, China
| | - Xiufeng Xu
- Department of Psychiatry, The First Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, 650032, China
| | - Zhizhong Wang
- Department of Epidemiology and Statistics, School of Public Health and Management, Ningxia Medical University, Yinchuan, Ningxia, 750004, China
| | - Yifeng Xu
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai JiaoTong University School of Medicine, Shanghai, China
| | - Tao Li
- Mental Health Centre of West China Hospital, Sichuan University, Chengdu, 610041, Sichuan, China
- Department of Psychiatry, Hangzhou Seventh People's Hospital, Hangzhou, 310013, Zhejiang, China
| | - Xiaofei Hou
- Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, Tianjin, China
| | - Xiangdong Xu
- The Fourth People's Hospital in Urumqi, Urumqi, 830002, China
| | - Limin Wang
- National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 100050, China
| | - Yongping Yan
- Department of Epidemiology, the Fourth Military Medical University, Xi'an, 710032, Shaanxi Province, China
| | - Shuiyuan Xiao
- Department of Social Medicine and Health Management, School of Public Health, Central South University, Changsha, 410078, Hunan, China
| | - Xiangdong Du
- Suzhou Guangji Hospital, Suzhou, 215008, Jiangsu, China
| | - Guohua Li
- Chifeng Anding Hospital, Chifeng, 024000, Inner Mongolia Autonomous Region, China
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Li W, Cheng P, Liu Z, Ma C, Liu B, Zheng W, Scarisbrick D, Lu J, Li L, Huang Y, Wang L, Yan Y, Xiao S, Zhang Y, Zhang T, Yan J, Yu Y, Xu X, Wang Z, Xu Y, Li T, Xu G, Xu X, Xue M, Li G, Jia F, Shi J, Zhang N, Du X, Sang H, Zhang C, Liu B. Post-traumatic stress disorder and traumatic events in China: a nationally representative cross-sectional epidemiological study. Psychiatry Res 2023; 326:115282. [PMID: 37290364 DOI: 10.1016/j.psychres.2023.115282] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/13/2022] [Revised: 05/30/2023] [Accepted: 06/01/2023] [Indexed: 06/10/2023]
Abstract
Post-traumatic stress disorder (PTSD) is one of the most severe sequelae of trauma. But a nationally representative epidemiological data for PTSD and trauma events (TEs) was unavailable in China. This article firstly demonstrated detailed epidemiological information on PTSD, TEs, and related comorbidities in the national-wide community-based mental health survey in China. A total of 9,378 participants completed the PTSD-related interview of the CIDI 3.0. Lifetime prevalence and 12-month prevalence of PTSD in total respondents were 0.3% and 0.2%. while the conditional lifetime and 12-month prevalence of PTSD after trauma exposure were 1.8% and 1.1%. The prevalence of exposure to any type of TE was 17.2%. Among individuals with the exposed to TEs, younger, without regular work (being a homemaker or retried), and intimate relationship breakdown (separated/Widowed/Divorced), living rurally were associated with either the lifetime PTSD or the 12-month PTSD, while the count of a specific TE, the unexpected death of loved one, was related to both. Alcohol dependence was the most common comorbidity among male participants with PTSD but major depressive disorder (MDD) for female counterparts. Our study can provide a reliable reference for future identification and intervention for people with PTSD.
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Affiliation(s)
- Weihui Li
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha 410011, Hunan, China
| | - Peng Cheng
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha 410011, Hunan, China
| | - Zhaorui Liu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing 100191, China
| | - Chao Ma
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing 100191, China
| | - Bangshan Liu
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha 410011, Hunan, China
| | - Wanhong Zheng
- West Virginia University Department of Behavioral Medicine and Psychiatry, 930 Chestnut Ridge Road, Morgantown, WV 26505
| | - Dave Scarisbrick
- West Virginia University Department of Behavioral Medicine and Psychiatry, West Virginia University Department of Neuroscience 930 Chestnut Ridge Road, Morgantown, WV 26505
| | - Jin Lu
- Department of Psychiatry, The First Affiliated Hospital of Kunming Medical University, Kunming 650032, Yunnan, China
| | - Lingjiang Li
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha 410011, Hunan, China.
| | - Yueqin Huang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing 100191, China.
| | - Limin Wang
- National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China
| | - Yongping Yan
- Department of Epidemiology, the Fourth Military Medical University, Xi'an 710032, Shaanxi Province, China
| | - Shuiyuan Xiao
- Department of Social Medicine and Health Management, School of Public Health, Central South University, Changsha 410078, Hunan, China
| | - Yan Zhang
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha 410011, Hunan, China
| | - Tingting Zhang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing 100191, China
| | - Jie Yan
- Institute of Social Science Survey, Peking University, Beijing 100871, China
| | - Yaqin Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, Changchun 130021, Jilin, China
| | - Xiufeng Xu
- Department of Psychiatry, The First Affiliated Hospital of Kunming Medical University, Kunming 650032, Yunnan, China
| | - Zhizhong Wang
- Department of Epidemiology and Statistics, School of Public Health and Management, Ningxia Medical University, Yinchuan 750004, Ningxia, China
| | - Yifeng Xu
- Shanghai Mental Health Center, School of Medicine, Shanghai Jiao Tong University, Shanghai 200030, China
| | - Tao Li
- Mental Health Centre of West China Hospital, Sichuan University, Chengdu 610041, Sichuan, China
| | - Guangming Xu
- Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, Tianjin 300222, China
| | - Xiangdong Xu
- The Fourth People's Hospital in Urumqi, Urumqi 830002, China
| | - Meihua Xue
- The Affiliated Wuxi Mental Health Center with Nanjing Medical University, Wuxi 214151, Jiangsu, China
| | - Guohua Li
- Chifeng Anding Hospital, Chifeng 024000, Inner Mongolia Autonomous Region, China
| | - Fujun Jia
- Guangdong Mental Health Center, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou 510120, Guangdong, China
| | - Jianfei Shi
- Department of Psychiatry, Hangzhou Seventh People's Hospital, Hangzhou 310013, Zhejiang, China
| | - Ning Zhang
- Nanjing Brain Hospital, Nanjing 210029, Jiangsu, China
| | - Xinbai Du
- The Third People's Hospital of Qinghai, Xining 810007, Qinghai, China
| | - Hong Sang
- Changchun Sixth Hospital, Changchun 130052, Jilin, China
| | - Congpei Zhang
- Harbin First Specialized Hospital, Harbin 150000, Heilongjiang, China
| | - Bo Liu
- Jingzhou Mental Health Center, Jingzhou 434000, Hubei China
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Long-term disability in common mental disorders in Chinese community: evidence from a five-year follow-up study. BMC Psychiatry 2022; 22:727. [PMID: 36419029 PMCID: PMC9682650 DOI: 10.1186/s12888-022-04382-4] [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: 06/27/2022] [Accepted: 11/10/2022] [Indexed: 11/24/2022] Open
Abstract
BACKGROUND Common mental disorders are general term for mental disorders with high disability rates and significant social burden. The purpose of this study was to determine the degree of long-term disability associated with common mental disorders and to interpret the relationship between common mental disorders and long-term disability. METHODS Participants in the 2013 China Mental Health Survey were followed up by telephone between April and June 2018. This study evaluated long-term disability over a five-year period using the World Health Organization's Disability Assessment Schedule 2.0. Poisson regression was used to analyze the relationship between common mental disorders and long-term disability. RESULTS A total of 6269 patients were followed up by telephone. In patients with common mental disorders, the prevalence of disability ranged from 7.62% to 43.94%. The long-term disabilities were significantly associated with dysthymic disorder (DD, RR:2.40; 95% CI:1.87-3.03), major depressive disorder (MDD, RR:1.63; 95% CI:1.34-1.98), generalized anxiety disorder (GAD, RR:1.95; 95% CI:1.15-3.09), obsessive-compulsive disorder (OCD, RR:1.68; 95% CI:1.24-2.22) and alcohol use disorder (AUD, RR: 1.42; 95% CI:0.99-1.96). CONCLUSIONS In China, common mental disorders raise the risk of long-term disability, and there is a critical need for monitoring patients with DD, MDD, GAD, OCD, and AUD. For improved quality of life and reduced disability levels, more resources need to be dedicated to mental health in the future.
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Zhao Y, Di X, Li S, Zeng X, Wang X, Nan Y, Xiao L, Koplan J, Chen Z, Liu S. Prevalence, frequency, intensity, and location of cigarette use among adolescents in China from 2013-14 to 2019: Findings from two repeated cross-sectional studies. THE LANCET REGIONAL HEALTH. WESTERN PACIFIC 2022; 27:100549. [PMID: 35923777 PMCID: PMC9340429 DOI: 10.1016/j.lanwpc.2022.100549] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
BACKGROUND The burden of disease caused by tobacco use is a grave public health concern in China. Preventing smoking initiation among adolescents will lower the prevalence of adult tobacco use later. Surveillance of tobacco use among adolescents helps set priorities in developing tobacco control policies. We aim to ascertain the prevalence and differences of cigarette use across sex, grade, and region among middle and high school students in 2019 and associated changes from 2013-14 to 2019 among middle school students. METHODS Using a multistage stratified cluster-randomized sampling design with national and provincial representativeness, we conducted two school-based cross-sectional surveys in 2013-14 and in 2019. A total of 155 117 middle school students in grades 7-9 in 2013-14 and 288 192 middle and high school students in grades 7-12 in 2019 were interviewed. Self-reported experimental and current (past 30-day) cigarette use among middle school and high school students; frequent use (≥20 days in the past 30 days) and intensity (>20 cigarettes per day) of smoking among current cigarette users; and location of smoking among current cigarette users were investigated. All estimates were weighted based on the complex sampling design. FINDINGS The 2013-14 survey (overall response rate: 98.1%) included 155 117 middle school students (47.1% girl). The 2019 survey (overall response rate: 98.7%) included 147 270 middle school students (46.5% girl), 106 432 academic high school students (50.8% girl) and 34 490 vocational high school students (43.8% girl). In 2019, the prevalence rate of experimental and current cigarette use was 12.9% and 3.9% for middle school students, 21.6% and 5.6% for academic high school students, and 30.3% and 14.7% for vocational high school students, respectively, with large sex and regional differences. The prevalences of smoking on 20 or more days and daily cigarette use in the past 30 days were higher in vocational high school (5.9%, 4.1%) than in academic high school (1.8%, 1.2%) and middle school (0.7%, 0.5%), and higher among boys than girls. The proportions of current cigarette users smoking more than 20 cigarettes per day in the past 30 days for girls were higher than for boys in academic high school. Students usually smoke at school and at home. Boys were more likely to use cigarettes in an internet cafe, while girls often smoked at social venues. From 2013-14 to 2019, the prevalences of experimental and current cigarette use declined by 5.0% and 2.0% (percentage points), respectively, among middle school students but increased by 1.4% and 0.5% (percentage points) among rural girls. Among current cigarette users in middle school students, the proportions of heavy cigarette use (>20 cigarettes per day) have increased by 1.8 percentage points, mainly among boys, by 2.2% (percentage points). INTERPRETATION From 2013-14 to 2019, the prevalences of experimental and current cigarette use among middle school students decreased overall but increased among rural girls, while the intensity of cigarette use rose among boys. Cigarette use among Chinese adolescents differs across sex and regions, with higher rates among boys, in rural areas, and in the Western region (low socioeconomic status). Smoking is much more prevalent in vocational high schools than the other settings. Effective targeted tobacco control interventions among adolescents are urgently needed in China. FUNDING Dr. Zhuo Chen is supported by National Natural Science Foundation (Grant#: 72174098) through the University of Nottingham Ningbo China.
