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Reilly S, Hobson-Merrett C, Gibbons B, Jones B, Richards D, Plappert H, Gibson J, Green M, Gask L, Huxley PJ, Druss BG, Planner CL. Collaborative care approaches for people with severe mental illness. Cochrane Database Syst Rev 2024; 5:CD009531. [PMID: 38712709 PMCID: PMC11075124 DOI: 10.1002/14651858.cd009531.pub3] [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] [Indexed: 05/08/2024]
Abstract
BACKGROUND Collaborative care for severe mental illness (SMI) is a community-based intervention that promotes interdisciplinary working across primary and secondary care. Collaborative care interventions aim to improve the physical and/or mental health care of individuals with SMI. This is an update of a 2013 Cochrane review, based on new searches of the literature, which includes an additional seven studies. OBJECTIVES To assess the effectiveness of collaborative care approaches in comparison with standard care (or other non-collaborative care interventions) for people with diagnoses of SMI who are living in the community. SEARCH METHODS We searched the Cochrane Schizophrenia Study-Based Register of Trials (10 February 2021). We searched the Cochrane Common Mental Disorders (CCMD) controlled trials register (all available years to 6 June 2016). Subsequent searches on Ovid MEDLINE, Embase and PsycINFO together with the Cochrane Central Register of Controlled Trials (with an overlap) were run on 17 December 2021. SELECTION CRITERIA Randomised controlled trials (RCTs) where interventions described as 'collaborative care' were compared with 'standard care' for adults (18+ years) living in the community with a diagnosis of SMI. SMI was defined as schizophrenia, other types of schizophrenia-like psychosis or bipolar affective disorder. The primary outcomes of interest were: quality of life, mental state and psychiatric admissions at 12 months follow-up. DATA COLLECTION AND ANALYSIS Pairs of authors independently extracted data. We assessed the quality and certainty of the evidence using RoB 2 (for the primary outcomes) and GRADE. We compared treatment effects between collaborative care and standard care. We divided outcomes into short-term (up to six months), medium-term (seven to 12 months) and long-term (over 12 months). For dichotomous data we calculated the risk ratio (RR) and for continuous data we calculated the standardised mean difference (SMD), with 95% confidence intervals (CIs). We used random-effects meta-analyses due to substantial levels of heterogeneity across trials. We created a summary of findings table using GRADEpro. MAIN RESULTS Eight RCTs (1165 participants) are included in this review. Two met the criteria for type A collaborative care (intervention comprised of the four core components). The remaining six met the criteria for type B (described as collaborative care by the trialists, but not comprised of the four core components). The composition and purpose of the interventions varied across studies. For most outcomes there was low- or very low-certainty evidence. We found three studies that assessed the quality of life of participants at 12 months. Quality of life was measured using the SF-12 and the WHOQOL-BREF and the mean endpoint mental health component scores were reported at 12 months. Very low-certainty evidence did not show a difference in quality of life (mental health domain) between collaborative care and standard care in the medium term (at 12 months) (SMD 0.03, 95% CI -0.26 to 0.32; 3 RCTs, 227 participants). Very low-certainty evidence did not show a difference in quality of life (physical health domain) between collaborative care and standard care in the medium term (at 12 months) (SMD 0.08, 95% CI -0.18 to 0.33; 3 RCTs, 237 participants). Furthermore, in the medium term (at 12 months) low-certainty evidence did not show a difference between collaborative care and standard care in mental state (binary) (RR 0.99, 95% CI 0.77 to 1.28; 1 RCT, 253 participants) or in the risk of being admitted to a psychiatric hospital at 12 months (RR 5.15, 95% CI 0.67 to 39.57; 1 RCT, 253 participants). One study indicated an improvement in disability (proxy for social functioning) at 12 months in the collaborative care arm compared to usual care (RR 1.38, 95% CI 0.97 to 1.95; 1 RCT, 253 participants); we deemed this low-certainty evidence. Personal recovery and satisfaction/experience of care outcomes were not reported in any of the included studies. The data from one study indicated that the collaborative care treatment was more expensive than standard care (mean difference (MD) international dollars (Int$) 493.00, 95% CI 345.41 to 640.59) in the short term. Another study found the collaborative care intervention to be slightly less expensive at three years. AUTHORS' CONCLUSIONS This review does not provide evidence to indicate that collaborative care is more effective than standard care in the medium term (at 12 months) in relation to our primary outcomes (quality of life, mental state and psychiatric admissions). The evidence would be improved by better reporting, higher-quality RCTs and the assessment of underlying mechanisms of collaborative care. We advise caution in utilising the information in this review to assess the effectiveness of collaborative care.
