A Primary Care Healthy Choices Intervention Program for Overweight and Obese School-Age Children and Their Parents

ARTICLE

A Primary Care Healthy Choices Intervention Program for Overweight and Obese School-Age Children and Their Parents Diana Jacobson, PhD, RN, PNP-BC, & Bernadette Mazurek Melnyk, PhD, RN, CPNP/PMHNP, FNAP, FAAN

ABSTRACT Introduction: The escalating crisis of childhood overweight and obesity creates an urgent demand for evidence-based interventions that can be used by primary care providers. Therefore, the purpose of this study was to test the feasibility, acceptability, and preliminary efficacy of a theory-based Healthy Choices Intervention (HCI) Program with fifteen 912 year old overweight and obese children and their parents in a primary care setting. Methods: A 1-group, 7-week pre-/posttest study design was used. Outcome measures included: body mass index (BMI) percentile, physical activity and nutrition knowledge, beliefs, choices and behaviors, anxiety, depression, self-concept, and social competence. Results: Children and parents found the HCI to be useful and informative. Positive effects of the HCI for the children

Diana Jacobson, Assistant Professor, Arizona State University College of Nursing and Health Innovation, Phoenix, AZ. Bernadette Mazurek Melnyk, Dean and Distinguished Foundation Professor in Nursing, Arizona State University College of Nursing and Health Innovation, Phoenix, AZ. Conflicts of interest: None to report. Correspondence: Diana Jacobson, PhD, RN, PNP-BC, Arizona State University College of Nursing and Health Innovation, 500 N 3rd St, Phoenix, AZ 85004; e-mail: [email protected]. 0891-5245/$36.00 Copyright Ó 2012 by the National Association of Pediatric Nurse Practitioners. Published by Elsevier Inc. All rights reserved. doi:10.1016/j.pedhc.2010.07.004

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included decreased BMI percentile, increased knowledge, beliefs, choices and behaviors, and self-control. Positive effects of the intervention for the parents included increased knowledge, beliefs, behaviors, and decreased anxiety. Discussion: This study provides evidence to support the feasibility, acceptability, and preliminary effects of the HCI with overweight and obese school-age children and their parents within a primary care setting. J Pediatr Health Care. (2012) 26, 126-138.

KEY WORDS School-age obesity, primary care interventions, cognitive behavior skills building

The escalating health crisis of pediatric obesity has been well documented, with approximately 17% of youth in the United States between the ages of 6 and 19 years identified as obese (body mass index [BMI] $95th percentile for age and gender) (Ogden et al., 2006). In addition, data from the National Health and Nutrition Examination Survey (NHANES) (2007-2008) show that 11.9% of children and adolescents between the ages of 2 and 19 years have BMIs measuring at or above the 97th percentile; 16.9% were at or above the 95th percentile; and 31.7% were at or above the 85th percentile of BMI for age (Ogden, Carroll, Curtin, Lamb, & Flegal, 2010). Pediatric primary care providers (e.g., nurse practitioners and physicians) are in an ideal situation to intervene with overweight and obese school-age children and their families with evidence-based strategies to address this chronic health problem (Davis Journal of Pediatric Health Care

et al., 2007; Whitlock, Orleans, Pender, & Allan, 2002; Whitlock, Williams, Gold, Smith, & Shipman, 2005). There has been limited research and inconsistent findings in the few studies that have examined the effects of overweight intervention programs on both the school-age child’s physical and psychosocial health (Barlow & Dietz, 2002; U.S. Preventive Services Task Force, 2005). The few intervention programs that have included psychosocial interventions have centered the intervention activities within the school curriculum or at weight loss clinics rather than in the child’s primary health care home (Cameron, 1999; Epstein, Valoski, Wing, & McCurley, 1994; Sherman, Alexander, Gomez, & Marole, 1992). Current Expert Committee recommendations for the assessment, prevention, and treatment of youth overweight and obesity call for primary care providers to be at the center of a nationwide effort to address obesity in the primary care setting (Barlow & the Expert Committee, 2007). In the primary care setting, comprehensive care for the overweight and obese child or adolescent should be initiated and delivered immediately upon the assessment of this chronic health condition (Spear et al., 2007). Despite the publication of recommendations from a variety of professional organizations, translating these recommendations into practice remains a challenge because research suggests there is limited adoption of guidelines and recommendations by health care providers (Anderson & Butcher, 2006; Cabana et al., 1999; Story et al., 2002). Mabry and colleagues reported that despite consensus guidelines recommending the use of BMI for the diagnosis and management of obesity, BMI was documented in only 5% of initial visits for children diagnosed with obesity during a routine well-child visit in a general pediatric practice (Mabry et al., 2005). A chart audit of well-child visits also revealed less than 1% (0.93%) of visits that documented a diagnosis of obesity (Cook, 2005). This study addresses a substantial gap in the science of intervention research by testing the feasibility, acceptability, and preliminary short-term effects of a theory-based reproducible Healthy Choices Intervention (HCI) Program based on current research evidence and Expert Committee recommendations within primary care settings. LITERATURE REVIEW Factors Influencing Overweight and Obesity in Children It is widely accepted that obesogenic environments that encourage children to overeat unhealthy calorie-dense foods and carbonated beverages while promoting inactivity with television viewing or video games is adversely affecting the health of youth. Children are not obtaining moderate to vigorous physical activity opportunities. The amount, duration, and intensity of physical www.jpedhc.org