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Affiliation(s)
- Yan Zhao
- Tobacco Control Office, Chinese Center for Disease Control and Prevention, 27# Nanwei Road, Xicheng District, Beijing 100050, China
- Department of Public Health, School of Public Health, Inner Mongolia Medical University, Huhehot, Inner Mongolia 010110, China
| | - Xinbo Di
- Tobacco Control Office, Chinese Center for Disease Control and Prevention, 27# Nanwei Road, Xicheng District, Beijing 100050, China
| | - Sixuan Li
- Tobacco Control Office, Chinese Center for Disease Control and Prevention, 27# Nanwei Road, Xicheng District, Beijing 100050, China
- Ningbo Municipal Center for Disease Control and Prevention, 237# Yongfeng Road, Haishu District, Ningbo, Zhejiang Province 315010, China
| | - Xinying Zeng
- Tobacco Control Office, Chinese Center for Disease Control and Prevention, 27# Nanwei Road, Xicheng District, Beijing 100050, China
| | - Xiaofeng Wang
- Information Center, Chinese Center for Disease Control and Prevention, 155# Changbei Road, Changping District, Beijing 102206, China
| | - Yi Nan
- Tobacco Control Office, Chinese Center for Disease Control and Prevention, 27# Nanwei Road, Xicheng District, Beijing 100050, China
| | - Lin Xiao
- Tobacco Control Office, Chinese Center for Disease Control and Prevention, 27# Nanwei Road, Xicheng District, Beijing 100050, China
| | - Jeffrey Koplan
- Emory Global Health Institute, Emory University, Atlanta 30322 Georgia, USA
| | - Zhuo Chen
- College of Public Health, University of Georgia, Athens 30602 Georgia, USA
- School of Economics, University of Nottingham Ningbo China 315100 Ningbo, Zhejiang Province, China
| | - Shiwei Liu
- Tobacco Control Office, Chinese Center for Disease Control and Prevention, 27# Nanwei Road, Xicheng District, Beijing 100050, China
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7
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Tan W, Chen L, Zhang Y, Xi J, Hao Y, Jia F, Hall BJ, Gu J, Wang S, Lin H, Lin X. Regional years of life lost, years lived with disability, and disability-adjusted life-years for severe mental disorders in Guangdong Province, China: a real-world longitudinal study. Glob Health Res Policy 2022; 7:17. [PMID: 35725574 PMCID: PMC9208127 DOI: 10.1186/s41256-022-00253-3] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2022] [Accepted: 06/01/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND To understand the magnitude and spatial-temporal distribution of the regional burden attributable to severe mental disorders is of great essential and high policy relevance. The study aimed to address the burden of severe mental disorders by evaluating the years of life lost, years lived with disability, and disability-adjusted life-years (DALYs) in Guangdong, China. METHODS We undertook a longitudinal study based on a multicenter database established by the Health Commission of Guangdong, involving a total of 21 prefectures and four economic regions in the Guangdong province. A total of 520,731 medical records from patients with severe mental disorders were collected for 2010-2020. Data were analyzed via an integrated evaluation framework by synthesizing prevalence estimates, epidemiological adjustment as well as comorbidity assessment to develop internally consistent estimates of DALY. DALY changes during 2010-2020 were decomposed by population growth and aging and further grouped by Socio-demographic Index (SDI). DALYs were projected to 2030 by the weighted median annualized rate of change in 2010-2020. RESULTS In 2010-2020, the average DALYs for severe mental disorders reached 798,474 (95% uncertainty interval [UI]: 536,280-1,270,465) person-years (52.2% for males, and 47.8% for females). Severe mental disorders led to a great amount of disease burden, especially in Guangzhou, Shenzhen, and Foshan cities. Schizophrenia and mental retardation with mental disorders were the two leading sources of the burden ascribed to severe mental disorders. Population growth and aging could be accountable for the increasing burden of severe mental disorders. Economic regions with higher SDI carried a greater burden but had lower annualized rates of change in DALYs. The overall burden of severe mental disorders is projected to rise modestly over the next decade. CONCLUSIONS The findings urge prioritization of initiatives focused on public mental health, prevention strategies, health resources reallocation, and active involvement of authorities to effectively address the anticipated needs.
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Affiliation(s)
- Wenyan Tan
- Guangdong Mental Health Center, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Lichang Chen
- Department of Medical Statistics and Center for Health Information Research and Guangdong Key Laboratory of Medicine, School of Public Health, Sun Yat-Sen University, 74 Zhongshan 2nd Rd, Guangzhou, 510080, Guangdong, China
| | - Yuqin Zhang
- Department of Medical Statistics and Center for Health Information Research and Guangdong Key Laboratory of Medicine, School of Public Health, Sun Yat-Sen University, 74 Zhongshan 2nd Rd, Guangzhou, 510080, Guangdong, China
| | - Junyan Xi
- Department of Medical Statistics and Center for Health Information Research and Guangdong Key Laboratory of Medicine, School of Public Health, Sun Yat-Sen University, 74 Zhongshan 2nd Rd, Guangzhou, 510080, Guangdong, China
| | - Yuantao Hao
- Peking University Center for Public Health and Epidemic Preparedness & Response, Peking University, Beijing, 100191, China
| | - Fujun Jia
- Guangdong Mental Health Center, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Brian J Hall
- Global Public Health, New York University (Shanghai), Shanghai, 200122, China
| | - Jing Gu
- Department of Medical Statistics and Center for Health Information Research and Guangdong Key Laboratory of Medicine, School of Public Health, Sun Yat-Sen University, 74 Zhongshan 2nd Rd, Guangzhou, 510080, Guangdong, China.,Sun Yat-Sen Global Health Institute, Sun Yat-Sen University, Guangzhou, 510080, Guangdong, China
| | - Shibin Wang
- Guangdong Mental Health Center, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Haicheng Lin
- Guangdong Mental Health Center, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, Guangdong, China.
| | - Xiao Lin
- Department of Medical Statistics and Center for Health Information Research and Guangdong Key Laboratory of Medicine, School of Public Health, Sun Yat-Sen University, 74 Zhongshan 2nd Rd, Guangzhou, 510080, Guangdong, China. .,Sun Yat-Sen Global Health Institute, Sun Yat-Sen University, Guangzhou, 510080, Guangdong, China.
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8
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Badu E, O'Brien AP, Mitchell R, Osei A. Factors associated with the quality of mental health services and consumers' functionality using tertiary-based services. Perspect Psychiatr Care 2022; 58:592-607. [PMID: 33942311 DOI: 10.1111/ppc.12820] [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: 01/01/2021] [Revised: 03/25/2021] [Accepted: 04/09/2021] [Indexed: 12/27/2022] Open
Abstract
PURPOSE Assess factors associated with the quality of mental health services. DESIGN AND METHODS Cross-sectional design, quantitative data, and 510 consumers from three psychiatric facilities. RESULTS The average age of consumers was 34 years and 51.57% males. Consumers reported mixed satisfaction with the quality of mental health services (mean = 3.2; SD = 0.56) but were dissatisfied with the range of interventions (mean = 1.57; SD = 0.77). Predisposing (age, education, and primary occupation), enabling (insurance status), and need factors (mental health status) were significantly associated with quality indicators (range of interventions, efficacy, and overall satisfaction). These factors were significantly associated with consumers' functionality (cognition, mobility, self-care, getting along, life activities, and participation). PRACTICE IMPLICATIONS Policymakers and clinicians are encouraged to incorporate the predisposing, enabling, and need factors into mental health planning, monitoring, and advocacy to improve service outcomes.
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Affiliation(s)
- Eric Badu
- School of Nursing and Midwifery, Faculty Health and Medicine, The University of Newcastle, Callaghan, New South Wales, Australia
| | - Anthony P O'Brien
- Faculty of Health, Southern Cross University, New South Wales, Australia
| | - Rebecca Mitchell
- Health & Wellbeing Research Unit (HoWRU), Macquarie Business School, Macquarie University, Macquarie Park, New South Wales, Australia
| | - Akwasi Osei
- Ghana Mental Health Authority, Ghana Health Services, Accra, Ghana
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9
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Badu E, O'Brien AP, Mitchell R, Osei A. A Qualitative Study of Consumers' Experiences of the Quality of Mental Health Services in Ghana. Issues Ment Health Nurs 2022; 43:172-183. [PMID: 34129434 DOI: 10.1080/01612840.2021.1931584] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
Abstract
Integrating consumers' experiences into quality mental health service assessment is relevant to improve service outcomes. Despite this, limited studies have attempted to explore consumers' experiences, particularly in developing countries, such as Ghana. This paper aims to explore consumers' subjective experiences of the quality of mental health services. A qualitative method involving in-depth interviews was used to collect data from 21 consumers of mental health services. Thematic analysis was used to analyse the data, which is discussed using a realistic evaluation approach. The study identifies four themes, 33 inductive codes and 594 references. The themes used to interpret the verbatim narratives are the available mental health services, therapeutic interaction with the professionals, competency and skills of the professionals, and the changes experienced in the consumers' lives. The study indicates that the mental health services aim to provide a range of treatments and medications as well as recovery-oriented services, using mechanisms such as ensuring an effective therapeutic relationship and improving technical competency and skills. The contextual factors and the mechanisms have helped to achieve some changes in the lives of consumers (increased satisfaction, reduced symptoms, improved functionality, feeling normal, improved living skills and self-care, work and capabilities, and social inclusion). The study concludes that policymakers and clinicians should integrate evidence-based recovery services, principles and values into the existing mental health services. The mechanisms used to promote quality of mental health services should be strengthened, through periodic monitoring and evaluation, using approaches such as sensor data capturing, to ensure good coordination and continuity.
