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A Pilot Examination of Outcomes Froman Adolescent Residential TreatmentFacility Health and Wellness Interventionon Body Mass IndexLaura R. Greyber LMSW a b , Catherine N. Dulmus PhD c , MariaCristalli MPH b & Julee Jorgensen RN ba School of Social Work, University at Buffalo , Buffalo , New York ,USAb Hillside Family of Agencies , Rochester , New York , USAc Buffalo Center for Social Research and School of Social Work,University at Buffalo , Buffalo , New York , USAAccepted author version posted online: 20 Sep 2013.Publishedonline: 12 Nov 2013.

To cite this article: Laura R. Greyber LMSW , Catherine N. Dulmus PhD , Maria Cristalli MPH & JuleeJorgensen RN (2013) A Pilot Examination of Outcomes From an Adolescent Residential TreatmentFacility Health and Wellness Intervention on Body Mass Index, Residential Treatment for Children &Youth, 30:4, 239-261, DOI: 10.1080/0886571X.2013.841918

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Residential Treatment for Children & Youth, 30:239–261, 2013Copyright © Taylor & Francis Group, LLCISSN: 0886-571X print/1541-0358 onlineDOI: 10.1080/0886571X.2013.841918

A Pilot Examination of OutcomesFrom an Adolescent Residential TreatmentFacility Health and Wellness Intervention

on Body Mass Index

LAURA R. GREYBER, LMSWSchool of Social Work, University at Buffalo, Buffalo, New York, USA, and Hillside Family of

Agencies, Rochester, New York, USA

CATHERINE N. DULMUS, PhDBuffalo Center for Social Research and School of Social Work, University at Buffalo,

Buffalo, New York, USA

MARIA CRISTALLI, MPH and JULEE JORGENSEN, RNHillside Family of Agencies, Rochester, New York, USA

Specific Aims and Methodological Design: Using a pre–posttestdesign, the objective of this exploratory pilot study is to test theoutcomes of a comprehensive wellness group intervention in reduc-ing obesity measured by body mass index (BMI) for adolescentsliving in a residential treatment facility (RTF). The second majorobjective of this study is to test possible interactions of demographicand diagnostic characteristics on the outcome BMI percentage. Thefirst hypothesis is that the wellness group intervention will signifi-cantly improve participants’ BMI from unhealthy to healthy ranges.To analyze the first hypothesis, the overweight and obese BMI rangeswill be combined to create the unhealthy category. Secondly, it ishypothesized that the intervention will significantly improve indi-viduals’ BMI ranges from obese to overweight, and from overweightto healthy weight when comparing pre- to posttests. Lastly, it ishypothesized that post-BMI percentage will be predicted by pre-BMIcategories (obese, overweight, and healthy).

Sample: The participants were sampled from an existing RTF andconsisted of 28 adolescents, both male with serious and chronic

Address correspondence to Laura R. Greyber, LMSW, School of Social Work, Universityat Buffalo, 219 Parker Hall, Buffalo, NY 14214-8004, USA. E-mail: lgreyber@buffalo.edu

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240 L. R. Greyber et al.

emotional disorders. Demographic information was unavailablefor two of the 28 participants in this study.

Data Collection and Measures: Participants’ BMI (N = 28) wasmeasured at pre- and post-testing by the staff members at the RTFas well as demographic and diagnostic data including gender, eth-nicity, age, and mental and physical health diagnosis (N = 26).

Data Analysis and Results: Demographic and diagnostic datawas analyzed using descriptive frequencies. Data on pre–postBMI measures was analyzed using McNemar chi-square analy-ses. All of the hypotheses were supported. Results indicate thatparticipants significantly improved their BMI scores from pre- toposttesting—specifically the number of youth in unhealthy rangessignificantly improved to healthy ranges; and, the number of youthwho moved from obese to overweight, and overweight to healthyimproved. Lastly, results indicate that pre-BMI categories were sig-nificantly predictive of post-BMI percentage.

Conclusions: The findings of this pilot study have implicationsfor practice, policy, and research in all areas of child and adoles-cent wellness, including social work, psychology, health, medical,and education, to name a few. Results indicate that providinga comprehensive health and wellness intervention that integratesall aspects of well-being, is perhaps a worthwhile intervention toimproving the health of youth in residential treatment facilities.Limitations include a small sample size and limited methodologicalrigor due to design (pre–posttest single group design with no con-trol). An additional limitation is the lack of data on psychotropicmedication use for the sample. While the current research is apilot exploratory study, it provides valuable information for futureresearch with larger sample sizes and the use of control groups.

The obesity epidemic in the Unites States has caused much concern as ofrecent, especially for the healthy growth and development of children andadolescents. Within roughly 30 years, the prevalence of obesity among chil-dren and adolescents has dramatically increased by approximately 16.7%,with a host of various consequences including diabetes (Center for DiseaseControl [CDC], 2010). Perhaps most startling, research indicates that “60%of overweight children had at least one CVD [Cardiovascular Disease] riskfactor, while 25% of overweight children had two or more CVD risk factors”(CDC, 2010). While both biological and genetic factors contribute to weightissues, environmental factors are perhaps most easily modified and can betargeted through prevention and intervention.

In light of most recent reports that youth have been diagnosed withatherosclerosis, diabetes, and other health risks once known as adulthooddisorders, it seems imperative to address such issues through prevention and

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Wellness 241

management (CDC, 2010). Unhealthy lifestyle behaviors among adolescentshave contributed to poor bones and skin, dental problems, eating disorders,constipation, iron deficiency anemia, and high blood pressure and choles-terol to name a few (CDC, 2009). Other concerns related to overweightand obesity include psychosocial and emotional effects such as low self-esteem, stigmatization, systematic social discrimination, psychological stress,and poor self-image (Correll & Carlson, 2006). Often times, both physicaland psychological consequences of overweight and obesity persist long intoadulthood. Current estimates from the CDC (2010) indicate that “childrenwho became obese by age eight were more severely obese as adults . . .

and one-third of all children born in 2000 will develop diabetes in theirlifetime.”