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Affiliation(s)
- Siobhan Reilly
- Centre for Applied Dementia Studies, Faculty of Health Studies, University of Bradford, Bradford, UK
- Wolfson Centre for Applied Health Research, Bradford, UK
- Division of Health Research, Lancaster University, Lancaster, UK
| | - Charley Hobson-Merrett
- Primary Care Plymouth, University of Plymouth, Plymouth, UK
- National Institute for Health Research Applied Research Collaboration South West Peninsula, Plymouth, UK
| | | | - Ben Jones
- College of Medicine and Health, University of Exeter, Exeter, UK
| | - Debra Richards
- Primary Care Plymouth, University of Plymouth, Plymouth, UK
| | - Humera Plappert
- Primary Care Clinical Sciences, University of Birmingham, Birmingham, UK
| | | | - Maria Green
- Pennine Health Care NHS Foundation Trust, Bury, UK
| | - Linda Gask
- Health Sciences Research Group, Manchester Academic Health Science Centre, University of Manchester, Manchester, UK
| | - Peter J Huxley
- Centre for Mental Health and Society, School of Health Sciences, Bangor University, Bangor, UK
| | - Benjamin G Druss
- Department of Health Policy and Management, Emory University, Atlanta, USA
| | - Claire L Planner
- Centre for Primary Care and Health Services Research, University of Manchester, Manchester, UK
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Kanofsky JD, Viswanathan S, Wylie-Rosett J. Lifestyle Coaching May Be an Effective Treatment for Schizophrenia. Am J Lifestyle Med 2024; 18:156-161. [PMID: 38559781 PMCID: PMC10979723 DOI: 10.1177/15598276221142307] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/04/2024] Open
Abstract
This commentary critiques the Danish CHANGE trial, which evaluated 3 levels of outpatient intervention intensity, in a group of outpatients with obesity and schizophrenia. Neither adding care coordination with weekly nurse contacts alone nor combining this treatment with assertive community lifestyle coaching as compared to treatment as usual improved outcomes, which included cardiovascular disease risk calculation, cardiorespiratory fitness, weight, and self-reported behaviors such as smoking, physical activity, and diet. The CHANGE trial investigators appear strongly averse to recommending the development and implementation of lifestyle medicine programs as a major component when treating outpatients with severe mental disorders. The potential dismissal of lifestyle medicine as a component of treatment for severe mental disorders is problematic. Valuable lessons can be learned from more thoroughly analyzing secondary outcomes such as medical and psychiatric hospitalization rates and total health care cost. The CHANGE trial data analysis needs to be expanded beyond the focus on changes in weight and serum cholesterol. Insulin resistance and high refined carbohydrate intake may be major factors in determining both the medical and psychiatric clinical course of schizophrenia. Assertive community lifestyle coaching is a novel treatment modality. Evidence strongly suggests assertive community lifestyle coaching substantially decreases both psychiatric and medical hospitalization rates.
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Affiliation(s)
- Jacob Daniel Kanofsky
- Bronx Psychiatric Center, Bronx, NY, USA (JDK); Department of Psychiatry and Behavioral Sciences, Albert Einstein College of Medicine, Bronx, NY, USA (JDK); Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA (SV, JWR); and New York Regional Center for Diabetes Translational Research, Albert Einstein College of Medicine, Bronx, NY, USA (JWR)
| | - Shankar Viswanathan
- Bronx Psychiatric Center, Bronx, NY, USA (JDK); Department of Psychiatry and Behavioral Sciences, Albert Einstein College of Medicine, Bronx, NY, USA (JDK); Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA (SV, JWR); and New York Regional Center for Diabetes Translational Research, Albert Einstein College of Medicine, Bronx, NY, USA (JWR)
| | - Judith Wylie-Rosett
- Bronx Psychiatric Center, Bronx, NY, USA (JDK); Department of Psychiatry and Behavioral Sciences, Albert Einstein College of Medicine, Bronx, NY, USA (JDK); Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA (SV, JWR); and New York Regional Center for Diabetes Translational Research, Albert Einstein College of Medicine, Bronx, NY, USA (JWR)
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3
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Murphy KA, Sarker E, Stuart EA, Cook C, Goldsholl S, Daumit GL. Effect of Care Management on Cholesterol for Individuals with Serious Mental Illness: a Secondary Analysis of an RCT. J Gen Intern Med 2024; 39:354-356. [PMID: 37950107 PMCID: PMC10853150 DOI: 10.1007/s11606-023-08510-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/13/2023] [Accepted: 10/24/2023] [Indexed: 11/12/2023]
Affiliation(s)
- Karly A Murphy
- Division of General Internal Medicine, Department of Medicine, University of California San Francisco, San Francisco, CA, USA.
| | - Elizabeth Sarker
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Elizabeth A Stuart
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Courtney Cook
- Division of General Internal Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Stacy Goldsholl
- Division of General Internal Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Gail L Daumit
- Division of General Internal Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
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Gerber M, Cody R, Beck J, Brand S, Donath L, Eckert A, Hatzinger M, Imboden C, Kreppke JN, Lang UE, Ludyga S, Mans S, Mikoteit T, Oswald A, Schweinfurth-Keck N, Zahner L, Faude O. Cardiorespiratory fitness and cardiovascular risk among in-patients with depression compared to healthy controls. Front Psychiatry 2023; 14:1193004. [PMID: 37409158 PMCID: PMC10318346 DOI: 10.3389/fpsyt.2023.1193004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/24/2023] [Accepted: 05/31/2023] [Indexed: 07/07/2023] Open
Abstract
Introduction Compared to the general population, individuals with depression have an increased risk for cardiovascular diseases. Nevertheless, little is known so far whether cardiorespiratory fitness (CRF) moderates this relationship. Therefore, we examined whether common physiological cardiovascular risk factors differ between patients with depression and healthy (non-depressed) controls, whether patients and controls differ in CRF, and whether higher CRF is associated with a lower cardiovascular risk in both patients and healthy controls. Additionally, we examined whether within the patient sample, cardiovascular risk factors differ between patients with mild, moderate and severe depression, and whether the relationship between symptom severity and cardiovascular risk is moderated by patients' CRF levels. Methods Data from a multi-centric, two-arm randomized controlled trial (RCT) was analyzed, including 210 patients (F32, single episode: n = 72, F33, recurrent major depression: n = 135, F31-II, bipolar type II: n = 3) and 125 healthy controls. Waist circumference, body mass index, body fat, blood pressure, cholesterol levels, triglycerides, and blood glucose were considered as cardiovascular risk markers. CRF was assessed with a submaximal ergometer test. Differences between groups were examined via χ2-tests and (multivariate) analyses of covariance. Results Compared to healthy controls, patients with depression had a higher cardiovascular risk as evident from about half of the examined indicators. In the total sample, participants with good CRF had more favourable scores across nearly all risk markers than counterparts with poor CRF. For most variables, no interaction occurred between group and fitness, indicating that in patients and controls, similar differences existed between participants with poor and good CRF. Few differences in risk markers were found between patients with mild, moderate and severe depression, and no interaction occurred between depression severity and CRF. Discussion Patients with depression and healthy controls differ in several cardiovascular risk markers, putting patients at increased risk for CVDs. In contrast, people with good CRF show more favourable cardiovascular risk scores, a relationship which was observed in both healthy controls and patients with depression. Physical health of psychiatric patients should receive the clinical attention that it deserves. Lifestyle interventions targeting healthy diet and/or physical activity are recommended as a physically active and healthy lifestyle contributes equally to patients' mental well-being and cardiovascular health.
