A Virtual Childhood Obesity Collaborative: Satisfaction With Online Continuing Education

ARTICLE

A Virtual Childhood Obesity Collaborative: Satisfaction With Online Continuing Education Bonnie Gance-Cleveland, PhD, RNC, PNP, FAAN, Heather Aldrich, PhD, Danielle Dandreaux, PhD, Keri Bolton Oetzel, PhD, & Sarah Schmiege, PhD ABSTRACT Introduction: This descriptive study evaluated school-based health center (SBHC) providers’ satisfaction with Webbased continuing education as part of a virtual childhood obesity intervention. Bonnie Gance-Cleveland, Loretta C. Ford Endowed Chair, College of Nursing, University of Colorado, Aurora, CO. Heather Aldrich, Professional Research Coordinator, College of Nursing, University of Colorado, Aurora, CO. Danielle Dandreaux, Program Director, Center for Improving Health Outcomes in Children, Teens, and Families, College of Nursing and Health Innovation, Arizona State University, Phoenix, AZ. Keri Bolton Oetzel, Independent Consultant, Raglan, New Zealand. Sarah Schmiege, Assistant Research Professor, Department of Biostatistics and Informatics, University of Colorado, Aurora, CO. This project was supported by grant number R18HS018646 from the Agency for Healthcare Research and Quality. The content is solely the responsibility of the authors and does not necessarily represent the official views of the Agency for Healthcare Research and Quality.

Method: Thirty-six participants from 24 SBHCs in six states participated in the training modules. Modules were divided into four learning sessions, with a total of 17 training modules. Participants completed satisfaction surveys after each module, as well as an overall survey at the end of the training. Questions were rated on a 4-point Likert scale (4 = strongly agree, 3 = agree, 2 = disagree, 1 = strongly disagree). Results: Participation in the first two learning sessions was higher than the last two. Provider satisfaction of training modules by question type and content area was quite high (m = 3.66-3.33). Overall satisfaction means ranged from 3.76 to 3.24. Many providers also reported plans to make changes in their practice after completing the training. Discussion: This study demonstrated that a virtual childhood obesity collaborative is an acceptable delivery method for continuing education. J Pediatr Health Care. (2015) 29, 413-423.

KEY WORDS Virtual learning collaborative, Web-based continuing education, childhood obesity, quality improvement, school-based health centers

Conflicts of interest: None to report. Correspondence: Bonnie Gance-Cleveland, PhD, RNC, PNP, FAAN, College of Nursing, University of Colorado Anschutz Medical Campus, 13120 E 19th Ave, Aurora, CO 80045; e-mail: [email protected]. 0891-5245/$36.00 Copyright Q 2015 by the National Association of Pediatric Nurse Practitioners. Published by Elsevier Inc. All rights reserved. Published online March 14, 2015. http://dx.doi.org/10.1016/j.pedhc.2015.01.006

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In the United States, it is estimated that 34.2% of children 6 to 11 years of age are overweight or obese (body mass index [BMI] $ 85th percentile) and 17.7% are obese (BMI $ 95th percentile; Ogden, Carroll, Kit, & Flegal, 2014). Childhood obesity is associated with being overweight or obese as an adult (Singh, Mulder, Twisk, van Mechelen, & Chinapaw, 2008a) and having increased risk for psychological disorders, hyperlipidemia, diabetes, and other long-term health consequences (Biro & Wien, 2010; Reilly & Kelly, 2011; September/October 2015

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Strauss & Pollack, 2003). Significant race/ethnicity health disparities exist in the prevalence of childhood obesity and related chronic conditions, with 38.1% of non-Hispanic Black and 46.2% of Hispanic children classified as overweight or obese compared with 29.4% of non-Hispanic White children aged 6 to 11 years (Ogden et al., 2014). Socioeconomic status is also associated with obesity-related health disparities (Ogden, Lamb, Carroll, & Flegal, 2010; Singh, Kogan, Van Dyck, & Siahpush, 2008b; Singh, Siahpush, & Kogan, 2010; Wang & Zhang, 2006). School-based health centers (SBHCs) have been established to provide care to poor, vulnerable children, including those of ethnic minority groups. SBHCs— that is, clinics housed in or linked to a school—provide integrated care with comprehensive medical, mental health, social services, and sometimes dental health services on the school campus, making this an ideal setting for reaching persons most affected by obesity-related health disparities (Keeton, Soleimanpour, & Brindis, 2012). According to the most recent survey by the School-Based Health Alliance, there are 1,930 SBHCs in the United States (Lofink et al., 2013). SBHCs have been shown to positively influence a variety of physical and mental health outcomes for children and adolescents including immunizations, oral health, asthma, reproductive health, health promotion, and illness prevention through increased access to care (Keeton et al., 2012). Recognizing obesity as a national concern and the need for practical guidance for providers, professional organizations have convened experts to review the evidence and develop guidelines aimed at the prevention, assessment, and treatment of overweight in children and adolescents (Barlow, 2007; National Association of Pediatric Nurse Practitioners [NAPNAP], 2006; National Heart, Lung, and Blood Institute, 2005). Experts recognized that the traditional prescriptive, acute care approach was not working to treat this epidemic. Therefore, a family-centered focus, including motivational interviewing (MI) and use of the Chronic Care Model (CCM), is encouraged to promote healthy weight in children (Barlow, 2007; NAPNAP, 2006). Despite expert guidelines suggesting use of BMI percentile to assess for overweight/ obesity, fewer than 50% of providers reported using BMI percentile for diagnosing overweight or obesity in their patients (Small, Anderson, Sidora-Arcoleo, & Gance-Cleveland, 2009). Dissemination of guidelines typically has not changed provider behavior, and it has been shown that knowledge of guidelines is not associated with adherence (Cook, Weitzman, Auinger, & Barlow, 2005; Dorsey, Wells, Krumholz, & Concato, 2005; Mabry et al., 2005; Mazur et al., 2013; Rausch, Perito, & Hametz, 2011; Sharifi et al., 2013). Web-based training is gaining in popularity for delivering continuing education to health care providers. A 414

