A Randomized, Controlled Multisite Study of Behavioral Interventions for Veterans with Mental Illness and Antipsychotic Medication-Associated Obesity
respectively]. The majority of LB participants kept
food and activity journals (92%)
A Randomized, Controlled Multisite Study of Behavioral Interventions for Veterans with Mental Illness and Antipsychotic Medication-Associated Obesity
Zachary D. Erickson
Crystal L. Kwan
Hollie A. Gelberg 2
Irina Y. Arnold
Valery Chamberlin 0 1
Jennifer A. Rosen
Chandresh Shah 1
Charles T. Nguyen 3
Gerhard Hellemann 8
Dixie R. Aragaki 0 7
Charles F. Kunkel 0 7
Melissa M. Lewis 1
Neena Sachinvala 0 1
Patrick A. Sonza
Joseph M. Pierre 0 1
Donna Ames 0 1
0 David Geffen School of Medicine at University of California-Los Angeles , Los Angeles, CA , USA
1 Mental Health Service at VA Greater Los Angeles Healthcare System , Los Angeles, CA , USA
2 Research Service at VA Greater Los Angeles Healthcare System , Los Angeles, CA , USA
3 Department of Mental Health at VA Medical Center , Long Beach, CA , USA
4 University of Southern California School of Pharmacy , Los Angeles, CA , USA
5 University of the Pacific School of Pharmacy , Stockton, CA , USA
6 Department of Pharmacy at VA Northern California Healthcare System , Martinez, CA , USA
7 Physical Medicine and Rehabilitation Service at VA Greater Los Angeles Healthcare System , Los Angeles, CA , USA
8 Semel Institute for Neuroscience & Human Behavior at University of California-Los Angeles , Los Angeles, CA , USA
antipsychotic; weight management; obesity; behavioral intervention; mental health; J Gen Intern Med 32(Suppl 1); S32-S9 DOI; 10; 1007/s11606-016-3960-3 © Society of General Internal Medicine 2016
BACKGROUND: Weight gain and other metabolic
sequelae of antipsychotic medications can lead to medication
non-adherence, reduced quality of life, increased costs,
and premature mortality. Of the approaches to address
this, behavioral interventions are less invasive, cost less,
and can result in sustained long-term benefits.
OBJECTIVE: We investigated behavioral weight
management interventions for veterans with mental illness across
four medical centers within the Veterans Affairs (VA)
DESIGN: We conducted a 12-month, multi-site extension
of our previous randomized, controlled study, comparing
treatment and control groups.
PARTICIPANTS: Veterans (and some non-veteran
women) diagnosed with mental illness, overweight (defined as
having a BMI over 25), and required ongoing
INTERVENTIONS: One group received BLifestyle
Balance^ (LB; modified from the Diabetes Prevention
Program) consisting of classes and individual nutritional
counseling with a dietitian. A second group received less
intensive BUsual Care^ (UC) consisting of weight
monitoring and provision of self-help.
MAIN MEASURES: Participants completed
anthropometric and nutrition assessments weekly for 8 weeks, then
monthly. Psychiatric, behavioral, and physical
assessments were conducted at baseline and months 2, 6, and
12. Metabolic and lipid laboratory tests were performed
KEY RESULTS: Participants in both groups lost weight.
