Patient-Reported Outcomes to Describe Global Health and Family Relationships in Pediatric Weight Management

Abstract

Background:

Patient-reported outcomes (PROs) can assess chronic health. The study aims were to pilot a survey through the PEDSnet Healthy Weight Network (HWN), collecting PROs in tertiary care pediatric weight management programs (PWMP) in the United States, and demonstrate that a 50% enrollment rate was feasible; describe PROs in this population; and explore the relationship between child/family characteristics and PROs.

Methods:

Participants included 12- to 18-year-old patients and parents of 5- to 18-year-olds receiving care at PWMP in eight HWN sites. Patient-Reported Outcomes Measurement Information System (PROMIS^®) measures assessed global health (GH), fatigue, stress, and family relationships (FR). T-score cut points defined poor GH or FR or severe fatigue or stress. Generalized estimating equations explored relationships between patient/family characteristics and PROMIS measures.

Results:

Overall, 63% of eligible parents and 52% of eligible children enrolled. Seven sites achieved the goal enrollment for parents and four for children. Participants included 1447 children. By self-report, 44.6% reported poor GH, 8.6% poor FR, 9.3% severe fatigue, and 7.6% severe stress. Multiple-parent household was associated with lower odds of poor GH by parent proxy report [adjusted odds ratio (aOR) 0.69, 95% confidence interval (CI) 0.55–0.88] and poor FR by self-report (aOR 0.36, 95% CI 0.17–0.74). Parents were significantly more likely to report that the child had poor GH and poor FR when a child had multiple households.

Conclusions:

PROs were feasibly assessed across the HWN, although implementation varied by site. Nearly half of the children seeking care in PWMP reported poor GH, and family context may play a role. Future work may build on this pilot to show how PROs can inform clinical care in PWMP.

Introduction

Childhood obesity in the United States has increased among both school-age children (6–11 years) and adolescents (12–19 years) over the last two decades and affects ∼19.3% of children and 20.9% of adolescents.¹ The PEDSnet Healthy Weight Network (HWN) was formed in 2014 to bring together patients with obesity, their parent/guardians, clinicians, and researchers to collaborate in prioritization and execution of research and quality improvement activities in tertiary care pediatric weight management programs (PWMP).

The Patient-Centered Outcomes Research Institute funded HWN under an award to eight children's hospitals/health systems as part of PEDSnet, a clinical data research network.² A key deliverable for HWN was development and implementation of a survey to collect patient-reported outcomes (PROs) relevant to childhood obesity and informed by patient and parent stakeholders.

PROs refer to information that comes directly from the patient without interpretation by medical staff.³ PROs allow patients and parents to report on conditions where quality of life and patient perception of a condition's impact on health are integrated into the goals of care. In pediatrics, PROs provide a perspective into the impact of chronic health conditions and disease status and its treatment.⁴

The Patient-Reported Outcomes Measurement Information System (PROMIS^®) is a collection of assessments designed for pediatric patients across general health areas, including emotional health and global well-being, and used to investigate pediatric chronic conditions, including cancer, sickle cell, and rheumatologic disease.^5,6 Each assessment is designed to have validity, reliability, and the ability to detect change among a certain patient population.⁴

A study of 136 children with obesity using 8 self-report PROMIS scales revealed higher anger and fatigue and lower mobility in patients with higher BMI percentiles.⁵ Other studies have used health-related quality of life (HRQOL) scales to investigate overall and psychosocial health and suggest reduced HRQOL among children and adolescents with obesity.⁷

Children with chronic conditions, such as asthma or diabetes, may have weaker family relationships (FR) when they are older or challenged by concomitant mental health concerns,⁸ and a relationship between family functioning and pediatric obesity has also been observed.⁹

The aims of this study were (1) to pilot a survey through the HWN to collect PROs relevant to childhood obesity; (2) to describe PROs in this population; and (3) to explore the relationship between child and family characteristics and PROs. The goals were to demonstrate that at least a 50% response rate for the survey was feasible in the context of routine care delivery and provide descriptive and exploratory analyses to inform future research and improvement efforts.

Materials and Methods

Participants

Participants included patients aged 12–18 years and parent/guardians (hereafter “parents”) of patients aged 5–18 years receiving care for pediatric obesity at tertiary care PWMP in one of eight HWN participating hospitals/health systems. Participants had to be proficient in English or Spanish. Patients and/or parents not physically or cognitively able to self-report on a survey, as determined by the parents or existing diagnoses documented in the patient's medical chart or reported by their physician, were excluded.