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synthesis of 11 systematic reviews and meta-analyses found health care providers to be satisfied with computer-mediated learning, including Web-based training (Militello, Gance-Cleveland, Aldrich, & Kamal, 2014). Benefits of Web-based training include flexibility, individualized learning, accommodation of different learning styles, and consistent educational delivery with reduced instructional burden, Web-based while challenges are training is gaining in often related to techpopularity for nology access or proficiency (Militello et al., delivering 2014). Interactive continuing Web-based learning education to health appears to be the most effective, using casecare providers. based scenarios, links to practice tools, and multi-component interventions over time (Militello et al., 2014). Additionally, a systematic review of interventions to improve primary care screening found that successful interventions emphasized collaborative learning, office-systems changes, and tracking progression over time, but few of the studies focused on followup (Van Cleave et al., 2012). CONCEPTUAL FRAMEWORK: HEALTH DISPARITIES COLLABORATIVE AND CCM The framework that guides this study is the Health Disparities Collaborative, which incorporates the CCM (Figure 1). This approach to care is an innovative, data-driven, public health partnership that has improved care for chronic diseases through improved health care delivery systems emphasizing the use of computer information systems and implementation of evidence-based practice (Martin, Larsen, Shea, Hutchins, & Alfaro-Correa, 2007). The CCM is a synthesis of evidence-based system changes to guide quality improvement (QI) and disease management activities (Wagner, 1998). The goal of the collaborative was rapid QI through the Institute for Healthcare Improvement’s Breakthrough Series methodology, the CCM, and learning sessions (Chin et al., 2004). The Breakthrough Series process promotes QI through collaborative learning strategies with quarterly learning sessions, dialogue, process reports, and feedback. Monthly conference calls provide case coaching, progress reports, descriptions of rapid Plan-Do-Study-Act (PDSA) cycles, and reports of adherence to guidelines. At the learning sessions, team members learn QI techniques and share lessons learned. The CCM is a synthesis of evidence-based system changes that might be used to guide QI and disease management activities (Wagner, 1998). The American Medical Association obesity recommendations suggest Journal of Pediatric Health Care

FIGURE 1. The Chronic Care Model.

BMI% = body mass index percentile; BP% = blood pressure percentile; HSK = HeartSmartKids (decisionsupport system); MI = motivational interviewing. Adapted with permission from Jacobson and GanceCleveland (2011). This figure appears in color online at www.jpedhc.org. the use of the CCM to guide care for overweight/obese children (Barlow, 2007). The model includes practice changes to provide the family with self-management support using relationship-focused methods such as MI; provider decision support for evidence-based care; delivery-system redesign to promote better care and follow-up; and clinical information systems to provide data to evaluate the progress made toward meeting goals. Indirect evidence from the National Health Disparities Collaboratives on Asthma, Diabetes, and Depression suggests that practice-based changes made at the system level will improve patient outcomes (Bodenheimer, 2003; Bodenheimer, Wagner, & Grumbach, 2002a, 2002b; Bray et al., 2005; Hupke, Camp, Chaufournier, Langley, & Little, 2004; McCullough, Davis, Austin, & Wagner, 2004; Norris & Olson, 2004). The proposed model recognizes that children live in the context of their family, school, and community and that culture and environment have an impact on the child’s health. The collaborative approach includes providers advocating for community and environmental changes to promote healthier environments. Cumulative evidence supports the integrated framework for practice improvement, with findings suggesting that use of the collaborative, including the CCM, leads to improved patient care and better health outcomes (Coleman, Austin, Brach, & Wagner, 2009). A systematic review www.jpedhc.org

of interventions to improve primary care screening found that successful interventions emphasized the collaborative learning, office-systems changes, and tracking progression over time, but few of the studies focused on follow-up, an area that needs attention (Van Cleave et al., 2012). Application of the breakthrough series approach to QI and the CCM in the study involved conducting a practice self-assessment, training staff on obtaining and documenting BMI and blood pressure, counseling children and their families using recommendations, evaluating practice for adherence to guidelines using a continuous QI process, and advocating for environmental changes. The purpose of this descriptive study was to evaluate providers’ satisfaction with Web-based continuing education regarding recommendations for the prevention and treatment of childhood obesity. It is part of a larger comparative effectiveness, randomized controlled trial of Web-based training with and without health information technology decision support on providers’ implementation of the guidelines in SBHCs serving children 5 to 12 years of age. METHODS Study Design The study consisted of the examination of survey results pertaining to provider satisfaction with Web-based continuing education regarding the obesity guidelines. Recruitment of a geographically diverse sample from a nationally representative group of providers was facilitated by partnerships with the National Assembly of School-based Health Centers (now the School-based Healthcare Alliance) and the National Association of Pediatric Nurse Practitioners. Electronic flyers were sent to providers in SBHCs through each national organization. The principal investigator conducted a telephone screening with interested participants until 24 SBHCs (four centers in six states—Arizona, Colorado, Michigan, New Mexico, North Carolina, and New York) were recruited. Human subject approval was obtained from each of the SBHCs and informed consent was obtained from each provider prior to the initiation of the study (Gance-Cleveland, Dandreaux, Aldrich, & Kamal, 2015). Web-based Training Intervention The Web-based training was delivered using Ning (www.ning.com), a social networking site that can be used to create a custom online community. Ning was chosen as the platform for this training because it integrates social networking and community building with a password-protected Web site, in addition to being scalable, flexible, and customizable. Training modules were first developed in PowerPoint (www.office. microsoft.com), where they were transformed using Adobe Presenter (www.adobe.com/products/ presenter) into engaging multimedia experiences by adding narration, animations, interactivity, quizzes, September/October 2015

