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Elsie M. Taveras, MD, MPH, Richard Marshall, MD, Mona Sharifi, MD, MPH, Earlene Avalon, PhD, Lauren Fiechtner, MD, MPH, Christine Horan, MPH, Monica Gerber, MPH, John Orav, PhD, Sarah N. Price, MPH, Thomas Sequist, MD, MPH, and Daniel Slater, MD.
Author Information and AffiliationsNovel approaches to care delivery that leverage clinical and community resources could improve body mass index (BMI) and family-centered outcomes.
To examine the extent to which 2 clinical-community interventions improved child BMI z-score, parent sense of empowerment, and child health-related quality of life (HR-QoL).
We conducted a 2-arm, randomized controlled trial from June 2014 to June 2016 with measures at baseline and 1 year. We enrolled 721 children ages 2 to 12 years with a BMI ≥85th percentile from 6 primary care practices of Atrius Health. Children were randomized to 1 of 2 arms: (1) enhanced primary care (eg, electronic alerts and clinical decision support tools for pediatric weight management, educational materials, a Neighborhood Resource Guide, and monthly text messages promoting behavior change) or (2) enhanced primary care plus contextually tailored, individual health coaching (twice-weekly text messages and 6 telephone or video contacts) to support behavior change and link families to community resources. In intent-to-treat analyses, we used multiple imputation and linear repeated measures models to examine 1-year changes in age- and sex-specific BMI z-score, HR-QoL as measured by the Pediatric Quality of Life Inventory (PedsQL) version 4.0, and parent sense of empowerment.
At 1 year, we obtained BMI z-scores from 664 children (92%) and parent-reported outcomes from 657 parents (91%). Baseline mean (SD) child age was 8.0 (3.0) years; 35% were White, 33% Black, 22% Hispanic, and 10% other; 44% lived in households with annual incomes <$50 000. We observed significant improvements in BMI z-score in both the enhanced primary care group (−0.06 units; 95% CI, −0.10 to −0.02) and the enhanced primary care plus coaching group (−0.09 units; 95% CI, −0.13 to −0.05) but no statistically significant difference between the 2 arms (−0.02 units; 95% CI, −0.08 to 0.03). Both intervention arms also significantly improved parent sense of empowerment. Parents in the enhanced primary care plus coaching group, but not in the enhanced care group, reported improvements in their child's HR-QoL (1.53 units; 95% CI, 0.51-2.56). However, there were no significant differences between the arms in either family-centered outcome.
Two interventions that included high-quality clinical care for obesity and linkages to community resources resulted in improved family-centered outcomes for childhood obesity and improvements in child BMI from baseline to 1 year, but there were no significant differences between the 2 interventions.
Childhood overweight and obesity place a significant burden on morbidity and quality of life. As of 2012, in the United States, the prevalence of childhood overweight and obesity appears to have plateaued and may even be decreasing among 2- to 5-year old children.1 Yet, overall prevalence remains at historically high levels and substantial racial/ethnic disparities continue to persist, and, in the case of Hispanic children, may even be widening.2-4 Health care system–based interventions to reduce obesity have been somewhat effective but are often of limited effectiveness due to myriad social and environmental barriers that impede improvement in obesity-related behaviors.5,6
An important but often overlooked aspect of interventions to improve obesity and reduce disparities is the careful consideration of the socioenvironmental context in which decisions related to health behaviors are being made—and in which behavior change is expected to occur. Neighborhood socioeconomic characteristics and built-environment factors including food and physical activity can significantly influence health behaviors and may contribute to disparities in childhood obesity.7-11 Understanding community levels of poverty and unemployment as well as individual, health-related social problems could assist health practitioners in providing targeted resources and selecting referrals to local health and social service agencies.12 Sophisticated geographic information systems (GIS) analyses can provide community-level data on access to food establishments that could assist in meal-planning discussions with families. GIS methods and community mapping could also provide information about recreational spaces and playgrounds as well as transportation availability that might influence parents' decision-making regarding their child's physical activity options. Thus, characterizing the environment can assist in developing a tailored clinical-community intervention that could be adapted to an individual's environment and needs.