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Affiliation(s)
- Markus Gerber
- Department for Sport, Exercise and Health, University of Basel, Basel, Switzerland
| | - Robyn Cody
- Department for Sport, Exercise and Health, University of Basel, Basel, Switzerland
| | | | - Serge Brand
- Department for Sport, Exercise and Health, University of Basel, Basel, Switzerland
- Adult Psychiatric Clinics (UPKE), University of Basel, Basel, Switzerland
- Sleep Disorders Research Center, Kermanshah University of Medical Sciences, Kermanshah, Iran
- Substance Use Prevention Research Center and Sleep Disorder Research Center, Kermanshah, University of Medical Sciences (KUMS), Kermanshah, Iran
- School of Medicine, Tehran University of Medical Sciences (TUMS), Tehran, Iran
| | - Lars Donath
- German Sport University Cologne, Cologne, Germany
| | - Anne Eckert
- Adult Psychiatric Clinics (UPKE), University of Basel, Basel, Switzerland
| | - Martin Hatzinger
- Psychiatric Services Solothurn, Solothurn, Switzerland, and University of Basel, Solothurn, Switzerland
| | | | - Jan-Niklas Kreppke
- Department for Sport, Exercise and Health, University of Basel, Basel, Switzerland
| | - Undine E. Lang
- Adult Psychiatric Clinics (UPKE), University of Basel, Basel, Switzerland
| | - Sebastian Ludyga
- Department for Sport, Exercise and Health, University of Basel, Basel, Switzerland
| | - Sarah Mans
- Private Clinic Wyss, Münchenbuchsee, Switzerland
| | - Thorsten Mikoteit
- Psychiatric Services Solothurn, Solothurn, Switzerland, and University of Basel, Solothurn, Switzerland
| | - Anja Oswald
- Psychiatric Clinic Sonnenhalde, Riehen, Switzerland
| | | | - Lukas Zahner
- Department for Sport, Exercise and Health, University of Basel, Basel, Switzerland
| | - Oliver Faude
- Department for Sport, Exercise and Health, University of Basel, Basel, Switzerland
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Dalcin AT, Yuan CT, Jerome GJ, Goldsholl S, Minahan E, Gennusa J, Fink T, Gudzune KA, Daumit GL, Dickerson F, Thompson DA, Wang NY, Martino S. Designing Practical Motivational Interviewing Training for Mental Health Practitioners Implementing Behavioral Lifestyle Interventions: Protocol for 3 Pilot Intervention Studies. JMIR Res Protoc 2023; 12:e44830. [PMID: 36927501 PMCID: PMC10132009 DOI: 10.2196/44830] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2022] [Revised: 01/13/2023] [Accepted: 01/31/2023] [Indexed: 02/03/2023] Open
Abstract
BACKGROUND Motivational interviewing (MI) is an evidence-based, patient-centered communication method shown to be effective in helping persons with serious mental illness (SMI) to improve health behaviors. In clinical trials where study staff conducted lifestyle interventions incorporating an MI approach, cardiovascular disease (CVD) risk profiles of participants with SMI showed improvement. Given the disproportionate burden of CVD in this population, practitioners who provide somatic and mental health care to persons with SMI are ideally positioned to deliver patient-centered CVD risk reduction interventions. However, the time for MI training (traditionally 16-24 hours), follow-up feedback, and the coaching required to develop and maintain patient-centered skills are significant barriers to incorporating MI when scaling up these evidence-based practices. OBJECTIVE We describe the design and development of the following 2 scalable MI training approaches for community mental health practitioners: real-time brief workshops and follow-up asynchronous avatar training. These approaches are being used in 3 different pilot implementation research projects that address weight loss, smoking cessation, and CVD risk reduction in people with SMI who are a part of ALACRITY Center, a research-to-practice translation center funded by the National Institute of Mental Health. METHODS Clinicians and staff in community mental health clinics across Maryland were trained to deliver 3 distinct evidence-based physical health lifestyle interventions using an MI approach to persons with SMI. The real-time brief MI workshop training for ACHIEVE-D weight loss coaches was 4 hours; IMPACT smoking cessation counselors received 2-hour workshops and prescribers received 1-hour workshops; and RHYTHM CVD risk reduction program staff received 4 hours of MI. All workshop trainings occurred over videoconference. The asynchronous avatar training includes 1 common didactic instructional module for the 3 projects and 1 conversation simulation unique to each study's target behavior. Avatar training is accessible on a commercial website. We plan to assess practitioners' attitudes and beliefs about MI and evaluate the impact of the 2 MI training approaches on their MI skills 3, 6, and 12 months after training using the MI Treatment Integrity 4.2.1 coding tool and the data generated by the avatar-automated scoring system. RESULTS The ALACRITY Center was funded in August 2018. We have implemented the MI training for 126 practitioners who are currently delivering the 3 implementation projects. We expect the studies to be complete in May 2023. CONCLUSIONS This study will contribute to knowledge about the effect of brief real-time training augmented with avatar skills practice on clinician MI skills. If MI Treatment Integrity scoring shows it to be effective, brief videoconference trainings supplemented with avatar skills practice could be used to train busy community mental health practitioners to use an MI approach when implementing physical health interventions. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID) DERR1-10.2196/44830.