LB participants had a greater decrease in average waist
circumference [F(1,1244) = 11.9, p < 0.001] and percent
body fat [F(1,1121) = 4.3, p = 0.038]. Controlling for
For Irina Y. Arnold, the MD degree was obtained in Russia
Patients taking antipsychotic drugs (APDs) may experience
side effects such as obesity, diabetes, dyslipidemia, and
cardiovascular disease.1–5 Weight gain can lead to medication
non-adherence and subsequent psychiatric relapse.6, 7 The
total US cost of treatment for people with psychotic disorders
in 2013 was estimated at $11.5 billion.8 Comorbid drug
addiction, tobacco dependence, and obesity may all contribute to
increased costs and shortened lifespans by 10–25 years9 and a
3.5-fold increased mortality risk.10
Approaches to address weight gain include
pharmacotherapy,5 bariatric surgery,11, 12 and behavioral interventions.13, 14
Pharmacotherapy, while shown to have a short-term effect, is
often ineffective in the long term.5 Bariatric surgery also
provides short-term results for people with psychiatric
symptoms, but results 1 year post-surgery are significantly less
than in those without psychiatric illness.11 Cognitive barriers
and amotivation may accompany mental illness, affecting
adherence to lifestyle changes. The weight gain liabilities of
some APDs can also make it more difficult to maintain weight
loss. Therefore, patients taking APDs may require additional
pre- and postoperative care to improve long-term weight
In contrast, a behavioral approach is the least medically
invasive and unlikely to have side effects associated with
p h a r m a c o t h e r a p y a n d s u rg e r y. T h e U n i t e d S t a t e s
Preventative Services Task Force (USPSTF) found behavioral
interventions can result in weight loss and improved metabolic
parameters in the general population. They recommend
intensive, multicomponent programs utilizing groups, individual
sessions, dietary modification, exercise, self-monitoring, goal
setting, addressing barriers, and maintenance planning.15
Awareness of APD-associated weight gain prompted
development of behavioral interventions for patients with mental
illness. Intervention studies demonstrate weight loss and
improved metabolic profiles compared to control groups.5, 9, 13,
14, 16–21 While durations of interventions vary, these studies
highlight the importance of nutrition and exercise
modification. Weight loss interventions can reduce concomitant
medication use and overall cost.22–24 This study replicated and
expanded our original behavioral intervention research,25
which added to the literature with a longer 12-month
intervention and focus on veterans with APD-associated obesity.
We developed a behavioral weight management program for
persons taking APDs based on the Diabetes Prevention
Program (DPP), a diet and exercise program that has
demonstrated reduced risk of diabetes.26 Our program, tested at the VA
West Los Angeles Medical Center,25 also met USPSTF
recommendations for higher-intensity behavioral interventions.15
Results of the randomized, controlled study’s intention-to-treat
analysis indicated that intervention participants were predicted
to lose an average 4.6 kg compared to control participants
predicted to gain an average 0.6 kg over 12 months.
Building on the single-site trial’s successes, we tested this
research program at the original and three additional locations.
The 12-month controlled, parallel, superiority design was
retained; the intervention group was hypothesized to gain
more health knowledge, make more healthy lifestyle changes,
and achieve better cardiovascular and mental health outcomes.
Secondary hypotheses involved weight loss negatively
correlating with psychiatric symptoms while positively correlating
with motivation and better treatment adherence by the
intervention group. This article describes the program’s efficacy at
these four sites.
This study was registered with ClinicalTrials.gov (identifier
NCT01052714) and approved by Institutional Review Boards
at the VA Greater Los Angeles and VA Long Beach Healthcare
Systems. Participants signed informed consent after receiving
detailed study information, viewing a video presentation about
informed consent,27 and passing a study participation
comprehension assessment. Conserved participants’ guardians were
required to co-sign consent.
Study Population and Setting
Research activities took place in research offices near
mental health clinics at four southern California VA locations.
R e c r u i t m e n t o c c u r r e d S e p t e m b e r 2 0 1 0 t h r o u g h
March 2014 using flyers and presentations. Inclusion
criteria were: age 18–70 years old; diagnosis of mental
illness per DSM-IV; APD treatment; BMI over 25 or
weight gain over 7% on APDs; and medical and psychiatric
stability, confirmed by chart reviews and primary care
provider approval. Exclusion criteria were hospitalizations
within 30 days, substance abuse history without sobriety
over the previous 90 days, and homelessness. Follow-up
with the final participant concluded by June 2015.
We assumed a conventional medium effect size, with desired
power of 80% and two-tailed α set at 0.05, and determined a
sample size of n = 60 (per treatment group). A computer
pregenerated random number list randomized participants to
parallel groups with a balanced allocation ratio (1:1), with clinical
raters masked to randomization. Participants were stratified by
APD-associated weight-gain risk (high: clozapine/olanzapine;
medium: quetiapine/risperidone; low: aripiprazole/
ziprasidone; negligible: haloperidol/other), with those on
multiple medications assigned based on the highest-risk
medication. Participants (n = 121) were randomized into the more
intensive BLifestyle Balance^ intervention group (LB, n =
62) or the less intensive BUsual Care^ intervention group
(UC, n = 59).