Another underused approach to obesity management and disparities reduction is to identify innovative strategies from positive outliers (also referred to in the literature as positive deviants). Positive outliers are defined as individuals who have succeeded where many others have not to change their health behaviors, reduce their body mass index (BMI), and develop resilience in the context of adverse built and social environments.13,14 The premise of this positive outlier approach is that solutions to problems that face a community often exist within that community, and that these successful members of the community possess strategies that can be generalized and promoted to improve the outcomes of others. Such individuals could help guide intervention development for other families in their same neighborhoods who have struggled with behavior change.
We designed the Connect for Health randomized controlled trial to leverage clinical and community resources to improve obesity and family-centered outcomes. The intervention was built upon practices of positive outlier families as well as strategies recommended by a diverse group of stakeholders representing parents, children, pediatric clinicians, and community/public health providers.15,16 We hypothesized that children randomized to the intervention arm to receive enhanced primary care plus a contextually tailored intervention delivered by trained health coaches would have greater reductions in BMI z-score compared with children randomized to a control group to receive enhanced primary care plus nontailored health coaching. In this report, we summarize the main outcomes of Connect for Health.
The design and implementation of Connect for Health was informed by a diverse group of stakeholders representing clinicians, community and public health providers, parents, and children. Members of the research and clinical team have long-standing collaborative relationships from developing previous obesity interventions,17 and thus a key activity in preparation for this study was to build a strong network of cross-collaboration among stakeholders who had not yet worked with each other.
Using established methods on engagement18 and the PCORI Methodology Standards,19 we worked with our clinician team to identify positive outlier children and families who would be interested in participating in focus group discussions about their experiences.15,16 Several children and parents from these focus groups were already participating as ongoing members of our parent and youth advisory boards. Leaders and staff of youth-serving community-based organizations, including the YMCA, provided critical input on the ideas and activities we ultimately implemented. Based on principles of engagement, the research team delineated the role of stakeholder participants as well as discussed, the relevance and importance of the work being developed and the ways in which input from all stakeholders would be utilized. Keys to successful implementation, incorporation of study activities into practice, and sustainability of project activities rely on engagement of stakeholders at several critical points before and during the intervention. The research and stakeholder group met on a monthly basis after the start of the study to discuss barriers and facilitators to implementation.
Patient advisory committees have been increasingly used in health care systems to gather patient-centered input on a variety of health care processes and to accelerate improvement.20 Engaging patients as active participants in designing and conducting health care research is increasingly recognized as critical to ensuring that the research questions posed and outcomes measured are relevant and important to patients.21-23 In this study, we convened parent and youth advisory boards to inform the study development. The Parent Board consisted of 11 parents whose children received care in the participating pediatric practices and was led by a parent whose children received their care at 1 of the practices. The Youth Board consisted of their children, who were between 10 and 12 years old. We recruited board members from among focus group and interview participants in our formative work with positive outlier children and their parents. Board members provided in-depth information about their own successful strategies that could be generalized and promoted to improve the outcomes of other families, advised the research team on the perspectives of potential trial participants, and provided feedback on specific components of the study. The Board met in person 1 to 2 times in each study year and communicated as needed more regularly to discuss study methods and implementation, including recruitment, informed consent, outcome measures, data collection, incentives, retention, and intervention design. Parents and youth on the advisory boards received a modest stipend for their participation.
Before the start of the study, we conducted 5 focus groups with parents (n = 41) and 4 focus groups with children (n = 21) who were identified from their electronic health record to have reduced or maintained their BMI despite having had a history of a BMI ≥95th percentile. We have previously published the methods and results of this formative work.12,13 Parents reported several practices that facilitated their ability to help their child improve his or her BMI. Among them were (1) making changes as a family rather than solely for the child; (2) implementing limits and rules around snacking, screen time, and activity, and maintaining consistency around those rules; (3) being involved in the decision-making with their health care providers about their child's weight management; (4) using more immediate rather than long-term outcomes of weight management to motivate change; and (5) maximally leveraging community resources to support behavior change. Children emphasized the value of positive support from their family and the importance of their peer relationships in motivating their behavior change. Parents and children outlined many outcomes that mattered most to them related to weight management, including not being bullied or teased, feeling good about oneself, fitting into age-appropriate clothing, and being able to keep up with other children during a physical activity. As a result, our intervention included an emphasis on social and emotional wellness. The feedback we received specifically informed our outcome measures, the neighborhood resources we included in our intervention, the youth-serving community-based organizations that we partnered with, and our approach to coaching (eg, shared decision-making and family-centered care were key training topics for the health coaches).