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Affiliation(s)
- Arlene Taylor Dalcin
- Division of General Internal Medicine, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, United States.,Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins Medical Institution, Baltimore, MD, United States
| | - Christina T Yuan
- Department of Health Policy and Management, Johns Hopkins University Bloomberg School of Public Health,, Baltimore, MD, United States
| | - Gerald J Jerome
- Division of General Internal Medicine, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, United States.,College of Health Professions, Towson University, Towson, MD, United States
| | - Stacy Goldsholl
- Division of General Internal Medicine, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Eva Minahan
- Division of General Internal Medicine, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Joseph Gennusa
- Division of General Internal Medicine, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Tyler Fink
- Division of General Internal Medicine, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Kimberly A Gudzune
- Division of General Internal Medicine, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, United States.,Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins Medical Institution, Baltimore, MD, United States
| | - Gail Lois Daumit
- Division of General Internal Medicine, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, United States.,Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins Medical Institution, Baltimore, MD, United States
| | - Faith Dickerson
- Department of Psychology, Sheppard Pratt, Baltimore, MD, United States
| | - David A Thompson
- Department of Anesthesiology and Critical Care Medicine, Johns Hopkins School of Medicine, Baltimore, MD, United States
| | - Nae-Yuh Wang
- Division of General Internal Medicine, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, United States.,Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins Medical Institution, Baltimore, MD, United States
| | - Steve Martino
- Department of Psychiatry, Yale University, West Haven, CT, United States.,VA Connecticut Healthcare System, West Haven, CT, United States
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6
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Molin J, Jonsson LI, Antonsson H. From traditional counselling to health-promoting conversations? Registered nurses' experiences of providing health counselling to people living with severe mental ill-health in supported housing. Int J Ment Health Nurs 2023; 32:875-883. [PMID: 36861747 DOI: 10.1111/inm.13133] [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: 11/09/2022] [Revised: 01/19/2023] [Accepted: 02/09/2023] [Indexed: 03/03/2023]
Abstract
People with severe mental ill-health have lower life expectancies than the rest of the population, partly due to unhealthy lifestyles. Counselling to help these people improve their health can also be complex, and registered nurses are key to its success. The aim of this study was to elucidate registered nurses' experiences of providing health counselling to people living with severe mental ill-health in supported housing. We conducted eight individual semi-structured interviews with registered nurses working in this context and subjected the responses to qualitative content analysis. The results show that registered nurses who counsel people with severe mental ill-health feel dispirited, but they defend their often fruitless endeavours and strive, through health counselling, to help these people meet healthier lifestyle goals. Shifting the focus from traditional health counselling to person-centred care using health-promoting conversations could strengthen registered nurses in their efforts towards improving lifestyles among people living with severe mental ill-health in supported housing. Therefore, to facilitate healthier lifestyles among this population, we recommend that community healthcare support registered nurses working in supported housing by educating them in the use of health-promoting conversations, including teach-back techniques.
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Affiliation(s)
- Jenny Molin
- Department of Nursing, Umeå University, Umeå, Sweden.,Department of Clinical Science, Division of Psychiatry, Umeå, Sweden
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7
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Murphy KA, Daumit GL. Establishing a Care Continuum for Cardiometabolic Conditions for Patients with Serious Mental Illness. Curr Cardiol Rep 2023; 25:193-202. [PMID: 36847991 PMCID: PMC10042919 DOI: 10.1007/s11886-023-01848-z] [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] [Accepted: 02/03/2023] [Indexed: 03/01/2023]
Abstract
PURPOSE OF REVIEW Addressing cardiometabolic risk factors in persons with serious mental illness requires early screening and proactive medical management in both medical and mental health settings. RECENT FINDINGS Cardiovascular disease remains the leading cause of death for persons with serious mental illness (SMI), such as schizophrenia or bipolar disorder, much of which is driven by a high prevalence of metabolic syndrome, diabetes, and tobacco use. We summarize barriers and recent approaches to screening and treatment for metabolic cardiovascular risk factors within physical health and specialty mental health settings. Incorporating system-based and provider-level support within physical health and psychiatric clinical settings should contribute to improvement for screening, diagnosis, and treatment for cardiometabolic conditions for patients with SMI. Targeted education for clinicians and leveraging multi-disciplinary teams are important first steps to recognize and treat populations with SMI at risk of CVD.