education in schools have decreased dramatically in the past decade, especially as the student’s grade level increases (Centers for Disease Control and Prevention, 2005; Kann, TellJohann, & Wooley, 2007). Obesity is the end result of increased energy intake and reduced energy expenditure. Importantly, failure to evaluate the family’s attitudes and beliefs about healthy weight and lifestyle prior to initiating healthy lifestyle interventions neglects the importance of family health history, cultural influences, and family strengths in the development of beneficial obesity interventions (Fitzgibbon & Stolley, 2004; Sherry et al., 2004). Effects of Pediatric Obesity on Mental Health It may be difficult for children to adopt and maintain healthy lifestyle behaviors because of psychosocial factors (Gray, Janicke, Ingerski, & Silverstein, 2008; Melnyk et al., 2009; Phuphaibul, Thanooruk, Leucha, Sirapongam, & Kanobdee, 2005). Overweight and obese school-age children often manifest low self-esteem, depressive symptomatology, anxiety, and decreased social competence (French, Story, & Perry, 1995; Jelalian & Saelens, 1999; Sjoberg, Nilsson, & Leppert, 2005; Strauss & Pollack, 2003; Vila et al., 2004). These psychosocial problems contribute to the overweight child’s maladjustment to the demands of increasing social interactions within the family and the environment (Mustillo et al., 2003; Van Vlierberghe & Braet, 2007; Young-Hyman et al., 2006; Zeller, Saelens, Roehrig, Kirk, & Daniels, 2004). Self-esteem in obese children may be dependent upon the accumulating effects of peer victimization and cultural and societal pressures to be thin. These effects may explain lower self-esteem in overweight and obese adolescents when compared with children younger than 10 years of age (Storch et al., 2007; Strauss, 2000). Likewise for depressive and anxiety symptomatology, White and Hispanic overweight youth from the 2003 National Survey on Children’s Health experienced increasing depression and anxiety as BMI increased (BeLue, Francis, & Colaco, 2009). Worries about behavioral competence and peer judgments become more prominent after 8 years of age when worries about physical well-being are superseded with worries about the social evaluations of the child’s peer group (Greco & Morris, 2005; Hebebrand & Herpertz-Dahlmann, 2009; Muris & van der Heiden, 2006). Primary Care Interventions Improving knowledge concerning healthy nutrition choices and the benefits of increased physical activity has been the mainstay of obesity intervention programs for children and families. Studies have demonstrated the benefits of physical activity on musculoskeletal and cardiovascular health, adiposity, self-concept, depressive symptoms, anxiety, and academic performance March/April 2012

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FIGURE. Healthy Choices Intervention conceptual model.

Increased Beliefs & Knowledge

Primary Care Healthy Choices Intervention (HCI)

Emotional and Behavioral Outcomes

Knowledge Acquisition Modeling Goal Setting Problem Solving Cue Recognition Restructured Negative Thoughts

Improved Self-Esteem Less Depressive and Anxiety Symptoms Improved Social Competence Healthy Nutrition and Physical Activity Choices and Behavior

(Berkey et al., 2000; Rowlands, Eston, & Ingledew, 1999; Sallis et al., 1997; Sibley & Etnier, 2003; Strauss, Rodzilsky, Burack, & Colin, 2001). Incorporating healthy family lifestyle education in conjunction with parenting-skills training has demonstrated weight loss (Golley, Magarey, Baur, Steinbeck, & Daniels, 2007). Unfortunately, few effective, feasible, and acceptable primary care interventions have been developed and tested (Jelalian, Wember, Bungeroth, & Birmaher, 2007). The active components included in the most comprehensive intervention programs for school-age children in other settings (e.g., schools, specialty clinics, and university research centers) have included parental involvement, nutritional education, and promotion of physical activity with an emphasis on decreased sedentary behaviors combined with cognitive behavior skills building (CBSB) and/or behavior modification. A recent extensive literature review utilizing Medline, CINAHL, PsychInfo, and PubMed search engines revealed only three intervention studies that focused the intervention on overweight and obese school-age children, ages 9 to 12 years, in a primary care setting (Cotton et al., 2006; Ewing et al., 2009; McCallum et al., 2007). It is apparent that researchers are just beginning to extend and translate previous research findings into “real world” clinical settings. Best evidence from prior intervention studies with children and families in all settings demonstrate that obesity intervention should comprehensively address the physical and psychosocial aspects of the problem and include interactive nutrition and physical activity knowledge building content in order to guide families to set goals and begin to take steps toward healthy lifestyle behaviors. 128

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THEORETICAL FRAMEWORK Cognitive Theory (CT) guided the development of the HCI Program tested in this study (Beck, 1964; 1976). CT is an integrated theory linking cognitive, affective, social, and developmental processes to behavior. A child’s thoughts and perceptions concerning interactions with others and the world are cognitively organized into schemas (e.g., an individual’s cognitions) that help process and organize complex information into meaningful patterns over time. According to Beck (1967), schemas are an individual’s organized cognitive representations about prior experiences that influence the expectancies and interpretations of new experiences. It is theorized that schemas about the self and others become negative and distorted through a gradual process of repetitively learned misconceptions or exposure to harmful environments during cognitive development (i.e., teasing and bullying) (Beck, 1967). Peer rejection, being liked to a lesser extent by peers, and being the recipient of peer bullying and aggression are often the social ramifications of being overweight as a child (Janssen, Craig, Boyce, & Pickett, 2004). Cognitive behavior skills building supports behavior change by increasing the individual’s evaluation of his or her own emotional responses and behavior; it also corrects misconceptions and guides the individual to choose more adaptive, realistic attitudes in response to negative schema, emotions, and behavior. The Figure depicts the pathway that was hypothesized after the introduction of the HCI Program regarding the psychosocial outcomes of self-esteem, depressive symptoms, anxiety, and social competence. The outcomes focusing on the improvement of the individual’s healthy nutrition and physical activity choices and Journal of Pediatric Health Care

TABLE 1. Demographic data (N = 17 children and 17 parents) Demographic variable Parent age (y) Parent weight (kg) Parent height (cm) Parent BMI Child age (mo) Child weight (kg) Child height (cm) Child BMI Child BMI % Child BMI z score

Mean

SD

Range

39.76 90.90 163.01 34.01 129.03 57.97 148.63 26.09 .960 1.91

7.92 23.39 6.42 7.56 15.19 10.55 8.76 3.13 .04 .42

28-56 60.87-145.60 151.76-173.99 23.79-51.80 108-151 40.19-77.20 133.40-163.20 21.11-31.38 .86-.99 1.08-2.43