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Affiliation(s)
- Eric Badu
- School of Nursing and Midwifery, Faculty Health and Medicine, The University of Newcastle, Callaghan, NSW, Australia
| | - Anthony Paul O'Brien
- School Nursing and Midwifery, Faculty Health and Medicine, The University of Newcastle, Callaghan, NSW, Australia
| | - Rebecca Mitchell
- Health & Wellbeing Research Unit (HoWRU), Macquarie Business School, Macquarie University, Macquarie Park, NSW, Australia
| | - Akwasi Osei
- Ghana Mental Health Authority, Ghana Health Services, Accra, Ghana
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10
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Cui X, Li M, Li P, Li J, Hou X, Yan G, Li P, Su X, Qin D, Zhang Y, Gu Y, Yin H, Xu G. Help-Seeking Behaviors and Related Factors in Chinese Patients With Major Depressive Disorder: A Community-Based Cross-Sectional Study. Front Psychiatry 2022; 13:934428. [PMID: 35873223 PMCID: PMC9298966 DOI: 10.3389/fpsyt.2022.934428] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/02/2022] [Accepted: 06/09/2022] [Indexed: 11/24/2022] Open
Abstract
BACKGROUND Although evidence-based and effective treatments are available for people with major depressive disorder (MDD), a substantial number do not seek or receive help. Therefore, this study aimed to (1) investigate the total help-seeking rate and first-time help-seeking choices; (2) explore the perceived helpfulness of 23 potential sources; and (3) evaluate the factors related to help-seeking behaviors among patients with MDD. MATERIALS AND METHODS Data came from the Tianjin Mental Health Survey (TJMHS), which included a representative sample of adult community residents (n = 11,748) in the Chinese municipality of Tianjin. Of these, 439 individuals were diagnosed with lifetime MDD according to the Diagnostic and Statistical Manual-fourth edition (DSM-IV) and administered a help-seeking questionnaire. RESULTS In a survey, 28.2% of patients with MDD living community reported that they had ever sought any help during their entire lifetime before the interview, with 8.2% seeking help in mental healthcare settings, 8.0% only in other healthcare settings, and 12.0% only in non-healthcare sources (e.g., family, friends, and spiritual advisor). Among help-seekers, the first help mainly was sought in non-healthcare sources (61.3%), followed by healthcare settings (25.8%) and mental healthcare settings (12.9%). The majority of MDD individuals thought the non-healthcare sources were not helpful and mental healthcare settings were helpful or possibly helpful to solve mental problems. Female, having 10-12 or higher education years, comorbid anxiety disorders were associated with increased help-seeking. CONCLUSION A small percentage of individuals with MDD living in community of Tianjin sought help. They preferred non-healthcare sources to healthcare settings. Demographic and clinical features were associated with help-seeking behaviors.
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Affiliation(s)
- Xiaojuan Cui
- Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, Tianjin, China
| | - Minghui Li
- Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, Tianjin, China
| | - Peijun Li
- Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, Tianjin, China
| | - Jinhao Li
- Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, Tianjin, China
| | - Xiaofei Hou
- Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, Tianjin, China
| | - Guoli Yan
- Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, Tianjin, China
| | - Peiyao Li
- Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, Tianjin, China
| | - Xuyang Su
- Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, Tianjin, China
| | - Danni Qin
- Institute of Applied Psychology, Tianjin University, Tianjin, China
| | - Yijiao Zhang
- Institute of Applied Psychology, Tianjin University, Tianjin, China
| | - Yan Gu
- Tianjin Third Central Hospital, Tianjin, China
| | - Huifang Yin
- Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, Tianjin, China
| | - Guangming Xu
- Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, Tianjin, China
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Hu Y, Huang Y, Wang L, Liu Z, Wang L, Yan J, Zhang M, Lv P, Guan Y, Ma C, Huang Z, Zhang T, Chen H. Disability and Comorbidity of Mood Disorders and Anxiety Disorders With Diabetes and Hypertension: Evidences From the China Mental Health Survey and Chronic Disease Surveillance in China. Front Psychiatry 2022; 13:889823. [PMID: 35669270 PMCID: PMC9163306 DOI: 10.3389/fpsyt.2022.889823] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/04/2022] [Accepted: 04/26/2022] [Indexed: 12/02/2022] Open
Abstract
BACKGROUND The China Mental Health Survey was carried out using the same sampling frame with the China Chronic Diseases and Risk Factors Surveillance. This paper explores the relationship between the disability and the comorbidity of mood disorders and anxiety disorders with diabetes and hypertension. METHODS A large-scale nationally representative sample with both mental disorders and chronic diseases was collected from 157 Disease Surveillance Points in 31 provinces across China. Face-to-face interviews were conducted by trained lay interviewers to make diagnoses of mood disorders and anxiety disorders using the Composite International Diagnostic Interview. Diabetes and hypertension were diagnosed from self-report and blood examination or body measurement. Sampling design weights, non-response adjustment weights, and post-stratification adjustment weights were applied during the analyses of comorbidity and disability. RESULTS Totally 15,000 respondents had information of mental disorders and physical diseases. In the patients with mood disorders or anxiety disorders, the weighted prevalence rates of diabetes or hypertension were not higher than those in persons without the above mental disorders, but the weighed disability rates increased when having the comorbidity of hypertension (P < 0.05). The severity of disability was higher among patients with comorbidity of diabetes and anxiety disorders, or hypertension and mood disorders, compared with that among patients without the physical comorbidity (P < 0.05). After adjusted by age, gender and education, patients with comorbidity of mental disorders and physical disorders had the highest disability, followed by the patients with mental disorders only, and physical diseases only. CONCLUSIONS The disability of mood disorders and anxiety disorders comorbid with diabetes and hypertension are more serious than that of any single disease. The relationship of mental and physical diseases is worth exploring in depth for comprehensive and integrated intervention to decrease the disability.
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Affiliation(s)
- Yuanyuan Hu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, National Health Commission Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Yueqin Huang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, National Health Commission Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Limin Wang
- National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Zhaorui Liu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, National Health Commission Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Linhong Wang
- National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Jie Yan
- School of Government, Peking University, Beijing, China
| | - Mei Zhang
- National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Ping Lv
- Institute of Social Science Survey, Peking University, Beijing, China
| | - Yunqi Guan
- National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Chao Ma
- Peking University Sixth Hospital, Peking University Institute of Mental Health, National Health Commission Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Zhengjing Huang
- National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Tingting Zhang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, National Health Commission Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Hongguang Chen
- Peking University Sixth Hospital, Peking University Institute of Mental Health, National Health Commission Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
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12
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Li B, Zhang G, Ma J, Kang M. Mortality rate of mental disorder trends in China from 2002 to 2020. Front Psychiatry 2022; 13:1039918. [PMID: 36458125 PMCID: PMC9707622 DOI: 10.3389/fpsyt.2022.1039918] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/08/2022] [Accepted: 10/31/2022] [Indexed: 11/17/2022] Open
Abstract
BACKGROUND The number of people with mental disorders is increasing in China, but there are few studies on the temporal trends and population distribution of mental disorder mortality. METHODS The mortality of mental disorders were derived from the China Health Statistics Yearbook published by the National Health and Family Planning Commission. Temporal trends in mortality were examined with a joinpoint regression using annual percent change (APC) and average annual percent change (AAPC). A Poisson regression model was utilized to test the population-level risk factors associated with the death of people with mental disorders. RESULTS The mortality of mental disorders in rural Chinese residents showed a decreasing trend from 2002 to 2020 [AAPC -2.06%, 95% confidence interval (CI) -3.16 to -0.91%]. The mortality of mental disorders in urban Chinese residents declined between 2005 and 2011 (APC -13.01%, 95% CI -21.08 to -4.13%). The mortality rate of mental disorders has decreased for urban males with an APC of -2.71% (95% CI -4.52 to -0.71) from 2002 to 2020. Urban women showed an increase in mental disorder mortality from 2002 to 2005 and from 2012 to 2020 with APCs of 19.65% (95% CI 0.64-42.32%) and 6.16% (95% CI 2.22-10.33%), respectively. Age was a significant risk factor for mental disorder mortality (odds ratio 1.28, 95% CI 1.23-1.32). CONCLUSION The dissemination of medical and health information, investment in medical and health resources, and the modification and optimization of regulations have led to a decrease in mental disorder mortality in China. It is vital to devote greater attention to elderly individuals suffering from mental disorders.
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Affiliation(s)
- Boxuan Li
- Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, Tianjin, China
| | - Guoshuang Zhang
- Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, Tianjin, China
| | - Jing Ma
- Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, Tianjin, China
| | - Mingxiu Kang
- Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, Tianjin, China
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13
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Peng R, Wang Y, Huang Y, Liu Z, Xu X, Ma Y, Wang L, Zhang M, Yan Y, Wang B, Xiao S, Zhou L, Li L, Zhang Y, Ma C, Zhang T, Yan J, Ding H, Yu Y, Kou C, Xu X, Lu J, Wang Z, He S, Xu Y, He Y, Li T, Guo W, Xu G, Yin H, Du X, Wu Y, Li G, Jia F, Shi J, Chen Z, Zhang N, Li S. The association of depressive symptoms with disability among adults in China. J Affect Disord 2022; 296:189-197. [PMID: 34607060 DOI: 10.1016/j.jad.2021.09.030] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/27/2021] [Revised: 07/30/2021] [Accepted: 09/12/2021] [Indexed: 02/05/2023]
Abstract
BACKGROUND The symptoms that patients with major depressive disorder (MDD) experience are the dominant contributing factors to its heavy disease burden. This study sought to identify key symptoms leading to disability in patients with MDD. METHODS Subjects consisted of patients who had a 12-month MDD diagnosis based on the China Mental Health Survey (CMHS). World Health Organization Disability Assessment Schedule 2.0 (WHODAS 2.0) was used to assess the degree of disability. The associations between depressive symptoms and disability were analyzed using a linear regression and logistic regression with a complex sampling design. RESULTS Of the 32,552 community residents, 655 patients were diagnosed with 12-month MDD. The disability rate due to MDD was 1.06% (95% CI: 0.85%-1.28%) among adults in Chinese community and 50.7% (95% CI: 44.3%-57.1%) among MDD patients. Depression was associated with all functional losses measured by the WHODAS. Feelings of worthlessness in life or inappropriate guilt, and psychomotor agitation or retardation were the key symptoms related to disability. Economic status, co-morbidity of physical diseases or anxiety disorders were correlates of disability scores. LIMITATIONS The disability rate might be underestimated due to the exclusion of MDD patients living in hospitals. The effect of treatments on disability was excluded. CONCLUSIONS Psychological symptoms, not somatic symptoms, contribute to disability in MDD patients. Disability worsens when physical diseases or anxiety disorders are present. More attention could be paid to psychological symptoms, physical diseases, and anxiety disorders in MDD patients with disabilities.