Assessments conducted throughout the study are in
Table 1.28–37 Psychiatric diagnosis was confirmed by study
psychiatrists or PhD-level psychologists using the Structured
Clinical Interview for DSM-IV checklist.38 Physical stability
was determined by physical examination, medical records,
Framingham risk assessment,39 electrocardiogram, Health/
Fitness Pre-Participation Screening Questionnaire,40 and, if
necessary after an investigator reviewed all of the above, an
exercise tolerance test (ETT). Of 33 participants who
underwent the ETT, clinicians admitted 30 to the study.
All study participants met with a research coordinator
weekly for the first 8 weeks and monthly through month 12.
At every visit, vital signs, weight, waist circumference, BMI,
and body fat percentage were recorded. Participants completed
a Treatment Adherence Questionnaire and Lifestyle Habits
Questionnaire about food, beverage, and exercise habits. If
participation ended early, month 12 assessments were
completed at the final visit.
Registered dietitians (RD) were trained to administer the
LB intervention by the PI; they also worked together for
6 months during the second dietitian’s training period.
As part of their VA dietetic training, they learned
cognitive-behavioral and motivational interviewing
techniques, reinforced further by the PI. To facilitate fidelity
across all sites, weekly team meetings were held to
ensure a standardized intervention was being provided.
The PI periodically observed and assessed fidelity of the
two dietitians qualitatively using a specially designed
fidelity checklist to assess quality of care during class
and individual coaching sessions.
Behavioral Intervention: Lifestyle Balance
Educational Materials and Group Classes. LB participants
received RD-led classes and individual nutrition counseling.
The LB curriculum included 16 topics (Table 2). The first
8 weeks, 60-min classes covered two topics per session.
Monthly booster classes reinforced healthy behaviors for the
remaining 10 months. Class size typically ranged from 1–4
people. Classes utilized multi-modal techniques including
colored handouts, written materials, food models, poster images,
and group discussions to accommodate visual, auditory, and
kinesthetic learning styles. Concepts were reviewed with
repetition to address potential cognitive barriers associated
with mental illness.41
Individual Nutrition Counseling. Following each class,
participants met RDs for 15 to 60 min of individualized
nutrition counseling, depending on participants’ needs and
time availability. RDs addressed each participant’s specific
nutrition-related concerns and helped participants set and
accomplish both short- and long-term goals.
RDs provided a comprehensive nutrition assessment at the first
session, including a 24-h food recall42 assessing participants’
dietary intake. RDs also reviewed medical records and physical
activity, stage of change,43 and cognitive ability. A discussion
followed about specific food and activity goals to initiate behavior
change. RDs used cognitive behavioral therapy techniques,44
motivational interviewing45, 46 and accountability tools, including
food and activity journals. RDs reviewed these journals during
participants’ appointments. For data analysis, 24-h food recalls42
were used with journals to quantify food and beverage intake
changes. These data were input into the USDA BSupertracker^
database47 and analyzed to assess behavioral changes.
During groups and individual sessions, RDs encouraged
change using positive affirmations and praise.41 To enhance
motivation and adherence to the program, participants received
rewards for meeting goals such as gift certificates, tote bags, and
BHealthy Plates.^ Following the DPP’s protocol BToolbox^ and
the in-vivo approach to social skills training,48 RDs met with
caregivers at 12 participants’ residences to discuss dietary
changes; they also taught healthy cooking classes and promoted
walking groups. During semi-annual class field trips, RDs provided
on-site education at restaurants and grocery stores.41 Once-daily
meal replacement shakes were offered when basic food and
exercise changes were less effective in meeting weight loss goals;
only 13 participants chose this option.49
UC participants met with research coordinators with a
frequency and duration equivalent to individual LB counseling
Table 3 Participant Demographic Characteristics
UC* (n = 42)
LB† (n = 62)
sessions. Anthropometric measures and vitals were recorded.