BMI, body mass index; SD, standard deviation.

behavior also are shown. Guided by CT, the process of cognitive change begins with the introduction of the critical components of the HCI Program. METHODS Design A pre-experimental, one-group pre-/posttest design was conducted to test the feasibility and acceptability and preliminary effects of this new HCI and its protocol in pediatric primary care. Participants The sample included 36 overweight and obese children and their parents or guardians who were identified in TABLE 2. Demographic data represented as percentages (N = 17) Demographic variable Parent gender Male Female Child gender Male Female Parent race/ethnicity White Hispanic Child race/ethnicity White Hispanic Household income per year > $100,000 $80,000-$99,000 $60,000-$79,000 $40,000-$59,000 $20,000-$39,000 Parent education Did not finish high school Finished high school or general equivalency diploma Did some college or training after high school Finished college Master or doctorate

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Frequency

Percent

1 16

6 94

6 11

35 65

11 6

65 35

11 6

65 35

2 3 7 3 2

11.8 17.6 41.2 17.6 11.8

1 2

5.9 11.8

6

35.3

7 1

41.2 5.9

an urban primary care setting in a southwestern state. Of these identified and eligible children, 17 parentchild dyads (47%) consented and assented to take part in the study. The mean age of the children was 10 years, 7 months (SD = 15.1 months). The mean weight was 127.5 lb (SD = 23.21) or 57.97 kg (SD = 10.55), with a mean BMI percentile of .96 (SD = .04). The mean age of the parents or legal guardians was 39.8 years (SD = 7.9 years), with an age range of 28 to 56 years. The mean weight of the parent was 199.98 lb (SD = 51.46) or 90.91 kg (SD = 23.40), with a mean BMI of 34.01 (SD = 7.56). Tables 1 and 2 depict demographic data that more fully describe the participants in the study. All families provided their own transportation to the clinic or obtained transportation from family or friends in order to attend the face-to-face intervention sessions. Intervention Length and Content Children (and parents) received seven HCI Program weekly contacts: four personalized face-to-face clinic sessions alternated with three telephone sessions. The clinic intervention sessions took approximately 30 minutes to 1 hour. The telephone sessions took approximately 30 to 45 minutes, including time to speak to both the parent and child separately. The design of the intervention was adapted from the COPE/Healthy Lifestyles TEEN (Thinking, Emotions, Exercise and Nutrition) Intervention Program (Melnyk et al., 2006; Melnyk et al., 2007; Melnyk et al., 2009) and included the current Expert Committee recommendations on the management of obesity (Barlow & the Expert Committee, 2007). Intervention components included elements found to be effective in prior comprehensive intervention programs with overweight children (i.e., CBSB, increasing knowledge and beliefs, parental involvement, and psychosocial content) (Clark & Tiggemann, 2008; Johnston & Steele, 2007; Johnston, Tyler, & Foreyt, 2007; Kendall & Choudhury, 2003). The HCI Program content for each session is detailed in Table 3. After the first clinic intervention session, every subsequent clinic session began with March/April 2012

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TABLE 3. Healthy Choices Intervention weekly session content Session

Mode

Content

1 2 3 4 5 6 7

Clinic Telephone Clinic Telephone Clinic Telephone Clinic

Thinking-Feeling-Behaving triangle; habits; goal setting for nutrition, physical activity and positive thinking Identification and modification of negative thinking and emotion patterns; self-esteem; peer relationships Healthy nutrition and physical activity knowledge; cue recognition for unhealthy habits and thoughts Reading food labels and portion size distortion; over-coming barriers to goals with problem solving Physical activity and health; review of food diaries and pedometer logs to form goals or problem solve barriers Emotional, physical, and behavioral responses to stress; positive coping techniques; social case scenarios Putting in all together: review and discussion of entire program content

a review of the homework from the previous sessions in order to evaluate intervention adherence and reinforce content. Child and Parent Measures Child self-concept, anxiety, and depression were evaluated by self-report utilizing the Beck Youth Inventory II (2nd edition) (Beck, 2005; Beck, Beck, Jolly, & Steer, 2005). Three subscales (20 questions each) were utilized for this study, including the Self-Concept Inventory, Depression Inventory, and Anxiety Inventory. Cronbach’s a typically exceeds .86 (Beck et al., 2005). For this sample of children, the Cronbach’s a for the Self-Concept Inventory, Anxiety Inventory, and Depression Inventories was .94, .93, and .94, respectively. The Healthy Lifestyle Beliefs Scale (HLBS) (Melnyk & Small, 2004b) evaluates parent and children’s beliefs/ confidence about their ability to lead a healthy lifestyle. Parents respond to 16 items and children to 15 items on a 5-point Likert scale. Higher scores indicate stronger beliefs/confidence about the ability to engage in healthy lifestyle behaviors. Example items include: “I believe that I can reach the goals that I set for myself” and “I am certain that I can make healthy food choices.” This instrument was adapted for use with the schoolage child in this study. Cronbach’s a for the parent and child instruments with this sample was .73 and .77, respectively. The Healthy Choices Scale (HCS) (Melnyk & Small, 2004a) measures parent and child’s intention to make healthy choices concerning activities such as food selection, participation in physical activity, avoidance of sedentary activities such as television viewing, and decreasing stress. Participants respond to 16 items on a 5-point Likert scale. Higher scores indicate healthier lifestyle choices. Examples include: “I will exercise with my child (friends or parent)” and “I will set goals that I can reach.” This instrument was adapted for use with the school-age child in this study. Cronbach’s a in this sample were .65 for the parent and .86 for the child scales. Healthy lifestyle behaviors were measured with the Healthy Lifestyle Behaviors Scale developed for use in adolescent healthy lifestyle studies (Melnyk et al., 2006). Each of the 16 items measures current healthy lifestyles behavioral practices. Examples include: 130

