1
|
Chen L, Huai C, Song C, Wu S, Xu Y, Yi Z, Tang J, Fan L, Wu X, Ge Z, Liu C, Jiang D, Weng S, Wang G, Zhang X, Zhao X, Shen L, Zhang N, Wu H, Wang Y, Guo Z, Zhang S, Jiang B, Zhou W, Ma J, Li M, Chu Y, Zhou C, Lv Q, Xu Q, Zhu W, Zhang Y, Lian W, Liu S, Li X, Gao S, Liu A, He L, Yang Z, Dai B, Ye J, Lin R, Lu Y, Yan Q, Hu Y, Xing Q, Huang H, Qin S. Refining antipsychotic treatment strategies in schizophrenia: discovery of genetic biomarkers for enhanced drug response prediction. Mol Psychiatry 2024:10.1038/s41380-024-02841-w. [PMID: 39562719 DOI: 10.1038/s41380-024-02841-w] [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] [Received: 04/04/2024] [Revised: 11/06/2024] [Accepted: 11/11/2024] [Indexed: 11/21/2024]
Abstract
Schizophrenia (SCZ) is a severe mental disorder affecting around 1% of individuals worldwide. The variability in response to antipsychotic drugs (APDs) among SCZ patients presents a significant challenge for clinicians in determining the most effective medication. In this study, we investigated the biological markers and established a predictive model for APD response based on a large-scale genome-wide association study using 3269 Chinese schizophrenia patients. Each participant underwent an 8-week treatment regimen with one of five mono-APDs: olanzapine, risperidone, aripiprazole, quetiapine, or amisulpride. By dividing the response into ordinal groups of "high", "medium", and "low", we mitigated the bias of unclear treatment outcome and identified three novel significantly associated genetic loci in or near CDH12, WDR11, and ELAVL2. Additionally, we developed predictive models of response to each specific APDs, with accuracies ranging from 79.5% to 98.0%. In sum, we established an effective method to predict schizophrenia patients' response to APDs across three categories, integrating novel biomarkers to guide personalized medicine strategies.
Collapse
Affiliation(s)
- Luan Chen
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Shanghai Jiao Tong University, Shanghai, China
| | - Cong Huai
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Shanghai Jiao Tong University, Shanghai, China
| | - Chuanfu Song
- The Fourth People's Hospital of Wuhu, Wuhu, China
| | - Shaochang Wu
- The Second People's Hospital of Lishui, Lishui, China
| | - Yong Xu
- Shanxi Key Laboratory of Artificial Intelligence Assisted Diagnosis and Treatment for Mental Disorder, First Hospital of Shanxi Medical University, Taiyuan, China
- Department of Clinical Psychology, The Eighth Affiliated Hospital, Sun Yat-Sen University, Shenzhen City, Guangdong Province, China
| | - Zhenghui Yi
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jinsong Tang
- Department of Psychiatry, Sir Run-Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Lingzi Fan
- The Affiliated Encephalopathy Hospital of Zhengzhou University, Zhumadian Second People's Hospital, Zhumadian, China
| | - Xuming Wu
- Jiangsu Nantong Fourth People's Hospital, Nantong, Jiangsu Province, China
| | - Zhenhua Ge
- Jiangsu Nantong Fourth People's Hospital, Nantong, Jiangsu Province, China
| | - Chuanxin Liu
- Department of Psychiatry, Jining Medical University School of Mental Health, Jining, China
| | - Deguo Jiang
- Wenzhou Seventh People's Hospital, Wenzhou, China
| | - Saizheng Weng
- Fuzhou Neuro-psychiatric Hospital Affiliated to Fujian Medical University, Fuzhou, China
| | - Guoqiang Wang
- Wuxi Mental Health Center Affiliated to Nanjing Medical University, Wuxi, China
| | | | - Xudong Zhao
- Shanghai Pudong New Area Mental Health Center, Tongji University School of Medicine, Shanghai, China
| | - Lu Shen
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Shanghai Jiao Tong University, Shanghai, China
- Institutes of Biomedical Sciences, Fudan University, Shanghai, China
| | - Na Zhang
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Shanghai Jiao Tong University, Shanghai, China
- Shanghai Jiao Tong University Sichuan Research Institute (SJTUSRI), Chengdu, Sichuan Province, China
| | - Hao Wu
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Shanghai Jiao Tong University, Shanghai, China
| | - Yongzhi Wang
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Shanghai Jiao Tong University, Shanghai, China
| | - Zhenglin Guo
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Suli Zhang
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Shanghai Jiao Tong University, Shanghai, China
| | - Bixuan Jiang
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Shanghai Jiao Tong University, Shanghai, China
| | - Wei Zhou
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Shanghai Jiao Tong University, Shanghai, China
- Ministry of Education-Shanghai Key Laboratory of Children's Environmental Health & Department of Developmental and Behavioural Paediatric & Child Primary Care, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jingsong Ma
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Shanghai Jiao Tong University, Shanghai, China
| | - Mo Li
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Shanghai Jiao Tong University, Shanghai, China
| | - Yunpeng Chu
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Shanghai Jiao Tong University, Shanghai, China
| | - Chenxi Zhou
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Shanghai Jiao Tong University, Shanghai, China
| | - Qinyu Lv
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Qingqing Xu
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Wenli Zhu
- The Fourth People's Hospital of Wuhu, Wuhu, China
| | - Yan Zhang
- The Second People's Hospital of Lishui, Lishui, China
| | - Weibin Lian
- The Second People's Hospital of Lishui, Lishui, China
| | - Sha Liu
- Shanxi Key Laboratory of Artificial Intelligence Assisted Diagnosis and Treatment for Mental Disorder, First Hospital of Shanxi Medical University, Taiyuan, China
| | - Xinrong Li
- Shanxi Key Laboratory of Artificial Intelligence Assisted Diagnosis and Treatment for Mental Disorder, First Hospital of Shanxi Medical University, Taiyuan, China
| | - Songyin Gao
- The Affiliated Encephalopathy Hospital of Zhengzhou University, Zhumadian Second People's Hospital, Zhumadian, China
| | - Aihong Liu
- The Affiliated Encephalopathy Hospital of Zhengzhou University, Zhumadian Second People's Hospital, Zhumadian, China
| | - Lei He
- The Affiliated Encephalopathy Hospital of Zhengzhou University, Zhumadian Second People's Hospital, Zhumadian, China
| | - Zhenzhen Yang
- Department of Psychiatry, Jining Medical University School of Mental Health, Jining, China
| | - Bojian Dai
- Wenzhou Seventh People's Hospital, Wenzhou, China
| | - Jiaen Ye
- Wenzhou Seventh People's Hospital, Wenzhou, China
| | - Ruiqian Lin
- Fuzhou Neuro-psychiatric Hospital Affiliated to Fujian Medical University, Fuzhou, China
| | - Yana Lu
- Wuxi Mental Health Center Affiliated to Nanjing Medical University, Wuxi, China
| | - Qi Yan
- Jiangsu Nantong Fourth People's Hospital, Nantong, Jiangsu Province, China
| | - Yalan Hu
- Jiangsu Nantong Fourth People's Hospital, Nantong, Jiangsu Province, China
| | - Qinghe Xing
- Children's Hospital of Fudan University and Institutes of Biomedical Sciences of Fudan University, Shanghai, China
| | - Hailiang Huang
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA.