Connect for Health was conducted within 6 pediatric practices of Harvard Vanguard Medical Associates (HVMA), a multispecialty group practice in eastern Massachusetts with many years of experience with an electronic health record system and advanced team-based care model. The Connect for Health study design, eligibility, and recruitment have been described in detail elsewhere.24 We randomly assigned patients to 1 of 2 arms: (1) enhanced primary care or (2) enhanced primary care plus contextually tailored, individual health coaching. The enhanced primary care group served as the control arm even though these patients received some intervention previously incorporated into standard practice at HVMA. The primary outcomes included improvements in child BMI z-score in addition to family-centered outcomes that matter to parents and children, including pediatric health-related quality of life and parental resource empowerment. All study activities were approved by the Institutional Review Board at Partners Health Care System. The Connect for Health trial has been recorded in the clinicaltrials.gov national registry of randomized trials.
Eligibility for Connect for Health included (1) child age 2.0 to 12.9 years old, (2) child BMI ≥85th percentile for age and sex, and (3) family was not planning to leave HVMA within the study time frame. Recruitment began in June 2014 and ended March 2015; follow-up ended for all participants in March 2016. At the time of a visit with a child between the ages of 2 and 12 years with a BMI ≥85th percentile, HVMA clinicians received a BestPractice alert in the electronic health record that contained a link to electronically refer the patient to the Connect for Health study (Appendix A). After receiving the referral, study staff sent each family a letter providing more information about the study and inviting the family to participate. Research assistants then called parents to establish eligibility, explain the study, obtain verbal consent, and complete a telephone survey. We then randomized participants and mailed parents an enrollment letter informing them of their child's intervention group.
We randomized study participants from each of the participating pediatric practices in the order they were enrolled, organizing the lists into blocks of 4 in order to maintain balance between the 2 study arms in each of the practices. The lists were generated by the study biostatistician (JO) and maintained by the study project manager (CH). Allocation concealment was preserved by central allocation by the study program manager. Only the study project manager (CH) and study biostatistician (JO) had access to the randomization lists—the study project manager to allocate participants to the proper intervention and the study biostatistician to provide blinded reports of study progress and safety data.
All study participants, referring pediatricians, and research staff performing assessments were blinded to specific study hypotheses and to intervention assignment. Health coaches delivering the intervention were not blinded but only worked with participants in the intervention arm.
All pediatric primary care providers received a computerized clinical decision support (CDS) alert during primary care visits identifying 2- to 12-year-old children with a BMI ≥85th percentile and 2 additional CDS tools to assist in the management and follow-up of children with overweight or obesity.17,24,25 Clinicians also provided parents a comprehensive set of educational materials focusing on specified behavioral targets to support self-guided behavior change. Both the CDS tools and educational materials were based on the STAR trial and have been shown to be effective in improving child BMI.17 The materials focused primarily on decreases in screen time and sugar-sweetened beverages, improving diet quality, increases in moderate and vigorous physical activity, and improvement of sleep duration and quality. Based on our qualitative work with positive outlier families and feedback from our parent and youth advisory boards, we also developed materials to promote social and emotional wellness.
Participants randomized to the enhanced primary care group were exposed to the clinical best practices described above. In addition, participants received monthly text messages that contained links to publicly available resources to support behavior change (eg, links to the Let's Move! program).26 Participants also received a Neighborhood Resource Guide listing places that support healthy living in their community and surrounding areas.
In the enhanced primary care plus coaching arm, families received individualized health coaching tailored to their socioenvironmental context. Three trained health coaches contacted families every other month for 1 year via telephone, videoconference (using Vidyo, a HIPAA-compliant, password-protected software offered for free to families), or in-person visits, according to parent preference. These contacts were approximately 15 to 20 minutes in duration. Before the start of the intervention, the 2 health coaches received training from a senior health educator (S.P.) in behavior change theory and counseling, childhood obesity risk factors and management, providing family-centered care,27 motivational interviewing,28,29 and shared decision-making.30,31 Details of the health coach training and quality assurance have been previously described.24 Families also received twice-weekly text messages or emails in addition to monthly mailings.