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“I exercise with my child (or friends or parent)” and “I talk about my worries or stress every day.” Each item is rated on a 5-point Likert scale. Higher scores indicate more healthy lifestyles behaviors. The Healthy Lifestyle Behavior Scale was adapted for the school-age child in this study. Cronbach’s a for the instrument in this sample were .67 for the parent and .88 for the child scales. The Social Skills Rating System (SSRS) (Gresham & Elliot, 1990) is a 34-item (child) and a 55-item (parent) questionnaire that obtains information on the social skills, social problem behaviors, and academic problems of children as reported by the child and the parent. The parent evaluates the child on four social skills subscales and three problem behavior subscales. The child self-reports on four social skills subscales. For this sample of parents the Cronbach’s a was .90, and for this sample of children the Cronbach’s a was .83. The Activity Knowledge Questionnaire (AKQ) (Small & Melnyk, 2002) is a 12-item parent and eight-item child instrument that measures knowledge regarding physical activity. Examples of items include: “Exercise helps reduce stress and worries” and “Dancing is exercise.” Subjects respond by answering “yes,” “no,” or “don’t know.” Correct responses are totaled with higher scores indicating higher knowledge. A “don’t know” response is an incorrect response. The AKQ has been adapted for use with the school-age population. Cronbach’s a for the instrument in this parent sample was .52, and it was .65 in the child sample. The Nutrition Knowledge Questionnaire (NKQ) (Small & Melnyk, 2002) is a 20-item parent and 11-item child instrument containing questions about food nutritional information, portion sizes, eating habits, and healthy nutrition choices. Example items include: “Pretzels are higher in fat than potato chips” and “One serving size of meat should be the size of a deck of cards.” Subjects respond by answering “yes,” “no,” or “don’t know.” A “don’t know” response is an incorrect response. Correct responses are totaled with higher scores indicating higher knowledge. The NKQ has been adapted for use with the school-age population. For this sample of parents the Cronbach’s a was .83, and for this sample of children the Cronbach’s a was .73. The State-Trait Anxiety Inventory (STAI) (Spielberger, Gorsuch, & Lushene, 1977) is a self-report assessment of state and trait anxiety for adults. State anxiety reflects the Journal of Pediatric Health Care

individual’s reactions in specific situations. Trait anxiety refers to individual long-standing differences in reactions. This instrument has two 20-item scales. Internal consistency reliabilities for the A-Trait and A-State Scales range from 0.83 to 0.92. For this sample of parents the Cronbach’s a for Trait Anxiety was .94, and for State Anxiety it was .95. The Beck Depression Inventory (2nd edition) (BDIII) (Beck, Steer, & Brown, 1996) is a 21-item instrument assessing adult depression. Test-retest reliabilities with both college-age students and outpatients were .93. Parents’ BDI-II questionnaires were collected from intervention sites and scored promptly. Cronbach’s a for this sample of parents was .84. PROCEDURE Initiation of the study commenced after approval from the Institutional Review Board at Arizona State University. Children meeting the criteria for study participation (i.e., BMI $ 85th percentile; English speaking; no psychotic mental health disorder or developmental delay; no dietary or physical activity restrictions; and one parent or guardian willing to participate in all HCI sessions) were identified by four primary care providers from one pediatric office during a routine well and/or minor acute illness clinic visit. The investigator telephoned each identified and interested dyad and invited the parent and child to participate. At the first session, the child and parent were given and instructed in the use of a New Lifestyles Digiwalker (Model SW-200) pedometer. This brand of pedometer uses a built-in default for stride length. Self-monitoring records were discussed and, as practice, the child and parent entered that day’s food intake on his/her food diary with the interventionist’s assistance. In the succeeding weeks, the interventionist encouraged the child and parent to create nutrition, physical activity, and positive thinking goals for themselves utilizing motivational interviewing techniques. The parent and child were given notebooks with weekly workbook activities that reviewed session content for the child and introduced supplemental material for the parent. These weekly activities were to be completed at home prior to the next session. Analytical Strategy Preliminary analysis included descriptive statistics on all variables. The child’s BMI was calculated as (weight/height2)  703. The BMI z score was calculated from height, weight, gender, and age in months using parameters and formulas provided by the Centers for Disease Control and Prevention (National Center for Health Statistics, 2005). The BMI percentile was derived from the BMI z score using the normal distribution function in Microsoft Excel 2003. Summary scores were used in the analyses, which were calculated with data transformation functions within Statistical Package for the Social Sciences (verwww.jpedhc.org

sion 16.0) (SPSS, Inc., Chicago, IL). For parents and children completing the intervention, comparison of posttest to baseline measures using paired sample t tests determined whether the intervention demonstrated preliminary efficacy. Although inferential testing was conducted, the primary focus of the study was on assessing effect sizes. Initial effect sizes were calculated by subtracting the pre-test mean from the posttest mean and dividing the difference by the pooled standard deviation (Cohen, 1988). Determining effect size was necessary in order to (a) obtain an estimation of sample size for future larger studies and (b) determine the relative strength of the intervention. The criterion for statistical significance was set at .10 instead of the conventional .05 because of the small sample size in order to reduce the probability of type 2 errors. This is an acceptable approach to analyze data from pilot studies with small samples (Campbell, 2005; Cohen, 1994; Kraemer et al., 2003; Munro, 2005; Thompson, 2002). RESULTS Tables 1 and 2 describe the participants in the study. Each parent and child attended one baseline data collection session and four clinic intervention sessions alternated with three telephone sessions. One dyad (6%) dropped from the study after the second intervention session and one dyad (6%) dropped from the study after the third intervention session. Reasons given for study withdrawal included lack of time to attend the intervention sessions (reported by both participant dyads that dropped) and family demands Utilizing due to an extended quantitative and family member’s illness (reported by one dyad). open-ended Utilizing quantitaevaluations, tive and open-ended parents and evaluations, parents and children reported children reported that the HCI’s content that the HCI’s and delivery method content and (i.e., clinic and telephone) was highly acdelivery method ceptable and useful. (i.e., clinic and Interestingly, a few telephone) was children would not recommend the prohighly acceptable gram to their peers for and useful. fear of hurting a friend’s feelings by implying that they are “fat” or unhealthy. The difficulty in scheduling appointment times after school was noted by a number of parents, who suggested attending the program during the summer months and not over the winter holidays. The number of weeks required to complete the intervention ranged from 7 weeks to 13 weeks, with a mean March/April 2012