- Department of Medicine, Harvard Medical School, Boston, MA, USA.
| | - Shengying Qin
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Shanghai Jiao Tong University, Shanghai, China.
- Shanghai Jiao Tong University Sichuan Research Institute (SJTUSRI), Chengdu, Sichuan Province, China.
| |
Collapse
|
2
|
Noortman L, de Winter L, van Voorst A, Cahn W, Deenik J. Screening and prevalence of cardiometabolic risk factors in patients with severe mental illness: A multicenter cross-sectional cohort study in the Netherlands. Compr Psychiatry 2023; 126:152406. [PMID: 37506537 DOI: 10.1016/j.comppsych.2023.152406] [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: 04/25/2023] [Revised: 07/13/2023] [Accepted: 07/20/2023] [Indexed: 07/30/2023] Open
Abstract
BACKGROUND Due to increased cardiometabolic risks and premature mortality in people with severe mental illness (SMI), monitoring cardiometabolic health is considered essential. We aimed to analyse screening rates and prevalences of cardiometabolic risks in routine mental healthcare and its associations with patient and disease characteristics. METHODS We collected screening data in SMI from three mental healthcare institutions in the Netherlands, using most complete data on the five main metabolic syndrome (MetS) criteria (waist circumference, blood pressure, HDL-cholesterol, triglycerides, fasting blood glucose) within a 30-day timeframe in 2019/2020. We determined screened patients' cardiometabolic risks and analysed associations with patient and disease characteristics using multiple logistic regression. RESULTS In 5037 patients, screening rates ranged from 28.8% (waist circumference) to 76.4% (fasting blood glucose) within 2019-2020, and 7.6% had a complete measurement of all five MetS criteria. Older patients, men and patients with psychotic disorders had higher odds of being screened. Without regarding medication use, risk prevalences ranged from 29.6% (fasting blood glucose) to 56.8% (blood pressure), and 48.6% had MetS. Gender and age were particularly associated with odds for individual risk factors. Cardiometabolic risk was present regardless of illness severity and did generally not differ substantially between diagnoses, in-/outpatients and institutions. CONCLUSIONS Despite increased urgency and guideline development for cardiometabolic health in SMI last decades, screening rates are still low, and the MetS prevalence across screened patients is almost twice that of the general population. More intensive implementation strategies are needed to translate policies into action to improve cardiometabolic health in SMI.
Collapse
Affiliation(s)
- Laurien Noortman
- GGz Centraal, Amersfoort, the Netherlands; Faculty of Medicine, Utrecht University, Utrecht, the Netherlands
| | - Lars de Winter
- Phrenos Center of Expertise for Severe Mental Illnesses, Utrecht, the Netherlands
| | | | - Wiepke Cahn
- University Medical Centre Utrecht, Utrecht, the Netherlands; Altrecht, Utrecht, the Netherlands
| | - Jeroen Deenik
- GGz Centraal, Amersfoort, the Netherlands; School of Mental Health and Neuroscience, Maastricht University, Maastricht, the Netherlands.
| |
Collapse
|
3
|
van Tetering EMA, Muskens JB, Deenik J, Pillen S, Cahn W, von Rosenstiel I, Oomen M, Rommelse NN, Staal WG, Klip H. The short and long-term effects of a lifestyle intervention in children with mental illnesses: a randomized controlled trial (Movementss study). BMC Psychiatry 2023; 23:529. [PMID: 37480007 PMCID: PMC10362712 DOI: 10.1186/s12888-023-04884-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/07/2023] [Accepted: 05/17/2023] [Indexed: 07/23/2023] Open
Abstract
BACKGROUND A lifestyle including poor diet, physical inactivity, excessive gaming and inadequate sleep hygiene is frequently seen among Dutch children. These lifestyle behaviors can cause long-term health problems later in life. Unhealthy lifestyle and poor physical health are even more prevalent among children with mental illness (MI) such as autism, attention-deficit/hyperactivity disorder, depression, and anxiety. However, research on lifestyle interventions among children with MI is lacking. As a result, there are currently no guidelines, or treatment programs where children with MI and poor lifestyle can receive effective support. To address these issues and to provide insight into the effectiveness of lifestyle interventions in children with MI and their families, the Movementss study was designed. This paper describes the rationale, study design, and methods of an ongoing randomized controlled trial (RCT) comparing the short-term (12 weeks) and long-term (1 year) effects of a lifestyle intervention with care as usual (CAU) in children with MI and an unhealthy lifestyle. METHODS A total of 80 children (6-12 years) with MI according to DSM-V and an unhealthy lifestyle are randomized to the lifestyle intervention group or CAU at a specialized child and adolescent mental hospital. The primary outcome measure is quality of life measured with the KIDSCREEN. Secondary outcomes include emotional and behavior symptoms, lifestyle parameters regarding diet, physical activity, sleep, and screen time, cognitive assessment (intelligence and executive functions), physical measurements (e.g., BMI), parenting styles, and family functioning, prior beliefs, adherence, satisfaction, and cost-effectiveness. Assessments will take place at the start of the study (T0), after 12 weeks (T1), six months (T2), and 12 months of baseline (T3) to measure long-term effects. DISCUSSION This RCT will likely contribute to the currently lacking knowledge on lifestyle interventions in children with MI. TRIAL REGISTRATION trialsearch.who.int/ NL9822. Registered at November 2nd, 2021.
Collapse
Affiliation(s)
- Emilie M A van Tetering
- Karakter Child and Adolescent Psychiatry, Nijmegen, The Netherlands.
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboudumc, Nijmegen, The Netherlands.