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TABLE 1. Training modules listed by content area and learning session Content area Guidelines

LS1

Health disparities Chronic Care Model

LS1 LS1 LS2

Motivational interviewing

LS1 LS2

Advocacy Culturally sensitive care Virtual posters

LS3 LS3 LS4

a

Module titles

na

Overview Laboratory Screening Physical Activity Recommendations Nutrition Recommendations Health Disparities Collaborative Approach to Quality Improvement Introduction Clinical Information Systems Decision Support Delivery System Redesign Self-Management Support Introduction Assessing Readiness Values Identification Implementing Motivational Interviewing in Practice Be Our Voice Cultural Competency: Providing Culturally Sensitive Care Summarizing Practice Changes

33 29 29 26 30 31 26 24 26 27 30 29 27 28 6 18 10

Learning session

The number of participants who completed each module (total n = 36).

and software simulations. The training modules were grouped into four learning sessions (LSs; Table 1). The four LS topics were Obesity Care Guidelines (LS1), Advanced MI and CCM for Childhood Obesity (LS2), Community Collaboration and Partnerships (LS3), and Summarizing Practice Changes (LS4). Each LS included (1) self-paced, interactive, voiced PowerPoint presentations with case-based scenarios completed prior to (2) monthly conference calls, case coaching, and follow-up discussion, and (3) a virtual eLearning community for ongoing communication and sharing of resources. Consistent with recommendations in the literature, the Web-based training was case-based and interactive, included instructional design expertise and attention to Web usability (Beno, Hinchman, Kibbe, & Trowbridge, 2005; De Bourdeaudhuij, Stevens, Vandelanotte, & Brug, 2007; Joseph et al., 2007; Kroeze, Werkman, & Brug, 2006; Militello et al., 2014; Porter, Cai, Gribbons, Goldmann, & Kohane, 2004). The sessions were also designed to accommodate various learning styles, were oriented to busy professionals with limited time, and provided ongoing technical support. The Ning social networking site included an eLearning community with a chat room where participants could pose questions, share resources, and post the virtual posters created in the last learning session. All LSs were developed by the research team with expertise in the topic area, with the exception of the advocacy module in LS3. The advocacy module was developed by the National Institute for Children’s Health Quality (NICHQ) as a part of their ‘‘Be Our Voice’’ campaign to enhance participation of pediatric providers in advocating for healthier environments to promote healthy weights in children. The online virtual world with advocacy training was available to study participants through a partnership with NICHQ (2012). 416

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Each site was encouraged to have an interdisciplinary team (up to four members—i.e., the health care provider, support staff, administrator, dietitian, and/or counselor) complete the training to promote the health care system changes needed to implement the guidelines. In addition to the Web-based training, the practice teams received copies of Motivational Interviewing in Health Care: Helping Patients Change Behavior (Rollnick, Miller, & Butler, 2007) and copies of expert guidelines (Barlow, 2007; NAPNAP, 2006; Shaibi & Goran, 2008). Initially, webinars were planned for monthly calls, but because of limited technology available at many clinic sites, conference calls were deemed to be more appropriate. Calls were limited to 1 hour, once a month, with the remainder of the training occurring at the provider’s convenience. Orientation to the Web-based collaborative also took place in a conference call. Throughout the modules, participants completed interactive, multiple choice test questions to ensure application of knowledge to practice scenarios. Providers (and other team members, if relevant to their credentials) received continuing education credits for participating in the training. Data Collection Methods and Measures A link was included to complete a satisfaction survey using Survey Monkey (www.surveymonkey.com) after each training module. Each survey contained five questions covering the following topics: (1) the learning outcomes/educational objectives for this session were met, (2) the speaker was interesting and held my attention, (3) I will be able to use this information in future practice, (4) the speaker was knowledgable, and (5) the audiovisual aids/handouts were useful. All questions were rated on a 4-point Likert-type scale from strongly disagree (1) to strongly agree (4) or not applicable (n/a). Participants were also asked two open-ended questions: what the Journal of Pediatric Health Care

Open-ended questions were analyzed using a modified constant comparison method of analysis (Denzin & Lincoln, 2000; Krueger, 1997). Analysis of the data began with downloading the data into an Excel spreadsheet to facilitate microanalysis coding line by line. Data were further examined to unitize data into data clusters (Krueger, 1997). Data clusters were examined for overall themes regarding changes the providers planned to make while implementing the obesity prevention guidelines.

provider planned to change as a result of the training and any remaining feedback or comments. Upon completion of each survey, participants were awarded their continuing education credits for that training module. Additionally, at the end of the training, an overall satisfaction survey about the Web-based collaborative was sent to providers via e-mail. This survey consisted of 30 questions (some with multiple parts) using the same 4-point Likert-type scale previously described and two open-ended questions as previously described. Providers were asked about their satisfaction with the following topics: guidelines, QI, Web-based program, usability, presentation style, enhanced interaction, and eLearning community.