131

of 9.45 (SD = 2.2) weeks. No intervention sessions for any family were missed. If parents needed to reschedule, did not show up for an appointment, or were not home for the scheduled telephone call, the session was rescheduled and the intervention continued at the session the family was due for and continued until all seven sessions were completed. Approximately half of the families were able to finish the intervention within 9 weeks. The preliminary effects of the HCI Program on the child are reported in Table 4. For example, the children’s mean BMI percentile decreased significantly from .96 (SD = .04) to .94 (SD = .05). Although not statistically significant, a similar decrease was seen in the children’s mean depressive symptoms from Time 0 to Time 1, with a small to medium effect size of .38. Mean change in hours per day of video playing increased during the week by .14 hours, but video playing on the weekend decreased by .06 hours. It is clinically meaningful that although the results were not statistically significant, child beliefs, choices, self-concept, anxiety, and depressive symptomatology all demonstrated small effects after the intervention. The preliminary effects of the HCI Program on the parents are reported in Table 5. For example, the parents’ mean Beliefs significantly increased from Time 0 (64.82 [SD = 5.85] to Time 1 (68.47 [SD = 5.13]). Parent mean Behaviors also increased significantly from Time 0 to Time 1 with a large Cohen’s d effect size. Likewise, mean Nutrition knowledge significantly increased from Time 0 to Time 1, also with a large Cohen’s d effect size. Parent mean Choices essentially remained the same from Time 0 to Time 1, and this result was not statistically significant. DISCUSSION The evaluation questionnaire responses, intervention logs, attendance and fidelity records, and interventionist field note documentations of the HCI demonstrated that parents and children found the program to be informative and helpful. The most valuable open-ended statements included comments centering on principal program themes and content (e.g., positive thinking, portion sizes, food choices, and self-esteem) and CBSB (e.g., setting goals, increasing communication, recognition of unhealthy habits, awareness of stress responses, and interconnection of thoughts and actions). Both parents and children commented on the evaluation questionnaires and during the sessions about the amount of written homework that was required for monitoring of thinking, physical activity, and food intake and how this was difficult to maintain. The issue of participant burden in CBSB interventions arises because the activities the children and parents perform are used to enhance the cognitive change process. Self-reflection and self-monitoring are integral components of this form of intervention. It has not been determined in prior intervention research what amount 132

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of adherence to these activities is most beneficial. Many studies have documented the difficulties researchers have encountered in obtaining full participation in planned CBSB activities (Brehm, Rourke, Cassell, & Sethuraman, 2003; Germann, Kirschenbaum, & Rich, 2007; Herrera, Johnston, & Steele, 2004; Levine, Ringham, Kalarchian, Wisniewski, & Marcus, 2001; Melnyk et al., 2007). What is important to note is that this CBSB intervention, with a small sample size, demonstrated beneficial effects despite the fact that the participants did not complete all the written aspects of the program. After completing the HCI, children demonstrated increases in physical activity and nutrition knowledge scores and increases in their healthy lifestyle behaviors. The increases were statistically significant and clinically meaningful. The very large effect sizes seen in this study (Table 4) suggest that the intervention was particularly successful in changing these target behaviors. In addition, small to medium effect sizes were seen on the child beliefs and choices scales after the HCI Program (Table 4). CT supports these findings and begins to answer questions about the influence of psychological and social factors on the overweight and obese child’s ability to make behavior change (Luttikhuis et al., 2009). The theory predicts that the HCI would strengthen and increase not only the children’s knowledge about healthy lifestyles but also the children’s beliefs about their ability to lead a healthy lifeAfter completing style. The theory does not predict, however, the HCI, children that such a brief interdemonstrated vention would affect increases in weight loss. Yet the child’s mean BMI perphysical activity centile significantly and nutrition decreased from T0 to knowledge scores T1 (p = .000; Cohen’s d = .38). It is an imporand increases in tant finding that the their healthy child’s healthy lifestyle lifestyle behaviors. behaviors increased. A child’s belief in his or her ability to adopt a healthy lifestyle may mediate this weight change. Therefore these measured outcomes should be tested further in a future large-scale trial (Kraemer, Wilson, Fairburn, & Agras, 2002; Painter, Borba, Hynes, Mays, & Glanz, 2008). Another explanation for this finding may reflect either the parent’s extrinsic control over the child’s ability to make unhealthy choices (i.e., environmental control and parental disapproval over unhealthy food/ inactivity) or the child’s own improved healthy lifestyle behaviors, or both. The children’s mean self-concept score increased from T0 to T1, and mean anxiety and depressive symptoms Journal of Pediatric Health Care

TABLE 4. Child preliminary effects of the HCI (N = 15) Variable Weight (kg) Height (cm) BMI BMI percentile BMI z score Beliefs Choices Behaviors Activity Nutrition Self-concept Anxiety Depression Social skills, cooperation Social skills, assertion Social skills, empathy Social skills, self-control Social skills, total Parent report of child activity choice TV hours/day TV hours/day on weekend Video playing hours per day Video playing hours/day on weekend Child activity level choice Activity 60 min/day

Mean T0

SD T0

Mean T1

SD T1

Cohen’s d

57.97 148.63 26.09 .96 1.91 62.88 67.35 56.53 5.00 6.35 49.94 52.59 50.47 15.65 14.71 16.94 13.29 111.71 1.88

10.55 8.76 3.13 .04 .42 6.28 7.87 12.34 1.22 2.26 12.28 13.77 13.95 2.87 2.78 2.38 3.22 15.74 .99

57.51 150.88 25.08 .94 1.73 65.93 70.27 71.00 7.27 10.00 53.00 49.40 45.93 15.27 15.07 16.20 13.07 110.07 2.60