Although physical health is an indicator of overall wellness, mentalhealth is an equally important piece of the puzzle. It is estimated that approx-imately 10% of youth and 25% of adults in the U.S. experience a mentalillness (National Institute of Mental Health [NIMH], 2008). Most remarkable,of the 57.7 million adults living with a mental illness (NIMH, 2008), 50%experience comorbid health conditions (Camann, 2001). Although more isknown about comorbidities in adults, little emphasis has been placed onresearching the integration of physical and mental health services for chil-dren and adolescents with serious mental illness (SMI). However, estimatestaken in 1985 approximate that 20% of youth in out-of-home facilities wereclassified as also having a comorbid physical disorder or disability (Altshuler& Gleeson, 1999). By 1994, this percentage more than doubled to 45% to80% (Altshuler & Gleeson, 1999). The dramatic increase in comorbid dis-orders perhaps challenges traditional single-focused treatment models thatare perhaps incomplete and ineffective in producing sustainable change inoverall wellness.

Using a pre–posttest design, the objective of this pilot study is to testthe outcomes of a comprehensive wellness group intervention in reducingobesity measured by body mass index (BMI) for adolescents living in a resi-dential treatment facility (RTF). The second major objective of this study is totest the possible interaction effects of demographic and diagnostic variableson the outcome BMI percentage, such as gender, ethnicity, age, mental healthdisorders, and comorbid disorders. Researchers feel this study will add to theknowledge of base of important predictors in obtaining positive outcomes forBMI in adolescents receiving care in residential settings. To the researchersknowledge, limited studies exist that test integrated wellness interventions onBMI outcomes as well as examining the effects of demographic and diagnos-tic characteristics on health outcomes following the wellness intervention.This knowledge is vital to both the mental and physical health of youth whostruggle with obesity and who perhaps have limited choices for diet andexercise within residential settings.

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242 L. R. Greyber et al.

BACKGROUND: THE INTEGRATION OF PHYSICALAND MENTAL HEALTH

Wellness and Comorbidities

The definition of wellness is predicated on a positive equilibrium betweenmicro, mezzo, and macro systems that support the health, growth, and devel-opment of individuals (Prilleltensky & Nelson, 2000). The model of integratedphysical and mental healthcare has been emphasized in Mental Health: AReport from the Surgeon General (1999), which underscores the importanceof disease prevention and health promotion services that incorporate overallwellness.

Research indicates that overall wellness and comorbid conditions sharean inverse relationship—as the number of comorbid conditions increase,wellness levels decrease. Children and adolescents are at an increased riskfor physical illness when diagnosed with a mental illness, and conversely,chronic illness more than doubles the risk for mental illness (Garralda,2004). Moreover, other studies report that 58% of obese children havebeen diagnosed with a mental health disorder (Vila et al., 2004). Resultsfrom an epidemiological study with 5,414 children and youth suggest thatcomorbidities are highly prevalent and have detrimental effects on overallwellness (Waters, David, Nicolas, Wake, & Lo, 2008). Additionally, wellnessis impacted by the type of treatment received and treatment settings, suchas inpatient versus outpatient services. Vieweg et al. (2005) conducted asecondary data analysis with data from a large inpatient psychiatric facilitysample and found that residents had twice the prevalence rates of obesitywhen compared to a normed sample. Findings from these studies perhapsunderscore the idea that obesity and other physical health correlates ofmental illness are reaching epidemic proportions in this population.

The advent of antipsychotic use in child and adolescent populationshas further complicated the problem of obesity and other physical healthcomorbidities related to serious mental illness (SMI). Although efficacy andeffectiveness research is lacking in the child and adolescent population,antipsychotic medications are being dispensed at an increased rate in aneffort to quell mental health symptoms (Correll & Carlson, 2006). Adverseside effects of antipsychotic medications substantially increase health riskssuch as thyroid problems, diabetes, weight gain, and hypertension—ultimately jeopardizing the future health of children and adolescents (Theisenet al., 2001).

Wellness and Youth Risk Behaviors

In addition to physical health comorbidities, research also links mental illnessto risk behaviors such as smoking, sexual behavior, drug and or alcohol use,limited physical activity, and poor diet, which in due course impact overall

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Wellness 243

wellness (Bobrowski, Czbata, & Brykczynska, 2007; Strohle et al., 2007). It isclear that physical health, risk behaviors, and psychosocial and mental healthare highly interrelated, and each weaves into the concept of overall wellness.Accordingly, interventions must be developed and implemented to addressand target all aspects of wellness.

Family Wellness and Involvement

Conceptually, family members play various roles in the health and wellnessbehaviors of children and adolescents. Likewise, family units can be uti-lized in various ways in the prevention or management of poor health riskbehaviors. It is reported that higher levels of depression are found in moth-ers of obese youth when compared to non-obese samples (Vila et al., 2004).In addition, children’s eating habits, whether negative or positive, are learnedthrough role modeling and parental eating behaviors (Vila et al., 2004).Family participation in treatment may prove a vital resource for improv-ing not only child wellness, but also family wellness. Similar to family rolemodeling, children and adolescents living in out-of-home placements can beassumed to be influenced through staff role modeling as well.

LITERATURE REVIEW

Physical Health Interventions

The definition of health is often considered the identification of physicalillness and health risk behaviors such as smoking, alcohol and drug use,physical inactivity, poor diet, sedentary lifestyle, unsafe sexual activity, and illhealth and safety practices (CDC, 2008). In addition, body mass index (BMI),fruit and vegetable intake, soda consumption, television viewing, physicaleducation, and video-game playing are also considered indicators of healthin youth populations (CDC, 2008).