RESULTS Sample Demographics Of the 24 SBHCs in 6 states, a total of 36 participants took part in the virtual childhood obesity collaborative. Participants were from Arizona (n = 4), Colorado (n = 6), New Mexico (n = 6), Michigan (n = 6), New York (n = 8), and North Carolina (n = 6). All but one of the participants was female. Participants included nurse practitioners (n = 21, 58.3%), medical doctors (n = 6, 16.6%), physician assistants (n = 5, 13.9%), registered nurses (n = 2, 5.6%), one health educator (2.8%), and one who did not report (2.8%). The number of participants who completed each training module is presented in Table 1. Completion rates of the first two learning sessions were much higher than the final two sessions. The format for LS3 and LS4 differed from the first two sessions. Despite the outstanding nature of the virtual city experience in LS3, participants struggled with accessing the material that required an additional registration through NICHQ. In LS4, many of the participants in our study had not created a poster before and were overwhelmed with the task, which limited participation. Four participants (11.1%) completed all 17 training modules, and 23 participants (63.9%) completed at least 75% of the modules. Six participants (16.7%) completed fewer than 5 of the 17 training modules.

Data Analysis Data from each survey were downloaded from Survey Monkey into an Excel spreadsheet (www.office. microsoft.com) that was uploaded into an SPSS database (version 20, IBM Corp., Armonk, NY), where data were cleaned and verified. Data analysis was conducted with SAS (version 9.2, SAS Institute Inc., Cary, NC). Descriptive statistics were calculated for provider demographic characteristics, as well as satisfaction scores for individual training module surveys and the overall survey. Training module results were first analyzed by combining all 17 modules by the five survey questions (learning objectives were met, interesting speaker, information useful in practice, knowledgeable speaker, and useful audiovisual aids and handouts). Training module results were also collapsed into a composite score for six content areas based on face validity: evidence-based guidelines, MI, CCM, health disparities, advocacy, and culturally sensitive care. The overall satisfaction survey was analyzed by combining questions into seven content areas: guidelines, QI, Webbased program, usability, presentation style, enhanced interaction, and eLearning community.

TABLE 2. Participant satisfaction of training modules by question type and content area Question type/content area Question typeb Learning objectives met Interesting speaker Use information in practice Knowledgeable speaker Useful audiovisual/handout Content areab Guidelines Health disparities Chronic Care Model Motivational interviewing Advocacy Culturally sensitive care

Mean

SD

Minimum

Maximum

na

3.63 3.43 3.55 3.66 3.56

0.37 0.45 0.35 0.34 0.38

2.73 2.40 2.93 3.00 2.80

4.00 4.00 4.00 4.00 4.00

36 36 36 36 36

3.58 3.48 3.53 3.63 3.40 3.33

0.38 0.46 0.40 0.47 0.54 0.73

2.95 2.80 2.84 1.60 2.80 1.00

4.00 4.00 4.00 4.00 4.00 4.00

33 30 32 31 6 18

a

The number of participants who completed a survey in each category (total n = 36). All questions were rated on a 4-point Likert scale (1 = strongly disagree, 4 = strongly agree), and composite scores were calculated for each category listed.

b

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Participant Satisfaction—Individual Training Modules Participant satisfaction scores are presented in Table 2. Mean satisfaction scores by question type were quite high (> 3 out of 4 for all questions). The composite score ranged from 3.66 for knowledgable speaker to 3.43 for interesting speaker. Satisfaction scores by content area were also high, ranging from 3.63 for MI to 3.33 for culturally sensitive care. Themes regarding providers’ plans for change are presented in Table 3. Many providers (23% to 64%) reported specific examples of how they planned to Many providers change their practice (23% to 64%) after completing each reported specific module. For the guidelines modules, proexamples of how viders reported, ‘‘We they planned to have already changed change their our perspective in realizing how important it practice after is to get accurate meacompleting each surements and have module. the percentiles in each chart to trigger working on changing lifestyles’’ and ‘‘My entire practice related to obesity has changed. Prior to this study we were not even measuring BMIs.’’ Another provider responded, ‘‘More MI, better tracking system for labs and follow-ups.’’ Training on the health disparities collaborative included QI, CCM, and the team approach using the PDSA improvement process. Samples of changes providers reported include ‘‘Use PDSA cycles to make small improvements in practice,’’ and ‘‘More frequent QI studies.’’ Additional training on the CCM included computer information systems, decision support, delivery system redesign, and self-management support. Examples of changes providers reported in this section include: ‘‘Try to implement a system where we are better prepared to see the patient when the provider walks into the exam room’’ and ‘‘We have developed a limited registry, accessible by all involved in the collaborative, to keep information up to date and to be able to track progress of our obese patients.’’ The MI training consisted of three modules: an introduction, assessing readiness, and values clarification. Participants reported engaging patients, discussing changes differently, and using resources provided in the training. One of the tools used in this training was the readiness ruler, a visual analog scale shown to patients to rate their readiness to change. One provider reported, ‘‘Using MI respectively and compassionately to motivate and energize kids and their parents has been so helpful. They are taking responsibility for themselves and this is the first step.’’ Another clinician reported, ‘‘I started implementing the readiness ruler and the kids love it!!’’ 418

