Jeanie Tse, MD, FRCPC, is Director of Integrated Health, Institute for Community Living (ICL); and Clinical Assistant Professor of Psychiatry, NYU School of Medicine. Elisa Chow, PhD, is Director of Outcomes Evaluation, ICL. Rosemarie Sultana-Cordero, MA, LMHC, is Clinical Coordinator, Integrated Health, ICL. Marcia Titus-Prescott, RN, is Associate Director of Integrated Health and Nursing, ICL. Ruth Chiles, RD, is Director of Nutrition, ICL. Andrew Cleek, PsyD, is Director, Urban Institute for Behavioral Health. Elizabeth Cleek, PsyD, is Vice President, Program Design, Evaluation and Systems Implementation, ICL.
This work was supported by the New York State Health Foundation; the United Hospitals Fund; the New York Community Trust; and the Brooklyn Community Foundation. The authors acknowledge the contributions of Peter Campanelli, PsyD; Stella Pappas; Cynthia Williams; Shivonne Blake; Le-Nise Watson-Hudson; Drew LaStella, PhD; and Matt Wofsy, as well as numerous staff and consumers at ICL and multiple provider agencies, especially The Bridge; F.E.G.S.; and William F. Ryan Community Health Center.
Dr. Tse, Dr. Chow, Ms. Sultana-Cordero, Ms. Titus-Prescott, Ms. Chiles, Mr. Cleek, and Ms. Cleek have disclosed no relevant financial relationships.
Address correspondence to: Jeanie Tse, MD, FRCPC, Institute for Community Living, Inc., 40 Rector St., New York, NY 10006; phone: 212-385-3030; fax: 212-385-2380; email: firstname.lastname@example.org.
People with serious mental illnesses die an average of 25 years earlier than people in the general population.1 An estimated 60% of this excess mortality is attributed to common preventable and treatable medical conditions, including heart disease, stroke, and diabetes. This has moved providers toward making the delivery of primary care an integral part of behavioral health services — treating people holistically rather than only “from the neck up.”2
People with serious mental illness (SMI) have a higher prevalence of cardiometabolic risk factors, including rates of obesity almost twice that of the general population3,4 The interactions between genotype and environment are complex and poorly understood. Dysfunctional mesolimbic reward patterns may lead to unhealthy food choices.5 These are often in tandem with financial constraints on patients, including living in neighborhoods where fresh fruits and vegetables are difficult to obtain. Symptoms of mental illness, including low energy and anhedonia, may lead to decreased physical activity. Lack of access to exercise facilities often compounds the problem. Antipsychotic medications also play a role, with histaminergic and serotonergic systems implicated in weight gain, although mechanisms for hypertriglyceridemia and insulin resistance are yet unknown.6 In addition, complex gene-environment interactions are involved in nicotine addiction, with 75% to 85% of people with SMI reporting that they smoke.7
Although most cardiometabolic risk factors can be modified, people with SMI experience multiple barriers to care, including discrimination, lack of provider training, and fragmentation of the health care system. Addressing these disparities requires major shifts in public and provider awareness, and integration of health service provision and reimbursement.8,9,10 At the level of the individual with SMI, barriers to effective self-management of cardiometabolic risks include poor health literacy, problem-solving skills, and motivation to change.11–14 Psychoeducation and cognitive behavioral interventions have been shown effective in reducing weight in people with SMI.15–18 Some of these interventions focus on motivation, which may be affected by negative symptoms and multiple stressors in people with SMI.
Many studies have supported the effectiveness of motivational interviewing (MI) in improving a range of health behaviors and outcomes, including body mass index (BMI).19 MI is a counseling style that has evolved from William R. Miller’s early work with people struggling with recovery from alcohol use disorders.12 By placing the emphasis on a person’s intrinsic motivation for change, which is rooted in that person’s values and goals, MI works with a person’s ambivalence to change, seeking to “roll with resistance” rather than to oppose it. The counseling interventions used in MI are tailored to the person’s stage of change (Table 1), which can shift constantly.20
Table 1. Stages of Change
Any counseling opportunity begins with a request for permission to give the person nonjudgmental feedback about his/her behavior (eg, overeating) and its implications for well-being (eg, obesity). The counselor then engages the person in a discussion about his/her reasons for continuing the behavior (eg, “tastes good”), and the pros and cons of continuing the behavior. The counselor puts the focus on the person’s values and goals (eg, keeping a well-paying construction job) and guides the person to see where his/her current behavior diverges from values and goals (eg, increased weight exacerbates arthritis, interfering with the person’s ability to perform physical work). The ultimate aim is for the person to identify a first step he/she can take toward change.