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Affiliation(s)
- Karly A Murphy
- Division of General Internal Medicine, University of California San Francisco School of Medicine, 1701 Divisidero Street, Suite 500, 94117, San Francisco, CA, USA.
| | - Gail L Daumit
- Division of General Internal Medicine, Johns Hopkins School of Medicine, Baltimore, MD, USA
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8
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Kho A, Daumit GL, Truesdale KP, Brown A, Kilbourne AM, Ladapo J, Wali S, Cicutto L, Matthews AK, Smith JD, Davis PD, Schoenthaler A, Ogedegbe G, Islam N, Mills KT, He J, Watson KS, Winn RA, Stevens J, Huebschmann AG, Szefler SJ. The National Heart Lung and Blood Institute Disparities Elimination through Coordinated Interventions to Prevent and Control Heart and Lung Disease Alliance. Health Serv Res 2022; 57 Suppl 1:20-31. [PMID: 35383917 PMCID: PMC9108215 DOI: 10.1111/1475-6773.13983] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2021] [Revised: 02/05/2022] [Accepted: 02/08/2022] [Indexed: 11/27/2022] Open
Abstract
OBJECTIVE To describe the National Heart Lung and Blood Institute (NHLBI) sponsored Disparities Elimination through Coordinated Interventions to Prevent and Control Heart and Lung Disease (DECIPHeR) Alliance to support late-stage implementation research aimed at reducing disparities in communities with high burdens of cardiovascular and/or pulmonary disease. STUDY SETTING NHBLI funded seven DECIPHeR studies and a Coordinating Center. Projects target high-risk diverse populations including racial and ethnic minorities, urban, rural, and low-income communities, disadvantaged children, and persons with serious mental illness. Two projects address multiple cardiovascular risk factors, three focus on hypertension, one on tobacco use, and one on pediatric asthma. STUDY DESIGN The initial phase supports planning activities for sustainable uptake of evidence-based interventions in targeted communities. The second phase tests late-stage evidence-based implementation strategies. DATA COLLECTION/EXTRACTION METHODS Not applicable. PRINCIPAL FINDINGS We provide an overview of the DECIPHeR Alliance and individual study designs, populations, and settings, implementation strategies, interventions, and outcomes. We describe the Alliance's organizational structure, designed to promote cross-center partnership and collaboration. CONCLUSIONS The DECIPHeR Alliance represents an ambitious national effort to develop sustainable implementation of interventions to achieve cardiovascular and pulmonary health equity.
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Affiliation(s)
- Abel Kho
- Center for Health Information Partnerships (CHiP)Northwestern University Feinberg School of MedicineChicagoIllinoisUSA
| | - Gail L. Daumit
- Department of MedicineJohns Hopkins University School of MedicineBaltimoreMarylandUSA
| | - Kimberly P. Truesdale
- Department of Nutrition, Gillings School of Global Public HealthUniversity of North CarolinaChapel HillNorth CarolinaUSA
| | - Arleen Brown
- Department of Internal MedicineUniversity of Los Angeles School of MedicineLos AngelesCAUSA
| | - Amy M. Kilbourne
- Department of Learning Health SciencesUniversity of Michigan MedicineAnn ArborMichiganUSA
- Quality Enhancement Research Initiative (QUERI)U.S. Department of Veterans AffairsWashington, D.C.USA
| | - Joseph Ladapo
- Department of MedicineUniversity of Florida College of MedicineGainesvilleFloridaUSA
| | - Soma Wali
- Department of Internal MedicineUniversity of Los Angeles School of MedicineLos AngelesCAUSA
| | - Lisa Cicutto
- Department of MedicineNational Jewish Health, Community Outreach and ResearchDenverColoradoUSA
| | | | - Justin D. Smith
- Department of Population Health SciencesUniversity of Utah HealthSalt Lake CityUtahUSA
| | - Paris D. Davis
- Total Resource Community Development OrganizationNorthwestern UniversityChicagoIllinoisUSA
| | - Antoinette Schoenthaler
- Department of Population HealthNew York University Grossman School of MedicineNew YorkNew YorkUSA
| | - Gbenga Ogedegbe
- Department of Population HealthNew York University Grossman School of MedicineNew YorkNew YorkUSA
| | - Nadia Islam
- Department of Population HealthNew York University Grossman School of MedicineNew YorkNew YorkUSA
| | - Katherine T. Mills
- Department of EpidemiologyTulane University School of Public Health and Tropical MedicineNew OrleansLouisianaUSA
| | - Jiang He
- Department of EpidemiologyTulane University School of Public Health and Tropical MedicineNew OrleansLouisianaUSA
| | - Karriem S. Watson
- NIH All of Us Bethesda, MD; FormerlyUniversity of Illinois in Chicago Hospital and Health Sciences System, Mile Square Health Center ChicagoIllinoisUSA
| | - Robert A. Winn
- Massey Cancer CenterVirginia Commonwealth UniversityRichmondVirginiaUSA
| | - June Stevens
- Department of Nutrition, Gillings School of Global Public HealthUniversity of North CarolinaChapel HillNorth CarolinaUSA
| | - Amy G. Huebschmann
- Department of Medicine, Division of General Internal MedicineUniversity of Colorado Denver School of MedicineAuroraColoradoUSA
| | - Stanley J. Szefler
- Department of PediatricsUniversity of Colorado Denver School of MedicineDenverColoradoUSA
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9
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Kemp JVA, Bernier E, Lebel C, Kopala-Sibley DC. Associations Between Parental Mood and Anxiety Psychopathology and Offspring Brain Structure: A Scoping Review. Clin Child Fam Psychol Rev 2022; 25:222-247. [PMID: 35201543 DOI: 10.1007/s10567-022-00393-5] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/14/2022] [Indexed: 12/22/2022]
Abstract
A family history of mood and anxiety disorders is one of the most well-established risk factors for these disorders in offspring. A family history of these disorders has also been linked to alterations in brain regions involved in cognitive-affective processes broadly, and mood and anxiety disorders specifically. Results from studies of brain structure of children of parents with a history of mood or anxiety disorders (high-risk offspring) have been inconsistent. We followed the PRISMA protocol to conduct a scoping review of the literature linking parental mood and anxiety disorders to offspring brain structure to examine which structures in offspring brains are linked to parental major depressive disorder (MDD), anxiety, or bipolar disorder (BD). Studies included were published in peer-reviewed journals between January 2000 and July 2021. Thirty-nine studies were included. Significant associations between parental BD and offspring caudate volume, inferior frontal gyrus thickness, and anterior cingulate cortex thickness were found. Associations were also identified between parental MDD and offspring amygdala and hippocampal volumes, fusiform thickness, and thickness in temporoparietal regions. Few studies have examined associations between parental anxiety and high-risk offspring brain structure; however, one study found associations between parental anxiety symptoms and offspring amygdala structure, and another found similar associations with the hippocampus. The direction of grey matter change across studies was inconsistent, potentially due to the large age ranges for each study and the non-linear development of the brain. Children of parents with MDD and bipolar disorders, or elevated anxiety symptoms, show alterations in a range of brain regions. Results may further efforts to identify children at high risk for affective disorders and may elucidate whether alterations in specific brain regions represent premorbid markers of risk for mood and anxiety disorders.