Many efforts, including school-based interventions, have been devel-oped and examined to improve child and adolescent health and riskbehaviors. Findings from multiple studies indicate that providing health inter-ventions in school-based settings can improve overall obesity levels, producesignificant weight reductions, and reduce television viewing hours, whileincreasing fruit and vegetable consumption (Gortmaker et al., 1999; Hawley,Beckman, & Bishop, 2006).

Mental Health Interventions

The definition of mental health is a “state of successful performance ofmental function resulting in productive activities, fulfilling relationships withother people, and the ability to adapt to change and to cope with adversity.Mental health is indispensable to personal wellbeing” (Office of the Surgeon

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244 L. R. Greyber et al.

General, 1999, p. 4). Mental health has been conceptualized and measuredby the following factors: cognitive functioning and development, behavior,emotional or psychosocial adjustment, and school performance (Altshuler& Gleeson, 1999). Under the umbrella of mental illness is a subcategoryoften referred to SMI which is characterized by a decreased ability to focus,impaired memory, attention deficits, severe impairment in functional ability(minimum of 30 days), mood and anxiety disorders, and possible suicidaltendencies, other self-harm, or acts of violence (NIMH, 2008).

Methods in addressing child and adolescent mental illness includemedications and psychosocial interventions, as well as social support andfamily involvement techniques. Antipsychotic medications are typically pre-scribed for disorders such as attention deficit hyperactivity disorder (ADHD),mood and anxiety disorders, externalizing disorders, and psychotic disorders(Correll & Carlson, 2006). Conversely, psychosocial interventions includecognitive behavioral therapy (CBT), systematic behavioral family therapy,and more. Findings from a randomized trial testing CBT, systematic behav-ioral family therapy, and nondirective supportive therapy for adolescentswith depression indicate that 84% of the participants recovered within twoyears regardless of therapy type (Birmaher et al., 2000). Browne, Gafni,Roberts, Byrne, and Majumdar (2004) suggest the following modalitiesof addressing mental illness: role-playing, self-modeling, cognitive behav-ior therapy, rational emotional therapy, lectures, class series, peer led orteacher led groups, discussion groups, skills training, and primary preven-tion. Primary prevention efforts often consist of case management and familycounseling (Browne et al., 2004).

Integrated Wellness Interventions

Rather than single-focused targets such as physical or mental health, wellnessis conceptualized as a multifaceted equilibrium of overall functioning,resiliency, and coping (Altshuler & Gleeson, 1999). Child wellness is based“on the satisfaction of material, physical, affective, and psychological needs.Wellness is an ecological concept; a child’s wellness is determined by thelevel of parental, familial, communal, and social wellness” (Prilleltensky &Nelson, 2000, p. 87). Strategies to address child wellness should be sup-ported across micro, mezzo, and macro levels and should include child,family or parent, community, and societal focused programs (Prilleltensky &Nelson, 2000).

Wellness promotion is one way to enhance the mental and physicalhealth of children and adolescents by incorporating and integrating areassuch as physical, psychological, behavioral, and social components (Miller,Gilman, & Martens, 2007). Research indicates that school-based wellnessinterventions can improve overall wellness, prevent physical and mentalillnesses, and bolster quality of life (Miller et al., 2007). Additionally, physical

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activity has been shown to simultaneously improve both mental and physicalhealth (Nabkasorn et al., 2005).

In another study testing overall wellness outcomes, CBT was tested asan additional component in a non-dietary lifestyle intervention with a sam-ple of inpatient children and adolescents (Braet, Tanghe, Decaluwe, Moens,& Rosseell, 2004). Findings from this post-program evaluation indicate thatthe integrated wellness intervention resulted in a weight loss of 31.7%.Additionally, 82% of the participants reached their goals of a 10% weightloss. Reported improvement in self-esteem, school competence, self-worth,self-efficacy, and emotional problems were also noted in this study (Braetet al., 2004). While it appears that both physical and mental health interven-tions designed to address single target behaviors are effective in changingsingle behaviors, integrated interventions are perhaps the most appropriatemeans of addressing overall wellness.

Specific Aims and Methodological Design

Using a pre–posttest design, the objective of this exploratory pilot studywas to test the outcomes of a comprehensive wellness group interventionin reducing obesity measured by BMI for adolescents living in a RTF. Thesecond major objective of this study is to explore which groups at pre-testingchanged the most over time, or for which groups at pre-testing was the inter-vention most effective. The first hypothesis is that the wellness group inter-vention will significantly improve participants’ BMI from unhealthy to healthyranges. To analyze the first hypothesis, the overweight and obese BMI rangeswill be combined to create the unhealthy category. Second, it is hypothesizedthat the intervention will significantly improve individuals’ BMI ranges fromobese to overweight, and from overweight to healthy weight when com-paring pre- to posttests. Lastly, it is hypothesized that post-BMI percentagewill be predicted by pre-BMI range. For the purposes of the current study,BMI range is defined by the categories of obese, overweight, and healthyranges.

METHODS

Sample

Data was collected by facility staff from a total sample of 28 adolescents(ages 13–18), male (n = 16) and female (n = 10), living in a local RTF.Demographic characteristics were missing for two of the 28 participants inthis study. Sample characteristics are listed in Table 1. As diagnosed by aphysician, eligibility criteria for the RTF include the presence of a seriousand chronic emotional disorder marked by one or more of the following:disordered thinking, a mood disorder, a personality disorder, and or a

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TABLE 1 Demographic Characteristics of Participant

Characteristic Frequency Percent

EthnicityCaucasian 22 84.6African American 2 7.7Hispanic 1 3.8Biracial 1 3.8

GenderMale 16 61.5Female 10 38.5

Age of admittance7 1 3.88 1 3.89 1 3.810 1 3.812 1 3.813 6 23.114 2 7.715 6 23.116 2 7.717 4 15.418 1 3.8

behavior disorder with lack of impulse control (Hillside Family of Agencies,2010). Children and adolescents with emotional disorders experience symp-toms that are chronic and endure for a lengthy amount of time. Lastly,symptoms and or behaviors substantially interfere with functioning in dailyactivities across many environments including but not limited to: home,school, and community (Hillside Family of Agencies, 2010).