Integrated Health Toolkit
A large-scale implementation of an MI-based psychoeducational and behavioral program addressing cardiometabolic risks in community behavioral health settings is described below. Two toolkits were developed to assist behavioral health counselors in using MI in residential and clinical settings: Healthy Living and Diabetes Self-Management. Both included modular-style workbooks written at a fifth-grade reading level. MI-style language was used to provide health education and skills training on a range of topics (Table 2, see page 475). Questions are provided to elicit thoughts and feelings about change and to guide exploration of options for change. At the end of each module, the stage of change is self-assessed. If the person was ready to commit to change, the workbook facilitated the development of specific, concrete, and achievable action steps. Self-evaluation of the change process was encouraged, with small successes accruing to generate momentum toward goals such as weight reduction.
Table 2. Workbook Modules
Other tools designed to address barriers to care for people with SMI were pocket-sized cards that encouraged an individual with SMI to ask primary care providers for health information and facilitated tracking of primary health indicators, including weight. A set of form letters that dovetail with the prompts on the pocket-cards let primary care providers and psychiatrists know that their patient was participating in a self-management program and could benefit from support in learning more about improving health. Clinical algorithms led behavioral health staff step-by-step through evidence-based/best-practice assessment and treatment, and forms designed to identify those with higher levels of health risks, were designed to help staff provide integrated physical and behavioral health care.
Crucial to the implementation of these toolkits was staff training centered on MI skills, taught experientially through interactive discussion and role play.21 Staff were encouraged to review the workbook alongside the SMI population they served — to be supportive counselors rather than health experts. The goal was to make health information as accessible as possible for those of any level of education.
The Healthy Living Toolkit was piloted in 49 behavioral health programs at the Institute for Community Living (ICL), a New York-based nonprofit serving more than 10,000 people annually. ICL serves a population equally divided by gender; most are black or Hispanic. The most common mental illnesses in the cohort were schizophrenia, schizoaffective disorder, bipolar disorder or depression, and substance use disorder comorbidity. Many of those served by ICL also had histories of comorbid health conditions, homelessness, and/or trauma.
From May 2010 to April 2011, training on MI and the use of the toolkit was provided to 146 behavioral health workers, with about 50 staff attending each quarterly refresher training course and 32 attending inservice training. Most trainees were Bachelor’s-degree-level case managers working in residential and outreach settings. More than 300 workbooks and more than 500 workbook chapter handbooks were distributed. Almost 1,400 people with SMI participated in groups and/or individual counseling (69% individual only; 7% group only; 24% group and individual). Eighty-three individuals were able to participate in cooking demonstrations, and 27 participated in a 12-week cooking skills course. One hundred individuals participated in a physical activity program.
The Healthy Living Questionnaire (HLQ), a self-assessment of health behaviors developed to support clinical treatment planning and goal-setting, was completed by participants at quarterly time points. Over the program’s 1-year duration, the HLQ included the SF-8 Health Outcomes Questionnaire22 (a validated eight-item self-report health survey), and seven questions regarding health behaviors as covered in the Healthy Living Workbook. To evaluate and measure the pilot program’s success, at 9 months, all participants were asked, “During the past year, how often did you visit your primary care provider (PCP)?” Significant improvement in participants’ visits to their respective PCPs were found (mean 1.55 vs. 2.89 at 9 months, n = 448, P < .02). Participants in the physical activity program had significant decreases in weight (216 vs. 213 lb, n = 44, P < .000) and waist circumference (44 vs. 43 inches, n = 44, P < .002) after 6 months of participation.
Between September 2008 and September 2010, the Diabetes Self-Management Toolkit was piloted in 54 programs across 19 behavioral health agencies in New York state, in conjunction with the Urban Institute for Behavioral Health. A total of 324 staff were trained in MI and the use of the toolkit, including cooks, who had a large influence on participants’ food choices. Trained staff engaged 358 participants with diabetes or prediabetes in group or individual counseling. Most counseling participants were male (57.5%), aged 40 to 59 years (67.5%) and non-whites (70%).
Participants’ diabetes information pocket cards were reviewed by counseling staff to evaluate access to diabetes monitoring tests recommended by the Diabetes Quality Improvement Project.23 These included A1c and Blood pressure levels, Cholesterol and kiDney function labs, Eye exams, and Foot exams — collectively referred to in the toolkit as the “ABCDEFs of diabetes.” After 6 months, significant increases were observed in the proportion of those who had recorded a test date for A1c (51.5 vs. 64.7%, n = 108, P < .01); urine protein (49.2% vs. 59.2%, n = 101, P < .01); and foot exams (60.2% vs. 74.8%, n = 101, P < .05) in the previous year. A significant increase in the proportion of those who had recorded test dates for all six ABCDEFs in the previous year also was found (18.8% vs. 34.8%, n = 92, P < .01).