- Department of Psychiatry, Radboud University Medical Centre, Nijmegen, The Netherlands.
| | - Jet B Muskens
- Karakter Child and Adolescent Psychiatry, Nijmegen, The Netherlands
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboudumc, Nijmegen, The Netherlands
- Department of Psychiatry, Radboud University Medical Centre, Nijmegen, The Netherlands
| | - Jeroen Deenik
- GGz Centraal, Department of Science, Amersfoort, The Netherlands
- School for Mental Health and Neuroscience, Maastricht University, Maastricht, The Netherlands
| | - Sigrid Pillen
- Kinderslaapexpert BV (Pediatric Sleep Expert Ltd), Mook, The Netherlands
| | - Wiepke Cahn
- Department of Psychiatry, University Medical Centre Utrecht, Utrecht, The Netherlands
| | | | | | - Nanda N Rommelse
- Karakter Child and Adolescent Psychiatry, Nijmegen, The Netherlands
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboudumc, Nijmegen, The Netherlands
- Department of Psychiatry, Radboud University Medical Centre, Nijmegen, The Netherlands
| | - Wouter G Staal
- Karakter Child and Adolescent Psychiatry, Nijmegen, The Netherlands
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboudumc, Nijmegen, The Netherlands
- Department of Psychiatry, Radboud University Medical Centre, Nijmegen, The Netherlands
- Leiden Institution for Brain and Cognition, Leiden, The Netherlands
| | - Helen Klip
- Karakter Child and Adolescent Psychiatry, Nijmegen, The Netherlands
| |
Collapse
|
4
|
Deenik J, van Lieshout C, van Driel HF, Frederix GWJ, Hendriksen IJM, van Harten PN, Tenback DE. Cost-Effectiveness of a Multidisciplinary Lifestyle-Enhancing Treatment for Inpatients With Severe Mental Illness: The MULTI Study V. SCHIZOPHRENIA BULLETIN OPEN 2022; 3:sgac022. [PMID: 39144774 PMCID: PMC11206082 DOI: 10.1093/schizbullopen/sgac022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 08/16/2024]
Abstract
Economic evaluations of lifestyle interventions for people with mental illness are needed to inform policymakers and managers about implementing such interventions and corresponding reforms in routine mental healthcare. We aimed to evaluate changes in healthcare costs 18 months after the implementation of a multidisciplinary lifestyle-enhancing treatment for inpatients with severe mental illness (MULTI) versus treatment as usual (TAU). In a cohort study (n = 114; 65 MULTI, 49 TAU), we retrospectively retrieved cost data in Euros on all patient sessions, ward stay, medication use, and hospital referrals in the quarter year at the start of MULTI (Q1 2014) and after its evaluation (Q3 2015). We used linear regression analyses correcting for baseline values and differences between groups, calculated deterministic incremental cost-effectiveness ratios for previously shown changes in physical activity, metabolic health, psychosocial functioning, and additionally quality of life, and performed probabilistic sensitivity analyses including cost-effectiveness planes. Adjusted regression showed reduced total costs per patient per quarter year in favor of MULTI (B = -736.30, 95%CI: -2145.2 to 672.6). Corresponding probabilistic sensitivity analyses accounting for uncertainty surrounding the parameters showed statistically non-significant cost savings against health improvements for all health-related outcomes in MULTI compared to TAU. It is concluded that MULTI did not increase healthcare costs while improving health outcomes. This indicates that starting lifestyle interventions does not need to be hampered by costs. Potential societal and economic value may justify investment to support implementation and maintenance. Further research is needed to study this hypothesis.
Collapse
Affiliation(s)
- Jeroen Deenik
- Scientific Research Department, GGz Centraal, Amersfoort, The Netherlands
- School for Mental Health and Neuroscience, Maastricht University, Maastricht, The Netherlands
| | - Chris van Lieshout
- THINC, Julius Center for Health Science and Primary Care, University Medical Centre Utrecht, Utrecht, The Netherlands
| | - Harold F van Driel
- Scientific Research Department, GGz Centraal, Amersfoort, The Netherlands
| | - Geert W J Frederix
- THINC, Julius Center for Health Science and Primary Care, University Medical Centre Utrecht, Utrecht, The Netherlands
| | | | - Peter N van Harten
- Scientific Research Department, GGz Centraal, Amersfoort, The Netherlands
- School for Mental Health and Neuroscience, Maastricht University, Maastricht, The Netherlands
| | | |
Collapse
|
5
|
Deenik J, Czosnek L, Teasdale SB, Stubbs B, Firth J, Schuch FB, Tenback DE, van Harten PN, Tak ECPM, Lederman O, Ward PB, Hendriksen IJM, Vancampfort D, Rosenbaum S. From impact factors to real impact: translating evidence on lifestyle interventions into routine mental health care. Transl Behav Med 2021; 10:1070-1073. [PMID: 31169897 PMCID: PMC7543082 DOI: 10.1093/tbm/ibz067] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
The scandal of premature mortality in people with serious mental illness is well established. Despite an increase in studies evaluating the efficacy of lifestyle interventions, translating this evidence into routine clinical care and policies is challenging, in part due to limited effectiveness or implementation research. We highlight the challenge of implementation that is increasingly recognized in clinical practice, advocate for adopting implementation science to study the implementation and systematic update of effective interventions in practice and policy, and provide directions for future research.