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Affiliation(s)
- Jennifer V A Kemp
- Department of Psychiatry, University of Calgary, Calgary, AB, Canada. .,Hotchkiss Brain Institute, Calgary, AB, Canada. .,Mathison Centre for Mental Health Research & Education, Calgary, AB, Canada. .,Faculty of Cumming School of Medicine, University of Calgary, Foothills Hospital Teaching Research and Wellness Building, 3280 Hospital Dr NW, Calgary, AB, T2N 4Z6, Canada.
| | - Emily Bernier
- Department of Psychiatry, University of Calgary, Calgary, AB, Canada.,Hotchkiss Brain Institute, Calgary, AB, Canada.,Mathison Centre for Mental Health Research & Education, Calgary, AB, Canada
| | - Catherine Lebel
- Alberta Children's Hospital Research Institute, Calgary, AB, Canada.,Hotchkiss Brain Institute, Calgary, AB, Canada.,Mathison Centre for Mental Health Research & Education, Calgary, AB, Canada.,Department of Radiology, University of Calgary, Calgary, AB, Canada
| | - Daniel C Kopala-Sibley
- Department of Psychiatry, University of Calgary, Calgary, AB, Canada.,Alberta Children's Hospital Research Institute, Calgary, AB, Canada.,Hotchkiss Brain Institute, Calgary, AB, Canada.,Mathison Centre for Mental Health Research & Education, Calgary, AB, Canada
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10
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Baker AL, Forbes E, Pohlman S, McCarter K. Behavioral Interventions to Reduce Cardiovascular Risk Among People with Severe Mental Disorder. Annu Rev Clin Psychol 2022; 18:99-124. [PMID: 35175861 DOI: 10.1146/annurev-clinpsy-072720-012042] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Cardiovascular disease (CVD) is the leading cause of death among people with severe mental disorder (SMD). CVD risk factors occur at the individual, health system, and socio-environmental levels and contribute not only to high rates of CVD but also to worsening mental health. While acknowledging this wider context, this review focuses on behavioral interventions for seven CVD risk behaviors-smoking, physical inactivity, excessive alcohol consumption, low fruit and vegetable intake, inadequate sleep, poor social participation, and poor medication adherence-that are common among people with SMD. We survey recent meta-reviews of the literature and then review additional key studies to provide clinical recommendations for behavioral interventions to reduce CVD risk among people with SMD. A transdiagnostic psychological approach from the start of mental health treatment, drawing upon multidisciplinary expertise to address multiple risk behaviors, is recommended. Expected final online publication date for the Annual Review of Clinical Psychology, Volume 18 is May 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
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Affiliation(s)
- Amanda L Baker
- School of Medicine and Public Health, College of Health, Medicine and Wellbeing, University of Newcastle, Callaghan, New South Wales, Australia;
| | - Erin Forbes
- School of Medicine and Public Health, College of Health, Medicine and Wellbeing, University of Newcastle, Callaghan, New South Wales, Australia;
| | - Sonja Pohlman
- School of Psychology, College of Engineering, Science and Environment, University of Newcastle, Callaghan, New South Wales, Australia
| | - Kristen McCarter
- School of Psychology, College of Engineering, Science and Environment, University of Newcastle, Callaghan, New South Wales, Australia
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11
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Huang W, Chang CH, Stuart EA, Daumit GL, Wang NY, McGinty EE, Dickerson FB, Igusa T. Agent-Based Modeling for Implementation Research: An Application to Tobacco Smoking Cessation for Persons with Serious Mental Illness. IMPLEMENTATION RESEARCH AND PRACTICE 2021; 2. [PMID: 34308355 DOI: 10.1177/26334895211010664] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
Background Implementation researchers have sought ways to use simulations to support the core components of implementation, which typically include assessing the need for change, designing implementation strategies, executing the strategies, and evaluating outcomes. The goal of this paper is to explain how agent-based modeling could fulfill this role. Methods We describe agent-based modeling with respect to other simulation methods that have been used in implementation science, using non-technical language that is broadly accessible. We then provide a stepwise procedure for developing agent-based models of implementation processes. We use, as a case study to illustrate the procedure, the implementation of evidence-based smoking cessation practices for persons with serious mental illness (SMI) in community mental health clinics. Results For our case study, we present descriptions of the motivating research questions, specific models used to answer these questions, and a summary of the insights that can be obtained from the models. In the first example, we use a simple form of agent-based modeling to simulate the observed smoking behaviors of persons with SMI in a recently completed trial (IDEAL, Comprehensive Cardiovascular Risk Reduction Trial in Persons with SMI). In the second example, we illustrate how a more complex agent-based approach that includes interactions between patients, providers and site administrators can be used to provide guidance for an implementation intervention that includes training and organizational strategies. This example is based in part on an ongoing project focused on scaling up evidence-based tobacco smoking cessation practices in community mental health clinics in Maryland. Conclusion In this paper we explain how agent-based models can be used to address implementation science research questions and provide a procedure for setting up simulation models. Through our examples, we show how what-if scenarios can be examined in the implementation process, which are particularly useful in implementation frameworks with adaptive components.