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The advocacy module was developed by NICHQ as described previously. Of the participants who completed this module, they reported, ‘‘Follow through with advocacy plans’’ and ‘‘Joining community groups.’’ The culturally sensitive care module focused on providing care for different ethnic groups. Participants reported, ‘‘Use MI in a cultural context,’’ ‘‘Increase awareness of my own biases,’’ and ‘‘Ask, Ôare there food you wish you could give your family, but cannot due to financial/other reasons.Õ’’ The final learning session was completion of a virtual poster describing a practice change implemented at their site. Ten providers completed virtual posters, covering five topics for practice change (some contained multiple topics): documentation of BMI and/or blood pressure percentiles (n = 3), follow-up appointments with overweight/obese children (n = 4), laboratory assessments (n = 3), increasing parental involvement (n = 1), and creating a tool kit (n = 1). Virtual posters were posted on the eLearning community (Figure 2). Providers presented the findings from their posters during monthly conference calls, leading to animated discussions. Participant Satisfaction—Overall At the completion of the training, participants were asked to provide feedback on the overall experience with the virtual learning collaboration (Figure 3). Satisfaction was high; all seven composite scores were above 3.2 (agree to strongly agree range) on the 4-point Likerttype scale (n = 25). Satisfaction with the program received the highest score (3.76), and enhanced interaction received the lowest score (3.24). The overall survey reiterated intentions to change as outlined in the individual modules, with use of MI being mentioned most frequently. In addition, two participants commented on difficulties with accessing the Web-based training and needing more orientation in navigating the social network site. One provider responded, ‘‘I had a lot of trouble accessing it [the training] initially and never really felt comfortable with it. Perhaps a little more help at the beginning to get on and play with it with some would have helped me.’’ A final comment from another participant referred to the value of the training for an ongoing reference and for training new staff. DISCUSSION The learning collaborative model for QI developed by the Institute for Healthcare Improvement to increase clinician adherence to guidelines and engage in QI processes has established positive outcomes for in-person training (Bordley, Margolis, Stuart, Lannon, & Keyes, 2001; Institute for Healthcare Improvement, 2004; Margolis et al., 2004; Wilson, Berwick, & Cleary, 2003). Providers, including nurses and nurse practitioners, could implement the findings of this study by starting with a Journal of Pediatric Health Care

TABLE 3. Responses to open-ended question after each training module regarding what the participants intend to change na

Plan to change, %b

Overview

33

63.6

Laboratory Screening

29

34.5

Physical Activity Recommendations

29

34.5

Nutrition Recommendations

26

23.1

Health disparities

Health Disparities Collaborative Approach to Quality Improvement

30

63.3

Chronic Care Model

Introduction

31

45.2

Clinical Information Systems

26

34.6

Decision Support

24

29.2

Content area Guidelines

Module title

Change themes Improve assessment: BP/BP% guidelines, laboratory assessments, family history Follow-up: More frequent follow-up and monitoring, follow up obese children more rigorously, follow recommendations for frequency of follow-up visits MI and counseling: Learn more about MI and incorporate into visits, encourage parents to take an active role in developing healthy strategies, write prescription for healthy behaviors Resources: Refer back to training materials, use posters in clinic to increase awareness, use educational materials for portion control Multidisciplinary team: Multidisciplinary approach for overweight and obese patients, collaborate with mental health Improve assessment: Follow recommendations for laboratory assessments, start checking laboratory values at 10 years of age, recommend lipid panels, use fasting blood glucose instead of HgbA1C Follow-up: Retest every 2 years, repeat laboratory tests when appropriate Resources: Use reference charts, laminate presentation slides to use in clinic MI and counseling: Use MI, counsel families on physical activity and inactivity, set realistic goals, help families develop goals Resources: Refer patients to community resources for activity, look into after-school programs Parent involvement: Encourage parents to be more active with kids, review inactivity and screen time with families Improve assessment: Rephrasing questions about eating habits, streamline diet history Resources: Use resources to illustrate good dietary habits (i.e., www. choosemyplate.gov, handouts), print materials from the training for patients Patient education: Encourage infant eating habits with families, focus on key nutritional concepts when educating patients QI: Apply PDSA process, improve quality of obesity care, more frequent QI at clinic, start with small steps, use PDSA to improve BP% documentation Chronic Care Model: Incorporate into obesity care and other aspects of chronic health care Collaboration: Develop team to improve obesity care and follow-up, assign duties to medical assistant Parent involvement: Put together a list of community resources for parents, offer guidelines to parents, proactive phone discussions with parents upset about overweight/obesity diagnosis Patient registry: Flag system for laboratory test results and follow-up appointments, development of patient registry QI: Formalize QI process, improve BP% documentation, integrate multiple decision support tools and clinical delivery systems, improve system to be better prepared to see patient Administrative/system implications: Look at impact on staff when clinical decisions are made; seek senior management support Patient registry: Develop registry for patients with BMI $85%, track appointments and follow-ups, utilize EMR for reports, start with a small registry to try out with select patients, use with PDSAs, use to evaluate care and monitor effectiveness, track progress of obese patients Evidence-based practice: Incorporate recommendations into practice, be more aware of evidence-based guidelines Referrals: Make a list of places to refer patients, follow guidelines for referral to tertiary care centers Patient registry: Create a registry of obesity patients and begin analysis for change (Continued on page 420)

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TABLE 3. Continued. Content area