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Affiliation(s)
- Rui Peng
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing 100191, China
| | - Yongshi Wang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing 100191, China
| | - Yueqin Huang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing 100191, China.
| | - Zhaorui Liu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing 100191, China.
| | - Xiangdong Xu
- The Fourth People's Hospital in Urumqi, Urumqi 830002, China
| | - Yanjuan Ma
- The Fourth People's Hospital in Urumqi, Urumqi 830002, China
| | - Limin Wang
- National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China
| | - Mei Zhang
- National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China
| | - Yongping Yan
- Department of Epidemiology, the Fourth Military Medical University, Xi'an 710032, Shaanxi Province, China
| | - Bo Wang
- Department of Epidemiology, the Fourth Military Medical University, Xi'an 710032, Shaanxi Province, China
| | - Shuiyuan Xiao
- Department of Social Medicine and Health Management, School of Public Health, Central South University, Changsha 410078, Hunan, China
| | - Liang Zhou
- Department of Social Medicine and Health Management, School of Public Health, Central South University, Changsha 410078, Hunan, China
| | - Lingjiang Li
- Mental Health Institute, the Second Xiangya Hospital, Central South University, Changsha 410011, Hunan, China
| | - Yan Zhang
- Mental Health Institute, the Second Xiangya Hospital, Central South University, Changsha 410011, Hunan, China
| | - Chao Ma
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing 100191, China
| | - Tingting Zhang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing 100191, China
| | - Jie Yan
- Institute of Social Science Survey, Peking University, Beijing 100871, China
| | - Hua Ding
- Institute of Social Science Survey, Peking University, Beijing 100871, China
| | - Yaqin Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, Changchun 130021, Jilin, China
| | - Changgui Kou
- Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, Changchun 130021, Jilin, China
| | - Xiufeng Xu
- Department of Psychiatry, The First Affiliated Hospital of Kunming Medical University, Kunming 650032, Yunnan, China
| | - Jin Lu
- Department of Psychiatry, The First Affiliated Hospital of Kunming Medical University, Kunming 650032, Yunnan, China
| | - Zhizhong Wang
- Department of Epidemiology and Health Statistics, School of Public Health and Management, Ningxia Medical University, Yinchuan 750004, Ning Xia, China
| | - Shulan He
- Department of Epidemiology and Health Statistics, School of Public Health and Management, Ningxia Medical University, Yinchuan 750004, Ning Xia, China
| | - Yifeng Xu
- Shanghai Mental Health Center, School of Medicine, Shanghai Jiao Tong University, Shanghai 200030, China
| | - Yanling He
- Shanghai Mental Health Center, School of Medicine, Shanghai Jiao Tong University, Shanghai 200030, China
| | - Tao Li
- Mental Health Centre of West China Hospital, Sichuan University, Chengdu 610041, Sichuan, China
| | - Wanjun Guo
- Mental Health Centre of West China Hospital, Sichuan University, Chengdu 610041, Sichuan, China
| | | | - Huifang Yin
- Tianjin Anding Hospital, Tianjin 300222, China
| | - Xiangdong Du
- Suzhou Guangji Hospital, Suzhou 215008, Jiangsu, China
| | - Yue Wu
- The Affiliated Wuxi Mental Health Center with Nanjing Medical University, Wuxi, Jiangsu 214151, China
| | - Guohua Li
- Chifeng Anding Hospital, Chifeng 024000, Inner Mongolia Autonomous Region, China
| | - Fujun Jia
- Guangdong General Hospital, Guangdong Mental Health Institute, Guangzhou 510120, Guangdong, China
| | - Jianfei Shi
- Department of Psychiatry, Hangzhou Seventh People's Hospital, Hangzhou 310013, Zhejiang, China
| | - Zheli Chen
- The Third People's Hospital of Huzhou, Huzhou 313000, Zhejiang, China
| | - Ning Zhang
- Nanjing Brain Hospital Affiliated to Nanjing Medical University, Nanjing 210029, Jiangsu, China
| | - Shengju Li
- The Third People's Hospital of Qinghai, Xining 810007, Qinghai, China
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14
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Lu J, Xu X, Huang Y, Li T, Ma C, Xu G, Yin H, Xu X, Ma Y, Wang L, Huang Z, Yan Y, Wang B, Xiao S, Zhou L, Li L, Zhang Y, Chen H, Zhang T, Yan J, Ding H, Yu Y, Kou C, Shen Z, Jiang L, Wang Z, Sun X, Xu Y, He Y, Guo W, Jiang L, Li S, Pan W, Wu Y, Li G, Jia F, Shi J, Shen Z, Zhang N. Prevalence of depressive disorders and treatment in China: a cross-sectional epidemiological study. Lancet Psychiatry 2021; 8:981-990. [PMID: 34559991 DOI: 10.1016/s2215-0366(21)00251-0] [Citation(s) in RCA: 372] [Impact Index Per Article: 93.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/09/2021] [Revised: 06/21/2021] [Accepted: 06/30/2021] [Indexed: 02/08/2023]
Abstract
BACKGROUND In China, depressive disorders have been estimated to be the second leading cause of years lived with disability. However, nationally representative epidemiological data for depressive disorders, in particular use of mental health services by adults with these disorders, are unavailable in China. The present study, part of the China Mental Health Survey, 2012-15, aims to describe the socioeconomic characteristics and the use of mental health services in people with depressive disorders in China. METHODS The China Mental Health Survey was a cross-sectional epidemiological survey of mental disorders in a multistage clustered-area probability sample of adults of Chinese nationality (≥18 years) from 157 nationwide representative population-based disease surveillance points in 31 provinces across China. Trained investigators interviewed the participants with the Composite International Diagnostic Interview 3.0 to ascertain the presence of lifetime and 12-month depressive disorders according to DSM-IV criteria, including major depressive disorder, dysthymic disorder, and depressive disorder not otherwise specified. Participants with 12-month depressive disorders were asked whether they received any treatment for their emotional problems during the past 12 months and, if so, the specific types of treatment providers. The Sheehan Disability Scale (SDS) was used to assess impairments associated with 12-month depressive symptoms. Data-quality control procedures included logic check by computers, sequential recording check, and phone-call check by the quality controllers, and reinterview check by the psychiatrists. Data were weighted according to the age-sex-residence distribution data from China's 2010 census population survey to adjust for differential probabilities of selection and differential response, as well as to post-stratify the sample to match the population distribution. FINDINGS 28 140 respondents (12 537 [44·6%] men and 15 603 [55·4%] women) completed the survey between July 22, 2013, and March 5, 2015. Ethnicity data (Han or non-Han) were collected for only a subsample. Prevalence of any depressive disorders was higher in women than men (lifetime prevalence odds ratio [OR] 1·44 [95% CI 1·20-1·72] and 12-month prevalence OR 1·41 [1·12-1·78]), in unemployed people than employed people (lifetime OR 2·38 [95% CI 1·68-3·38] and 12-month OR 2·80 [95% CI 1·88-4·18]), and in people who were separated, widowed, or divorced compared with those who were married or cohabiting (lifetime OR 1·87 [95% CI 1·39-2·51] and 12-month OR 1·85 [95% CI 1·40-2·46]). Overall, 574 (weighted % 75·9%) of 744 people with 12-month depressive disorders had role impairment of any SDS domain: 439 (83·6%) of 534 respondents with major depressive disorder, 207 (79·8%) of 254 respondents with dysthymic disorder, and 122 (59·9%) of 189 respondents with depressive disorder not otherwise specified. Only an estimated 84 (weighted % 9·5%) of 1007 participants with 12-month depressive disorders were treated in any treatment sector: 38 (3·6%) in speciality mental health, 20 (1·5%) in general medical, two (0·3%) in human services, and 21 (2·7%) in complementary and alternative medicine. Only 12 (0·5%) of 1007 participants with depressive disorders were treated adequately. INTERPRETATION Depressive disorders in China were more prevalent in women than men, unemployed people than employed, and those who were separated, widowed, or divorced than people who were married or cohabiting. Most people with depressive disorders reported social impairment. Treatment rates were very low, and few people received adequate treatment. National programmes are needed to remove barriers to availability, accessibility, and acceptability of care for depression in China. FUNDING National Health Commission and Ministry of Science and Technology of People's Republic of China. TRANSLATION For the Chinese translation of the abstract see Supplementary Materials section.
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Affiliation(s)
- Jin Lu
- Department of Psychiatry, The First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Xiufeng Xu
- Department of Psychiatry, The First Affiliated Hospital of Kunming Medical University, Kunming, China; The Fourth People's Hospital in Urumqi, Urumqi, China
| | - Yueqin Huang
- Institute of Mental Health, Peking University Sixth Hospital, National Clinical Research Center for Mental Disorders & Key Laboratory of Mental Health, Ministry of Health, Peking University, Beijing, China.
| | - Tao Li
- Mental Health Centre, West China Hospital, Sichuan University, Chengdu, China
| | - Chao Ma
- Institute of Mental Health, Peking University Sixth Hospital, National Clinical Research Center for Mental Disorders & Key Laboratory of Mental Health, Ministry of Health, Peking University, Beijing, China
| | | | | | - Xiangdong Xu
- Department of Psychiatry, The First Affiliated Hospital of Kunming Medical University, Kunming, China; The Fourth People's Hospital in Urumqi, Urumqi, China
| | - Yanjuan Ma
- The Fourth People's Hospital in Urumqi, Urumqi, China
| | - Limin Wang
- National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Zhengjing Huang
- National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Yongping Yan
- Department of Epidemiology, the Fourth Military Medical University, Xi'an, China
| | - Bo Wang
- Department of Epidemiology, the Fourth Military Medical University, Xi'an, China
| | - Shuiyuan Xiao
- Department of Social Medicine and Health Management, School of Public Health, Central South University, Changsha, China
| | - Liang Zhou
- Department of Social Medicine and Health Management, School of Public Health, Central South University, Changsha, China
| | - Lingjiang Li
- Mental Health Institute, the Second Xiangya Hospital, Central South University, Changsha, China
| | - Yan Zhang
- Mental Health Institute, the Second Xiangya Hospital, Central South University, Changsha, China
| | - Hongguang Chen
- Institute of Mental Health, Peking University Sixth Hospital, National Clinical Research Center for Mental Disorders & Key Laboratory of Mental Health, Ministry of Health, Peking University, Beijing, China
| | - TingTing Zhang
- Institute of Mental Health, Peking University Sixth Hospital, National Clinical Research Center for Mental Disorders & Key Laboratory of Mental Health, Ministry of Health, Peking University, Beijing, China
| | - Jie Yan
- Institute of Social Science Survey, Peking University, Beijing, China
| | - Hua Ding
- Institute of Social Science Survey, Peking University, Beijing, China
| | - Yaqin Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, Changchun, China
| | - Changgui Kou
- Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, Changchun, China
| | - Zonglin Shen
- Department of Psychiatry, The First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Linling Jiang
- Department of Psychiatry, The First Affiliated Hospital of Kunming Medical University, Kunming, China; Mental Health Centre, West China Hospital, Sichuan University, Chengdu, China
| | - Zhizhong Wang
- Department of Epidemiology and Statistics, School of Public Health, Ningxia Medical University, Yinchuan, China
| | - Xian Sun
- Department of Epidemiology and Statistics, School of Public Health, Ningxia Medical University, Yinchuan, China
| | - Yifeng Xu
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yanling He
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Wanjun Guo
- Mental Health Centre, West China Hospital, Sichuan University, Chengdu, China
| | - Lijun Jiang
- Department of Psychiatry, The First Affiliated Hospital of Kunming Medical University, Kunming, China; Mental Health Centre, West China Hospital, Sichuan University, Chengdu, China
| | - Shengyan Li
- The Third People's Hospital of Qinghai Province, Xining, Qinghai, China
| | - Wen Pan
- Suzhou Psychiatric Hospital, The Affiliated Guangji Hospital of Soochow University, Suzhou, Jiangsu, China
| | - Yue Wu
- Wuxi Mental Health Center, Nanjing Medical University, Wuxi, Jiangsu, China
| | - Guohua Li
- Chifeng Anding Hospital, Chifeng, Inner Mongolia, China
| | - Fujun Jia
- Guangdong Mental Health Center, Guangzhou, Guangdong, China
| | - Jianfei Shi
- Department of Psychiatry, Hangzhou Seventh People's Hospital, Hangzhou, Zhejiang, China
| | - Zhongxia Shen
- The Third People's Hospital of Huzhou, Huzhou, Zhejiang, China
| | - Ning Zhang
- Nanjing Brain Hospital, affiliated to Nanjing Medical University, Nanjing, Jiangsu, China
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Badu E, Mitchell R, O'Brien AP, Osei A, Rubin M. Measuring Disability in Consumers of mental health services - psychometric properties of the World Health Organization Disability Assessment Schedule 2.0 (WHODAS 2.0) in Ghana. Int J Ment Health Nurs 2021; 30:1274-1288. [PMID: 34291551 DOI: 10.1111/inm.12911] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/29/2020] [Accepted: 06/28/2021] [Indexed: 11/30/2022]
Abstract
The World Health Disability Assessment Scale (WHODAS-2.0) has widely been accepted as the standard measure of disability. However, psychometric testing is mostly performed in developed countries. This paper aims to assess the psychometric properties (reliability, validity) of the WHODAS-2.0 among consumers of mental health services in Ghana. Two translators (expert in English language and Akan language) performed forward and backward translation of the WHODAS-2.0 from English language to Ghanaian language (Twi). A total of 510 consumers of mental health services were recruited consecutively to complete the WHODAS-2.0 using RedCAP. Confirmatory factor analysis was used to analyse the data. All domains in the 6-factor solutions had excellent internal consistency (ω = 0.90-0.98), sufficient convergent validity and had satisfactory discriminant validity except for domain on participation. The CFA model confirmed that the data had a good model fit, CFI = 0.97, TLI = 0.96, RMESA = 0.05, RMR = 0.03; NFI = 0.94; χ2 = 1243.8, df = 529, P < 0.001. Although the WHODAS 2.0 had satisfactory psychometric properties and was thus considered to be a reliable and valid measure for assessing disability and level of functioning in consumers of mental health services, researchers and clinicians should re-consider items within the participation domain. Also, practitioners are encouraged to integrate the WHODAS-2.0 into the collection of data on clinical outcomes, as well as, collecting data on government social protection intervention programmes for consumers.