Health coaches used a motivational interviewing style of counseling and shared decision-making techniques30,31 to provide family-centered care in addressing childhood obesity risk factors and management. At each contact, health coaches used an online community resource map developed for the study32 to identify resources within each family's community that could support behavior change, including nutritional support (ie, local farmers markets, supermarkets); places for physical activity (ie, Boys and Girls Clubs, swimming pools, recreation centers, ice rinks, and YMCAs); and social support services (ie, Supplemental Nutrition Program for Women, Infants, and Children offices). In addition, through a partnership with the YMCA, health coaches offered families a 1-month free family membership to area YMCAs to encourage physical activity and community connections. Families were also offered the opportunity to take part in 1 of 12 healthy grocery shopping programs throughout the course of the intervention led by a community partner, Cooking Matters®, empowering families to cook healthy meals and to learn ways to shop and eat well on a limited budget.
To engage parents and children in setting behavior change goals, health coaches used a behavior change decision aid tool developed by our study team that helped families identify outcomes that mattered most to them and potential motivators for engaging in behavior change. The tool facilitated shared decision-making to determine parents' goals and set the agenda for health coaching. Following each contact, the health coach mailed the family a packet that included issues of a healthy cooking magazine for children, handouts for parents about behavior change goals, and materials designed specifically for children. Intervention materials for children were developmentally appropriate. Parents also received interactive text messages twice weekly during the 1-year period. These messages were based on the well-received text message campaign implemented in the STAR trial.33
We obtained height and weight from children's electronic health record at baseline and at 1 year. In routine practice standardized across all 6 study sites, medical assistants measured children's weight, without shoes, using electronic, calibrated scales, and height using a stadiometer. We calculated BMI, age- and sex-specific BMI z-scores, and BMI categories (BMI <85th, BMI 85th through <95th, BMI >95th through <120% of 95th percentile, and BMI ≥120% of the 95th percentile).34
Parent-reported outcomes were assessed using telephone surveys at baseline and at 1 year. Parents reported their child's health-related quality of life using the 4 subscales of the PedsQL-4.0 (physical, emotional, social, and school).35,36 We also assessed parents' sense of empowerment (hereafter referred to as parental resource empowerment) using the child weight management subscale of the Parent Resource Empowerment Scale.25 The 5 items in the scale assessed parents' perceived knowledge of resources, ability to access resources, comfort with accessing resources, knowledge of how to find resources, and ability to acquire resources related to child weight management. For each question, parents responded “strongly disagree,” “disagree,” “agree,” or “strongly agree,” which were worth 1 to 4 points, respectively. Items were averaged to create a summary parental resource empowerment score (range = 1-4). Cronbach's α for this score was .87.37
Using questionnaires at baseline and at 1 year, we obtained each child's race/ethnicity as well as each parent's educational attainment and height and weight, from which we calculated BMI. We also assessed annual household income. To assess the feasibility of the study and parents' acceptance of and satisfaction with the intervention components, we asked parents to rate how satisfied they were with several aspects of the program, including the text messages and information on community resources. To assess unintended consequences, we also asked parents if their participation in the program affected their satisfaction with their child's health care services HVMA.
We performed analysis from June 2016 to October 2016. We analyzed distributions of participant characteristics across the 2 study arms using t test and chi-square test and found them to be balanced at baseline (P > .05). We anticipated that 338 children per arm would complete the study, which would allow us to detect to detect a difference between arms in the change in BMI as small as 0.24 and to detect a difference between arms in the change in PedsQL of 2.5 points, with 90% power and 5% type I error. As suggested by the recent US Preventive Service Task Force Draft Evidence Review of childhood obesity management, BMI z-score changes in the range of 0.15 to 0.20 are considered to constitute a clinically important benefit for many children.38 We performed multiple imputations using chained equations to impute missing outcomes for the approximately 8% of the 721 enrollees who did not have BMI outcomes at 1-year follow-up. In intent-to-treat analyses, we assessed the effect of the intervention on BMI z-score, PedsQL-4.0 summary score, and the Parent Resource Empowerment score using generalized linear repeated measure models to account for clustering by study site and within each participant over time. We used analogous logistic repeated measures models to model the effect of the intervention on the odds of being in a lower BMI category at follow-up compared with baseline. We adjusted all models for HVMA site. We implemented the models using the GLIMMIX and GENMOD procedures in SAS, version 9.4 (SAS Institute).