11.52 9.32 3.32 .05 .45 8.84 9.56 6.38 .59 .93 11.65 12.10 9.73 4.46 3.26 3.43 4.23 19.71 1.30

.04 .25+ .31+ .38+ .42+ .40+ .33+ 1.5+++ 2.5+++ 2.3+++ .26+ .25+ .38+ .10 .12 .26+ .06 .09 .63++

2.94 2.94 1.53 2.06

1.14 1.48 1.11 10.55

2.33 2.67 1.67 2.00

.98 1.11 .90 .93

2.06 2.47

8.76 3.13

2.07 3.60

1.39 2.06

Mean diff

CI low

CI upper

.46 2.24 1.01 .02 .18 3.05 2.91 14.47 2.27 3.65 3.06 3.19 4.54 .38 .36 .74 .23 1.64 .72

.20 2.12 .52 .01 .09 5.80 5.33 18.75 2.66 4.63 9.35 2.85 1.58 .50 1.65 .05 1.05 3.41 1.11

.62 1.50 .93 .02 .16 1.00 1.86 7.51 1.74 2.83 2.95 5.11 7.58 2.10 1.38 2.19 1.85 10.74 .09

.57++ .21+ .15 .05

.61 .27 .14 .06

.14 .71 .82 .59

.01 .51++

.01 1.13

.39 2.07

t

df

p

.905 10.311 6.225 4.555 6.475 1.244 .849 4.116 8.401 7.299 .916 .502 1.153 1.084 .155 1.677 .487 .913 2.073

14 14 14 14 14 14 14 14 14 14 14 14 14 14 14 14 14 14 14

.381 .000*** .000*** .000*** .000*** .234 .410 .001*** .000*** .000*** .375 .624 .268 .297 .879 .116 .634 .377 .057*

.94 .84 .29 .72

1.309 .151 .845 .180

14 14 14 14

.212 .882 .413 .860

.25 .19

.367 2.125

14 14

.719 .052*

BMI, body mass index; CI, confidence interval; HCI, Healthy Choices Intervention; SD, standard deviation. + Small effect size. ++ Medium effect size. +++ Large effect size. *.10 significance level. ** .05 significance level. ***.01 significance level.

scores decreased. Although not statistically significant, there were small to medium positive effects after the intervention. The size of these changes may have been influenced by the brief length and low intensity of the HCI intervention. Comprehensive multi-component interventions may require longer interventions in order to see positive effects, especially when the inclusion of so many important intervention components has been found to be beneficial in prior research. Although the intervention was targeted to the child, the parent actively participated in the content of all workbook activities and may have received benefit from the CBSB techniques. After completing the HCI, parent mean physical activity and nutrition knowledge scores significantly increased (Table 5). Parents’ mean beliefs scores increased significantly, demonstrating a medium to large effect size. This finding indicates an increase in parents’ beliefs in their ability to lead a healthy lifestyle. Even though the sample size was insufficient to test for mediation, this finding for this CBSB intervention is encouraging because beliefs and knowledge are contended to positively influence the measured outcomes. www.jpedhc.org

Parents mean healthy lifestyle behavior scores also demonstrated statistically significant increases from T0 to T1. As theorized and seen in previous research (Melnyk et al., 2006; Melnyk et al., 2007; Melnyk et al., 2009), the mechanism of behavior change may be mediated by parental beliefs in their ability to make changes and lead a healthy lifestyle. What would be interesting to pursue in future research is to try to determine at what point in the intervention an increase in beliefs began to change behavior. With a larger sample size, the study design could add an evaluation of beliefs at midpoint in the intervention or after certain didactic information is presented. Parents mean intention to make healthy choices scores decreased slightly at T1. Parents were fully aware that they were asked to participate in the study because the child was overweight or obese. At the initiation of any program to change unhealthy behavior, individuals may be overly optimistic or have full intention to make all necessary changes to make the program successful. It is important that goal setting for the parent and child not be extrinsically mandated. The child and parent March/April 2012

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TABLE 5. Parent preliminary effects of the HCI (N = 15) Variable

Mean T0

SD T0

Mean T1

SD T1

Cohen’s d

Weight (kg) BMI Beliefs Choices Behaviors Activity Nutrition State anxiety Trait anxiety BDI Parent SSRS, cooperation Parent SSRS, assertion Parent SSRS, responsibility Parent SSRS, self-control Parent SSRS, standard score Parent SSRS, externalizing Parent SSRS, internalizing Parent SSRS, hyperactivity Parent problem standard score Parent report of child’s TV

90.91 34.01 64.82 75.53 55.65 10.24 16.00 62.12 57.88 13.88 9.94 15.59 13.59 11.65 94.35 4.82 5.35 4.47 107.3 3.06

23.40 7.56 5.85 3.34 7.03 1.52 3.54 25.97 12.89 8.04 3.51 2.15 2.45 4.05 14.19 2.96 3.35 2.83 18.18 1.60

90.62 33.66 68.47 73.87 69.40 11.80 19.60 50.07 58.73 12.87 11.20 15.80 14.00 12.73 96.13 3.47 5.07 3.93 103.1 2.47

25.79 8.30 5.13 6.10 7.92 .41 .63 9.91 12.71 10.59 3.51 1.93 2.17 3.22 14.50 2.82 3.28 3.19 19.28 1.55

.01 .04 .66++ .35+ 1.8+++ 1.6+++ 1.7+++ .67++ .07 .11 .36+ .10 .18 .29+ .12 .47+ .09 .18 .22+ .38+

Mean diff .28 .35 3.64 1.66 13.75 1.56 3.60 12.05 .85 1.02 1.26 .21 .41 1.09 1.78 1.36 .29 .54 4.22 .59

CI low .48 .19 5.81 1.53 17.27 2.42 5.64 1.24 18.09 1.59 .31 .82 1.26 43.94 5.41 .45 .85 .34 2.20 .19