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Affiliation(s)
- Eric Badu
- School of Nursing and Midwifery, Faculty Health and Medicine, The University of Newcastle, Callaghan, Australia
| | - Rebecca Mitchell
- Macquarie Business School, Macquarie University, North Ryde, Australia
| | - Anthony Paul O'Brien
- School of Nursing and Midwifery, Faculty Health and Medicine, The University of Newcastle, Callaghan, Australia
| | - Akwasi Osei
- Ghana Mental Health Authority, Ghana Health Services, Accra, Ghana
| | - Mark Rubin
- School of Psychology, The University of Newcastle, Callaghan, Australia
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16
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Liu Z, Li P, Yin H, Li M, Yan J, Ma C, Ding H, Li Q, Huang Z, Yan Y, Kou C, Hu M, Wen J, Chen S, Jia C, Huang Y, Xu G. Future Trends in Disability and Its Determinants Among Chinese Community Patients With Anxiety Disorders: Evidence From a 5-Year Follow-Up Study. Front Psychiatry 2021; 12:777236. [PMID: 34955923 PMCID: PMC8695844 DOI: 10.3389/fpsyt.2021.777236] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/15/2021] [Accepted: 11/11/2021] [Indexed: 11/13/2022] Open
Abstract
Background: Anxiety disorders (ADs) are a group of disorders with a high disability rate and bring a huge social burden. In China, information on future trends in the disability among community ADs patients and its determinants are rare. The objectives of this study are to describe the future trends in the disability among ADs patients living in community and to investigate the determinants of the disability. Methods: Participants diagnosed with 12-month ADs in the China Mental Health Survey (CMHS) were followed up by telephone from April to June 2018 to assess the future trends in the disability in a 5-year interval using the World Health Organization's Disability Assessment Schedule 2.0. The disability rate was reported and its determinants were analyzed by complex sample design multivariate logistic regression. Results: Totally 271 patients were interviewed by telephone and 33 informants finished proxy interviews. The disability rates were 45.9% and 14.3% among ADs patients at baseline and during the follow-up. Patients with general anxiety disorder (GAD) or agoraphobia with/without panic disorder (AGP) had the lower decrease and higher disability during the follow-up than patients with other subtypes. Patients aged in middle age (aged 40-49 years old, OR = 11.12, 95% CI: 4.16-29.72), having disability at baseline (OR = 7.18, 95% CI: 1.37-37.73), having comorbidity with three or more physical diseases (OR = 9.27, 95% CI: 2.48-34.71), and having comorbidity with other mental disorders (OR = 3.97, 95% CI: 1.13-13.96) had higher disability during the follow-up. Conclusions: The disability rate tends to decrease among ADs patients living in communities. Treatment priority should be given for ADs patients with disability and those in middle age. Treatments for the comorbidity of other mental disorders or physical diseases should be considered when treating anxiety.
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Affiliation(s)
- Zhaorui Liu
- National Clinical Research Center for Mental Disorders & Key Laboratory of Mental Health, Peking University Sixth Hospital (Institute of Mental Health), Ministry of Health (Peking University), Beijing, China
| | - Peijun Li
- Mental Health Center of Tianjin Medical University, Tianjin Anding Hospital, Tianjin, China
| | - Huifang Yin
- Mental Health Center of Tianjin Medical University, Tianjin Anding Hospital, Tianjin, China
| | - Minghui Li
- Mental Health Center of Tianjin Medical University, Tianjin Anding Hospital, Tianjin, China
| | - Jie Yan
- School of Government, Peking University, Beijing, China
| | - Chao Ma
- National Clinical Research Center for Mental Disorders & Key Laboratory of Mental Health, Peking University Sixth Hospital (Institute of Mental Health), Ministry of Health (Peking University), Beijing, China
| | - Hua Ding
- Institute of Social Science Survey, Peking University, Beijing, China
| | - Qiang Li
- Institute of Social Science Survey, Peking University, Beijing, China
| | - Zhengjing Huang
- National Center for Chronic and Noncommunicable Disease Control and Prevention, Beijing, China
| | - Yongping Yan
- Department of Epidemiology, The Fourth Military Medical University, Xi'an, China
| | - Changgui Kou
- Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, Changchun, China
| | - Mi Hu
- Xiangya School of Public Health, Changsha, China
| | - Jing Wen
- Department of Epidemiology and Health Statistics, School of Public Health and Management at Ningxia Medical University, Yinchuan, China
| | - Shulin Chen
- Department of Psychological and Behavior Science, Zhejiang University, Hangzhou, China
| | - Cunxian Jia
- Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University & Shandong University Center for Suicide Prevention Research, Jinan, China
| | - Yueqin Huang
- National Clinical Research Center for Mental Disorders & Key Laboratory of Mental Health, Peking University Sixth Hospital (Institute of Mental Health), Ministry of Health (Peking University), Beijing, China
| | - Guangming Xu
- Mental Health Center of Tianjin Medical University, Tianjin Anding Hospital, Tianjin, China
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17
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Su RC, Huang LH, Li J, Zhou B, Zhao JJ, Li H. The Sichuan Mental Health Survey: Methodology. Front Psychiatry 2021; 12:645355. [PMID: 34603092 PMCID: PMC8484526 DOI: 10.3389/fpsyt.2021.645355] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/23/2020] [Accepted: 08/03/2021] [Indexed: 12/04/2022] Open
Abstract
The Sichuan Mental Health Survey (SMHS) is a provincially representative survey with a coherent methodology to obtain the prevalence of multiple mental disorders and data of services used and to analyze the psychological and social risk factors or correlates in Sichuan, China. Mental disorders include anxiety disorders, mood disorders, schizophrenia, and other psychotic disorders, drug use and alcohol use disorders, impulse control disorder, and eating disorders. A cross-sectional design is employed to sample adults from 200 communities/villages in all 21 prefectural-level municipalities of Sichuan Province in a five-stage provincially representative disproportionate stratified sampling design. The participants need to be interviewed face to face by trained interviewers from local primary healthcare institutions and by psychiatrists. The quality control staff implement data quality control by checking records and statistics in the interview system, and then re-interviewing checks are done by the psychiatrists. Data is weighted to adjust the sample distribution to match the whole population. The outcomes of the SMHS would not only demonstrate the serious challenges posed by the high burdens of mental disorders but also offer baseline data for policymakers and healthcare professionals to study and resolve the factors that influence mental health in Sichuan, China.
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Affiliation(s)
- Rong-Cheng Su
- Key Laboratory of Psychosomatic Medicine, Chinese Academy of Medical Sciences, Chengdu, China.,Sichuan Provincial Center for Mental Health, Sichuan Academy of Medical Sciences and Sichuan Provincial People's Hospital, Chengdu, China
| | - Li-Hong Huang
- Key Laboratory of Psychosomatic Medicine, Chinese Academy of Medical Sciences, Chengdu, China.,Sichuan Provincial Center for Mental Health, Sichuan Academy of Medical Sciences and Sichuan Provincial People's Hospital, Chengdu, China
| | - Jia Li
- Key Laboratory of Psychosomatic Medicine, Chinese Academy of Medical Sciences, Chengdu, China.,Sichuan Provincial Center for Mental Health, Sichuan Academy of Medical Sciences and Sichuan Provincial People's Hospital, Chengdu, China
| | - Bo Zhou
- Key Laboratory of Psychosomatic Medicine, Chinese Academy of Medical Sciences, Chengdu, China.,Sichuan Provincial Center for Mental Health, Sichuan Academy of Medical Sciences and Sichuan Provincial People's Hospital, Chengdu, China
| | - Jia-Jun Zhao
- Key Laboratory of Psychosomatic Medicine, Chinese Academy of Medical Sciences, Chengdu, China.,Sichuan Provincial Center for Mental Health, Sichuan Academy of Medical Sciences and Sichuan Provincial People's Hospital, Chengdu, China
| | - Hui Li
- Key Laboratory of Psychosomatic Medicine, Chinese Academy of Medical Sciences, Chengdu, China.,Sichuan Provincial Center for Mental Health, Sichuan Academy of Medical Sciences and Sichuan Provincial People's Hospital, Chengdu, China
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18
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Yu YH, Peng MM, Bai X, Luo W, Yang X, Li J, Liu B, Thornicroft G, Chan CLW, Ran MS. Schizophrenia, social support, caregiving burden and household poverty in rural China. Soc Psychiatry Psychiatr Epidemiol 2020; 55:1571-1580. [PMID: 32200431 DOI: 10.1007/s00127-020-01864-2] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/21/2019] [Accepted: 03/11/2020] [Indexed: 10/24/2022]
Abstract
PURPOSE Household poverty associated with schizophrenia has been long described. However, the mechanisms by which schizophrenia may have influenced the economic status of a household in rural communities are still unclear. This study aimed to test an integrated model of schizophrenia, social support and caregiving burden on household poverty in a rural community in China. METHODS A mental health survey using identical methods and ICD-10 was conducted in six townships of Xinjin County (population ≥ 15 years old, n = 152,776), Chengdu, China in 2015. Identified persons with schizophrenia (n = 661) and their caregivers completed a joint questionnaire of sociodemographic information, illness conditions, social support and caregiving burden. Descriptive analysis was applied first to give an overview of the dataset. Then, multivariable regression analyses were conducted to examine the associative factors of social support, caregiving burden and household income. Then, structural equation modeling (SEM) was used to estimate the integrated model of schizophrenia, social support, caregiving burden and household income. RESULTS Households with patient being female, married, able to work and having better social function were better off. Larger household size, higher social support and lower caregiving burden also had salient association with higher household income. The relationship between schizophrenia and household poverty appeared to be mediated by the impacts of schizophrenia on social support and caregiving burden. CONCLUSION There was a strong association between schizophrenia and household poverty, in which social support and caregiving burden may had played significant roles on mediating it. More precise poverty alleviation policies and interventions should focus on supporting recovery for persons with schizophrenia, as well as on increasing social support and on reducing family caregiving burden.