RTF Description

The primary goal of the RTF, under the umbrella of Hillside Family ofAgencies, is to return youth to their home communities within a relativelyshort amount of time. Residents live in either cottages or community-basedgroup homes as they are in need of 24-hour-a-day, seven-day-a-week caredue to the severity of their emotional disturbance. Family and individual ther-apy is conducted by highly trained staff and specialists who assist participantsin understanding and managing their symptoms, learning new skills, andadapting to challenges. Residents also receive therapeutic recreation and maybe prescribed medication if necessary to alleviate symptoms. Additionally,the RTF emphasizes and enhances family members’ ability to participatein RTF activities, therapy, and treatment. While receiving both group andindividual therapy, residents also attend the campus schools which providetailored education to youth (Hillside Family of Agencies, 2010).

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Health and Wellness Group Intervention

The health and wellness group intervention was delivered within a RTF foradolescents who were receiving traditional services from highly trained spe-cialists including nurses and dieticians, within Hillside Family of Agencies.Under the following mission, the health and wellness group interventionwas designed to “Create an environment which assists the client in healthylifestyle changes such as: diet, exercise, and wellness education in order topromote a positive lifestyle in combination in achieving a healthy weight”(Hillside Family of Agencies, personal communication, March 10, 2009). Theintervention targeted lifestyle areas such as diet, exercise, and medication.Following dietary guidelines in addition to avoiding the use of food forreward, and planning for healthy snacks were key intervention areas used toaddress diet (See Appendix A for the Meal and Snack Protocol). To improveexercise levels, the health and wellness intervention required participants tocomplete 60 minutes of physical activity for three out of the five weekdays,in combination with reducing sedentary activities and encouraging activeplay such as swimming and biking (See Appendix B for the Fitness andActivity Protocol).

The participants of the intervention also developed an action plan,which identified key strategies to address the four intervention focus areasincluding diet, physical activity, medical, and education. Controllable fac-tors were identified such as diet and physical activities, education, and staffrole modeling. Community resources were also utilized throughout the inter-vention including the local Young Men’s Christian Association (YMCA) andWegmans Food Markets.

Data Collection and Measures

Demographic and diagnostic characteristics were collected upon admittanceto the RTF and included the following variables: gender, age, ethnicity, andmental and physical health diagnoses. Demographic information was missingfor two of the 28 participants in this study. Body mass index was measuredby facility staff pre- and post-intervention. While BMI does not directly mea-sure body fat, it has been indicated by the CDC as a reliable measure toassess body fat for children, teens, and adults (2009). BMI is calculated usinga formula with inputted weight, height, age, and gender. To convert BMInumbers to percentiles, the BMI number is plotted on the CDC’s BMI-for-agegrowth chart. “Percentiles are the most commonly used indicator to assessthe size and growth patterns of individual children in the United States. Thepercentile indicates the relative position of the child’s BMI number amongchildren of the same sex and age” (CDC, 2009). Once percentiles are indi-cated, the growth chart allows for the appropriate placement of childrenand adolescents into BMI categories including underweight, healthy weight,

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248 L. R. Greyber et al.

TABLE 2 BMI-For-Age Weight Status Range and BMI Percentiles (CDC, 2009)

BMI range BMI percentile range

Underweight Less than the 5th percentileHealthy weight 5th percentile to less than 85th percentileOverweight 85th percentile to less than 95th percentileObese Equal to or greater than the 95th percentile

overweight, and obese which are listed in Table 2 (CDC, 2009). Multiplestudies have used the BMI to examine obesity levels among children andadolescents (Gortmaker et al., 1999; Hawley et al., 2006).

Data Analysis

Demographic and diagnostic characteristics of the sample were analyzedusing descriptive statistics including gender, ethnicity, age at admittance,and mental health and physical health diagnosis (see Table 1). A total of30 different mental health diagnoses and five physical health disorders wererepresented across the participants in the sample. To analyze such diag-noses, researchers categorized mental and physical illnesses based on theaxial categories of the American Psychiatric Association (2000) Diagnosticfor Statistical Manual for Mental Disorders IV-TR. Therefore, axis 1 wascategorized as mood disorders, with subcategories including depressive,anxiety, and bipolar disorders. Axis 2 disorders included the followingmajor categories: pervasive developmental disorders, personality disorders,axis 2 deferred disorders, attention deficit and disruptive behavior dis-orders, and an other category which included Tic disorders and similardiagnoses. Lastly, axis 3, or general medical conditions, was representedby health problems present in the sample: asthma, chronic ear infec-tion, enuresis due to general medical condition, hearing loss, and Lyme’sdisease.

Baseline BMI scores were analyzed using descriptive statistics, in partic-ular frequencies, sums, and averages, and are listed in Table 3. To test bothof the hypotheses, and determine if the health and wellness group inter-vention successfully improved BMI percentiles ranges, data was analyzedusing chi-square analysis with McNemar’s tests. Non-parametric techniqueswere chosen to analyze the nominal data in order to examine BMI changefrom pre- to posttesting through frequencies. To analyze the first hypoth-esis, overweight and obese BMI ranges were combined to create theunhealthy category, while the healthy category consisted of the healthy BMIrange. To examine the second hypothesis, obese, overweight, and healthyBMI ranges were analyzed. Lastly, to examine within and between groupdifferences, a MANOVA was conducted.