Patients with ICD-9 codes 758.0 (Down's syndrome), 759.81 (Prader–Willi syndrome), or 759.83 (fragile X syndrome) were excluded. Those with ICD-9 codes 299–299.9 (autism disorders), 314 (attention deficit disorders), and 315–315.9 (developmental delays) were screened by a clinician or site principal investigator for eligibility. Patients were not excluded based on BMI.

Setting

Participants were recruited from eight PEDSnet institutions in the United States: Boston Children's Hospital; Cincinnati Children's Hospital Medical Center (CCHMC); Children's Hospital of Philadelphia; Children's Hospital Colorado; Nationwide Children's Hospital; Nemours Children's Health System, including Nemours Children's Hospital, DE, and Nemours Children's Hospital, FL; Seattle Children's Hospital; and St. Louis Children's Hospital.

HWN utilized a Master Reliance Agreement, and the CCHMC Institutional Review Board reviewed and approved the study, including waiver of informed consent/assent.

Screening and Recruitment of Participants

Methods and resources for screening and recruiting participants varied across sites. Seven sites had staff prescreen patients for eligibility at upcoming visits using their electronic health record (EHR). Eligible participants were approached at a visit and invited to participate. One site utilized EHR alerts that notified staff about eligible patients. No participation incentive was offered. Patients and families on the HWN team consulted on study implementation.

Data Collection

Data collection was completed at each site using either a paper or electronic version of each survey depending on workflow, site preference, and available resources. Sites conducted data collection for ∼90 days between April 2015 and September 2015, with four sites using each collection method (Table 1). Electronic surveys were generated using either REDCap (Research Electronic Data Capture)¹⁰ or DatStat Illume (Copyright © 2015 DatStat, Seattle, WA).

Table 1.

Site Recruitment and Enrollment

Site	Start date	End date	Survey administration mode	Eligible screened (n)	Enrolled (n)	Survey participation rate (%)	Eligible screened (n)	Enrolled (n)	Survey participation rate (%)
Site	Start date	End date	Survey administration mode	Parent/guardian			Child
Overall				2317	1461	63	1211	638	52
1	May 12, 2015	August 13, 2015	Paper	288	115	40	137	54	39
2	May 15, 2015	August 21, 2015	Paper	109	56	51	52	25	48
3	May 28, 2015	September 1, 2015	Electronic	199	103	52	82	31	38
4	June 3, 2015	September 1, 2015	Paper	136	98	72	131	90	69
5	May 29, 2015	August 28, 2015	Paper	464	314	67	241	157	65
6	April 14, 2015	July 15, 2015	Electronic	37	35	95	21	20	95
7	May 26, 2015	August 28, 2015	Electronic	472	430	91	225	89	40
8	May 22, 2015	August 28, 2015	Electronic	612	310	50	322	172	53

Recruitment and survey data were collected locally and submitted to the PEDSnet Data Coordinating Center (DCC) at Children's Hospital of Philadelphia. Clinical data were collected from the EHR independently and submitted to the DCC. These data could not be linked to survey data for this feasibility study, but available BMI data were provided for descriptive purposes.

Survey Development

The HWN team, including patients and parents, clinicians, and researchers, met in September 2014 to design the HWN charter, select PROs for the survey, and develop the study protocol. This meeting included 19 clinical staff and 15 parents and patients as stakeholders from HWN sites. Family stakeholders prioritized areas for data collection, including FR and structure, mental health, and well-being.

Survey Measures

Surveys were available in English and Spanish with parent proxy and adolescent versions. Each survey included an introduction designed by the patients and families about why the survey and PROs are important, including information about how the survey was codesigned with patients and families and would help inform care that patients received from their clinical team.

Each survey included consent information, sociodemographic questions, selected PROMIS measures to assess PROs, and an assessment of interest in future study participation. The child and parent surveys included 20 and 24 questions, respectively.

Sociodemographic data

The survey collected information to describe the child's age and gender; parent's gender and marital status; and the composition of the household. Both the child and parent were asked to report the child's race and ethnicity (categories in Table 2 chosen during the design meeting with patient and parent input). Questions about marital status and household composition were from the Psychosocial Assessment Tool with permission.¹¹

Table 2.