Collapse
Affiliation(s)
- Jeroen Deenik
- Scientific Research Department, GGz Centraal, Amersfoort, The Netherlands.,School for Mental Health and Neuroscience, Maastricht University, Maastricht, The Netherlands
| | - Louise Czosnek
- The Mary MacKillop Institute for Health Research, Melbourne, Australia
| | - Scott B Teasdale
- School of Psychiatry, University of New South Wales, Sydney, Australia.,Keeping the Body in Mind Program, South Eastern Sydney Local Health District, Sydney, Australia
| | - Brendon Stubbs
- Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.,Physiotherapy Department, South London and Maudsley NHS Foundation Trust, London, UK
| | - Joseph Firth
- NICM Health Research Institute, Western Sydney University, Sydney, Australia.,Division of Psychology and Mental Health, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
| | - Felipe B Schuch
- Department of Methods and Sports Techniques, Federal University of Santa Maria (UFSM), Santa Maria, Brazil
| | - Diederik E Tenback
- Center for Transcultural Psychiatry Veldzicht, Balkbrug, The Netherlands
| | - Peter N van Harten
- Scientific Research Department, GGz Centraal, Amersfoort, The Netherlands.,School for Mental Health and Neuroscience, Maastricht University, Maastricht, The Netherlands
| | | | - Oscar Lederman
- Keeping the Body in Mind Program, South Eastern Sydney Local Health District, Sydney, Australia.,School of Medical Sciences, University of New South Wales, Sydney, Australia
| | - Philip B Ward
- School of Psychiatry, University of New South Wales, Sydney, Australia.,Schizophrenia Research Unit, Ingham Institute of Applied Medical Research, Liverpool, NSW, Australia
| | | | - Davy Vancampfort
- Department of Rehabilitation Sciences, KU Leuven, Leuven, Belgium.,University Psychiatric Center, KU Leuven, Leuven, Belgium
| | - Simon Rosenbaum
- School of Psychiatry, University of New South Wales, Sydney, Australia.,Black Dog Institute, Prince of Wales Hospital, Sydney, Australia
| |
Collapse
|
6
|
Deenik J, Tenback DE, Tak ECPM, Blanson Henkemans OA, Rosenbaum S, Hendriksen IJM, van Harten PN. Implementation barriers and facilitators of an integrated multidisciplinary lifestyle enhancing treatment for inpatients with severe mental illness: the MULTI study IV. BMC Health Serv Res 2019; 19:740. [PMID: 31640706 PMCID: PMC6806487 DOI: 10.1186/s12913-019-4608-x] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2018] [Accepted: 10/03/2019] [Indexed: 12/18/2022] Open
Abstract
BACKGROUND Despite an increase in studies showing the efficacy of lifestyle interventions in improving the poor health outcomes for people with severe mental illness (SMI), routine implementation remains ad hoc. Recently, a multidisciplinary lifestyle enhancing treatment for inpatients with SMI (MULTI) was implemented as part of routine care at a long-term inpatient facility in the Netherlands, resulting in significant health improvements after 18 months. The current study aimed to identify barriers and facilitators of its implementation. METHODS Determinants associated with the implementation of MULTI, related to the innovation, the users (patients, the healthcare professionals (HCPs)), and the organisational context, were assessed at the three wards that delivered MULTI. The evidence-based Measurement Instrument for Determinants of Innovations was used to assess determinants (29 items), each measured through a 5-point Likert scale and additional open-ended questions. We considered determinants to which ≥20% of the HCPs or patients responded negatively ("totally disagree/disagree", score < 3) as barriers and to which ≥80% of HCPs or patients responded positively ("agree/totally agree", score > 3) as facilitators. We included responses to open-ended questions if the topic was mentioned by ≥2 HCPs or patients. In total 50 HCPs (online questionnaire) and 46 patients (semi-structured interview) were invited to participate in the study. RESULTS Participating HCPs (n = 42) mentioned organisational factors as the strongest barriers (e.g. organisational changes and financial resources). Patients (n = 33) mentioned the complexity of participating in MULTI as the main barrier, which could partly be due to organisational factors (e.g. lack of time for nurses to improve tailoring). The implementation was facilitated by positive attitudes of HCPs and patients towards MULTI, including their own role in it. Open responses of HCPs and patients showed strong commitment, collaboration and ownership towards MULTI. CONCLUSIONS This is the first study analysing the implementation of a pragmatic lifestyle intervention targeting SMI inpatients in routine clinical care. Positive attitudes of both HCPs and patients towards such an approach facilitated the implementation of MULTI. We suggest that strategies addressing organisational implementation barriers are needed to further improve and maintain MULTI, to succeed in achieving positive health-related outcomes in inpatients with SMI.
Collapse
Affiliation(s)
- Jeroen Deenik
- GGz Centraal, Utrechtseweg 266, 3818EW Amersfoort, the Netherlands
- School for Mental Health and Neuroscience, Maastricht University, PO Box 616, 5200MD Maastricht, the Netherlands
| | | | - Erwin C. P. M. Tak
- Tak Advies en Onderzoek, Hooigracht 38/K, 2312KV Leiden, the Netherlands
| | | | - Simon Rosenbaum
- School of Psychiatry, University of New South Wales, Hospital Road, Randwick NSW, Sydney, 2031 Australia
- Black Dog Institute, Prince of Wales Hospital, Hospital Road, Randwick NSW, Sydney, 2031 Australia
| | | | - Peter N. van Harten
- GGz Centraal, Utrechtseweg 266, 3818EW Amersfoort, the Netherlands
- School for Mental Health and Neuroscience, Maastricht University, PO Box 616, 5200MD Maastricht, the Netherlands
| |
Collapse
|
7
|
Lambden B, Berge J, Forsell Y. Structured physical exercise and recovery from first episode psychosis in young adults, the FitForLife study. Psychiatry Res 2018; 267:346-353. [PMID: 29957552 DOI: 10.1016/j.psychres.2018.06.001] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/16/2018] [Revised: 04/11/2018] [Accepted: 06/02/2018] [Indexed: 01/06/2023]
Abstract
Optimising autonomy is increasingly important in recovery from psychosis. To date, physical exercise has shown promise in the treatment of severe, enduring mental illnesses including psychosis - when used as an adjunct treatment. To assess the association between physical exercise and autonomy in young adults, a simple pre-post experimental design was utilised. Individuals aged 18-35 years, treated at one of three specialist outpatient units for first-episode psychosis in Stockholm, Sweden were invited to participate in a 12-week programme of structured group exercise. Autonomy was measured using four questions from the Camberwell Assessment of Needs questionnaire (physical health, social and close relationship and daily tasks). Comparisons were made between: 'no attendance' and 'any attendance'. The latter group was bisected into higher and lower categories. Ninety-four participants enrolled with a post-intervention response rate of 61%. Significant reductions were seen in self-rated needs for care, though there was no significant change in total scores or evidence of a dose response association. The results suggest a plausible association between physical exercise and autonomy which may represent the recovery process following the first episode of psychosis. Further randomised control trials are needed to explore the potential causality and robustness of this change.
Collapse
Affiliation(s)
- Benjamin Lambden
- Public Health Sciences, Karolinska Institute, Solnavägen 1, Plan 6, Solna, Stockholm 171 77, Sweden.