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Affiliation(s)
- Wanyu Huang
- Department of Civil and Systems Engineering, Johns Hopkins University
| | - Chia-Hsiu Chang
- Department of Civil and Systems Engineering, Johns Hopkins University
| | - Elizabeth A Stuart
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health.,Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health.,Department of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health
| | - Gail L Daumit
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health.,Department of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health.,Division of General Internal Medicine, Johns Hopkins University School of Medicine.,Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health.,Welch Center for Prevention, Epidemiology and Clinical Research, Johns Hopkins University
| | - Nae-Yuh Wang
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health.,Division of General Internal Medicine, Johns Hopkins University School of Medicine.,Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health.,Welch Center for Prevention, Epidemiology and Clinical Research, Johns Hopkins University
| | - Emma E McGinty
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health.,Department of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health
| | | | - Takeru Igusa
- Department of Civil and Systems Engineering, Johns Hopkins University.,Department of Mental Health, Johns Hopkins Bloomberg School of Public Health.,Department of Applied Mathematics and Statistics, Johns Hopkins University
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12
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Murphy KA, Dalcin A, McGinty EE, Goldsholl S, Heller A, Daumit GL. Applying Care Coordination Principles to Reduce Cardiovascular Disease Risk Factors in People With Serious Mental Illness: A Case Study Approach. Front Psychiatry 2021; 12:742169. [PMID: 35002793 PMCID: PMC8727450 DOI: 10.3389/fpsyt.2021.742169] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/15/2021] [Accepted: 11/30/2021] [Indexed: 11/13/2022] Open
Abstract
People with serious mental illness (SMI) have a 2-3-fold higher mortality than the general population, much of which is driven by largely preventable cardiovascular disease. One contributory factor is the disconnect between the behavioral and physical health care systems. New care models have sought to integrate physical health care into primary mental health care settings. However, few examples of successful care coordination interventions to improve health outcomes with the SMI population exist. In this paper, we examine challenges faced in coordinating care for people with SMI and explore pragmatic, multi-disciplinary strategies for overcoming these challenges used in a cardiovascular risk reduction intervention shown to be effective in a clinical trial.
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Affiliation(s)
- Karly A Murphy
- Division of General Internal Medicine, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, United States.,Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Arlene Dalcin
- Division of General Internal Medicine, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, United States.,Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Emma E McGinty
- Department of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States.,Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
| | - Stacy Goldsholl
- Division of General Internal Medicine, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Ann Heller
- Division of General Internal Medicine, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Gail L Daumit
- Division of General Internal Medicine, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, United States.,Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University School of Medicine, Baltimore, MD, United States.,Department of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States.,Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
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13
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Abstract
PURPOSE OF REVIEW To provide an overview of the update of the evidence-based and consensus-based German S3 guideline on psychosocial therapies for severe mental illnesses (SMI), with particular attention to current developments and future research tasks. RECENT FINDINGS There has been a significant increase in studies on the effectiveness of psychosocial interventions in treatment of people with SMI. In the guideline a distinction is made between system-level interventions (e.g. multidisciplinary team-based psychiatric community care) and single-handed (nonteam-based) interventions (e.g. psychoeducation). Furthermore, principles of treatment (e.g. recovery-orientation) and self-help interventions (e.g. peer support) are addressed. The update of the guideline includes 33 recommendations and 12 statements. Compared with the first edition, there were upgrades in the recommendation of Supported Employment (A) and Supported Housing (A). Interventions such as peer support (B) and lifestyle interventions (A) were included for the first time. Developments are discussed in the context of most recent literature. Areas for further research are highlighted and fields for next updates such as antistigma interventions and supported parenting were identified. SUMMARY The present guideline offers an important opportunity to further improve health services for people with SMI. However, guideline implementation is challenging.