Self-reported diabetes self-management behaviors were also assessed using the Diabetes Skills Scale. Significant improvements were found on items regarding choosing healthy foods (n = 155, P < .05); checking feet daily (n = 165, P < .05); physical activity (n = 166; P = .01); and managing stress (n = 165, P < .01). Changes in available A1c levels and emergency department and inpatient utilization were not significant.
Fidelity to the treatment model was assessed using a checklist of motivational interviewing skills in four Healthy Living and eight Diabetes Self-Management counseling groups. High fidelity was found for most group facilitators, with no individual scores below a moderate rating.
Focus groups were conducted with both staff and participants in eight Healthy Living and eight Diabetes Self-Management participant programs. Implementation of toolkits was found to be feasible and acceptable, with staff, as well as participants, reporting changes to their health behaviors. Interprovider communication and collaboration were found to be the most challenging part of integrated health care provision, particularly in programs without ready access to health indicator information. Almost all programs planned to continue using the toolkits after grant funding had ended.
This was a quasi-experimental community program evaluation that utilized data from clinical tools collected by behavioral health workers, with a large amount of missing data. In order to validate the impact of these interventions, a controlled study is necessary. However, the feasibility and acceptability of this large-scale implementation suggests that further study of motivation-based interventions in underserved community settings is warranted.
The public health system traditionally reinforced the idea that care of the mind and the body should occur in separate places by separate providers with separate governance and funding. People with SMI and comorbid cardiometabolic risks “fell between the cracks” in this system, with physical health needs often neglected. The public health reimbursement structure increasingly emphasizes integrated care outcomes and system-wide cost efficiency. Health information technology (HIT) that facilitates interprovider communication and consumer access to personal health information is being incentivized. Physicians, nurses, social workers, and other behavioral health staff will need to be “cross-trained” to attend to the physical health needs of people with comorbid conditions. The shifts in reimbursement and HIT, as well as the emphasis on integrated care across disciplines, is expected to further support overarching health improvements for people with comorbid physical and behavioral health needs.
For behavioral health providers, a motivation-based toolkit that enables counselors to deliver integrated services within the current public health framework can be both a first step and a sustainable solution to a complex problem. For people with SMI, motivation, health literacy, and self-management skills can be the cornerstones of a person-centered, recovery-oriented approach to reducing morbidity and mortality and improving quality of life.
- National Association of State Mental Health Program Directors (NASMHPD) Medical Directors Council. Morbidity and mortality in people with serious mental illness. Technical report published October 2006. Available at www.nasmhpd.org. Accessed Sept. 27, 2011.
- Cook JA. Physical wellness: an integral feature of recovery. Psychiatr Rehabil J. 2001;34(4):271–272. doi:10.2975/34.4.2011.271.272 [CrossRef]
- Dickerson FB, Brown CH, Kreyenbuhl JA, et al. Obesity among individuals with serious mental illness. Acta Psychiatr Scand. 2005; 113(4):306–313. doi:10.1111/j.1600-0447.2005.00637.x [CrossRef]
- Osborn DPJ, Wright CA, Levy G, King MB, Deo R, Nazareth I. Relative risk of diabetes, dyslipidaemia, hypertension and the metabolic syndrome in people with severe mental illnesses: Systematic review and metaanalysis. BMC Psychiatry. 2008;8:84. doi:10.1186/1471-244X-8-84 [CrossRef]
- Holt RIG, Peveler RC. Obesity, serious mental illness and antipsychotic drugs. Diabetes Obes Metab. 2009; 11(7):665–679. doi:10.1111/j.1463-1326.2009.01038.x [CrossRef]
- Stahl SM, Mignon L, Meyer JM. Which comes first: Atypical antipsychotic treatment or cardiometabolic risk?Acta Psychiatr Scand. 2009;119(3):171–179. doi:10.1111/j.1600-0447.2008.01334.x [CrossRef]
- Ziedonis D, Williams JM, Smelson D. Serious mental Illness and tobacco addiction: A model program to address this common but neglected issue. Am J Med Sci. 2003; 326(4):223–230. doi:10.1097/00000441-200310000-00014 [CrossRef]
- Wishon Siegwarth AA, Konayagi C. The new health care reform act and Medicaid: New opportunities for psychiatric rehabilitation. Psychiatr Rehabil J. 2001; 34(4):277–284. doi:10.2975/34.4.2011.277.284 [CrossRef]
- Mesidor M, Gidugu V, Rogers ES, Kash-MacDonald VM, Boardman JB. A qualitative study: Barriers and facilitators to health care access for individuals with psychiatric disabilities. Psychiatr Rehabil J. 2001; 34(4): 285–294. doi:10.2975/34.4.2011.285.294 [CrossRef]
- Gautham S. Fourth revolution in psychiatry: Addressing comorbidity with chronic physical disorders. Indian J Psychiatry. 2010; 52(3):213–219. doi:10.4103/0019-5545.70973 [CrossRef]
- Bodenheimer T, Lorig K, Holman H, Grumbach K. Patient self-management of chronic disease in primary care. JAMA. 2002;288(19):2469–2475. doi:10.1001/jama.288.19.2469 [CrossRef]
- Miller WR, Rollnick S. Motivational Interviewing: Preparing People for Change. 2nd ed. New York: Guilford Press; 2002.