Participants answered questionnaires about diet, exercise, and
health. VA-approved self-help educational handouts on health
issues were provided. Due to ethical concerns and participant
request, 17 UC participants were allowed to begin the active
treatment at month 6, and these 17 crossover (CO) participants
were not included in any analysis after month 6.
Research staff collected and transcribed data into an electronic
database, utilizing double-entry for error checking.
Intent-totreat analyses of primary and secondary hypotheses were
performed using a general linear mixed model in SPSS on
the 121 randomized participants’ data.
Of 121 participants, 62 were randomized to LB and 59
to UC groups. The initial 8-week intervention period
was completed by 53 (86%) LB and 50 (85%) UC
participants, and the full 12-month follow-up period
was completed by 33 (53%) LB, 17 (29%) UC, and
15 CO participants (88%, data excluded after month 6).
Among the 56 non-completing participants, 20
voluntari l y w i t h d r e w. I n v e s t i g a t o r s t e r m i n a t e d 1 9 f o r
nonadherence to study procedures and 12 for adverse
medical or psychiatric changes (none study related).
Five were lost to follow-up (unresponsive to three
telephone calls and a letter). Analysis of baseline
demographic and clinical data (Table 3) revealed no
statistically significant differences between groups [χ2(4,N =
104) = 4.4, p = 0.35].
Knowledge of Healthy Lifestyles
On a self-developed knowledge quiz (Online Appendix 1), no
statistically significant change was found between groups. No
association was found between symptoms of cognitive
impairment and health knowledge.
Lifestyle Behavioral Changes
Exercise. There was no significant change over time in the
number of hours participants exercised per week [F(1,
1225) = 1.62, p = 0.20]. There was no significant difference
in the rate of change between groups [F(1,1225) = 0.67, p =
0.41], but LB reported an increase of an estimated 33 min per
week, while UC increased by an estimated 9 min per week.
Caloric Intake. Overall, average daily calorie intake was 2055
initially for LB participants, which declined to 1650 at week
52 (p < 0.001). Total empty calories decreased, for an average
reduction from 558 to 365 empty calories (i.e., solid fats,
added sugars) per day (p = 0.04).
Anthropometric and Laboratory Measures
Participants demonstrated statistically significant differences
in percent body fat change, which decreased for LB by an
average of 0.4 over 12 months, while the UC group decreased
by 0.2 [F(1,1121) = 4.3, p = 0.038]. Additionally, LB group
waist circumference decreased on average by 1.04 cm, while
the UC group increased by 0.25 cm [F(1,1244) = 11.9, p <
0.001]. Both groups lost weight compared to baseline, though
differences between groups at 1 year were not statistically
Age group stratification yielded no statistically significant
differences, but BMI level stratification revealed significant
differences in effect on weight [Table 4; F(3,1247) = 24.27, p
< 0.01]. Participants with BMIs under 25 or over 40 responded
better to LB. Those with BMIs between 25 to 40 responded
better to UC. Using gender as a moderator, a significant
threeway interaction was found among treatment effect, gender,
and weight. The treatment effect was larger for LB women,
who by 26 weeks lost on average 2.18 kg [F(1,1265) = 19.6, p
< 0.001] compared to between 0.5–1 kg for UC women and
men in both groups. BMI followed: LB women decreased 0.9
points [F(1,1246) = 13.9, p < 0.001]. Waist circumference and
body fat percentage also decreased, 2.92 cm [F(1,1243) =
22.5, p < 0.001] and 0.9% [F(1,1221) = 4.76, p = 0.029],
No significant differences were found between groups for
hemoglobin A1c. Lipid profiles were either non-significant
(HDL-cholesterol, triglycerides) or significant in the reverse
direction than hypothesized (cholesterol, LDL-cholesterol).
Correlation with Psychiatric Symptoms
While weight loss was correlated with improvement in quality
of life, no significant differences in quality of life scores were
seen between groups. For psychiatric symptoms measured by
validated scales for depression, psychosis, and anxiety,28–31 all
clinical scores decreased over time (ps < 0.001), but there were
no differences between groups. There was evidence of an
interaction effect of Beck Anxiety Inventory scores with the
treatment on change in weight over time: [F(1,165) = 3.7, p =
0.05]. Analysts performed a simple slope analysis to explore
this three-way interaction (Table 5). Higher anxiety scores
were associated with increased treatment effect; LB
participants with higher scores had more weight loss while UC
participants with higher scores showed reduced weight loss
or even weight gain.