Motivational interviewing

na

Plan to change, %b

Delivery System Redesign

26

38.5

Self-Management Support

27

44.4

Introduction

30

53.8

Assessing Readiness

29

48.3

Values Identification

27

40.7

Implementing MI in Practice

28

42.9

6

50.0

18

50.0

Module title

Advocacy

Be Our Voice

Culturally sensitive care

Cultural Competency: Providing Culturally Sensitive Care

Change themes Teamwork: Designate roles for obesity team, involve other team members in planning a PDSA, have a meeting to set a goal, provide staff training, delegate specific tasks to medical assistant QI Process: Create flow sheet for obesity care, identify PDSA, patient registry, incorporate BP% into practice Involve patient/family: Use MI, allow time for patient talk, collaborate with patient/family on goals, set small goals, integrate self-monitoring, use problem solving tool from training, assist patients with action plan for self-management Engage patient: Clarify what patient says, ask permission to talk about weight or share information Discuss change differently: Use more open-ended questions, elicit ideas from patient, engage patient Resources: References with MI techniques in each examination room, develop readiness ruler to send home with patient Engage patient: Ask permission to offer advice, work on engaging patients in the precontemplation stage Discuss change differently: Refrain from telling patients what to do Resources: Use readiness ruler more often, simplify readiness ruler for use with children Discuss change differently: Use more open-ended questions, find balance when talking about change with patients, use reflective and empathetic responses to discuss change, clarify values for patients to begin change Resources: Use the values chart, use the readiness ruler Engage patient: Ask for permission before giving advice, use more ‘‘and’’ statements instead of ‘‘but’’ statements, let patient suggest alternatives Discuss change differently: Give less advice, avoid suggesting change for patients who are ambivalent, help patients make their own decisions for change Advocacy: Follow through on advocacy plan, join community groups Resources: Utilize information for future advocacy activities Cultural sensitivity: Use MI in a cultural context, increase awareness of own biases, make diet assessment questions more open-ended and culturally sensitive Resources: Refer to diet assessment questions in the training

Note. BMI = body mass index; BP = blood pressure; BP% = blood pressure percentile; EMR = electronic medical record; MI = motivational interviewing; PDSA = Plan, Do, Study, Act; QI = quality improvement. a The number of participants who completed each training module. b The percentage of participants (out of those who completed each training module) who reported an intent to change.

baseline chart audit in their practice and using the PDSA worksheet to develop a plan for practice change. Providers.could This study used the implement the unique, Web-based collaborative approach findings of this that is emerging to study by starting reach a broader audiwith a baseline ence (John et al., 2014). Web-based chart audit in their training is a costpractice and using efficient and flexible the PDSA alternative to educating providers using inworksheet to person trainings. Webdevelop a plan for based training also practice change. expands the reach to

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include rural providers and those who serve vulnerable populations with limited access to resources for formal training programs. One major goal of this project was to support and provide better access for rural and underserved areas, specifically those providing care to members of ethnic minority groups. The intention was to reach practitioners who cannot easily access training. In the current study, provider satisfaction with Webbased training was high. These results are consistent with other Web-based training studies measuring satisfaction, as shown in a recent synthesis article (Militello et al., 2014). Participants also reported intention to change their practice based on the training. Research indicates that intention to change correlates with behavior change (Ajzen & Fishbein, 1980; Madden, Ellen, & Ajzen, 1992).

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FIGURE 2. An example of a storyboard poster created during learning session four.

Used with permission from Lynn Bakken. This figure appears in color online at www.jpedhc.org.

FIGURE 3. Participant means ( SD) of overall survey results (n = 25).

Composite satisfaction scores were calculated for each content area (1 = strongly disagree, 4 = strongly agree). This figure appears in color online at www. jpedhc.org.

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Strengths and Weaknesses Providers in the current study were selected from a nationally representative sample including both urban and rural SBHC providers distributed across the United States. Because the sample size of the current study was small, it may be difficult to generalize to a larger population. Additionally, providers in the current study chose to participate in the virtual eLearning obesity collaborative and may have higher satisfaction because of interest in the topic. The attrition rate may also have influenced the high satisfaction scores because those who chose not to complete the training may not have been as satisfied with the training. The following significant changes occurred in the practice sites that limited completion of the final learning sessions: two providers retired, two providers changed jobs, two providers had the hours at their center reduced, and two providers started the project late and did not participate in the final round of data collection. Although up to four people per site were

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encouraged to participant in the collaborative, many SBHCs are run by single providers, with limited support staff. Therefore, many sites did not have extra team members to participate. Even in the sites with additional team members participating, many of these participants only completed some of the training modules. Because of limited technology at many sites, as well as difficulty fitting training into an already busy schedule, additional team members may have chosen modules that were of most interest to them or their site. Also, multiple people at a site could have watched a module together or providers may have presented information to additional team members after participating in the training. Overall, participant satisfaction was high, reaching 24 SBHCs in diverse sites from remote rural communities to large urban centers, and many providers reported intentions to change practice. Challenges to Web-based training in the current study were the lack of computer literacy of providers and the lack of agency support for Web-based interventions. Some sites had difficulty with Web access, some had outdated computers that would not allow them to view the Webbased presentations or video vignettes, and some had minimal information technology support for on-site assistance with Internet and technology questions CONCLUSION This study demonstrates that developing a virtual childhood obesity collaborative is feasible for SBHC providers in a variety of geographic settings who work with at-risk youth, but participation varied by module. Usability of the Web-based training influenced participation. When additional steps were required to access the advocacy module through NICHQ, participation dropped significantly. Additionally, when participants were unfamiliar with activities (i.e., creating a virtual poster), they were reluctant to participate. Satisfaction was high and providers reported intentions to change their practice based upon the training. Data from this study suggest that participation in a virtual collaborative is feasible and acceptable and has the potential to improve the implementation of evidence-based practice. We thank Jinnette Senecal, Carol Stevens, Lisa Militello, Gabe Shaibi, and Punam Ohri-Vachaspati from Arizona State University for their support in developing the virtual collaborative and Sarah Barlow from Baylor University for reviewing the modules. We also thank Rabah Kamal at the University of Colorado for qualitative data management and analysis support. We are grateful to all the providers who participated in the collaborative and to Lynn Bakken for allowing us to use her poster in this article. REFERENCES Ajzen, I., & Fishbein, M. (1980). Understanding attitudes and predicting social behavior. Englewood Cliffs, NJ: Prentice Hall.