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Wellness 249

TABLE 3 Diagnostics

Disorder–Category Disorder Yes No% Yes

(Total N = 26)

Personality disorders(N = 4; 15.38%)

Antisocial PD 2 24 7.69Borderline PD 2 24 7.69

Mood disorders (N = 20;76.92%)

Anxiety disorder, NOS 4 22 15.38Bipolar disorder 6 20 23.08Depressive disorder,

NOS1 25 3.85

Major depressive 2 24 7.69Mood disorder, NOS 7 19 26.92Post-traumatic stress

disorder2 24 7.69

Attention, conduct,behavior disorders(N = 13; 50%)

ADHD 7 19 26.92Conduct disorder 4 22 15.38Disruptive behavior

disorder1 25 3.85

Oppositional defiantdisorder

1 25 3.85

Pervasive developmentaldisorder (N = 7;26.92%)

Borderline intellectualfunctioning

4 22 15.38

DD, PDD, Retts,Aspergers

3 23 11.54

Eating disorders (N = 1;3.85%)

Bulimia nervosa 1 25 3.85

Psychotic andschizophrenicdisorders (N = 4;15.38%)

Psychotic disorder, NOS 2 24 7.69Schizoaffective 1 25 3.85Schizophreniform 1 25 3.85

Tic, Tourette, OCD(N = 3; 11.54%)

Tic 1 25 3.85Tourette 1 25 3.85OCD 1 25 3.85

Medical (N = 6; 23.08%) Enueresis—due to GMC 1 25 3.85Hearing loss 1 25 3.85Lymes 1 25 3.85Otitis media, chronic 1 25 3.85Asthma 2 24 7.69

RESULTS

Demographic and Diagnostic Results

Participant demographic and diagnostic variables are listed in Table 1 andTable 3. The average age of the sample was 13.8 years old, and the samplewas largely Caucasian (84.6%). There were slightly more males than femalesin the sample as there were 10 females and 16 males. Upon admittance,a large number of adolescents were diagnosed with a mental health disor-der, multiple disorders, and most with a combination of mood, personality,and development disorders. In particular, 69.2% of the sample had a mentalhealth diagnosis, 69.2% also had multiple mental health disorders. At the lowend, 15.4% of participants had two mental health disorders, and at the high

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250 L. R. Greyber et al.

end, 11.5% of the sample had six mental health diagnosis. Approximately15% of the sample was diagnosed with a personality disorder, 77% with amood disorder, 50% with a behavior disorder, 27% with a pervasive devel-opmental disorder, and 15% with a psychotic and or schizophrenia disorder.A small number of participants had physical health disorders at admission(19.2%), other than obesity and overweight issues, one participant had aneating disorder (3.85%), and three were diagnosed with Tic, Tourette, andobsessive compulsive disorder.

Descriptive baseline and posttesting BMI ranges are reported in Table 4,whereas baseline and posttesting BMI unhealthy–healthy category percent-ages are reported in Table 5. A large percentage of participants at baselinetesting were represented in the obese BMI range. At pretesting, approxi-mately 18% of participants were in the healthy range compared to 39% atposttesting. The number of youth in the overweight range stayed the samefrom pre- to posttesting (28.6%); however, it does not represent the sameyouth at pre- to posttesting. Lastly, at pretesting, approximately 54% of youthwere in the obese category compared to 32.1% at posttesting.

When categories overweight and obese were combined into theunhealthy category, 82.1% of youth were considered unhealthy at prestest-ing compared to 60.7% at posttesting. Comparatively, at pretesting, 19.5% ofyouth were in the healthy category and at posttesting, the number of youthin this category increased by 21.4%.

Body Mass Index—Pre- to Posttesting Results

Following a McNemar’s chi-square analysis, hypothesis one and two wereboth supported. It was hypothesized that a significant number of youth in thewellness intervention group would move from the unhealthy to the healthycategory. Results support this hypothesis that a significant difference in youthin the intervention group moved from the unhealthy to the healthy range(χ 2 = 4.230, p = .04; p < alpha .05, df = 1). More specifically, from pre-to posttesting, the number of youth ion the healthy range increased fromone to four. Additionally, the number of youth in the pre-unhealthy rangedecreased from 16 to 7. Results are listed in Table 6.

It was hypothesized that a significant number of individuals in thewellness intervention group would decrease show a decrease in BMI rangefrom pre- to posttesting. This hypothesis was supported (χ 2 = 16.853,p = .002, p < alpha .05; df = 4) and results are listed in Table 7.Table 7 represents the shift in BMI categories from pre- to posttesting. Forinstance, the number of youth that moved from the pre-obese category tothe post-overweight category was five. Six youth transitioned from the pre-overweight category to the post-normal category. Lastly, the number of youthin the pre-overweight category that transitioned to post-normal categorywas six.

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252 L. R. Greyber et al.

TABLE 5 Baseline and Posttesting Unhealthy/Healthy Percentages

BMI category Pre N in category Pre percentage Post N in category Post percentage

Healthy 5 17.9 11 39.3Unhealthy 23 82.1 17 60.7Total N = 28 N = 28

TABLE 6 McNemar’s Test Results for Hypothesis One

BMI category Post unhealthy Post healthy Total

Pre unhealthy 16 7 23Pre healthy 1 4 5Total 17 11 28

TABLE 7 McNemar’s Test Results for Hypothesis Two

BMI category Post obese Post overweight Post normal Total

Pre obese 9 5 1 15Pre overweight 0 2 6 8Pre normal 0 1 4 5Total 9 8 11 28

The results from the MANOVA analysis indicate that there was a signifi-cant difference in groups between pre- and post-testing on BMI (F = 31.65,p = .000, df = 2). These results suggest a significant change in BMI frompre- to posttesting. However, when analyzing the within-subject effects orpre-BMI classification by time, there was no significant difference (t = 2.63,p = .092, df = 2). In further examination of the MANOVA analysis, brokendown by pre-BMI classification, results suggest that both the obese and nor-mal weight group (at pretesting) significantly changed over time, while theoverweight group did not.