| | - Jonas Berge
- Clinical Addiction Research Unit, Lund University, Lund, Sweden
| | - Yvonne Forsell
- Public Health Sciences, Karolinska Institute, Solnavägen 1, Plan 6, Solna, Stockholm 171 77, Sweden
| |
Collapse
|
8
|
Abstract
BACKGROUND Cardiorespiratory fitness (CRF) among people with severe mental illness (SMI) (i.e., schizophrenia, bipolar disorder, and major depressive disorder) is a critical clinical risk factor given its relationship to cardiovascular disease and premature mortality. OBJECTIVES This study aimed to: (1) investigate the mean CRF in people with SMI versus healthy controls; (2) explore moderators of CRF; and (3) investigate whether CRF improved with exercise interventions and establish if fitness improves more than body mass index following exercise interventions. METHODS Major electronic databases were searched systematically. A meta-analysis calculating Hedges' g statistic was undertaken. RESULTS Across 23 eligible studies, pooled mean CRF was 28.7 mL/kg/min [95 % confidence interval (CI) 27.3 to 30.0 mL/kg/min, p < 0.001, n = 980]. People with SMI had significantly lower CRF compared with controls (n = 310) (Hedges' g = -1.01, 95 % CI -1.18 to -0.85, p < 0.001). There were no differences between diagnostic subgroups. In a multivariate regression, first-episode (β = 6.6, 95 % CI 0.6-12.6) and inpatient (β = 5.3, 95 % CI 1.6-9.0) status were significant predictors of higher CRF. Exercise improved CRF (Hedges' g = 0.33, 95 % CI = 0.21-0.45, p = 0.001), but did not reduce body mass index. Higher CRF improvements were observed following interventions at high intensity, with higher frequency (at least three times per week) and supervised by qualified personnel (i.e., physiotherapists and exercise physiologists). CONCLUSION The multidisciplinary treatment of people with SMI should include a focus on improving fitness to reduce all-cause mortality. Qualified healthcare professionals supporting people with SMI in maintaining an active lifestyle should be included as part of multidisciplinary teams in mental health treatment.
Collapse
|
9
|
Cella M, Okruszek Ł, Lawrence M, Zarlenga V, He Z, Wykes T. Using wearable technology to detect the autonomic signature of illness severity in schizophrenia. Schizophr Res 2018; 195:537-542. [PMID: 28986005 DOI: 10.1016/j.schres.2017.09.028] [Citation(s) in RCA: 49] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/06/2017] [Revised: 09/19/2017] [Accepted: 09/21/2017] [Indexed: 10/18/2022]
Abstract
INTRODUCTION Research suggests that people with schizophrenia have autonomic dysfunctions. These have been linked to functioning problems, symptoms and considered a risk factor for illness chronicity. The aim of this study is to introduce a new Mobile Health (mHealth) method using wearable technology to assessing autonomic activity in people's everyday life. We aim to evaluate the new method acceptability and characterise the association between schizophrenia illness features and autonomic abnormalities. METHOD Thirty participants with schizophrenia and 25 controls were asked to wear a mHealth device measuring autonomic activity and movements during their normal everyday life. Measures of device use acceptability were collected from all participants. Participants with schizophrenia were also assessed for symptoms and functioning levels. Measures of heart rate variability (HRV), electrodermal activity (EDA) and movement were collected by the device and groups were compared. Correlation between physiological measures, functioning, symptoms and medication levels were assessed in people with schizophrenia. RESULTS The mHealth device method proved to be acceptable and produced reliable measures of autonomic activity and behaviour. Compared to controls, people with schizophrenia showed lower levels of HRV, movement and functioning. In people with schizophrenia illness severity, particularly positive symptoms, was associated with parasympathetic deregulation. CONCLUSIONS Autonomic abnormalities can be detected using wearable technology from people's everyday life. These are in line with previous research and support the notion that autonomic deregulation are relevant illness features for mental and physical health in schizophrenia. This method may be developed as a monitoring system for well-being and relapse prevention.
Collapse
Affiliation(s)
- Matteo Cella
- Department of Psychology, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK.
| | - Łukasz Okruszek
- Department of Psychology, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK; Institute of Psychology, Polish Academy of Sciences, Warsaw, Poland
| | - Megan Lawrence
- Department of Psychology, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK
| | - Valerio Zarlenga
- Department of Psychology, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK
| | - Zhimin He
- Department of Psychology, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK
| | - Til Wykes
- Department of Psychology, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK
| |
Collapse
|
10
|
Bressington D, Chien WT, Mui J, Lam KKC, Mahfoud Z, White J, Gray R. Chinese Health Improvement Profile for people with severe mental illness: A cluster-randomized, controlled trial. Int J Ment Health Nurs 2018; 27:841-855. [PMID: 28786197 DOI: 10.1111/inm.12373] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 06/13/2017] [Indexed: 12/12/2022]
Abstract
The aim of the present study was to establish the feasibility of conducting a full-scale trial and to estimate the preliminary effect of a Chinese Health Improvement Profile (CHIP) intervention on self-reported physical well-being of people with severe mental illness (SMI). The study used a parallel-group, open-label, cluster-randomized, controlled trial (RCT) design. Twelve community psychiatric nurses (CPN) and their corresponding 137 patients with SMI were randomized into the CHIP or treatment-as-usual (TAU) groups. After training, the CPN completed the CHIP at baseline and 12 months, and the findings were used to devise an individualized care plan to promote health behaviour change. Patients were assessed at baseline and 6 and 12 months after starting the intervention. There was an observed positive trend of improvement on the physical component subscale of SF12v2 in the CHIP group compared to the TAU group after 12 months, but the difference did not reach statistical significance (P = 0.138). The mental component subscale showed a similar positive trend (P = 0.077). CHIP participants were more satisfied with their physical health care than TAU patients (P = 0.009), and the CPN were positive about the usefulness/acceptability of the intervention. There were significant within-group improvements in the total numbers of physical health risks, as indicated by the CHIP items (P = 0.005). The findings suggest that it is feasible to conduct a full-scale RCT of the CHIP in future. The CHIP is an intervention that can be used within routine CPN practice, and could result in small-modest improvements in the physical well-being of people with SMI.
Collapse
Affiliation(s)
- Daniel Bressington
- School of Nursing, The Hong Kong Polytechnic University, Hung Hom, Hong Kong
| | - Wai Tong Chien
- School of Nursing, The Hong Kong Polytechnic University, Hung Hom, Hong Kong
| | - Jolene Mui
- Castle Peak and Siu Lam Hospitals, Hong Kong, Hong Kong
| | - Kar Kei Claire Lam
- School of Nursing, The Hong Kong Polytechnic University, Hung Hom, Hong Kong
| | - Ziyad Mahfoud
- Department of Health Policy and Research, Weill Cornell Medicine, Ar-Rayyan, Qatar
| | | | - Richard Gray
- College of Science, Health and Engineering, La Trobe University, Melbourne, Victoria, Australia
| |
Collapse
|
11
|
Physical Health Care for People with Severe Mental Illness: the Attitudes, Practices, and Training Needs of Nurses in Three Asian Countries. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2018; 15:ijerph15020343. [PMID: 29462859 PMCID: PMC5858412 DOI: 10.3390/ijerph15020343] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 01/08/2018] [Revised: 02/02/2018] [Accepted: 02/12/2018] [Indexed: 11/18/2022]
Abstract
People with severe mental illness (SMI) have considerable unmet physical health needs and an increased risk of early mortality. This cross-sectional survey utilized the Physical Health Attitude Scale (PHASe) to examine the attitudes, practices, and training needs of nurses towards physical health care of people with SMI in three Asian countries (Hong Kong, Japan, Qatar). Cross-country differences were explored and linear regression was used to investigate if nurses’ attitudes and confidence were associated with their level of involvement in physical health care. A total of 481 questionnaires were returned. Hong Kong nurses were less involved in physical health care than those from Japan and Qatar. Nurses’ attitudes and confidence were significant predictors of their participation in managing physical health. Compared with western countries, more nurses in this study felt that mental illness was a barrier to improving physical health. Three-quarters reported that they needed additional training in promoting cardiometabolic health. The perceived need for additional training in physical health care was held by Mental Health Nurses (MHN) irrespective of their type of nursing registration and nationality. Nurse educators and service providers should reconsider the physical health care training requirements of nurses working in mental health settings in order to improve the physical health of people with SMI.