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Barlow, S. E. (2007). Expert committee recommendations regarding the prevention, assessment, and treatment of child and adolescent overweight and obesity: Summary report. Pediatrics, 120(4), S164-S192. Beno, L., Hinchman, J., Kibbe, D., & Trowbridge, F. (2005). Design and implementation of training to improve management of pediatric overweight. The Journal of Continuing Education in the Health Professions, 25(4), 248-258. Biro, F. M., & Wien, M. (2010). Childhood obesity and adult morbidities. The American Journal of Clinical Nutrition, 91(5), 1499S1505S. Bodenheimer, T. (2003). Interventions to improve chronic illness care: Evaluating their effectiveness. Disease Management, 6(2), 63-71. Bodenheimer, T., Wagner, E. H., & Grumbach, K. (2002a). Improving primary care for patients with chronic illness. Journal of the American Medical Association, 288(14), 1775-1779. Bodenheimer, T., Wagner, E. H., & Grumbach, K. (2002b). Improving primary care for patients with chronic illness: The chronic care model, Part 2. Journal of the American Medical Association, 288(15), 1909-1914. Bordley, W. C., Margolis, P. A., Stuart, J., Lannon, C., & Keyes, L. (2001). Improving preventive service delivery through office systems. Pediatrics, 108(3), e41. Bray, P., Roupe, M., Young, S., Harrell, J., Cummings, D. M., & Whetstone, L. M. (2005). Feasibility and effectiveness of system redesign for diabetes care management in rural areas: The eastern North Carolina experience. The Diabetes Educator, 31(5), 712-718. Chin, M. H., Cook, S., Drum, M. L., Jin, L., Guillen, M., Humikowski, C. A., . Schaefer, C. T. (2004). Improving diabetes care in midwest community health centers with the health disparities collaborative. Diabetes Care, 27(1), 2-8. Coleman, K., Austin, B. T., Brach, C., & Wagner, E. H. (2009). Evidence on the chronic care model in the new millennium. Health Affairs, 28(1), 75-85. Cook, S., Weitzman, M., Auinger, P., & Barlow, S. E. (2005). Screening and counseling associated with obesity diagnosis in a national survey of ambulatory pediatric visits. Pediatrics, 116(1), 112-116. De Bourdeaudhuij, I., Stevens, V., Vandelanotte, C., & Brug, J. (2007). Evaluation of an interactive computer-tailored nutrition intervention in a real-life setting. Annals of Behavioral Medicine, 33(1), 39-48. Denzin, N. K., & Lincoln, Y. (2000). Handbook of qualitative research. Thousand Oaks, CA: Sage. Dorsey, K. B., Wells, C., Krumholz, H. M., & Concato, J. (2005). Diagnosis, evaluation, and treatment of childhood obesity in pediatric practice. Archives of Pediatrics & Adolescent Medicine, 159(7), 632-638. Gance-Cleveland, B., Dandreaux, D., Aldrich, H., & Kamal, R. (2015). Challenges conducting multicenter translational research: Promoting adherence to childhood obesity guidelines. IRB: Ethics & Human Research, 37(1), 6-11. Hupke, C., Camp, A. W., Chaufournier, R., Langley, G. J., & Little, K. (2004). Transforming diabetes health care part 1: Changing practice. Diabetes Spectrum, 17(2), 102-106. Institute for Healthcare Improvement. (2004). The breakthrough series: IHI’s collaborative model for achieving breakthrough improvement. Diabetes Spectrum, 17(2), 97-101. Jacobson, D., & Gance-Cleveland, B. (2011). A systematic review of primary healthcare provider education and training using the Chronic Care Model. Obesity Reviews, 12(5), e244-e256. John, T., Morton, M., Weissman, M., O’Brien, E., Hamburger, E., Hancock, Y., & Moon, R. Y. (2014). Feasibility of a virtual learning collaborative to implement an obesity QI project in 29 pediatric practices. International Journal for Quality in Health Care, 26(2), 205-213. Joseph, C. L., Peterson, E., Havstad, S., Johnson, C. C., Hoerauf, S., Stringer, S., . Strecher, V. (2007). A web-based, tailored