Primary care clinicians referred 1752 children from 6 pediatric practices to the Connect for Health study over a 9-month recruitment period. We attempted to contact the parents of 1545 children to assess eligibility. We enrolled 721 children in the study; 361 participants were randomized to the enhanced primary care group, and 360 families were assigned to the enhanced primary care plus coaching group (Figure 1). During the intervention period, 1 participant withdrew from the study, citing a lack of time for the study activities. At 1 year, we obtained follow-up BMI data from 664 children (92.0%) and parent survey data from 667 parents (92.5%). Table 1 shows the characteristics of the study sample. Baseline mean (SD) age was 8.0 (3.0) years; 35.0% were White, 33.3% Black, 21.8% Hispanic, and 9.9% other; 45.4% lived in households with annual incomes <$50 000. There were no significant differences in any baseline characteristics between the patients randomized to each intervention arm.
CONSORT Flow Diagram for the Connect for Health Study.
Baseline Characteristics of Participants in the Connect for Health Study, Overall and by Intervention Assignment.
Table 2 shows participants' unadjusted and adjusted changes in BMI z-score and in BMI category (ie, being in a lower category from baseline to 1-year follow-up). We observed significant changes in BMI z-score in both the enhanced primary care group (−0.06 units; 95% CI, −0.10 to −0.02) and the enhanced primary care plus coaching group (−0.09 units; 95% CI, −0.13 to −0.05). Although we observed slightly more improvement in BMI z-score among the enhanced primary care plus coaching group compared with the enhanced primary care group alone, there were no statistically significant differences between the 2 intervention arms (−0.02 units; 95% CI, −0.08 to 0.03).
Changes in BMI z-Score and Categories From Baseline to 1 Year, by Intervention Assignment (N = 721).
At 1-year follow-up, we found that 9.3% of children in the enhanced primary group and 11.6% of children in the enhanced primary care plus coaching group no longer had a BMI in the overweight or obese range. Overall, we observed higher odds in both the enhanced primary care group (odds ratio [OR], 1.18; 95% CI, 1.03-1.35) and the enhanced primary care plus coaching group (1.23; 95% CI, 1.08-1.40) of being in a lower BMI category than participants were at baseline; however, there was no statistically significant difference in odds between the 2 intervention arms (P = .70).
We conducted post hoc analyses to examine whether our observations of improved BMI z-score in both intervention arms could be explained by an underlying temporal trend toward improvement. Among 560 children with BMI z-scores available 1 year before baseline, at baseline, and at 1-year follow-up, we found that BMI z-score was increasing in the year before enrollment in the enhanced primary care group (0.23 units; 95% CI, 0.18-0.29) and the enhanced primary care plus coaching group (0.16 units; 95% CI, 0.11-0.22) and then decreased in both groups in the year following enrollment (Figure 2).
Adjusted Mean BMI z-Score Changes From Prebaseline (1 Year Before Baseline), Baseline, and 1-Year Follow-Up (N = 560).
Table 3 shows changes in participants' health-related quality of life and in parental resource empowerment during the 1-year intervention. Parents in the enhanced primary care plus coaching group (1.53 units; 95% CI, 0.51-2.56), but not in the enhanced care alone group (0.65 units; 95% CI, −0.38 to 1.67), reported improvements in their child's health-related quality of life, but the clinical significance of this magnitude of improvement is uncertain. Parental resource empowerment increased in both intervention arms (Table 3); however, there were no statistically significant differences in either family-centered outcome between the 2 intervention arms.
Changes in Pediatric Health-Related Quality of Life and Parental Resource Empowerment From Baseline to 1 Year, by Intervention Assignment (N = 721).
Parents' Perceptions of the Feasibility and Acceptability of the C4H Interventions.
We aimed for participants in the enhanced primary care group to receive monthly text messages and a Neighborhood Resource Guide. In follow-up interviews, 91% of parents reported that they received the text messages and 53% were satisfied with their content. Although we mailed the Neighborhood Resource Guide to 100% of participants, only 60% remembered receiving it, and of them, 66% reported being very satisfied with its content.