Collapse
|
12
|
Mitchell AJ, Hardy S, Shiers D. Parity of esteem: Addressing the inequalities between mental and physical healthcare. BJPSYCH ADVANCES 2018. [DOI: 10.1192/apt.bp.114.014266] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
SummaryParity of esteem means valuing mental health as much as physical health in order to close inequalities in mortality, morbidity or delivery of care. There is clear evidence that patients with mental illness receive inferior medical, surgical and preventive care. This further exacerbated by low help-seeking, high stigma, medication side-effects and relatively low resources in mental healthcare. As a result, patients with severe mental illness die 10–20 years prematurely and have a high rate of cardiometabolic complications and other physical illnesses. Many physical healthcare guidelines and policy recommendations address parity of esteem, but their implementation to date has been poor. All clinicians should be aware that inequalities in care are adversely influencing mental health outcomes, and managers, healthcare organisations and politicians should provide resources and education to address this gap.Learning Objectives• Understand the concept of parity of esteem• Be aware of the current inequalities in mental healthcare• Appreciate how parity of esteem may be improved
Collapse
|
13
|
Mugisha J, De Hert M, Stubbs B, Basangwa D, Vancampfort D. Physical health policies and metabolic screening in mental health care systems of sub-Saharan African countries: a systematic review. Int J Ment Health Syst 2017; 11:31. [PMID: 28428816 PMCID: PMC5395896 DOI: 10.1186/s13033-017-0141-7] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/06/2017] [Accepted: 04/13/2017] [Indexed: 01/08/2023] Open
Abstract
BACKGROUND There is a need for interventions to address the escalating mental health burden in sub-Saharan Africa (SSA). Addressing physical health needs should have a central role in reducing the burden and facilitating recovery in people with severe mental illness (SMI). We systematically investigated (1) physical health policies in the current mental health plans, and (2) the routine metabolic screening rates for people with SMI in SSA. METHODS The Mental Health Atlas and MiNDbank of the World Health Organization were screened for physical health policies in mental health plans. Next, we systematically searched PubMed from inception until February 1st, 2017 for relevant studies on metabolic screening rates in people with SMI in SSA. RESULTS The current systematic review shows that in 22 screened plans only 6 made reference to a physical health component or policy. Only the South-African mental health plan reported about routine screening and treatment of physical illness for people with SMI. In 2 South-African studies (n = 431) routine screening was unacceptably low with less than 1% adequately screened for all modifiable metabolic syndrome risk factors. CONCLUSIONS Our review data clearly show that a physical health policy is yet to be embraced in mental health care systems of most SSA countries. There is a clear need for integrated mental and medical services in SSA. All psychiatric services, including poorly developed community-based primary health care settings should standardly assess the body mass index and waist circumference at initiation of psycho-pharmacotherapy, and afterwards at regular intervals. Optimal monitoring should include assessments of fasting glucose, lipids, cholesterol, and blood pressure. Mental health care providers in SSA countries need to be informed that their roles extend beyond taking care of the mental health of their patients and assume responsibility for the physical health of their patients as well. Policy makers should be made aware that investment in continued medial education and in screening for physical health risks could optimize mental and physical health improvements. The increased physical health needs of people with mental illness should be integrated into the existing Information, Education and Communication public health awareness programs of the World Health Organization.
Collapse
Affiliation(s)
- James Mugisha
- Butabika National Referral and Mental Health Hospital, Kampala, Uganda
- Kyambogo University, Kampala, Uganda
| | - Marc De Hert
- KU Leuven-University of Leuven, University Psychiatric Center KU Leuven, Louvain-Kortenberg, Belgium
| | - Brendon Stubbs
- Physiotherapy Department, South London and Maudsley NHS Foundation Trust, London, UK
- Health Service and Population Research Department, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, De Crespigny Park, London, UK
| | - David Basangwa
- Butabika National Referral and Mental Health Hospital, Kampala, Uganda
| | - Davy Vancampfort
- KU Leuven-University of Leuven, University Psychiatric Center KU Leuven, Louvain-Kortenberg, Belgium
- Department of Rehabilitation Sciences, KU Leuven-University of Leuven, Louvain, Belgium
| |
Collapse
|
14
|
Haddad M, Llewellyn-Jones S, Yarnold S, Simpson A. Improving the physical health of people with severe mental illness in a low secure forensic unit: An uncontrolled evaluation study of staff training and physical health care plans. Int J Ment Health Nurs 2016; 25:554-565. [PMID: 27443217 DOI: 10.1111/inm.12246] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/25/2015] [Revised: 03/31/2016] [Accepted: 05/03/2016] [Indexed: 01/05/2023]
Abstract
The life expectancy of people with severe mental illnesses is substantially reduced, and monitoring and screening for physical health problems is a key part of addressing this health inequality. Inpatient admission presents a window of opportunity for this health-care activity. The present study was conducted in a forensic mental health unit in England. A personal physical health plan incorporating clearly-presented and easily-understood values and targets for health status in different domains was developed. Alongside this, a brief physical education session was delivered to health-care staff (n = 63). Printed learning materials and pedometers and paper tape measures were also provided. The impact was evaluated by a single-group pretest post-test design; follow-up measures were 4 months' post-intervention. The feasibility and acceptability of personal health plans and associated resources were examined by free-text questionnaire responses. Fifty-seven staff provided measures of attitudes and knowledge before training and implementation of the physical health plans. Matched-pairs analysis indicated a modest but statistically-significant improvement in staff knowledge scores and attitudes to involvement in physical health care. Qualitative feedback indicated limited uptake of the care plans and perceived need for additional support for better adoption of this initiative. Inpatient admission is a key setting for assessing physical health and promoting improved management of health problems. Staff training and purpose-designed personalized care plans hold potential to improve practice and outcomes in this area, but further support for such innovations appears necessary for their uptake in inpatient mental health settings.