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Affiliation(s)
- Yue-Hui Yu
- Department of Social Work and Social Administration, The University of Hong Kong, Hong Kong, China
| | - Man-Man Peng
- Department of Social Work and Social Administration, The University of Hong Kong, Hong Kong, China
| | - Xue Bai
- Department of Applied Social Sciences, The Hong Kong Polytechnic University, Hong Kong, China
| | - Wei Luo
- Xinjin Second People's Hospital, Xinjin, 611432, Chengdu, China
| | - Xin Yang
- Guangyuan Mental Health Center, Guangyuan, 628000, China
| | - Jun Li
- Sichuan Veteran Hospital, Yuantong, Sichuan, China
| | - Bo Liu
- Jingzhou Mental Health Center, Jingzhou, 434000, Hubei, China
| | - Graham Thornicroft
- Centre for Global Mental Health, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Cecilia Lai Wan Chan
- Department of Social Work and Social Administration, The University of Hong Kong, Hong Kong, China
| | - Mao-Sheng Ran
- Department of Social Work and Social Administration, The University of Hong Kong, Hong Kong, China.
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19
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Tan W, Lin H, Lei B, Ou A, He Z, Yang N, Jia F, Weng H, Hao T. The psychosis analysis in real-world on a cohort of large-scale patients with schizophrenia. BMC Med Inform Decis Mak 2020; 20:132. [PMID: 32646484 PMCID: PMC7477870 DOI: 10.1186/s12911-020-1125-0] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022] Open
Abstract
Background With China experiencing unprecedented economic development and social change over the past three decades, Chinese policy makers and health care professionals have come to view mental health as an important outcome to monitor. Our study conducted an epidemiological study of psychosis in Guangdong province, with 20 million real-world follow-up records in the last decade. Methods Data was collected from Guangdong mental health information platform from 2010 to 2019, which had standardized disease registration and follow-up management for nearly 600,000 patients with six categories of mental diseases and 400,000 patients with schizophrenia. We conducted clinical staging for the disease course of the patients and divided the data with various factors into different stages of disease. Quantitative analysis was utilized to investigate the high relevant indicators to the disease. The results were projected on geography map for regional distribution analysis. Results The majority cases of mental disease incidence were between the age of 15 and 29, while the peak age for both male and female was between 20 to 24 years old. The disease course with the largest number of patients’ cases was between 5 to 10 years. The therapeutic effect of patients gradually decreased with the development of disease course, while the risk increased with the disease course. The analysis of influencing factors showed that poor economic conditions incurred higher risk scores, and good medication adherence was effective in improving treatment outcomes. In addition, receiving good education contributed to the reduction of the risk of schizophrenia and the improvement of the efficiency of early treatment. Through the analysis of regional distribution of schizophrenia disease, developed economic conditions and favorable resource conditions could promote the reduction of disease risk, while in economically backward regions, it often accompanied with lower therapeutic effect and higher disease risk. Conclusions Certain demographic factors had a relatively prominent impact on the therapeutic effect and risk of schizophrenia, such as high-quality medication adherence. Therapeutic effect and risk were highly correlated. Backward economic conditions often associated with poor efficacy and higher risk assessment, and the developed economy and better medical resource are beneficial for the treatment of psychotic.
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Affiliation(s)
- Wenyan Tan
- Guangdong Mental Health Center, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Science, Guangzhou, China
| | - Haicheng Lin
- Guangdong Mental Health Center, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Science, Guangzhou, China
| | - Baoxin Lei
- School of Computer Science, South China Normal University, Guangzhou, China
| | - Aihua Ou
- Department of Big Data Research of Medicine, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Zehui He
- Department of Big Data Research of Medicine, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Ning Yang
- The Affiliated Brain Hospital of Guangzhou Medical University (Guangzhou Huiai Hospital), Guangzhou, China
| | - Fujun Jia
- Guangdong Mental Health Center, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Science, Guangzhou, China.
| | - Heng Weng
- Department of Big Data Research of Medicine, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China.
| | - Tianyong Hao
- School of Computer Science, South China Normal University, Guangzhou, China.
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20
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Badu E, O’Brien AP, Mitchell R, Osei A. Mediation and moderation effects of health system structure and process on the quality of mental health services in Ghana - structural equation modelling. PLoS One 2020; 15:e0233351. [PMID: 32442192 PMCID: PMC7244180 DOI: 10.1371/journal.pone.0233351] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2020] [Accepted: 05/04/2020] [Indexed: 11/19/2022] Open
Abstract
INTRODUCTION Incorporating consumers' perspectives into the quality of mental health service measurement is a growing priority among mental health professionals' and policymakers. Despite this, there is limited empirical evidence related to consumer perspectives of quality of mental health services. This study, therefore, aims to measure the mediation and moderation effects of health system structure and process on mental health quality in Ghana. METHODS A random sample of 510 consumers were recruited to complete the Verona Satisfaction Scale (54-items), together with the WHO Disability Assessment Instrument (36 items) using the Redcap application. Confirmatory factor analysis (CFA) and Structural Equation Modelling were used to test the hypothesised theory using STATA 15. RESULTS The CFA showed that the hypothesised model had a good fit to the data. The findings confirmed the hypothesis that the process constructs mediate the relationship between the health system structure and the outcome of mental health services. Specifically, the health system structure had a positive and significant causal relationship with the mediator-process (β = 0.60; p<0.01) and outcome (β = 0.47; p<0.01). Additionally, the mediator-process had a positive causal relationship with the outcome of the mental health services (β = 0.32; p<0.01). Insurance status (β = 0.07; p>0.05) and type of services (β = 0.025; p>0.05) had a positive moderating effect on the relationship between health system structure and outcome but were not significant. CONCLUSION Improvements to mental health system structure and the process could promote the quality of services as experienced by consumers. Government stakeholders are encouraged to accordingly strengthen health systems with the aim of improving the mental health outcomes for consumers.
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Affiliation(s)
- Eric Badu
- School of Nursing and Midwifery, Faculty Health and Medicine, The University of Newcastle, Newcastle, Australia
- * E-mail: ,
| | - Anthony Paul O’Brien
- School Nursing and Midwifery, Faculty Health and Medicine, University of Newcastle, Newcastle, Australia
| | - Rebecca Mitchell
- Macquarie Business School, Macquarie University, Sydney, Australia
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21
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Li M, Huang Y, Liu Z, Shen R, Chen H, Ma C, Zhang T, Li S, Prince M. The association between frailty and incidence of dementia in Beijing: findings from 10/66 dementia research group population-based cohort study. BMC Geriatr 2020; 20:138. [PMID: 32293307 PMCID: PMC7158148 DOI: 10.1186/s12877-020-01539-2] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2019] [Accepted: 03/29/2020] [Indexed: 01/01/2023] Open
Abstract
BACKGROUND The relationship between frailty and dementia is unclear and there are very few population-based studies regarding this issue in China. The purpose of this study is to estimate the association between frailty and incident dementia in China, and to explore different effects of frailty established by three definitions of frailty on dementia incidence. METHODS A five-year prospective cohort study was carried out in 2022 participants aged 65 years and over in urban and rural sites in Beijing, China. The participants were interviewed by trained community primary health care workers from 2004 to 2009. Frailty was defined using modified Fried frailty phenotype, physical frailty definition, and multidimensional frailty definition. Dementia was diagnosed using the 10/66 dementia criterion for calculating cumulative incidence. Both competing risk regression models and Cox proportional hazards models were applied to examine the associations between frailty at baseline and five-year cumulative incidence of dementia. RESULTS At the end of follow-up the five-year cumulative incidence rates of dementia with frailty and without frailty defined by the modified Fried frailty were 21.0% and 9.6%, those defined by the physical frailty were 19.9% and 9.0%, and those defined by the multidimensional frailty were 22.8% and 8.9%, respectively. Compared with non-frail participants, frail people had a higher risk of incident dementia using multidimensional frailty definition after adjusting covariates based on competing risk regression model (HR = 1.47, 95% CI 1.01~2.17) and Cox proportional hazards model (HR = 1.56, 95% CI 1.07~2.26). The association between frailty and incident dementia was statistically significant in participants in the upper three quartiles of age (aged 68 years and over) using the multidimensional frailty definition based on the competing risk regression model (HR = 1.61, 95% CI 1.06~2.43) and Cox proportional hazard model (HR = 1.76, 95% CI 1.19~2.61). CONCLUSIONS Multidimensional frailty may play an inherent role in incident dementia, especially in the people aged over 68, which is significant for distinguishing high risk people and determining secondary prevention strategies for dementia patients.