DISCUSSION

Results from this study provide promising results that interventions target-ing multiple areas of overall wellness are both appropriate and positiveapproaches for not only maintaining, but also improving the health of ado-lescents in residential placements. At baseline, the majority of the adolescentsample was categorized in an unhealthy BMI category and percentile range.Perhaps most important, the largest differences were seen in the healthyweight and the obese ranges. More specifically, the number of participantsin the normal BMI range increased 21.4%, and the number of participants inthe obese range decreased from 53.6% to 32.1%.

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Wellness 253

The first hypothesis was that the wellness group intervention willsignificantly improve participant’s BMI from unhealthy to healthy ranges.To analyze the first hypothesis, the overweight and obese BMI ranges werecombined to create the unhealthy category. The first hypothesis was sup-ported; the intervention resulted in a significant number of individuals thatmoved from the unhealthy to the healthy BMI category. More specifically,at pretesting, five of the individuals were in the healthy BMI category com-pared to 11 at posttesting. Conversely, 23 of the 28 individuals fell withinone of the unhealthy BMI category (obese or overweight) at pretesting,which significantly decreased to 17 at posttesting. Converted into percent-ages, 82.1% were in the unhealthy category at the start of the intervention,compared to 60.7% at posttesting. The integrated health and wellness inter-vention dramatically improved BMI scores by 21.4% from unhealthy tohealthy.

While combining both the obese and overweight categories to examineoverall change from unhealthy to healthy allows for broad conclusions, thetesting of hypothesis two provides much more detail in the actual movementof participants from one BMI range to another. The second hypothesis wasthat the intervention will significantly improve individuals’ BMI range fromobese to overweight, and from overweight to healthy weight. The results ofthe chi-square analysis for hypothesis two indicate that individuals were ableto significantly decrease in BMI ranges from pre- to posttesting. Dramatically,one individual moved across two ranges from the obese to the healthy BMIrange. Additionally, from pre- to posttesting, 5 of the 15 obese participantsmoved into the overweight range, and 6 of the 8 overweight participantsmoved into the healthy range. Twenty-seven of the 28 participants eitherimproved their BMI range or remained the same—with the exception of oneparticipant moved from the healthy to the overweight BMI range. Focusingon the integration of physical and mental health, the intervention was able tosignificantly actuate positive lifestyle changes, decrease BMI, and ultimatelyimprove physical health.

Lastly, 48% of participants showed change in BMI categories, while 52%(15) of participants remained the same from pre- to posttest time points.Of those 15 participants who remained in the same BMI range, 9 remainedobese, 4 remained healthy, and 2 participants remained overweight. It shouldalso be discussed that all but two participants changed BMI ranges by oneincrement. In other words, those who were obese at pretesting moved tooverweight at posttesting, and overweight moved to healthy.

While the overall results for the MANOVA analysis were insignificantwhen examining time by pre-BMI classification, in depth review of the resultsindicate that certain groups had significant changes from pre- to posttesting.In particular, the obese and normal weight (pre-classification) changed sig-nificantly over time, while the overweight group did not significantly change.This result could reflect the idea that from pre- to posttesting, most of the

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obese group moved into the overweight group. At pretesting, 15 individualswere in the obese group and at posttesting 9 were in this group. For theoverweight group, there were 8 individuals at pretesting compared to 8 atposttesting. This indicates that individuals in the obese group moved into theoverweight group over time. While the number of individuals in the over-weight group remained the same across the intervention time period, thesenumbers do not represent the same individuals.

Limitations and Future Research

Although a pilot study, the first major limitation is small sample size whichlimits both the power and generalizability of this study. With such a smallsample size, it is difficult to determine any significance of demographic anddiagnostic factors on the post-BMI scores of the participants. It is possiblethat there were no interaction effects of gender, ethnicity, age, mental andphysical health diagnoses due to the small sample size with limited power todetect differences across groups. Future research would benefit from usinglarger sample sizes with power high enough to detect significances of pos-sible predictor and moderating variables. Additionally, future research mayrecruit more heterogeneous samples in order to examine any potential dif-ferences across groups based on demographic and diagnostic variables. Theuse of antipsychotic or psychotropic medications could also be examined infuture research as it is a major contributing factor to weight gain in someyouth. A limitation to the current study is that medication data was notavailable at the time of data collection.

Another limitation includes the lack of control or comparison group,which reduces the ability to determine causality between the interventionand the outcomes reported at posttesting. Threats to both internal and exter-nal validity are increased with the use of pretest-posttest single group design.The use of a stronger methodological design in future research would ben-efit the state of knowledge by having more confidence that the interventionin fact had a direct effect on the health of participants. Building uponthis exploratory pilot study would provide valuable insight into the effec-tiveness of wellness interventions on adolescents in RTFs as well as othersettings.

Lastly, the use of treatment process measures, multiple time point mea-sures, overall wellness measures, and the use of follow-up measures wouldbe valuable to implement in future research. Treatment process measureswould allow for the examination of treatment components that potentiallyaffect outcomes of health for adolescents. Furthermore, it would be worth-while to examine overall wellness as opposed to single outcomes such asBMI in order to test the success of all treatment goals in a comprehensivewellness program. Follow-up measures would provide important insight intowhether or not treatment effects were maintained over time.

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Wellness 255

IMPLICATIONS

Policy and Practice Implications

With the rapidly growing obesity epidemic, and the high numbers ofyouth experiencing comorbid disorders, it is imperative that both preven-tion and treatment interventions are integrated to meet the needs of thisgrowing segment of the mental health population. Results from this studyindicate that it is worthwhile to integrate and target all aspects of healthand wellness to improve child and adolescent growth and development.Furthermore, preventive techniques and policies must be developed andemployed to quell potential adulthood implications of persisting childhooddisorders. It is estimated that over 27 types of mental illness have beenassociated with increased mortality and premature death, and that 84% ofadult inpatient residents required care from nursing staff (Cormac, Martin,& Ferriter, 2004). Lastly, in the adult population, it is estimated that 50%of individuals with SMI have at least one known comorbid physical illness(Camann, 2001).