Collapse
Affiliation(s)
- Mark Haddad
- Centre for Mental Health Research, School of Health Sciences, City University London.,East London National Health Service Foundation Trust, London, UK
| | | | - Steve Yarnold
- East London National Health Service Foundation Trust, London, UK
| | - Alan Simpson
- Centre for Mental Health Research, School of Health Sciences, City University London.,East London National Health Service Foundation Trust, London, UK
| |
Collapse
|
15
|
Stubbs B, Koyanagi A, Veronese N, Vancampfort D, Solmi M, Gaughran F, Carvalho AF, Lally J, Mitchell AJ, Mugisha J, Correll CU. Physical multimorbidity and psychosis: comprehensive cross sectional analysis including 242,952 people across 48 low- and middle-income countries. BMC Med 2016; 14:189. [PMID: 27871281 PMCID: PMC5118890 DOI: 10.1186/s12916-016-0734-z] [Citation(s) in RCA: 116] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/24/2016] [Accepted: 10/26/2016] [Indexed: 12/19/2022] Open
Abstract
BACKGROUND In people with psychosis, physical comorbidities, including cardiovascular and metabolic diseases, are highly prevalent and leading contributors to the premature mortality encountered. However, little is known about physical health multimorbidity in this population or in people with subclinical psychosis and in low- and middle-income countries (LMICs). This study explores physical health multimorbidity patterns among people with psychosis or subclinical psychosis. METHODS Overall, data from 242,952 individuals from 48 LMICs, recruited via the World Health Survey, were included in this cross-sectional study. Participants were subdivided into those (1) with a lifetime diagnosis of psychosis ("psychosis"); (2) with more than one psychotic symptom in the past 12 months, but no lifetime diagnosis of psychosis ("subclinical psychosis"); and (3) without psychotic symptoms in the past 12 months or a lifetime diagnosis of psychosis ("controls"). Nine operationalized somatic disorders were examined: arthritis, angina pectoris, asthma, diabetes, chronic back pain, visual impairment, hearing problems, edentulism, and tuberculosis. The association between psychosis and multimorbidity was assessed by multivariable logistic regression analysis. RESULTS The prevalence of multimorbidity (i.e., two or more physical health conditions) was: controls = 11.4% (95% CI, 11.0-11.8%); subclinical psychosis = 21.8% (95% CI, 20.6-23.0%), and psychosis = 36.0% (95% CI, 32.1-40.2%) (P < 0.0001). After adjustment for age, sex, education, country-wise wealth, and country, subclinical psychosis and psychosis were associated with 2.20 (95% CI, 2.02-2.39) and 4.05 (95% CI, 3.25-5.04) times higher odds for multimorbidity. Moreover, multimorbidity was increased in subclinical and established psychosis in all age ranges (18-44, 45-64, ≥ 65 years). However, multimorbidity was most evident in younger age groups, with people aged 18-44 years with psychosis at greatest odds of physical health multimorbidity (OR = 4.68; 95% CI, 3.46-6.32). CONCLUSIONS This large multinational study demonstrates that physical health multimorbidity is increased across the psychosis-spectrum. Most notably, the association between multimorbidity and psychosis was stronger among younger adults, thus adding further impetus to the calls for the early intervention efforts to prevent the burden of physical health comorbidity at later stages. Urgent public health interventions are necessary not only for those with a psychosis diagnosis, but also for subclinical psychosis to address this considerable public health problem.
Collapse
Affiliation(s)
- Brendon Stubbs
- Physiotherapy Department, South London and Maudsley NHS Foundation Trust, Denmark Hill, London, SE5 8AZ, UK. .,Health Service and Population Research Department, Institute of Psychiatry, Psychology and Neuroscience, King's College London, De Crespigny Park, London, Box SE5 8AF, UK.
| | - Ai Koyanagi
- Research and Development Unit, Parc Sanitari Sant Joan de Déu, Universitat de Barcelona, Fundació Sant Joan de Déu, Dr. Antoni Pujadas, 42, Sant Boi de Llobregat, Barcelona, 08830, Spain.,Instituto de Salud Carlos III, Centro de Investigación Biomédica en Red de Salud Mental, CIBERSAM, Monforte de Lemos 3-5 Pabellón 11, Madrid, 28029, Spain
| | - Nicola Veronese
- Geriatrics Division, Department of Medicine-DIMED, University of Padova, Padova, Italy.,Institute of Clinical Research and Education in Medicine (IREM), Padova, Italy
| | - Davy Vancampfort
- KU Leuven Department of Rehabilitation Sciences, Leuven, Belgium.,KU Leuven, University Psychiatric Center KU Leuven, Leuven-Kortenberg, Belgium
| | - Marco Solmi
- Institute of Clinical Research and Education in Medicine (IREM), Padova, Italy.,Department of Neurosciences, University of Padova, Padova, Italy.,Local Health Unit ULSS 17, Mental Health Department, Monselice, Padova, Italy
| | - Fiona Gaughran
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience King's College London, London, UK
| | - André F Carvalho
- Department of Psychiatry and Translational Psychiatry Research Group, Faculty of Medicine, Federal University of Ceará, Fortaleza, CE, Brazil
| | - John Lally
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience King's College London, London, UK.,Department of Psychiatry, Royal College of Surgeons in Ireland, Dublin, Ireland
| | - Alex J Mitchell
- Department of Cancer and Molecular Medicine, University of Leicester, Leicester, UK
| | - James Mugisha
- Kyambogo University, Kampala, Uganda.,Butabika National Referral and Mental Health Hospital, Kampala, Uganda
| | - Christoph U Correll
- The Zucker Hillside Hospital, Psychiatry Research, Northwell Health, Glen Oaks, New York, USA.,Hofstra Northwell School of Medicine, Hempstead, New York, USA
| |
Collapse
|
16
|
Firth J, Rosenbaum S, Stubbs B, Vancampfort D, Carney R, Yung AR. Preferences and motivations for exercise in early psychosis. Acta Psychiatr Scand 2016; 134:83-4. [PMID: 26992143 DOI: 10.1111/acps.12562] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- J Firth
- Institute of Brain, Behaviour and Mental Health, University of Manchester, Manchester, UK.
