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      Improving cardiovascular health and quality of life in people with severe mental illness: study protocol for a randomised controlled trial

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          Abstract

          Background

          The estimated 300,000 adults in Australia with severe mental illness (SMI) have markedly reduced life expectancy compared to the general population, mainly due to physical health comorbidities. Cardiovascular disease (CVD) is the commonest cause of early death and people with SMI have high rates of most modifiable risk factors, with associated quality of life (QoL) reduction. High blood pressure, smoking, dyslipidaemia, diabetes and obesity are major modifiable CVD risk factors. Poor delivery of recommended monitoring and risk reduction is a national and international problem. Therefore, effective preventive interventions to safeguard and support physical health are urgently needed in this population.

          Methods

          This trial used a rigorous process, including extensive piloting, to develop an intervention that delivers recommended physical health care to reduce CVD risk and improve QoL for people with SMI. Components of this intervention are integrated using the Flinders Program of chronic condition management (CCM) which is a comprehensive psychosocial care planning approach that places the patient at the centre of their care, and focuses on building their self-management capacity within a collaborative approach, therefore providing a recovery-oriented framework. The primary project aim is to evaluate the effectiveness and health economics of the CCM intervention. The main outcome measures examine CVD risk and quality of life. The second aim is to identify essential components, enablers and barriers at patient, clinical and organisational levels for national, sustained implementation of recommended physical health care delivery to people with SMI. Participants will be recruited from a community-based public psychiatric service.

          Discussion

          This study constitutes the first large-scale trial, worldwide, using the Flinders Program with this population. By combining a standardised yet flexible motivational process with a targeted set of evidence-based interventions, the chief aim is to reduce CVD risk by 20%. If achieved, this will be a ground-breaking outcome, and the program will be subsequently translated nationwide and abroad. The trial will be of great interest to people with mental illness, family carers, mental health services, governments and primary care providers because the Flinders Program can be delivered in diverse settings by any clinical discipline and supervised peers.

          Trial registration

          Australian and New Zealand Clinical Trials Registry, ACTRN12617000474358. Registered on 31 March 2017.

          Electronic supplementary material

          The online version of this article (10.1186/s13063-018-2748-7) contains supplementary material, which is available to authorized users.

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          Most cited references26

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          General cardiovascular risk profile for use in primary care: the Framingham Heart Study.

          Separate multivariable risk algorithms are commonly used to assess risk of specific atherosclerotic cardiovascular disease (CVD) events, ie, coronary heart disease, cerebrovascular disease, peripheral vascular disease, and heart failure. The present report presents a single multivariable risk function that predicts risk of developing all CVD and of its constituents. We used Cox proportional-hazards regression to evaluate the risk of developing a first CVD event in 8491 Framingham study participants (mean age, 49 years; 4522 women) who attended a routine examination between 30 and 74 years of age and were free of CVD. Sex-specific multivariable risk functions ("general CVD" algorithms) were derived that incorporated age, total and high-density lipoprotein cholesterol, systolic blood pressure, treatment for hypertension, smoking, and diabetes status. We assessed the performance of the general CVD algorithms for predicting individual CVD events (coronary heart disease, stroke, peripheral artery disease, or heart failure). Over 12 years of follow-up, 1174 participants (456 women) developed a first CVD event. All traditional risk factors evaluated predicted CVD risk (multivariable-adjusted P<0.0001). The general CVD algorithm demonstrated good discrimination (C statistic, 0.763 [men] and 0.793 [women]) and calibration. Simple adjustments to the general CVD risk algorithms allowed estimation of the risks of each CVD component. Two simple risk scores are presented, 1 based on all traditional risk factors and the other based on non-laboratory-based predictors. A sex-specific multivariable risk factor algorithm can be conveniently used to assess general CVD risk and risk of individual CVD events (coronary, cerebrovascular, and peripheral arterial disease and heart failure). The estimated absolute CVD event rates can be used to quantify risk and to guide preventive care.
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            Psychometric properties of the Medical Outcomes Study Sleep measure.

            Sleep is an active and highly organized biological process that is an important component of life. Self-report measures of sleep provide information that can be useful for characterizing the quality of sleep in subgroups of the population. A 12-item self-report sleep measure, the Medical Outcomes Study Sleep measure, was developed and evaluated previously in a sample of 3445 individuals with chronic illness. In this study, we evaluate the psychometric properties of the MOS Sleep measure in a nationally representative sample of 1011 US adults aged 18 and older and in a sample of 173 adults with neuropathic pain participating in a clinical drug trial. The average age of the general population sample was 46; 51% were female and 81% were white. The average age of the sample of adults with neuropathic pain was 72; 53% were female and 95% were white. Internal consistency reliability estimates for the MOS Sleep scales were 0.73 or higher, with the exception of the daytime somnolence scale in the US general population, which was 0.63. At baseline of the clinical trial, the neuropathic pain patients reported significantly more sleep disturbance and daytime somnolence, as well as less quantity and adequacy of sleep than patients in the general US population. The MOS Sleep scales were found to be responsive to change in the clinical trial with statistically significant improvements observed after administration of pregabalin for sleep disturbance (standardized response mean, SRM=-0.76, P=0.0007), shortness of breath (SRM=-0.20, P=0.0302), sleep adequacy (SRM=0.57, P=0.0014), sleep quantity (SRM=0.55, P=0.0086), and sleep problems (SRM=-0.62, P=0.0036). This study provides further support for the reliability and validity of the MOS Sleep measure. The instrument can be used to assess important aspects of sleep perceived by adults in the general population or participating in clinical studies.
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              Physical illness in patients with severe mental disorders. II. Barriers to care, monitoring and treatment guidelines, plus recommendations at the system and individual level.