Insight into psychiatric illness on the Self-Appraisal of
Illness Questionnaire (SAIQ)36 showed a significant
association with treatment effect on weight change [F(1,192) = 6.1,
p = 0.01] with higher scores associated with larger weight loss
for LB, while for UC higher scores were associated with less
weight loss or even weight gain (see Table 5). When
controlling for SAIQ, LB showed significantly greater weight
loss than UC [F(1,192 = 5.2, p = 0.02]. When asked questions
about insight regarding weight-related illness, responses also
showed higher weight-related SAIQ insight scores associated
with larger efficacy of LB [F(1,192) = 6.6, p = 0.01] and
significantly larger weight loss in LB compared to UC when
controlling for SAIQ [F(1,198) = 5.9, p = 0.02].
Based on participants’ self-report, no significant difference
was found in medication adherence or attendance at
psychiatric or study appointments between groups (97–99%; Online
Appendix 2). Ninety-two percent of LB participants
completed food and activity journals on a regular basis (n = 55).
Participants in both LB and UC lost weight. UC was designed
to be minimal, but regular research meetings to discuss diet
and exercise may have been enough to motivate healthy
lifestyle improvement, translating to weight loss. Even
provided only self-help materials, participants may have been
responsive to the accountability of frequent study
LB participants demonstrated important changes in
nutritional behaviors; they reduced overall caloric intake and
improved caloric quality by decreasing empty calories. They
experienced additional benefits, decreasing waist
circumference and adiposity, reflecting changes in body composition
from exercise and weight loss. Food and activity journals also
assisted participants in staying accountable to their goals.
Women seemed to be most responsive to LB, consistent
with other findings.50 Although the groups’ weight loss was
modest, the FDA considers 5% loss clinically important,15 and
national guidelines recommend counseling obese adults to
achieve clinical benefits from a modest 3%–5% loss.51
Among participants completing at least 6 months, 28% lost
5% bodyweight in LB (N = 42), while 17% lost 5% in UC
(N = 43) at last observation. The differences were not
statistically significant using chi-square analyses.
Participants with BMIs under 25 or over 40 benefitted most
from LB, suggesting the more intensive treatment could be
targeted to these groups. Participants under 25 BMI likely
passed screening because of recent rapid weight gain. Such
patients may benefit from LB as a preventative approach to
decrease their obesity risk. LB may also be a low-risk
approach for those with BMIs over 40, who have a high chronic
disease risk. For the majority of individuals taking APDs with
BMIs between 25–40, one can consider UC’s less intensive
approach for weight loss.
LB participants with more insight into both their psychiatric
illness and weight problem experienced the greatest weight
loss. This implies LB was more effective for this subgroup of
patients, because even with adequate insight UC participants
did not lose as much weight, perhaps lacking motivational LB
counseling. The association between higher anxiety scores and
greater weight loss was unexpected, yet interesting, and merits
LB participants were encouraged to reduce sugary beverage
intake and portion sizes. These strategies were also found most
helpful in the ACHIEVE study,52 reinforcing the idea that
simple strategies are effective for those with mental illness.
According to the authors, ACHIEVE participants were
provided two reduced-calorie meals as part of their outpatient
psychiatric rehabilitation programs,13 similar to participants
in the RENEW program14, 19 who received two meal
replacements per day. In contrast, the primary nutrition intervention in
this study involved classes and counseling to help participants
independently make healthier decisions. Based on the DPP
BToolbox,^ one meal replacement per day was used for 13
interested individuals who struggled losing weight.49
Study limitations included the selection of only patients with
sufficient motivation to seek enrollment and competency to
give informed consent because of research and HIPAA
regulations. Inclusion criteria favored more stable patients, which may
have yielded the extremely high treatment adherence we
observed. Their health was also monitored more closely during
participation, with direct access to RDs. However, some case
managers within high-intensity mental health programs make
scheduled home visits and may go to grocery stores with
veterans, so such attention can be provided without RDs.