CI upper .94 .39 .32 5.00 8.99 1.18 2.36 17.96 .44 3.19 2.85 .95 .73 37.39 3.54 2.48 1.78 1.54 12.73 1.14

t .57 .60 1.97 .94 5.59 5.08 4.30 2.02 1.85 .59 1.41 .133 .47 21.85 .37 2.54 .62 1.13 1.24 2.47

df

p

14 14 14 14 14 14 14 14 14 14 14 14 14 14 14 14 14 14 14 14

.578 .560 .069* .365 .000*** .000*** .001*** .063* .086* .565 .80 .896 .644 .000*** .719 .023** .543 .28 .23 .027*

BDI, Beck Depression Inventory; BMI, body mass index; CI, confidence interval; HCI, Healthy Choices Intervention; SD, standard deviation; SSRS, social skills rating system. + Small effect size. ++ Medium effect size. +++ Large effect size. *.10 significance level. **.05 significance level. ***.01 significance level.

benefit the most from motivational assistance that helps them recognize their own unhealthy behaviors and encourages problem solving in order to develop goals for healthy lifestyle behaviors. The HCI effect on the mean parent scores for State Anxiety and depression demonstrated decreases from T0 to T1 (Table 5). The statistically significant decrease in State Anxiety may reflect the parent’s greater understanding and ability to incorporate the CBSB techniques of stress reduction (i.e., meditation and deep breathing) and the daily positive thinking exercises into their everyday lives. The interventionist noted that a number of parents stated that it was helpful to have someone to talk to about their barriers to leading a healthy lifestyle. The time, attention, and concern from the interventionist may have provided treatment effect. Controlling for the interventionist’s time and attention in a future randomized controlled trial will help to control for this influence. It is well documented that parental depression is a risk factor for increased depressive symptomatology in the child (Clarke et al., 2001; Compton et al., 2004; Dattilio, 2005; Freres, 2002). Parents in this study were predominately overweight, obese, or morbidly obese (94%). The risk for the child to become overweight or obese increases with parent obesity (Whitaker, 134

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Wright, Pepe, Seidel, & Dietz, 1997; Whitaker, 2004), and previous research has documented that parent’s weight change predicts child’s weight change in obesity treatments that are family based (Wrotniak, Epstein, Paluch, & Roemmich, 2005). Parents did not lose weight in this study, which may indicate that the parent provided healthy stimulus control in the environment for the child but may not have succeeded themselves with adopting healthier lifestyles. Parental reports of children’s total and subscale scores on social competence revealed a statistically significant mean increase in the child’s self-control after participating in the intervention (Table 5). Many of the case scenarios discussed in the HCI centered around social situations where the child needed to make decisions, recognize his/her own emotions and the emotions of others, and problem solve when children in the case scenarios were confronted with barriers to a healthy lifestyle. Parental reports of children’s externalizing problem behaviors demonstrated a significant mean decrease and a medium effect. The HCI focused on communication and overcoming barriers, and this result may reflect the child’s increased ability to recognize and deal effectively with negative emotions after practicing the HCI CBSB techniques and problem-solving techniques. Journal of Pediatric Health Care

By parent report, there was a significant mean decrease, with medium effect size, in the amount of television that the child watched each day (Table 5). The mean number of hours of television viewing each day at T0 was 3.06 (SD = 1.6) hours and, after the HCI, it was 2.47 (SD = 1.55). Children reported a statistically significant increase (medium effect size) in the mean number of days that they exercised at least 60 minutes per day, suggesting that the HCI positively influenced the physical activity of the children in the study. The HCI aimed to decrease sedentary behaviors by encouraging children to spend 2 hours or less each day on “screen” activities. Implications for Clinical Practice Best evidence indicates that interventions for the overweight and obese child include the comprehensive components of nutrition, physical activity, CBSB or behavioral modification, parent involvement, and psychosocial content (Luttikhuis et al., 2009; Whitlock, O’Connor, Williams, Beil, & Lutz, 2008). Expert Committee recommendations for primary care providers have been formulated by examining best evidence, but these recommendations are clinical opinions and have not been evaluated empirically in “real world” clinical practice (Barlow & the Expert Committee, 2007). Primary care providers are becoming informed about how to identify and assess the overweight and obese child but now need to know what to do (Moore et al., 2003). The results of this pilot study begin to provide support for the Expert Committee’s recommendations. No systematic reviews of telephone interventions for physical activity, nutrition, or cognitive change in children and adolescents have been published. In the adult literature, Eakin and colleagues (Eakin, Lawler, Vandelanotte, & Owen, 2007) have evaluated telephone interventions for physical activity and dietary change and found this method of delivery to be effective. Trying to deliver new content over the telephone, even though the parent and child had the detailed information in front of them in their notebooks, was difficult. Telephone sessions in future studies should be utilized for positive feedback, discussion of barriers, encouragement, and review of prior intervention content, as was done in the study by Saelens and colleagues (Saelens et al., 2002). There were no appreciable mean changes in the number of servings of vegetables that the child consumed per day. On the child and parent food diaries, it was noted that few families routinely serve vegetables to their children. The intervention dose on nutritional healthy choices and the Traffic Light Diet can be strengthened in the future as was recently done by Epstein, Paluch, Beecher, and Roemmich (2008). Closer evaluation of food diary information can be utilized to encourage the children to work toward goals of increaswww.jpedhc.org