| | - S Rosenbaum
- Department of Exercise Physiology, University of New South Wales, Australia
| | - B Stubbs
- Physiotherapy Department, South London and Maudsley NHS Foundation Trust, UK
| | - D Vancampfort
- Department of Rehabilitation Sciences, KU Leuven, Leuven, Belgium
| | - R Carney
- Institute of Brain, Behaviour and Mental Health, University of Manchester, Manchester, UK
| | - A R Yung
- Institute of Brain, Behaviour and Mental Health, University of Manchester, Manchester, UK
| |
Collapse
|
17
|
Verdoux H, Pambrun E, Cortaredona S, Coldefy M, Le Neindre C, Tournier M, Verger P. Geographical disparities in prescription practices of lithium and clozapine: a community-based study. Acta Psychiatr Scand 2016; 133:470-80. [PMID: 26826542 DOI: 10.1111/acps.12554] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 12/17/2015] [Indexed: 12/30/2022]
Abstract
OBJECTIVE To explore the socioeconomic and health resource characteristics associated with geographical variations of lithium and clozapine dispensing rates in France. METHOD The study was performed using reimbursement data from the French Insurance Healthcare system over the period 2006-2013 in a community-based sample of persons aged 16 years and over. An ecological design was used to assess whether lithium and clozapine prescribing rates were associated with socioeconomic and health resource characteristics of the zone of residence (n = 95 French administrative subdivisions). RESULTS Large geographical disparities were observed in dispensing rates: lithium dispensing rates by zone of residence ranged from 0 to 6.6 per 1000 (mean 2.4 per 1000) and clozapine dispensing rates ranged from 0 to 4.9 per 1000 (mean 0.8 per 1000). Higher density of GPs and regular communication between mental health services and primary care were independently associated with higher rates of lithium and clozapine dispensing and with a higher proportion of lithium users among mood-stabilizer users. CONCLUSION A sufficient density of GPs and an effective communication and collaboration between mental healthcare services and primary care seems to favor greater access to psychotropic drugs with demonstrated efficacy but often viewed as 'risky' to prescribe.
Collapse
Affiliation(s)
- H Verdoux
- U657, University of Bordeaux, Bordeaux, France.,INSERM, U657, Bordeaux, France
| | - E Pambrun
- U657, University of Bordeaux, Bordeaux, France.,INSERM, U657, Bordeaux, France
| | - S Cortaredona
- ORS PACA, Observatoire Régional de la Santé Provence-Alpes-Côte d'Azur, Marseille, France.,INSERM, UMR912 (SESSTIM), Marseille, France.,UMR_S912, IRD, Aix Marseille Université, Marseille, France
| | - M Coldefy
- Institut de recherche et documentation en économie de la santé (IRDES), Paris, France.,Observatoire régional des urgences, Provence-Alpes-Côte d'Azur (ORU PACA), Marseille, France
| | - C Le Neindre
- Institut de recherche et documentation en économie de la santé (IRDES), Paris, France
| | - M Tournier
- U657, University of Bordeaux, Bordeaux, France.,INSERM, U657, Bordeaux, France
| | - P Verger
- ORS PACA, Observatoire Régional de la Santé Provence-Alpes-Côte d'Azur, Marseille, France.,INSERM, UMR912 (SESSTIM), Marseille, France.,UMR_S912, IRD, Aix Marseille Université, Marseille, France
| |
Collapse
|
18
|
Abstract
Individuals with serious mental illnesses such as psychosis still experience higher mortality rates than the general population, decades after data have linked the gap to increased rates of physical illness, delayed diagnosis, low treatment rates and worse outcomes from treatment received. The nature of the relationship between psychosis and comorbid physical illness is complex. Multiple strategies directed at different levels of disease process, health care systems and stakeholder culture are likely required to make sustained progress in reducing the mortality gap. Evidence for strategies that effectively reduce the burden of physical co-morbidity and lead to improved health outcomes are still in their infancy but growing at a reassuringly fast rate. This editorial considers the existing evidence base and makes suggestions for the development and future direction of this urgent research agenda and how this knowledge can be implemented in clinical practice.
Collapse
Affiliation(s)
- M. Docherty
- National Psychosis Service, South London and Maudsley NHS Foundation Trust, Denmark Hill, London SE5 8AZ, UK
- Institute of Psychiatry, Psychology and Neuroscience, Kings College London, De Crespigny Park, London SE5 8AF, UK
| | - B. Stubbs
- Physiotherapy Department, South London and Maudsley NHS Foundation Trust, Denmark Hill, London SE5 8AZ, UK
- Health Service and Population Research Department, Institute of Psychiatry, King's College London, De Crespigny Park, London SE5 8AF, UK
| | - F. Gaughran
- National Psychosis Service, South London and Maudsley NHS Foundation Trust, Denmark Hill, London SE5 8AZ, UK
- Institute of Psychiatry, Psychology and Neuroscience, Kings College London, De Crespigny Park, London SE5 8AF, UK
- Collaborative Leadership in Applied Heath Research Centre and Care, South London, UK
| |
Collapse
|
19
|
Affiliation(s)
- J. J. McGrath
- The University of Queensland, Queensland Brain Institute, St. Lucia, Australia
- Queensland Centre for Mental Health Research, The Park Centre for Mental Health, Richlands, Australia
| |
Collapse
|
20
|
Shiers D, Campion J, Bradshaw T. Authors' reply. Br J Psychiatry 2016; 208:398-9. [PMID: 27036701 DOI: 10.1192/bjp.208.4.398a] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Affiliation(s)
- David Shiers
- David Shiers, MBChB, MRCGP, MRCP(UK), School of Psychological Sciences, University of Manchester, Manchester M13 9PL, UK. ; Jonathan Campion, MBBS, MRCPsych, South London and Maudsley NHS Foundation Trust, and Faculty of Brain Sciences, University College London, London; Tim Bradshaw, RMN, PhD, School of Nursing, Midwifery and Social Work, University of Manchester, Manchester, UK
| | - Jonathan Campion
- David Shiers, MBChB, MRCGP, MRCP(UK), School of Psychological Sciences, University of Manchester, Manchester M13 9PL, UK. ; Jonathan Campion, MBBS, MRCPsych, South London and Maudsley NHS Foundation Trust, and Faculty of Brain Sciences, University College London, London; Tim Bradshaw, RMN, PhD, School of Nursing, Midwifery and Social Work, University of Manchester, Manchester, UK
| | - Tim Bradshaw
- David Shiers, MBChB, MRCGP, MRCP(UK), School of Psychological Sciences, University of Manchester, Manchester M13 9PL, UK. ; Jonathan Campion, MBBS, MRCPsych, South London and Maudsley NHS Foundation Trust, and Faculty of Brain Sciences, University College London, London; Tim Bradshaw, RMN, PhD, School of Nursing, Midwifery and Social Work, University of Manchester, Manchester, UK
| |
Collapse
|