Journal of Pediatric Health Care

asthma management program for urban African-American high school students. American Journal of Respiratory and Critical Care Medicine, 175(9), 888-895. Keeton, V., Soleimanpour, S., & Brindis, C. D. (2012). School-based health centers in an era of health care reform: Building on history. Current Problems in Pediatric and Adolescent Health Care, 42(6), 132-156. Kroeze, W., Werkman, A., & Brug, J. (2006). A systematic review of randomized trials on the effectiveness of computer-tailored education on physical activity and dietary behaviors. Annals of Behavioral Medicine, 31(3), 205-223. Krueger, R. A. (1997). Analyzing and reporting focus group results. Thousand Oaks, CA: Sage. Lofink, H., Kuebler, J., Juszczak, L., Schlitt, J., Even, M., Rosenberg, J., & White, I. (2013). 2010-2011 School-based health alliance census report. Washington, D.C.: School-Based Health Alliance. Mabry, I. R., Clark, S. J., Kemper, A., Fraser, K., Kileny, S., & Cabana, M. D. (2005). Variation in establishing a diagnosis of obesity in children. Clinical Pediatrics (Phila), 44(3), 221-227. Madden, T. J., Ellen, P. S., & Ajzen, I. (1992). A comparison of the theory of planned behavior and the theory of reasoned action. Personality and Social Psychology Bulletin, 18(1), 3-9. Margolis, P. A., Lannon, C. M., Stuart, J. M., Fried, B. J., Keyes-Elstein, L., & Moore, D. E., Jr. (2004). Practice based education to improve delivery systems for prevention in primary care: Randomised trial. BMJ, 328(7436), 388. Martin, M. B., Larsen, B. A., Shea, L., Hutchins, D., & Alfaro-Correa, A. (2007). State diabetes prevention and control program participation in the health disparities collaborative: Evaluating the first 5 years. Preventing Chronic Disease, 4(1), 1-10. Mazur, A., Matusik, P., Revert, K., Nyankovskyy, S., Socha, P., Binkowska-Bury, M., . Malecka-Tendera, E. (2013). Childhood obesity: Knowledge, attitudes, and practices of European pediatric care providers. Pediatrics, 132(1), e100-e108. McCullough, D. K., Davis, C., Austin, B. T., & Wagner, E. H. (2004). Constructing a bridge across the quality chasm: A practical way to get healthier, happier patients, providers, and health care delivery systems. Diabetes Spectrum, 17, 92-96. Militello, L. K., Gance-Cleveland, B., Aldrich, H., & Kamal, R. (2014). A methodological quality synthesis of systematic reviews on computer-mediated continuing education for healthcare providers. Worldviews on Evidence-Based Nursing, 11(3), 177-186. National Association of Pediatric Nurse Practitioners. (2006). Healthy eating and activity together (HEATSM) clinical practice guideline: Identifying and preventing overweight in childhood. Cherry Hill, NJ: National Association of Pediatric Nurse Practitioners. National Heart, Lung, and Blood Institute. (2005). The fourth report on the diagnosis, evaluation, and treatment of high blood pressure in children and adolescents. Retrieved from http:// www.nhlbi.nih.gov/health-pro/guidelines/current/hypertensionpediatric-jnc-4/ National Institute for Children’s Health Quality. (2012). Be our voice. Retrieved from http://obesity.nichq.org/solutions/be-our-voice Norris, S. L., & Olson, D. E. (2004). Implementing evidence-based diabetes care in geriatric populations. The chronic care model. Geriatrics, 59(6), 35-39. Ogden, C. L., Carroll, M. D., Kit, B. K., & Flegal, K. M. (2014). Prevalence of childhood and adult obesity in the United States, 2011-2012. Journal of the American Medical Association, 311(8), 806-814.

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Ogden, C. L., Lamb, M. M., Carroll, M. D., & Flegal, K. M. (2010). Obesity and socioeconomic status in children and adolescents: United States, 2005–2008. NCHS Data Brief, 51, 1-8. Porter, S. C., Cai, Z., Gribbons, W., Goldmann, D. A., & Kohane, I. S. (2004). The asthma kiosk: A patient-centered technology for collaborative decision support in the emergency department. Journal of the American Medical Informatics Association, 11(6), 458-467. Rausch, J. C., Perito, E. R., & Hametz, P. (2011). Obesity prevention, screening, and treatment: Practices of pediatric providers since the 2007 expert committee recommendations. Clinical Pediatrics, 50(5), 434-441. Reilly, J. J., & Kelly, J. (2011). Long-term impact of overweight and obesity in childhood and adolescence on morbidity and premature mortality in adulthood: Systematic review. International Journal of Obesity, 35(7), 891-898. Rollnick, S., Miller, W. R., & Butler, C. C. (2007). Motivational interviewing in health care: Helping patients change behavior (1st ed.). New York, NY: The Guilford Press. Shaibi, G. Q., & Goran, M. I. (2008). Examining metabolic syndrome definitions in overweight Hispanic youth: A focus on insulin resistance. The Journal of Pediatrics, 152(2), 171-176. Sharifi, M., Rifas-Shiman, S. L., Marshall, R., Simon, S. R., Gillman, M. W., Finkelstein, J. A., & Taveras, E. M. (2013). Evaluating the implementation of expert committee recommendations for obesity assessment. Clinical Pediatrics, 52(2), 131-138. Singh, A. S., Mulder, C., Twisk, J. W. R., van Mechelen, W., & Chinapaw, M. J. M. (2008a). Tracking of childhood overweight into adulthood: A systematic review of the literature. Obesity Reviews, 9(5), 474-488. Singh, G. K., Kogan, M. D., Van Dyck, P. C., & Siahpush, M. (2008b). Racial/ethnic, socioeconomic, and behavioral determinants of childhood and adolescent obesity in the United States: Analyzing independent and joint associations. Annals of Epidemiology, 18(9), 682-695. Singh, G. K., Siahpush, M., & Kogan, M. D. (2010). Rising social inequalities in US childhood obesity, 2003-2007. Annals of Epidemiology, 20(1), 40-52. Small, L., Anderson, D., Sidora-Arcoleo, K., & Gance-Cleveland, B. (2009). Pediatric nurse practitioners’ assessment and management of childhood overweight/obesity: Results from 1999 and 2005 cohort surveys. Journal of Pediatric Health Care, 23(4), 231-241. Strauss, R. S., & Pollack, H. A. (2003). Social marginalization of overweight children. Archives of Pediatrics & Adolescent Medicine, 157(8), 746-752. Van Cleave, J., Kuhlthau, K. A., Bloom, S., Newacheck, P. W., Nozzolillo, A. A., Homer, C. J., & Perrin, J. M. (2012). Interventions to improve screening and follow-up in primary care: A systematic review of the evidence. Academic Pediatrics, 12(4), 269-282. Wagner, E. H. (1998). Chronic disease management: What will it take to improve care for chronic illness? Effective Clinical Practice, 1(1), 2-4. Wang, Y., & Zhang, Q. (2006). Are American children and adolescents of low socioeconomic status at increased risk of obesity? Changes in the association between overweight and family income between 1971 and 2002. The American Journal of Clinical Nutrition, 84(4), 707-716. Wilson, T., Berwick, D. M., & Cleary, P. D. (2003). What do collaborative improvement projects do? Experience from seven countries. Joint Commission Journal on Quality and Safety, 29(2), 85-93.

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