- Everett A, Mahler J, Biblin J, Ganguli R, Mauer B. Improving the health of mental health consumers: Effective policies and practices. Available at www.oregon.gov/OHA/mentalhealth/wellness/policies-and-practices.pdf. Accessed Sept. 27, 2011.
- Richardson CR, Faulkner G, McDevitt J, Skriner GS, Hutchinson DS, Piette JD. Integrating physical activity into mental health services for persons with serious mental illness. Psychiatr Serv. 2005: 56:324–331. doi:10.1176/appi.ps.56.3.324 [CrossRef]
- Alvarez-Jimenez M, Hetrick SE, Gonzalez-Blanch C, Gleeson JF, McGorry PD. Non-pharmacological management of antipsychotic-induced weight gain: Systematic review and meta-analysis of randomized-controlled trials. Br J Psychiatry. 2008;193(2)101–107. doi:10.1192/bjp.bp.107.042853 [CrossRef]
- Melamed Y, Stein-Reisner O, Gelkopf M, et al. Multimodal weight control intervention for people with persistent mental disorders. Psychiatr Rehabil J. 2008; 31(3):194–200. doi:10.2975/31.3.2008.194.200 [CrossRef]
- Weber M, Wyne K. A cognitive/behavioral group intervention for weight loss in patients treated with atypical antipsychotics. Schizophr Res. 2006;83(1):95–101. doi:10.1016/j.schres.2006.01.008 [CrossRef]
- Brar JS, Ganguli R, Pandina G, Turkoz I, Berry S, Mahmoud R. Effects of behavioral therapy on weight loss in overweight and obese patients with schizophrenia or schizoaffective disorder. J Clin Psychiatry. 2005:66(2):205–212. doi:10.4088/JCP.v66n0208 [CrossRef]
- Rubak S, Sandbæk A, Lauritzen T, Christensen B. Motivational interviewing: A systematic review and meta-analysis. Br J Gen Pract. 2005;55(513):305–312.
- Prochaska JO, DiClemente CC. Stages and processes of self-change of smoking: Toward an integrative model of change. J Consult Clin Psychol. 1983; 51(3):390–395. doi:10.1037/0022-006X.51.3.390 [CrossRef]
- Barney C, Shea CS. The art of effectively teaching clinical interviewing skills using role playing: A primer. Psychiatr Clin N Am. 2007;30:e31–e50. doi:10.1016/j.psc.2007.03.001 [CrossRef]
- Ware JE, Kosinski M, Dewey JE, Gandek B. How to Score and Interpret Single-Item Health Status Measures: A Manual for Users of the SF-8 Health Survey. Lincoln, RI: QualityMetric Incorporated; 2001.
- Fleming BB, Greenfield S, Engelgau MM, Pogach LM, Clauser SB, Parrott MADQIP Group. The Diabetes Quality Improvement Project: Moving science into health policy to gain an edge on the diabetes epidemic. Diabetes Care. 2001; 24(10):1815–1820. doi:10.2337/diacare.24.10.1815 [CrossRef]
Stages of Change
|Pre-contemplation||“I have no problem with my weight.”|
|Contemplation||“Maybe I could try to be more active.”|
|Preparation||“If I want to lose weight, I should ask my doctor about it.”|
|Action||“I am drinking one less soda a day as a first step.”|
|Maintenance||“I have to remind myself not to overeat during the holidays.”|
|Recurrence||“I got off track with my exercise routine, but I’m going to come up with a plan to start up again.”|
|Healthy Living Toolkit||Diabetes Self-Management Toolkit|
Caring for your mental health
Taking charge of checkups
Choosing healthy foods
Being physically active
Talking about sex
Using the ER
Taking care of teeth
Caring for your diabetes and mental health
Choosing healthy foods
Being physically active
Checking blood glucose
Taking care of feet
Taking care of my teeth
Having a sick-day plan