ing fruit and vegetable consumption on a daily basis. Assistance from a nutritional specialist in planning the nutritional components of the HCI in future research will enhance the child and parent’s understandings of their nutritional needs. Limitations and Recommendations for Future Research The findings from this study should be interpreted in the context of several methodological limitations that may have contributed to the results. The one group’s pre-/posttest design weakens the study’s internal validity. The small convenient sample size does not allow for the results to be generalized. Specifically, in-depth statistical analysis of subgroup differences (i.e., gender, age, and ethnicity) also could not be analyzed because of the small sample. Investigator bias also could have been introduced into the study because the first author was the only interventionist. Another potential limitation concerns the utilization of written self-report questionnaires. While self-report data can obtain valuable information from an individual’s perspective, individuals also can bias their responses to appear more socially desirable (Paulhus & Reid, 1991). In this study, the reliability and validity of selected instruments to measure the outcomes of interest was an important consideration, as was the examination of the data for extreme and moderacy response styles. Height and weight data were both quantitatively measured. Pedometers were primarily utilized as environmental cue recognition and goal-setting CBSB activities, even though the parent and child recorded daily steps and turned in pedometer logs to the interventionist every 2 weeks. Although no cost analysis was done within this pilot study, this important consideration must be factored into planning for the adoption of any healthy lifestyles intervention program into primary care practice (Glasgow, 2008). There is no doubt that there are more than enough children in the community who could benefit from the HCI, but the program will not be adopted if primary care providers cannot be reimbursed for the time that would be required to deliver obesity interventions. The American Academy of Pediatrics (AAP) has developed an insurance coding fact sheet for primary care providers that can increase the providers’ ability to receive appropriate insurance reimbursement for the care they deliver to overweight and obese pediatric patients and their families (AAP, 2004). Providing ongoing care within the pediatric medical home will optimize the child’s long-term health, which ultimately will decrease health care costs over the child’s lifespan (Janicke et al., 2009; Wang, Denniston, Lee, Galuska, & Lowry, 2010). It will be beneficial to plan a cost analysis of the HCI in a future randomized controlled trial. March/April 2012

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CONCLUSION Identifying the child as overweight or obese and providing behavioral counseling within brief primary care office visits has not yet been routinely instituted as recommended by the Expert Committee on child and adolescent overweight and obesity (Barlow & Dietz, 1998; Barlow & the Expert Committee, 2007). Few prior theory-based intervention studies targeting the overweight and obese school-age child have This study is one of been conducted in the first to a primary care setting. demonstrate that As a result, overweight and obesity intervena comprehensive tion programs offered theory-based in pediatric primary CBSB intervention care settings such as the HCI are long overto address the due (Teutsch & Briss, problems of 2005). This study is school-age one of the first to demonstrate that a compreoverweight and hensive theory-based obesity is feasible CBSB intervention to and acceptable in address the problems of school-age overthe “real world” of weight and obesity is pediatric primary feasible and acceptable care. in the “real world” of pediatric primary care. It is evident that 9- to 12-year-old overweight and obese children and their parents are capable of and willing to participate fully in a CBSB intervention within the primary care setting. Supported by CT, the HCI Program demonstrated promising results with overweight and obese children and their parents in pediatric primary care.

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Strauss, R. S. (2000). Childhood obesity and self-esteem. Pediatrics, 105(1), e15. Strauss, R. S., & Pollack, H. A. (2003). Social marginalization of overweight children. Archives of Pediatrics & Adolescent Medicine, 157(8), 746-752. Strauss, R. S., Rodzilsky, D., Burack, G., & Colin, M. (2001). Psychosocial correlates of physical activity in healthy children. Archives of Pediatrics & Adolescent Medicine, 155, 897-902. Teutsch, S., & Briss, P. (2005). Spanning the boundary between clinics and communities to address overweight and obesity in children. Pediatrics, 116, 240-241. Thompson, B. (2002). “Statistical,” “practical,” and “clinical”: How many kinds of significance do counselors need to consider? Journal of Counseling and Development, 80(1), 64-71. U.S. Preventive Services Task Force. (2005). Screening and interventions for overweight in children and adolescents: Recommendation statement. Pediatrics, 116(1), 205-209. Van Vlierberghe, L., & Braet, C. (2007). Dysfunctional schemas and psychopathology in referred obese adolescents. Clinical Psychology & Psychotherapy, 14(5), 342-351. Vila, G., Zipper, E., Dabbas, M., Bertrand, C. P. H., Robert, J. J., Ricour, C., & Mouren-Simeoni, M. C. (2004). Mental disorders in obese children and adolescents. Psychosomatic Medicine, 66(3), 387-394. Wang, L., Denniston, M., Lee, S., Galuska, D., & Lowry, R. (2010). Long-term health and economic impact of preventing and reducing overweight and obesity in adolescence. Journal of Adolescent Health, 46, 467-473. Whitaker, R. C. (2004). Mental health and obesity in pediatric primary care: A gap between importance and action. Archives of Pediatrics & Adolescent Medicine, 158(8), 826-828. Whitaker, R. C., Wright, J., Pepe, M., Seidel, K., & Dietz, W. (1997). Predicting obesity in young adulthood from childhood and parental obesity. New England Journal of Medicine, 337, 869-873. Whitlock, E. P., O’Connor, E., Williams, S., Beil, T., & Lutz, K. (2008). Effectiveness of weight management programs in children and adolescents (Evidence Report/Technology Assessment No. 170 No. 08-E014). Rockville, MD: Agency for Healthcare Research and Quality. Whitlock, E. P., Orleans, C. T., Pender, N., & Allan, J. (2002). Evaluating primary care behavioral counseling interventions: An evidence-based approach. American Journal of Preventive Medicine, 22(4), 267-284. Whitlock, E. P., Williams, S. B., Gold, R., Smith, P. R., & Shipman, S. A. (2005). Screening and interventions for childhood overweight: A summary of evidence for the US preventive services task force. Pediatrics, 116(1), e125-e144. Wrotniak, B., Epstein, L., Paluch, R., & Roemmich, J. (2005). The relationship between parent and child self-reported adherence and weight loss. Obesity Research, 13(6), 1089-1096. Young-Hyman, D., Tanofsky-Kraff, M., Yanovski, S. Z., Keil, M., Cohen, M. L., Peyrot, M., & Yanovski, J. A. (2006). Psychological status and weight-related distress in overweight or at-risk-foroverweight children. Obesity, 14(12), 2249-2258. Zeller, M., Saelens, B., Roehrig, H., Kirk, S., & Daniels, S. (2004). Psychological adjustment of obese youth presenting for weight management treatment. Obesity Research, 12(10), 1576-1586.

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