For the enhanced primary care plus coaching group, we aimed to deliver biweekly text messages, 6 contacts with a health coach, and tailored information about community resources from the health coach. Participants were also invited to join their local YMCA (with a free 1-month membership) and attend a Cooking Matters workshop at their health center. In follow-up interviews, 100% of participants reported receiving the text messages and 72% were very satisfied with their content. Among the 360 participants in the enhanced primary plus health coaching group, 65% completed all 6 visits with a health coach; 96% of participants reported receiving neighborhood resource information and 76% were very satisfied with the information. Based on follow-up interviews, 81 parents (23%) reported joining their local YMCA and 64 parents (18%) reported attending 1 of the Cooking Matters workshops.
Overall, 48% of participants in the enhanced primary care arm and 63% of participants in the enhanced primary care plus health coaching arm reported that participation in Connect for Health increased their satisfaction with their child's health care services. Only 7 (1.1%) participants reported that their participation in the Connect for Health program decreased their satisfaction with their child's health care services, and there were no differences across study arms.
In this randomized controlled trial, we found that 2 interventions that delivered enhanced primary care and leveraged clinical and community resources for childhood obesity support resulted in modest improvements in child BMI z-score and greater resolution of elevated BMIs. While the magnitude of reduction in BMI z-score was higher in the intervention group that additionally received interactive, contextually tailored health coaching, the difference compared with the group exposed to enhanced care alone was not statistically or clinically significant. Both interventions also led to improved family-centered outcomes including child health-related quality of life and parental resource empowerment; however, there were no statistically significant differences in either family-centered outcome between the 2 intervention groups. Overall, the intervention components were feasible to deliver, acceptable to parents, and did not have adverse effects on parent's perceptions of their child's health care services.
The Connect for Health study was designed with the hypothesis that the intervention group receiving both enhanced primary care and health coaching tailored to children's community resources and social context would be more effective than the group receiving enhanced primary care alone. Yet, our findings did not support this hypothesis, and there are several potential reasons. First, the enhanced primary care group was not a typical “usual care” control group. The practices where we delivered the study had already made several updates to their electronic health record to include clinical decision support tools and to provide families with educational materials for self-guided behavior change support. It would have been unethical to undo these practice changes once they were already established and after evidence supported their effectiveness in improving child BMI.17 Second, based on feedback from our parent and youth advisory boards, we made the decision to add content on social and emotional wellness to existing parent educational materials and to provide passive information in the form of a booklet on neighborhood resources. Both of these enhancements to the materials available to the group that did not receive health coaching could have further strengthened the effects of the control group on improving BMI. Third, it is possible that the number of contacts, frequency, or content of the health coaching provided in the enhanced primary care plus coaching group was insufficient to produce greater effects than that of the enhanced primary care group alone.
While our findings did not support the original hypothesis of a greater intervention effect among the group that was individually coached, our findings do suggest that both intervention groups experienced improved BMI. Without a traditional control group, our results could be attributed to temporal trends or regression to the mean. Post hoc analyses of BMI changes before and after enrollment in the trial suggest, however, that the temporal trend was for BMI z-score to continue increasing after enrollment. Thus, our results are unlikely due to secular trends, but regression toward the mean may still be a possibility.