Similarly, high levels of adherence to food and activity
journaling within LB may be a result of constant reinforcement
by RDs. In a real-world setting, clinician visits may be shorter
because of higher patient volume. However, our results suggest
simply asking patients to keep food journals may be enough to
increase awareness of healthy choices. This part of LB may
generalize to non-research settings as journals themselves may
be effective tools for behavioral change. Simple changes can be
made by reviewing journals and setting goals at each visit.
Results may be less generalizable to the overall population
because veterans were the primary participants, though we
accepted some non-veteran women to increase their
representation beyond current VA levels. Excluding UC participants
who switched to LB and a drop-out rate similar to other weight
management studies53–55 limited statistical power.
Like our initial LB study, this multi-site replication and
extension indicate that individuals with mental illness
taking APDs are capable of making lifestyle changes
and improving health. Changes in nutritional behaviors,
waist circumference, and adiposity point toward
longterm outcomes that may lead to reduction in risk from
cardiovascular and metabolic diseases. In light of
moving toward personalized healthcare, hospital
administrators and clinicians can adopt LB and UC into existing
outpatient mental health programs, targeted to offer
relatively low-cost and noninvasive means to assist
veterans taking APDs. Participants with more insight into
their illness benefitted most from LB. Positive outcomes
for UC participants suggest less intensive treatments can
also help, with monitoring and accountability the likely
key elements of success. We believe these interventions
can be easily adopted in mental health programs, and
we hope to disseminate the program further.
Acknowledgments: The authors wish to thank Drs. Binyamin
Amrami, Hyung Kim, Frederick Martin, Christopher Reist, and Heidi
Weinreich as well as Matthew Baker, Luzviminda Cristobal, RN,
Michael King, Jr., Eugene Beau LaPorte, Jr., Shirley Mena, RN, Hilary
Meyer, Deborah Peters, RN, and Jillian Tessier for providing clinical
oversight, collaboration, and research assistance. We are also
thankful to the staff and Veterans of the Mental Health Clinics,
MHICM programs, and PRRCs at the VA Greater Los Angeles and
Long Beach Healthcare Systems for their support of this program.
This work was supported by VA Merit Review Project D7358-R from
the United States (US) Department of Veterans Affairs Rehabilitation
Research and Development Service, which had no input as to study
design, execution, analysis, or reporting. The contents do not
represent the views of the US Department of Veterans Affairs or the
United States Government.
Posters presented preliminary results of this study at the Annual
Meeting for the California Dietetic Association in Ontario, CA, in 2012
and at the California Academy of Nutrition and Dietetics Annual
Conference in Riverside, CA, in 2016.
Corresponding Author: Donna Ames, MD; Mental Health Service at
VA Greater Los Angeles Healthcare System, 11301 Wilshire Blvd.
B151H, Los Angeles, CA 90073, USA (e-mail: ).
Compliance with Ethical Standards:
Conflict of Interest: Dr. Charles Nguyen owns stock in Orexigen
Therapeutics, Inc., has received research grants from Forest
Laboratory, Inc., and is a consultant and part of the Speakers
Bureaus for Eisai Co., Ltd., and Otsuka America Pharmaceutical, Inc.
All other authors declare no conflicts of interest.
Wirshing DA, Boyd JA, Meng LR, Ballon JS, Marder SR, Wirshing WC.
The effects of novel antipsychotics on glucose and lipid levels. J Clin
Wirshing DA, Pierre JM, Eyeler J, Weinbach J, Wirshing WC.
Risperidone-associated new-onset diabetes. Biol Psychiatry.
Wirshing DA, Spellberg BJ, Erhart SM, Marder SR, Wirshing WC.
Novel antipsychotics and new onset diabetes. Biol Psychiatry.
Wirshing DA, Wirshing WC, Kysar L, et al. Novel antipsychotics: comparison
of weight gain liabilities. J Clin Psychiatry. 1999;60(6):358–363.
Das C, Mendez G, Jagasia S, Labbate LA. Second-generation
antipsychotic use in schizophrenia and associated weight gain: a critical review
and meta-analysis of behavioral and pharmacologic treatments. Ann Clin
Weiden PJ, Mackell JA, McDonnell DD. Obesity as a risk factor for
antipsychotic noncompliance. Schizophr Res. 2004;66(1):51–57.