Furthermore, mental illness represents 15% of the overall burden ofdisease (Office of the Surgeon General, 1999) and approximately $193 billionannually is allocated to lost earnings related to mental illness (NIMH, 2008).Additionally, it is estimated that depression is the leading cause of yearslost due to disabilities, breaching all socio-economic levels and across allcountries (World Health Organization [WHO], 2008). Given the exceedinglyhigh number of individuals experiencing mental illness, and the remarkableinfluences of mind and body, a comprehensive and integrated public healthmodel not only seems appropriate, but also highly demanded. The resultsfrom this study support the integration of physical and mental health servicesto improve overall well-being of children and adolescents with SMI. Theprovision of effective interventions, designed to meet all of the characteristicsand demands of comorbid disorders, has the potential to not only improvewell-being, but decrease the costs, disabilities, and lost earnings related tomental illness.

Overall health may go unrecognized, and often ignored in populationsof SMI. Both fragmented services, and barriers to such integrated services,are impeding access to the necessary services to create sustaining change inoverall wellness. Both the Surgeon General’s Report and other pushes suchas the consumer and recovery movements advocate for improving healthcarepolicy resulting in a reduction of barriers to accessing integrated care for bothphysical and mental illness (Camann, 2001).

In addition to accessibility barriers, the lack of available serviceproviders that are trained in addressing comorbid disorders poses anotherobstacle for this population. Cormac et al. (2004) suggest that althoughpsychiatrists are trained medical doctors, few have the necessary primarycare skills to treat the overall health of the SMI population. Researchers put

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forth that integrated health and mental health promotion, prevention, andmanagement are necessary given the excessive mortality rates among individ-uals with SMI (Cormac et al., 2004). Resources for improving healthcare andinpatient residential stays include the modification of current policies andimproved comprehensive training to provide the necessary tools to integratemultidisciplinary care into existing systems (Cormac et al., 2004). Advocacyfor healthcare that is coordinated and heavily focused on health promotion,physical activity, diet, healthy lifestyle, smoking cessation, and weight man-agement techniques may prove both worthwhile and cost effective (Cormacet al., 2004). The current study has implications on service delivery and socialwork practice areas.

Provided that the current healthcare system is designed to create com-petition between mental and physical health services, often vying for scarceresources, the integration of physical and mental healthcare is perhaps adaunting challenge. Typically, mental health insurance is carved out of alarger health insurance plan, or from other sources that may vary by state orcounty—creating further disparities within the system (Zolnierek, 2008). Suchdisparities may be quelled by providing and delivering integrated healthcareto all, including those with SMI. While a small pilot study, the current findingssuggest that integrating services for children and adolescents with comorbiddisorders can improve health correlates of mental illness. In addition, the cur-rent healthcare system is designed to treat individual and isolated disorders,with a plethora of specialty fields and specialists. There is some evidencethat indicates that limiting treatment to specialists has not met the uniqueneeds of the SMI population, who experience multidimensional correlates ofmental illness (Zolnierek, 2008).

Though a small pilot study, the health and wellness intervention has apositive effect on in creating healthy lifestyle changes, not only among resi-dents, but also staff. It is important to consider that this type of interventionrequires not only an individual change, but also and perhaps more important,an agency culture change. Both residents and staff in the treatment facility,in a sense, are vital components to the health and wellness intervention.In addition, management techniques like the health and wellness interven-tion should include therapy, physical activity planning, family involvement,psychoeducation, and staff support to name a few. Interventions like thehealth and wellness group, that are uniquely tailored to meet the needs ofindividuals with SMI related neurological, cognitive, behavioral, and socialdeficits should be examined in future research and considered in practice.Much like the health and wellness intervention reported here, agencies andconsumers would perhaps benefit from putting into place mission statementsthat drive the integration between physical and mental health, as well asorganizational policies and procedures to provide a framework for meetingthe needs of comorbid populations.

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Wellness 257

Research Implications

Although more is known about comorbid conditions in adults, little emphasishas been placed on researching integrated services for this growing segmentof children and adolescents with serious mental and physical illnesses. Thissmall pilot study exemplifies the necessity for more rigorous interventionstudies testing the effectiveness of health and wellness groups on multipleoutcomes of well-being. Future studies should examine all other outcomes ofwellness including mental and physical health, emotional health, academicsuccess, and social relationships. Testing overall wellness as a main outcomewhile examining effective treatment components based on age and devel-opmental stages may also prove beneficial. Additionally, research initiativesare necessary to test the effectiveness of various components within multidi-mensional wellness interventions. Some of these components may include,but are not limited to, staff factors such as role modeling and reinforcement,organizational climate and culture measures, as well as family involvementand other forms of support such as community resources. Future researchcould perhaps use a single-systems design to further examine the changes insmall intervention groups over time. Additionally, with larger sample sizes,future research studies could examine the differences in gender, age, andother demographic and diagnostic factors that may interact with changesacross time.

REFERENCES

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American Psychiatric Association. (2000). Diagnostic statistical manual of mentaldisorders (4th ed., text rev.). Arlington, VA: American Psychiatric Association.

Birmaher, B., Brent, D. A., Kolko, D., Baugher, M., Bridge, J., Holder, D., Iyengar,S., & Ulloa, R. E. (2000). Clinical outcomes after short-term psychotherapy foradolescents with major depression. Archives of General Psychiatry, 57 , 29–36.

Bobrowski, K. J., Czabata, J. C., & Brykczynska, C. (2007). Risk behaviors as adimension of mental health assessment in adolescents. Archives of Psychiatryand Psychotherapy, 1–2, 17–26.