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Affiliation(s)
- Minghui Li
- Peking University Sixth Hospital, Peking University Institute of Mental Health, National Health Committee Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Yueqin Huang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, National Health Committee Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China.
| | - Zhaorui Liu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, National Health Committee Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China.
| | - Rui Shen
- Peking University Sixth Hospital, Peking University Institute of Mental Health, National Health Committee Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Hongguang Chen
- Peking University Sixth Hospital, Peking University Institute of Mental Health, National Health Committee Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Chao Ma
- Peking University Sixth Hospital, Peking University Institute of Mental Health, National Health Committee Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Tingting Zhang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, National Health Committee Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Shuran Li
- Peking University Sixth Hospital, Peking University Institute of Mental Health, National Health Committee Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Martin Prince
- Global Health Institute, King's College London, London, UK
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Li H, Cheng X, Zhang D, Wang M, Dong W, Feng W. A UPLC-MS/MS Assay for Simultaneous Determination of Two Antipsychotics and Two Antidepressants in Human Plasma and Its Application in Clinic. Curr Pharm Biotechnol 2020; 21:60-69. [PMID: 31470784 DOI: 10.2174/1389201020666190830150549] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2019] [Revised: 05/22/2019] [Accepted: 08/16/2019] [Indexed: 11/22/2022]
Abstract
BACKGROUND Antidepressants and antipsychotics are widely prescribed drugs for the treatment of mental diseases. Therapeutic drug monitoring (TDM) is recommended for patients taking these drugs to ensure pharmaceutical efficacy, medication compliance and prevent toxicity. OBJECTIVE An ultra-high performance liquid chromatography/tandem-mass spectrometry (UPLC-MS/ MS) method was developed for simultaneous determination of two Antidepressants-Fluoxetine (FLU) and Escitalopram (ESC), and two antipsychotics-risperidone (RIS) and aripiprazole (ARI), in human plasma. METHODS The sample was processed by simple protein precipitation and the targeted analytes were separated on a C18 column by gradient elution with a mobile phase containing 0.1% formic acid (v/v) and acetonitrile. All the analytes were qualitative and quantitative measured by electrospray ionization source with Multiple Reaction Monitoring (MRM) in positive ion mode. A total of 56 plasma samples were obtained from out- or in-patients who were taking the cited four drugs for further analysis. RESULTS The calibration curves for FLU, ESC, RIS and ARI were linear in the range of 45-1800, 4-320, 2-200 and 50-1800 ng/mL, respectively. The entire analytical time for the analytes was 7.0 min for each run and the extraction efficiency was more than 90%. The sample was stable within various storage conditions. The trough concentrations in patients were measured with the validated method. CONCLUSION The developed method was successfully used for simultaneous determination of FLU, ESC, RIS and ARI in the plasma of the patients, which provides effective technical support for routine TDM of these four drugs and is of great clinic value for individual therapy.
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Affiliation(s)
- Houli Li
- Department of Pharmacy, First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Xiaoliang Cheng
- Department of Pharmacy, First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Di Zhang
- Department of Pharmacy, First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Maoyi Wang
- Department of Pharmacy, First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Weihua Dong
- Department of Pharmacy, First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Weiyi Feng
- Department of Pharmacy, First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
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Xu Y, Wang Y, Chen J, He Y, Zeng Q, Huang Y, Xu X, Lu J, Wang Z, Sun X, Chen J, Yan F, Li T, Guo W, Xu G, Tian H, Xu X, Ma Y, Wang L, Zhang M, Yan Y, Wang B, Xiao S, Zhou L, Li L, Zhang Y, Chen H, Zhang T, Yan J, Ding H, Yu Y, Kou C, Jia F, Liu J, Chen Z, Zhang N, Du X, Du X, Wu Y, Li G. The comorbidity of mental and physical disorders with self-reported chronic back or neck pain: Results from the China Mental Health Survey. J Affect Disord 2020; 260:334-341. [PMID: 31521871 DOI: 10.1016/j.jad.2019.08.089] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/26/2019] [Revised: 08/24/2019] [Accepted: 08/28/2019] [Indexed: 11/17/2022]
Abstract
BACKGROUND To investigate mental and physical health comorbidity with chronic back or neck pain in the Chinese population, and assess the level of disability associated with chronic back or neck pain. METHODS Data were derived from a large-scale and nationally representative community survey of adult respondents on mental health disorders in China (n = 28,140). Chronic back or neck pain, other chronic pain conditions and chronic physical conditions were assessed by self-report. Mental disorders were assessed by the Composite International Diagnostic Interview (CIDI). Role disability during the past 30 days was assessed with the World Health Organization Disability Assessment Schedule (WHO-DAS-II). RESULTS The 12-month prevalence of chronic back or neck pain was 10.8%. Most of respondents with chronic back or neck pain (71.2%) reported at least one other comorbid condition, including other chronic pain conditions (53.4%), chronic physical conditions (37.9%), and mental disorders (23.9%). It was found by logistic regression that mood disorders (OR = 3.7, 95%CI:2.8-4.8) showed stronger association with chronic back or neck pain than anxiety disorders and substance disorders. Most common chronic pains and physical conditions were significantly associated with chronic back or neck pain. Chronic back or neck pain was associated with role disability after controlling for demographics and for comorbidities. Physical and mental comorbidities explained 0.7% of the association between chronic back or neck pain and role disability. CONCLUSIONS Chronic back or neck pain and physical-mental comorbidity is very common in China and chronic back or neck pain may increase the likelihood of other physical and mental diseases. This presents a great challenge for both clinical treatment and public health education. We believe that further study needs to be conducted to improve the diagnostic and management skills for comorbidity conditions.
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Affiliation(s)
- Yifeng Xu
- Shanghai Mental Health Center, Shanghai JiaoTong University School of Medicine, Shanghai Key Laboratory of Psychotic Disorders, Shanghai, China
| | - Yan Wang
- Shanghai Mental Health Center, Shanghai JiaoTong University School of Medicine, Shanghai Key Laboratory of Psychotic Disorders, Shanghai, China
| | - Jianhua Chen
- Shanghai Mental Health Center, Shanghai JiaoTong University School of Medicine, Shanghai Key Laboratory of Psychotic Disorders, Shanghai, China
| | - Yanling He
- Shanghai Mental Health Center, Shanghai JiaoTong University School of Medicine, Shanghai Key Laboratory of Psychotic Disorders, Shanghai, China
| | - Qingzhi Zeng
- Shanghai Mental Health Center, Shanghai JiaoTong University School of Medicine, Shanghai Key Laboratory of Psychotic Disorders, Shanghai, China
| | - Yueqin Huang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing 100191, China.
| | - Xiufeng Xu
- Department of Psychiatry, The First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Jin Lu
- Department of Psychiatry, The First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Zhizhong Wang
- Department of Epidemiology and Statistics, School of Public Health, Ningxia Medical University, Yinchuan, China
| | - Xian Sun
- Department of Epidemiology and Statistics, School of Public Health, Ningxia Medical University, Yinchuan, China
| | - Jing Chen
- Shanghai Mental Health Center, Shanghai JiaoTong University School of Medicine, Shanghai Key Laboratory of Psychotic Disorders, Shanghai, China
| | - Feng Yan
- Shanghai Mental Health Center, Shanghai JiaoTong University School of Medicine, Shanghai Key Laboratory of Psychotic Disorders, Shanghai, China
| | - Tao Li
- Mental Health Centre, West China Hospital, Sichuan University, Chengdu, China
| | - Wanjun Guo
- Mental Health Centre, West China Hospital, Sichuan University, Chengdu, China
| | | | | | - Xiangdong Xu
- The Fourth People's Hospital in Urumqi, Urumqi, China
| | - Yanjuan Ma
- The Fourth People's Hospital in Urumqi, Urumqi, China
| | - Limin Wang
- National Center for Chronic and NonCommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Mei Zhang
- National Center for Chronic and NonCommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Yongping Yan
- Department of Epidemiology, Air Force Medical University of the Chinese People's Liberation Army, Xi'an, China
| | - Bo Wang
- Department of Epidemiology, Air Force Medical University of the Chinese People's Liberation Army, Xi'an, China
| | - Shuiyuan Xiao
- Department of Social Medicine and Health Management, School of Public Health, Central South University, Changsha, China
| | - Liang Zhou
- Department of Social Medicine and Health Management, School of Public Health, Central South University, Changsha, China
| | - Lingjiang Li
- Mental Health Institute, the Second Xiangya Hospital, Central-south University, Changsha, China
| | - Yan Zhang
- Mental Health Institute, the Second Xiangya Hospital, Central-south University, Changsha, China
| | - Hongguang Chen
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing 100191, China
| | - Tingting Zhang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing 100191, China
| | - Jie Yan
- Department of Biostatistics, School of Public Health, School of Government, and Institute of Social Science Survey, Peking University, Beijing, China
| | - Hua Ding
- Department of Biostatistics, School of Public Health, School of Government, and Institute of Social Science Survey, Peking University, Beijing, China
| | - Yaqin Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, Changchun, China
| | - Changgui Kou
- Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, Changchun, China
| | - Fujun Jia
- Guangdong Mental Health Center, Guangzhou, China
| | - Jian Liu
- The Seventh Hospital of Hangzhou, Hangzhou, China
| | - Zheli Chen
- Huzhou Third People's Hospital, Huzhou, China
| | - Ning Zhang
- Nanjing Brain Hospital Affiliated to Nanjing Medical University, Nanjing, China
| | - Xinbai Du
- The Third People's Hospital of Qinghai Province, Xining, China
| | - Xiangdong Du
- Suzhou Psychiatric Hospital, The Affiliated Guangji Hospital of Soochow University, Suzhou, China
| | - Yue Wu
- Wuxi Mental Health Center, Nanjing Medical University, Wuxi, China
| | - Guohua Li
- Chifeng Anding Hospital, Chifeng, China
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Song X, Anderson T, Himawan L, McClintock A, Jiang Y, McCarrick S. An Investigation of a Cultural Help-Seeking Model for Professional Psychological Services With U.S. and Chinese Samples. JOURNAL OF CROSS-CULTURAL PSYCHOLOGY 2019. [DOI: 10.1177/0022022119878506] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Help-seeking processes for participants in the People’s Republic of China and the United States were modeled in the present study. The decision to seek professional services for mental health problems (e.g., psychotherapy) has been primarily studied by applying principles from the theory of planned behavior and reasoned action (TPB). Application of the TPB has commonly been used with a three-level empirical model of help-seeking, whereby expectations/barriers to help-seeking predict attitudes toward therapy, which in turn predicts intentions and behaviors to seek professional help. Informed by the TPB, the present study added a cultural-contextual level to the model to account for the role of cultural identity variables, which included independent and interdependent self-construal as well as gender. The resulting four-level model, the cultural help-seeking (CHS) model, was compared with the conventional three-level help-seeking model using data collected from 296 college students from Mainland China and 334 college students from the United States. Separate analyses were conducted for the Chinese group and American group. Chinese versions of the questionnaires were developed for the present study using translation and back-translation procedures. Using structural regression modeling, the four-level CHS model provided a better fit than the three-level traditional model for both the U.S. and Chinese samples. However, the specific decisional pathways within this four-level model were structurally different for the U.S. and Chinese samples. Findings suggest that including cultural-contextual variables as a first level of the professional help-seeking model is supported by both samples.