Wong MMC, Chen EYH, Lui SSY, Tso S. Medication adherence and
subjective weight perception in patients with first-episode psychotic
disorder. Clin Schizophr Relat Psychoses. 2011;5(3):135–141.
US Department of Health and Human Services: Agency for Healthcare
Research and Quality. National Statistics on Mental Health
Hospitalizations: Schizophrenia and other psychotic disorders. Healthcare Cost and
Utilization Project (H-CUPnet). http://hcupnet.ahrq.gov/HCUPnet.jsp.
Accessed June 29, 2016.
Ames D, Carr-Lopez SM, Gutierrez MA, et al. Detecting and managing
adverse effects of antipsychotic medications. Psychiatr Clin North Am.
Olfson M, Gerhard T, Huang C, Crystal S, Stroup TS. Premature
mortality among adults with schizophrenia in the United States. JAMA
Rutledge T, Groesz LM, Savu M. Psychiatric factors and weight loss
patterns following gastric bypass surgery in a veteran population. Obes
Semanscin-Doerr DA, Windover A, Ashton K, Heinberg LJ. Mood
disorders in laparoscopic sleeve gastrectomy patients: does it affect early
weight loss? Surg Obes Relat Dis. 2010;6(2):191–196.
Daumit GL, Dickerson FB, Wang N-Y, et al. A behavioral weight-loss
intervention in persons with serious mental illness. N Engl J Med.
Brown C, Goetz J, Hamera E. Weight loss intervention for people with
serious mental illness: a randomized controlled trial of the RENEW
program. Psychiatr Serv. 2011;62(7):800–802.
Moyer VA. US Preventive Services Task Force. Screening for and
management of obesity in adults: US Preventive Services Task Force
recommendation statement. Ann Intern Med. 2012;157(5):373–378.
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.
McKibbin CL, Golshan S, Griver K, Kitchen K, Wykes TL. A healthy
lifestyle intervention for middle-aged and older schizophrenia patients
with diabetes mellitus: a 6-month follow-up analysis. Schizophr Res.
Wu M-K, Wang C-K, Bai Y-M, Huang C-Y, Lee S-D. Outcomes of obese,
clozapine-treated inpatients with schizophrenia placed on a six-month
diet and physical activity program. Psychiatr Serv. 2007;58(4):544–550.
Brown C, Goetz J, Hamera E, Gajewski B. Treatment response to the
RENEW weight loss intervention in schizophrenia: impact of intervention
setting. Schizophr Res. 2014;159(2–3):421–425.
Gill KJ, Zechner M, Zambo Anderson E, Swarbrick M, Murphy A.
Wellness for life: A pilot of an interprofessional intervention to address
metabolic syndrome in adults with serious mental illnesses. Psychiatr
Rehabil J. 2016;39(2):147–153.
McGinty EE, Baller J, Azrin ST, et al. Interventions to address medical
conditions and health-risk behaviors among persons with serious mental
illness: a comprehensive review. Schizophr Bull. 2016;42(1):96–124.
Kumar AA. Palamaner Subash Shantha G, Kahan S, Samson RJ, Boddu
ND, Cheskin LJ. Intentional weight loss and dose reductions of
antidiabetic medications—a retrospective cohort study. PLoS One.
Shantha GPS, Kumar AA, Kahan S, Cheah SY, Cheskin LJ. Intentional
weight loss and dose reductions of antihypertensive medications: a
retrospective cohort study. Cardiorenal Med. 2013;3(1):17–25.
Redmon JB , Bertoni AG , Connelly S , et al. Effect of the look AHEAD study intervention on medication use and related cost to treat cardiovascular disease risk factors in individuals with type 2 diabetes . Diabetes Care . 2010 ; 33 ( 6 ): 1153 - 1158 .
Erickson ZD , Mena SJ , Pierre JM , et al. Behavioral interventions for antipsychotic medication-associated obesity: a randomized, controlled clinical trial . J Clin Psychiatry . 2016 ; 77 ( 2 ): e183 - 189 .