Braet, C., Tanghe, A., Decaluwe, V., Moens, E., & Rosseell, Y. (2004). Inpatienttreatment for children with obesity: Weight loss, psychological well-being, andeating behavior. Journal of Pediatric Psychology, 29(7), 519–529.

Browne, G., Gafni, A., Roberts, J., Byrne, C., & Majumdar, B. (2004).Effective/efficient mental health programs for school-age children: Asynthesisof reviews. Social Science and Medicine, 58, 1367–1384.

Camann, M. A. (2001). To your health: Implementation of a wellness program fortreatment staff and persons with mental illness. Archives of Psychiatric Nursing,15(4), 182–187.

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Center for Disease Control. (2009). About BMI for children and teens. Retrievedfrom http://www.cdc.gov/healthyweight/assessing/bmi/childrens_bmi/about_childrens_bmi.html#What%20is%20BMI

Center for Disease Control. (2010). Healthy youth: Childhood obesity. Retrieved fromhttp://www.cdc.gov/HealthyYouth/obesity/index.htm.

Cormac, I., Martin, D., & Ferriter, M. (2004). Improving the physical health of long-stay psychiatric in-patients. Advances in Psychiatric Treatment, 10, 107–115.

Correll, C. U., & Carlson, H. E. (2006). Endocrine and metabolic adverse effectsof psychotrpic medications in children and adolescents. Journal of AmericanAcademy of Child and Adolescent Psychiatry, 45(7), 771–791.

Garralda, M. E. (2004). The Interface between physical and mental health problemsand medical help seeking in children and adolescents: A research perspective.Child and Adolescent Mental Health, 9, 146–155.

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Hawley, S. R., Beckman, H., & Bishop, T. (2006). Development of an obesity preven-tion and management program for children and adolescents in a rural setting.Journal of Community Health Nursing, 23(2), 69–80.

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Theisen, F. M., Linden, A., Geller, F., Schafer, H., Martin, M., Remschmidt, H., &Hebebrand, J. (2001). Prevalence of obesity in adolescent and young adultpopulations with and without schizophrenia and in relationship to antipsychoticmedication. Journal of Psychiatric Research, 35, 339–345.

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Waters, E., Davis, E., Nicolas, C., Wake, M., & Lo, S. K. (2008). The impact of child-hood conditions and concurrent morbidities of child health and well-being.Child: Care, Health, and Development, 34(4), 418–429.

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APPENDIX A: MEAL AND SNACK PROTOCOL

Purpose: To help promote the health and well-being of our clients, staff andfamilies by ensuring that compliance is maintained regarding healthy foodchoices.Staff are responsible and will be accountable for role-modeling these guide-lines on all off-campus outings.

Definitions:Meal: The food served and eaten in one settingSnack: Food eaten between mealsPortion (serving) Size: An amount of food served for one person: serving,helpingNon-Caffeinated: Does not contain caffeine (Sprite, Sierra Mist, juice, water)

(Water intake is not limited unless directed by health office)If staff takes a client off-campus the following guidelines shall be followed:

1. Approval for meal purchase should be obtained from the departmentsupervisor prior to an outing

2. Notify kitchen of off-campus meal (bag lunches should be encouraged)3. Cultural and religious nutrition requests should be reviewed by dietary on

an individual basis prior to an outing4. No buffets5. No energy drinks (Red Bull, Monster, Rockstar)6. Off-campus meals

a. Fast Food (client may choose only 1 item from i. ii. iii. And may haveiv and/or v with meal)

i. 1 sandwichii. 1 salad

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iii. 2 pieces of pizzaiv. 2 small fry or side dishv. 1 small dessert (dinner only)vi. 1 small non-caffeinated drink

b. Restauranti. 1 entrée with sideii. 1 small non-caffeinated drinkiii. 1 small dessert

c. Recreational events (movies, ice cream outings, spectator support[double-days, sky chiefs, crunch, SU, etc.] malls, water parks, iceskating, van rides, etc.)∗∗Choose from only one of the following choices below per applicableevent

i. 1 small popcorn or candy item or ice cream bar (movies)ii. 1 small ice cream or frozen yogurt (may have sprinkles, no sundaes,

and no milkshakes on ice cream outings)iii. Choose one: Small popcorn, nachos, soft pretzel, candy, small/

medium bag of chips, french fry, hotdog, hamburger, piece ofpizza, fried dough (spectator sports, malls, water parks, ice skating,van rides, etc.)and

iv. 1 small non-caffeinated drink or hot cocoa7. On-campus meals

a. Holiday, family, unit gatherings and/or cook-outsi. 1 serving size per item

8. On-campus parties (birthday/discharge)a. 1 piece of cake may be served on unit only

i. This will count as dessert for that dayb. Vegetable or fruit tray may be served in school

Absolutely no food shall be brought on campus from off-campusactivities or home-visits.

APPENDIX B: FITNESS AND ACTIVITY PROTOCOL

Purpose: To help promote the health and well-being of our clients, staff andfamilies by promoting physical activity within the client’s program.

Staff are responsible and will be accountable for role-modeling these guide-lines at all times.

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Definitions:Physical activity: Any form of exercise or movementActive: Involving physical effort and action

Guidelines: The following guidelines should be followed to ensure thephysical activity requirements are met for each client:

1. Three out of five days, Monday through Friday, it is expected that at leastone hour of physical activity is planned in the client’s recreation schedule

2. It is required that a trip to the YMCA be scheduled one out of the fivedays for each unit (This hour does not include travel time)a. If there is a consequence for behavior that does not allow the client

to participate in the planned activity, it is required that an alternativephysical activity be planned for that client.

b. If a client is on recreation restriction from a medical order then analternative recreational plan should be developed by the recreationtherapist in collaboration with the nursing department.

3. Activity level will be documented daily by the units via a designatedtracking system

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