              Physical disorders are, compared to the general population, more prevalent in people with severe mental illness (SMI). Although this excess morbidity and mortality is largely due to modifiable lifestyle risk factors, the screening and assessment of physical health aspects remains poor, even in developed countries. Moreover, specific patient, provider, treatment and system factors act as barriers to the recognition and to the management of physical diseases in people with SMI. Psychiatrists can play a pivotal role in the improvement of the physical health of these patients by expanding their task from clinical psychiatric care to the monitoring and treatment of crucial physical parameters. At a system level, actions are not easy to realize, especially for developing countries. However, at an individual level, even simple and very basic monitoring and treatment actions, undertaken by the treating clinician, can already improve the problem of suboptimal medical care in this population. Adhering to monitoring and treatment guidelines will result in a substantial enhancement of physical health outcomes. Furthermore, psychiatrists can help educate and motivate people with SMI to address their suboptimal lifestyle, including smoking, unhealthy diet and lack of exercise. The adoption of the recommendations presented in this paper across health care systems throughout the world will contribute to a significant improvement in the medical and related psychiatric health outcomes of patients with SMI.
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                Author and article information

                Contributors
                malcolm.battersby@flinders.edu.au
                michael.kidd@utoronto.ca , michael.kidd@flinders.edu.au
                julio.licinio@sahmri.com
                Phil.Aylward@sa.gov.au
                amanda.baker@newcastle.edu.au
                julie.ratcliffe@unisa.edu.au
                sjquinn@swin.edu.au
                david.castle@svha.org.au
                sara.zabeen@flinders.edu.au
                kate.fairweather-smith@flinders.edu.au
                sharon.lawn@flinders.edu.au
                Journal
                Trials
                Trials
                Trials
                BioMed Central (London )
                1745-6215
                11 July 2018
                11 July 2018
                2018
                : 19
                : 366
                Affiliations
                [1 ]Mental Health Services, Southern Adelaide Local Health Network (SAHLN), Margaret Tobin Centre, Bedford Park, South Australia 5042 Australia
                [2 ]ISNI 0000 0001 2157 2938, GRID grid.17063.33, Department of Family & Community Medicine, , University of Toronto, ; 500 University Avenue, Toronto, ON M5G 1V7 Canada
                [3 ]ISNI 0000 0004 0367 2697, GRID grid.1014.4, Global Primary Care, Southgate Institute for Health, Society and Equity, , Flinders University, ; GPO Box 2100, Adelaide, South Australia 5001 Australia
                [4 ]GRID grid.430453.5, South Australian Health and Medical Research Institute, ; North Terrace, Adelaide, South Australia 5000 Australia
                [5 ]ISNI 0000 0004 0625 890X, GRID grid.459526.9, Division of Medicine, Cardiac and Critical Care Services, Southern Adelaide Local Health Network (SALHN), , Flinders Cardiac Clinic, Flinders Private Hospital, ; Bedford Park, South Australia 5042 Australia
                [6 ]ISNI 0000 0000 8831 109X, GRID grid.266842.c, NHMRC Centre of Research Excellence in Mental Health and Substance Use, NHMRC Senior Research Fellow, School of Medicine and Public Health, , University of Newcastle, ; Callaghan, NSW 2308 Australia
                [7 ]ISNI 0000 0000 8994 5086, GRID grid.1026.5, Health Economics in the Institute for Choice, School of Business, , University of South Australia, ; City West Campus (WL3-65), GPO Box 2471, Adelaide, South Australia 5001 Australia
                [8 ]ISNI 0000 0004 0409 2862, GRID grid.1027.4, Department of Statistics, Data Science and Epidemiology, , Swinburne University of Technology, ; ATC-922, John Street, Hawthorn, VIC 3122 Australia
                [9 ]ISNI 0000 0000 8606 2560, GRID grid.413105.2, St. Vincent’s Hospital Melbourne and The University of Melbourne, ; PO Box 2900, Fitzroy, VIC 3065 Australia
                [10 ]ISNI 0000 0004 0367 2697, GRID grid.1014.4, Flinders Human Behaviour & Health Research Unit (FHBHRU), Discipline of Psychiatry, College of Medicine and Public Health, , Flinders University, Margaret Tobin Centre, ; GPO Box 2100, Adelaide, South Australia 5001 Australia
                Author information
                http://orcid.org/0000-0002-5464-8887
                Article
                2748
                10.1186/s13063-018-2748-7
                6042320
                29996886
                f3336de7-d193-49a0-9928-c053868b2314
                © The Author(s). 2018

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 2 March 2018
                : 19 June 2018
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100000925, National Health and Medical Research Council;
                Award ID: APP1121334
                Award Recipient :
                Categories
                Study Protocol
                Custom metadata
                © The Author(s) 2018

                Medicine
                flinders program,chronic condition self-management,chronic care model,cardiovascular disease,mental illness,health intervention,randomised controlled trial

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