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Badu E, O’Brien AP, Mitchell R. An integrative review on methodological considerations in mental health research - design, sampling, data collection procedure and quality assurance. Arch Public Health 2019; 77:37. [PMID: 31624592 PMCID: PMC6785873 DOI: 10.1186/s13690-019-0363-z] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2018] [Accepted: 07/22/2019] [Indexed: 01/30/2023] Open
Abstract
BACKGROUND Several typologies and guidelines are available to address the methodological and practical considerations required in mental health research. However, few studies have actually attempted to systematically identify and synthesise these considerations. This paper provides an integrative review that identifies and synthesises the available research evidence on mental health research methodological considerations. METHODS A search of the published literature was conducted using EMBASE, Medline, PsycINFO, CINAHL, Web of Science, and Scopus. The search was limited to papers published in English for the timeframe 2000-2018. Using pre-defined inclusion and exclusion criteria, three reviewers independently screened the retrieved papers. A data extraction form was used to extract data from the included papers. RESULTS Of 27 papers meeting the inclusion criteria, 13 focused on qualitative research, 8 mixed methods and 6 papers focused on quantitative methodology. A total of 14 papers targeted global mental health research, with 2 papers each describing studies in Germany, Sweden and China. The review identified several methodological considerations relating to study design, methods, data collection, and quality assurance. Methodological issues regarding the study design included assembling team members, familiarisation and sharing information on the topic, and seeking the contribution of team members. Methodological considerations to facilitate data collection involved adequate preparation prior to fieldwork, appropriateness and adequacy of the sampling and data collection approach, selection of consumers, the social or cultural context, practical and organisational skills; and ethical and sensitivity issues. CONCLUSION The evidence confirms that studies on methodological considerations in conducting mental health research largely focus on qualitative studies in a transcultural setting, as well as recommendations derived from multi-site surveys. Mental health research should adequately consider the methodological issues around study design, sampling, data collection procedures and quality assurance in order to maintain the quality of data collection.
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Affiliation(s)
- Eric Badu
- School of Nursing and Midwifery, The University of Newcastle, Callaghan, Australia
| | - Anthony Paul O’Brien
- Faculty of Health and Medicine, School Nursing and Midwifery, University of Newcastle, Callaghan, Australia
| | - Rebecca Mitchell
- Faculty of Business and Economics, Macquarie University, North Ryde, Australia
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Prevalence of mental disorders in China. Lancet Psychiatry 2019; 6:467-468. [PMID: 31122475 DOI: 10.1016/s2215-0366(19)30128-2] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/27/2019] [Revised: 02/28/2019] [Accepted: 03/25/2019] [Indexed: 11/24/2022]
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Huang Y, Wang Y, Wang H, Liu Z, Yu X, Yan J, Yu Y, Kou C, Xu X, Lu J, Wang Z, He S, Xu Y, He Y, Li T, Guo W, Tian H, Xu G, Xu X, Ma Y, Wang L, Wang L, Yan Y, Wang B, Xiao S, Zhou L, Li L, Tan L, Zhang T, Ma C, Li Q, Ding H, Geng H, Jia F, Shi J, Wang S, Zhang N, Du X, Du X, Wu Y. Prevalence of mental disorders in China: a cross-sectional epidemiological study. Lancet Psychiatry 2019; 6:211-224. [PMID: 30792114 DOI: 10.1016/s2215-0366(18)30511-x] [Citation(s) in RCA: 1288] [Impact Index Per Article: 214.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/02/2018] [Revised: 12/07/2018] [Accepted: 12/07/2018] [Indexed: 02/05/2023]
Abstract
BACKGROUND The China Mental Health Survey was set up in 2012 to do a nationally representative survey with consistent methodology to investigate the prevalence of mental disorders and service use, and to analyse their social and psychological risk factors or correlates in China. This paper reports the prevalence findings. METHODS We did a cross-sectional epidemiological survey of the prevalence of mental disorders (mood disorders, anxiety disorders, alcohol-use and drug-use disorders, schizophrenia and other psychotic disorders, eating disorder, impulse-control disorder, and dementia) in a multistage clustered-area probability sample of adults from 157 nationwide representative population-based disease surveillance points in 31 provinces across China. Face-to-face interviews were done with a two-stage design by trained lay interviewers and psychiatrists with the Composite International Diagnostic Interview, the Structured Clinical Interview for DSM-IV Axis I disorders, the Community Screening Instrument for Dementia from the 10/66 dementia diagnostic package, and the Geriatric Mental State Examination. Data-quality control procedures included logic check by computers, sequential recording check, and phone-call check by the quality controllers, and reinterview check by the psychiatrists. Data were weighted to adjust for differential probabilities of selection and differential response as well as to post-stratify the sample to match the population distribution. FINDINGS 32 552 respondents completed the survey between July 22, 2013, and March 5, 2015. The weighted prevalence of any disorder (excluding dementia) was 9·3% (95% CI 5·4-13·3) during the 12 months before the interview and 16·6% (13·0-20·2) during the participants' entire lifetime before the interview. Anxiety disorders were the most common class of disorders both in the 12 months before the interview (weighted prevalence 5·0%, 4·2-5·8) and in lifetime (7·6%, 6·3-8·8). The weighted prevalence of dementia in people aged 65 years or older was 5·6% (3·5-7·6). INTERPRETATION The prevalence of most mental disorders in China in 2013 is higher than in 1982 (point prevalence 1·1% and lifetime prevalence 1·3%), 1993 (point prevalence 1·1% and lifetime prevalence 1·4%), and 2002 (12-month prevalence 7·0% and lifetime prevalence 13·2%), but lower than in 2009 (1-month prevalence 17·5%). The evidence from this survey poses serious challenges related to the high burdens of disease identified, but also offers valuable opportunities for policy makers and health-care professionals to explore and address the factors that affect mental health in China. FUNDING National Health Commission of Health (Ministry of Health) and Ministry of Science and Technology of China.
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Affiliation(s)
- Yueqin Huang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China.
| | - Yu Wang
- National Center for Chronic and Non-Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Hong Wang
- Department of Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Zhaorui Liu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Xin Yu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Jie Yan
- School of Government, Peking University, Beijing, China
| | - Yaqin Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, Changchun, China
| | - Changgui Kou
- Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, Changchun, China
| | - Xiufeng Xu
- Department of Psychiatry, The First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Jin Lu
- Department of Psychiatry, The First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Zhizhong Wang
- Department of Epidemiology and Statistics, School of Public Health, Ningxia Medical University, Yinchuan, China
| | - Shulan He
- Department of Epidemiology and Statistics, School of Public Health, Ningxia Medical University, Yinchuan, China
| | - Yifeng Xu
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yanling He
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Tao Li
- Mental Health Centre, West China Hospital, Sichuan University, Chengdu, China
| | - Wanjun Guo
- Mental Health Centre, West China Hospital, Sichuan University, Chengdu, China
| | | | | | - Xiangdong Xu
- The Fourth People's Hospital in Urumqi, Urumqi, China
| | - Yanjuan Ma
- The Fourth People's Hospital in Urumqi, Urumqi, China
| | - Linhong Wang
- National Center for Chronic and Non-Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Limin Wang
- National Center for Chronic and Non-Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Yongping Yan
- Department of Epidemiology, Air Force Medical University of the Chinese People's Liberation Army, Xi'an, China
| | - Bo Wang
- Department of Epidemiology, Air Force Medical University of the Chinese People's Liberation Army, Xi'an, China
| | - Shuiyuan Xiao
- Department of Social Medicine and Health Management, School of Public Health, Central South University, Changsha, China
| | - Liang Zhou
- Department of Social Medicine and Health Management, School of Public Health, Central South University, Changsha, China
| | - Lingjiang Li
- Mental Health Institute, the Second Xiangya Hospital, Central-south University, Changsha, China
| | - Liwen Tan
- Mental Health Institute, the Second Xiangya Hospital, Central-south University, Changsha, China
| | - Tingting Zhang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Chao Ma
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Qiang Li
- Institute of Social Science Survey, Peking University, Beijing, China
| | - Hua Ding
- Institute of Social Science Survey, Peking University, Beijing, China
| | | | - Fujun Jia
- Guangdong Mental Health Center, Guangzhou, China
| | - Jianfei Shi
- The Seventh Hospital of Hangzhou, Hangzhou, China
| | | | - Ning Zhang
- Nanjing Brain Hospital Affiliated to Nanjing Medical University, Nanjing, China
| | - Xinbai Du
- The Third People's Hospital of Qinghai Province, Xining, China
| | - Xiangdong Du
- Suzhou Psychiatric Hospital, The Affiliated Guangji Hospital of Soochow University, Suzhou, China
| | - Yue Wu
- Wuxi Mental Health Center, Nanjing Medical University, Wuxi, China
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Liang D, Mays VM, Hwang WC. Integrated mental health services in China: challenges and planning for the future. Health Policy Plan 2018; 33:107-122. [PMID: 29040516 DOI: 10.1093/heapol/czx137] [Citation(s) in RCA: 146] [Impact Index Per Article: 20.9] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/11/2017] [Indexed: 11/12/2022] Open
Abstract
Eager to build an integrated community-based mental health system, in 2004 China started the '686 Programme', whose purpose was to integrate hospital and community services for patients with serious mental illness. In 2015, the National Mental Health Working Plan (2015-2020) proposed an ambitious strategy for implementing this project. The goal of this review is to assess potential opportunities for and barriers to successful implementation of a community-based mental health system that integrates hospital and community mental health services into the general healthcare system. We examine 7066 sources in both English and Chinese: the academic peer-reviewed literature, the grey literature on mental health policies, and documents from government and policymaking agencies. Although China has proposed a number of innovative programmes to address its mental health burden, several of these proposals have yet to be fully activated, particularly those that focus on integrated care. Integrating mental health services into China's general healthcare system holds great promise for increased access to and quality improvement in mental health services, as well as decreased stigma and more effective management of physical and mental health comorbidities. This article examines the challenges to integrating mental health services into China's general healthcare system, especially in the primary care sphere, including: accurately estimating mental health needs, integrating mental and physical healthcare, increasing workforce development and training, resolving interprofessional issues, financing and funding, developing an affordable and sustainable mental health system, and delivering care to specific subpopulations to meet the needs of China's diverse populace. As China's political commitment to expanding its mental health system is rapidly evolving, we offer suggestions for future directions in addressing China's mental health needs.
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Affiliation(s)
- Di Liang
- Department of Health Policy and Management in the UCLA Fielding School of Public Health, 650 Charles Young Dr. S., 31-269 CHS Box 951772, Los Angeles, CA 90095-1772, USA
| | - Vickie M Mays
- Department of Psychology, Department of Health Policy and Management in the UCLA Fielding School of Public Health, and UCLA BRITE Center for Science, Research and Policy, 1285 Franz Hall, Box 951563, Los Angeles, CA 90095-1563, USA
| | - Wei-Chin Hwang
- Department of Psychology, Claremont McKenna College, 850 Columbia Ave, Claremont, CA 91711, USA
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Xiang YT, Ng CH, Yu X, Wang G. Rethinking progress and challenges of mental health care in China. World Psychiatry 2018; 17:231-232. [PMID: 29856546 PMCID: PMC5980243 DOI: 10.1002/wps.20500] [Citation(s) in RCA: 78] [Impact Index Per Article: 11.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
Affiliation(s)
- Yu-Tao Xiang
- Faculty of Health Sciences, University of Macau, Macao SAR, China
- National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China
| | - Chee H Ng
- Department of Psychiatry, University of Melbourne, Melbourne, Australia
| | - Xin Yu
- Peking University Institute of Mental Health, Beijing, China
| | - Gang Wang
- National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China
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