Diabetes Prevention Program (DPP) Research Group. The Diabetes Prevention Program (DPP): description of lifestyle intervention . Diabetes Care . 2002 ; 25 ( 12 ): 2165 - 2171 .
Wirshing DA , Sergi MJ , Mintz J. A videotape intervention to enhance the informed consent process for medical and psychiatric treatment research . Am J Psychiatry . 2005 ; 162 ( 1 ): 186 - 188 .
Overall JE , Gorham DR . The brief psychiatric rating scale (BPRS): Recent developments in ascertainment and scaling . Psychopharmacol Bull . 1988 ; 24 ( 1 ): 97 - 99 .
Guy W. ECDEU Assessment Manual for Psychopharmacology, Revised. Rockville, MD: US Dept . of Health, Education, and Welfare , Public Health Service, Alcohol, Drug Abuse , and Mental Health Administration, National Institute of Mental Health, Psychopharmacology Research Branch, Division of Extramural Research Programs. 1976 .
Br J Soc Clin Psychol . 1967 ; 6 ( 4 ): 278 - 296 .
Beck A , Steer R . Beck Anxiety Inventory Manual. San Antonio, TX: Psychological Corp.; 1993 .
Weiden PJ , Miller AL . Which side effects really matter? Screening for common and distressing side effects of antipsychotic medications . J Psychiatr Pract . 2001 ; 7 ( 1 ): 41 - 47 .
DiClemente CC , Hughes SO . Stages of change profiles in outpatient alcoholism treatment . J Subst Abuse . 1990 ; 2 ( 2 ): 217 - 235 .
WHOQOL Group . The World Health Organization Quality of Life assessment (WHOQOL): position paper from the World Health Organization . Soc Sci Med . 1995 ; 41 ( 10 ): 1403 - 1409 .
First M , Spitzer R , Gibbon M , Williams J. Structured Clinical Interview for DSM-IV Axis I Disorders (SCID I) . New York, NY: Biometric Research Department; 1997 .
Balady GJ , Chaitman B , Driscoll D , et al. American College of Sports Medicine Position Stand and American Heart Association. Recommendations for cardiovascular screening, staffing, and emergency policies at health/fitness facilities . Med Sci Sports Exerc . 1998 ; 30 ( 6 ): 1009 - 1018 .
Moshfegh AJ , Rhodes DG , Baer DJ , et al. The US Department of Agriculture Automated Multiple-Pass Method reduces bias in the collection of energy intakes . Am J Clin Nutr . 2008 ; 88 ( 2 ): 324 - 332 .
Prochaska JO , Velicer WF . The transtheoretical model of health behavior change . Am J Health Promot AJHP . 1997 ; 12 ( 1 ): 38 - 48 .
Washington , DC: US Department of Veterans Affairs; 2011 .
Miller WR , Rollnick S. Motivational Interviewing: Helping People Change . New York, NY: Guilford Press; 2012 .
aspx. Accessed October 26 , 2016 .
Liberman RP , Glynn S , Blair KE , et al. In vivo amplified skills training: promoting generalization of independent living skills for clients with schizophrenia . Psychiatry . 2002 ; 65 ( 2 ): 137 - 55 .
Goodrich DE , Klingaman EA , Verchinina L , et al. Sex differences in weight loss among veterans with serious mental illness: observational study of a national weight management program . Womens Health Issues . 2016 .
Jensen MD , Ryan DH , Apovian CM , et al. 2013 AHA/ACC/TOS guideline for the management of overweight and obesity in adults: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines and The Obesity Society . Circulation.
2014 ; 129 ( 25 Suppl 2 ): S102 - 138 .
Vazin R , McGinty EE , Dickerson F , et al. Perceptions of strategies for successful weight loss in persons with serious mental illness participating in a behavioral weight loss intervention: a qualitative study . Psychiatr Rehabil J . 2016 ; 39 ( 2 ): 137 - 46 .
Colombo O , Ferretti VV , Ferraris C , et al. Is drop-out from obesity treatment a predictable and preventable event? Nutr J. 2014 ; 13 : 13 .
Individual , facility, and program factors affecting retention in a national weight management program . BMC Public Health . 2014 ; 14 : 363 .