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14
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Daumit GL, Dalcin AT, Dickerson FB, Miller ER, Evins AE, Cather C, Jerome GJ, Young DR, Charleston JB, Gennusa JV, Goldsholl S, Cook C, Heller A, McGinty EE, Crum RM, Appel LJ, Wang NY. Effect of a Comprehensive Cardiovascular Risk Reduction Intervention in Persons With Serious Mental Illness: A Randomized Clinical Trial. JAMA Netw Open 2020; 3:e207247. [PMID: 32530472 PMCID: PMC7293000 DOI: 10.1001/jamanetworkopen.2020.7247] [Citation(s) in RCA: 54] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
IMPORTANCE Persons with serious mental illness have a cardiovascular disease mortality rate more than twice that of the overall population. Meaningful cardiovascular risk reduction requires targeted efforts in this population, who often have psychiatric symptoms and cognitive impairment. OBJECTIVE To determine the effectiveness of an 18-month multifaceted intervention incorporating behavioral counseling, care coordination, and care management for overall cardiovascular risk reduction in adults with serious mental illness. DESIGN, SETTING, AND PARTICIPANTS This randomized clinical trial was conducted from December 2013 to November 2018 at 4 community mental health outpatient programs in Maryland. The study recruited adults with at least 1 cardiovascular disease risk factor (hypertension, diabetes, dyslipidemia, current tobacco smoking, and/or overweight or obesity) attending the mental health programs. Of 398 participants screened, 269 were randomized to intervention (132 participants) or control (137 participants). Data collection staff were blinded to group assignment. Data were analyzed on the principle of intention to treat, and data analysis was performed from November 2018 to March 2019. INTERVENTIONS A health coach and nurse provided individually tailored cardiovascular disease risk reduction behavioral counseling, collaborated with physicians to implement appropriate risk factor management, and coordinated with mental health staff to encourage attainment of health goals. Programs offered physical activity classes and received consultation on serving healthier meals; intervention and control participants were exposed to these environmental changes. MAIN OUTCOMES AND MEASURES The primary outcome was the change in the risk of cardiovascular disease from the global Framingham Risk Score (FRS), which estimates the 10-year probability of a cardiovascular disease event, from baseline to 18 months, expressed as percentage change for intervention compared with control. RESULTS Of 269 participants randomized (mean [SD] age, 48.8 [11.9] years; 128 men [47.6%]), 159 (59.1%) had a diagnosis of schizophrenia or schizoaffective disorder, 67 (24.9%) had bipolar disorder, and 38 (14.1%) had major depressive disorder. At 18 months, the primary outcome, FRS, was obtained for 256 participants (95.2%). The mean (SD) baseline FRS was 11.5% (11.5%) (median, 8.6%; interquartile range, 3.9%-16.0%) in the intervention group and 12.7% (12.7%) (median, 9.1%; interquartile range, 4.0%-16.7%) in the control group. At 18 months, the mean (SD) FRS was 9.9% (10.2%) (median, 7.7%; interquartile range, 3.1%-12.0%) in the intervention group and 12.3% (12.0%) (median, 9.7%; interquartile range, 4.0%-15.9%) in the control group. Compared with the control group, the intervention group experienced a 12.7% (95% CI, 2.5%-22.9%; P = .02) relative reduction in FRS at 18 months. CONCLUSIONS AND RELEVANCE An 18-month behavioral counseling, care coordination, and care management intervention statistically significantly reduced overall cardiovascular disease risk in adults with serious mental illness. This intervention provides the means to substantially reduce health disparities in this high-risk population. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT02127671.
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Affiliation(s)
- Gail L. Daumit
- Division of General Internal Medicine, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland
- Welch Center for Prevention, Epidemiology and Clinical Research, Johns Hopkins University, Baltimore, Maryland
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
- Department of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | - Arlene T. Dalcin
- Division of General Internal Medicine, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland
- Welch Center for Prevention, Epidemiology and Clinical Research, Johns Hopkins University, Baltimore, Maryland
| | | | - Edgar R. Miller
- Division of General Internal Medicine, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland
- Welch Center for Prevention, Epidemiology and Clinical Research, Johns Hopkins University, Baltimore, Maryland
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | - A. Eden Evins
- Department of Psychiatry, Massachusetts General Hospital, Boston
| | - Corinne Cather
- Department of Psychiatry, Massachusetts General Hospital, Boston
| | - Gerald J. Jerome
- Division of General Internal Medicine, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland
- Department of Kinesiology, Towson University, Towson, Maryland
| | - Deborah R. Young
- Department of Research and Evaluation, Kaiser Permanente Southern California, Pasadena
| | - Jeanne B. Charleston
- Division of General Internal Medicine, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland
- Welch Center for Prevention, Epidemiology and Clinical Research, Johns Hopkins University, Baltimore, Maryland
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | - Joseph V. Gennusa
- Division of General Internal Medicine, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Stacy Goldsholl
- Division of General Internal Medicine, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Courtney Cook
- Division of General Internal Medicine, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Ann Heller
- Division of General Internal Medicine, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Emma E. McGinty
- Department of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | - Rosa M. Crum
- Welch Center for Prevention, Epidemiology and Clinical Research, Johns Hopkins University, Baltimore, Maryland
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | - Lawrence J. Appel
- Division of General Internal Medicine, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland
- Welch Center for Prevention, Epidemiology and Clinical Research, Johns Hopkins University, Baltimore, Maryland
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | - Nae-Yuh Wang
- Division of General Internal Medicine, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland
- Welch Center for Prevention, Epidemiology and Clinical Research, Johns Hopkins University, Baltimore, Maryland
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
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