The magnitudes of effect on BMI z-score in our study (eg, −0.06 to −0.09 units) are similar and only modestly higher than those previously summarized (−0.04 units) in a meta-analysis of brief interventions in primary care.39 While interventions with these magnitudes of effect appear to have interrupted the increasing BMI trends in our population, questions remain about their clinical significance. There is currently a lack of direct evidence for any specific weight loss threshold that has clinical significance.38 An expert panel in Germany has suggested that a BMI z-score reduction of 0.20 units is associated with clinically significant improvement.40 Other studies suggest that changes of 0.15 BMI z-score units led to more healthful cardio-metabolic profiles.38 As suggested by the recent US Preventive Service Task Force Draft Evidence Review of childhood obesity management, regardless of the threshold of clinical significance chosen, simply arresting gain in excess BMI likely constitutes a clinically important benefit for many children.38
In addition to BMI, this study examined family-centered outcomes of importance to parents and children and informed by a parent advisory board and a youth advisory board. We found that parent-reported child health-related quality of life improved by 1.53 units among the enhanced primary care plus coaching group and appeared to be driven by large improvements—comparably higher than previous pediatric obesity trials39—in the psychosocial score of the PedsQL. These effects in the health coaching group were not significantly greater than those of the enhanced primary care group. These findings suggest that the educational content delivered in both intervention arms related to social and emotional wellness, including content on stress reduction, positive thinking, and bullying, may have driven the observed improvements in child quality of life. Both interventions also improved parents' perception of empowerment related to their child's weight management—a novel, family-centered measure that has been shown to drive changes in food intake, physical activity, and screen-related parenting among parents of children with obesity.41,42
Given the positive temporal trends across both intervention groups but lack of superiority of the enhanced primary care plus coaching group, pediatric primary practices may want to consider implementing just the intervention components in the enhanced primary care group. These included computerized, clinical decision support tools for primary care providers in the electronic health record, a comprehensive set of educational materials focused on specified behavioral targets to support family self-guided behavior change, text messages, and a list of neighborhood resources that support healthy living in the community. Implementation of these components would require (1) clinician education and academic detailing that could be delivered through a learning collaborative on the clinical decision support tools and educational materials, (2) clinical informatics support to program the clinical decision support tools into the electronic health records locally or centrally, (3) use of a platform to enroll families in a text messaging campaign and deliver automated messages, and (4) development of an inventory of local neighborhood resources that could support family behavior change.
As in any study, this one is subject to potential limitations. First, as previously described, our post hoc analyses showing an increasing trend in BMI z-score before intervention enrollment suggest either that we were successful in reversing an upward trend or that our results reflect regression to the mean; we are unable to rule out the possibility of the latter. Second, the study setting—a multisite delivery system with a robust electronic health record—may not be representative of many smaller pediatric practices in the United States and beyond. However, as a relatively large medical group, HVMA is a typical primary care setting for many children. Moreover, meaningful use incentives are promoting increases in electronic health record adoption in both large and small pediatric practices.43 Thus, the Connect for Health interventions are likely to generalize to more and more pediatric settings in the future.
Our intervention did not appear to decrease the percentage of children with severe obesity. Previous studies have suggested that the magnitude of decreases in net daily energy intake necessary for children with severe obesity to achieve a healthy weight is considerably greater than is feasible with the pediatric weight management that can be delivered in primary care–based interventions such as Connect for Health.44,45 Our findings support the urgent recommendation for evidence-based, more-aggressive weight management approaches for children with severe obesity.45
Two interventions that included a package of high-quality clinical care for obesity and linkages to community resources resulted in improved parent-reported outcomes for childhood obesity and improvements in child BMI. While individualized health coaching led to improvements in health-related quality of life, it did not have significantly greater effects on child BMI than did enhanced primary care alone.
Address correspondence to: Elsie M. Taveras, MD, MPH, Division of General Academic Pediatrics, Department of Pediatrics, Massachusetts General Hospital for Children, Boston, MA. Email: ude.dravrah.hgm@sarevat.eisle.
Research reported in this report was [partially] funded through a Patient-Centered Outcomes Research Institute® (PCORI®) Award (IH-1304-6739). Further information available at: https://www.pcori.org/research-results/2013/do-weight-management-programs-involving-health-coaches-improve-body-mass-index-and-parent-empowerment-children-obesity-or-who-are-overweight
BestPractice Alert (PDF, 126K)
Connect 4 Health Intervention Text Messages (PDF, 95K)
Taveras EM, Marshall R, Sharifi M, et al. (2018). Do Weight Management Programs Involving Health Coaches Improve Body Mass Index and Parent Empowerment for Children with Obesity or Who Are Overweight? Patient-Centered Outcomes Research Institute (PCORI). https://doi.org/10.25302/3.2018.IH.13046739
The [views, statements, opinions] presented in this report are solely the responsibility of the author(s) and do not necessarily represent the views of the Patient-Centered Outcomes Research Institute® (PCORI®), its Board of Governors or Methodology Committee.
This book is distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License which permits noncommercial use and distribution provided the original author(s) and source are credited. (See https://creativecommons.org/licenses/by-nc-nd/4.0/
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