Characteristics of the Population

Characteristic	n (%)
Child (N = 1447)
Gender
Male	595 (41)
Female	841 (58)
Other	4 (0.3)
Missing	7 (0.5)
Age (years)
5–11	707 (49)
12–18	727 (50)
Missing	13 (1)
Race and ethnicity^a
Asian/Pacific Islander	27 (2)
Black, non-Hispanic	426 (29)
Latino or Hispanic	348 (24)
Native American or Aleut	7 (0.5)
White/Caucasian, non-Hispanic	517 (36)
Other	104 (7)
Missing	18 (1)
Main caregiver married/partnered	759 (53)
Multiple-parent household^b	856 (59)
Other residents in the household^c	336 (23)
Other children in the household^d	971 (67)
Significant time in multiple households	282 (20)
Parent/guardian (N = 1379)
Gender
Male	246 (18)
Female	1113 (81)
Missing	20 (1)

Parent report of child's race and ethnicity was used to supplement missing child self-report of race and ethnicity.

Includes at least two of the following: mother, father, and/or step-parent.

Includes grandparents, other family, and/or family friend.

Includes siblings and/or step-siblings.

Patient-reported outcomes

The following scales were included: PROMIS Pediatric Scale, v1.0–Global Health 7; PROMIS Parent Proxy Scale, v1.0–Global Health 7; PROMIS Pediatric Short Form, v1.0–Family Relationships 4a; and PROMIS Parent Proxy Short Form, v1.0–Family Relationships 4a.^12–14 Domains assessed in the 7-item global health (GH) scale include mental health, physical health, and social health.^13,15

The 4-item PROMIS Pediatric Family Relationships scale assesses the quality of the child's experience with family members.¹⁴ PROMIS pediatric and parent proxy items were used to assess fatigue and psychological stress.¹⁶

Data Analysis

For the final data set, the enrolled parent or adolescent had to have a completed survey with at least one valid data element. The first survey completed was used if multiple surveys were submitted by the same respondent. Parent report of child's race and ethnicity was used to supplement missing child self-report of race and ethnicity. Descriptive data are reported as mean [standard deviation (SD)] or proportion.

As family context was identified as the primary focus of interest from our patient and family stakeholders, sociodemographic data were used to create measures of household composition, including a multiple-parent household meaning that among mother, father, and/or step-parent, at least two live with the child; other residents in the household (e.g., grandparent, other family); other children in the household (e.g., siblings); and whether the child spends significant time in multiple households (“yes” response to “Does your child live or spend a significant amount of time in more than one home?”). Household composition variables were based on the responses of parents supplemented by those of the child when parent data were missing.

PROMIS scale theta scores and standard errors were generated according to established item response theory (IRT) protocols by the PEDSnet DCC and translated into a standardized T-score with a mean of 50 and SD of 10 using the relationship: T-score = 10 × theta +50.^17,18 Higher PROMIS T-scores represent more of the concept being measured. For each measure, corresponding percentiles for mean PROMIS T-scores were identified, and established cut points for a nationally representative, US pediatric referent population that defined groups as having poor pediatric GH or FR or severe fatigue or stress were applied.¹⁹ Cut points for the full fatigue and psychological stress scales were used as estimates. Comparisons within dyads were made using McNemar's χ² and Cohen's κ coefficient.²⁰

For parent proxy and self-report, relationships between child and parent characteristics and odds of poor GH or FR and of severe fatigue or stress were assessed using generalized estimating equations to account for clustering by site. Models were adjusted for child age, child gender, parent gender, and child race and ethnicity in addition to variables significant in parent proxy or self-report bivariate analyses at p < 0.1. As primary caregiver marital status and multiple-parent household were highly correlated, models were only adjusted for the presence of a multiple-parent household, where appropriate.

Results

Participation Rates and Participant Characteristics

A total of 1461 parents (63% of eligible participants) and 638 children (52% of eligible participants) enrolled (Table 1). There was variability in participation by site, with seven of eight demonstrating at least 50% parent participation and four of eight at least 50% child participation (Table 1). Of those enrolled, 1379 (94%) parents and 530 (83%) children provided a complete survey, which was included in the final data set. There were 1447 children included by parent proxy and/or self-report and 462 parent–child dyads.

Children were evenly spread across the recruitment age range, with slightly higher representation of girls (58%). In addition, 426 (29%) were non-Hispanic Black, 517 (36%) non-Hispanic White, and 348 (24%) Hispanic. A total of 856 (59%) represented children in multiple-parent households, 336 (23%) had other residents, and 971 (67%) had other children in the home.

Based on EHR data available for 1205 enrolled participants, 97.1% had BMI ≥95th percentile, indicating obesity, and 65.5% had BMI at or above 120% of the 95th percentile, indicating severe obesity. Detailed characteristics are summarized in Table 2.

PRO Measures: Overall Summary

Child and parent proxy PROMIS mean T-scores and the corresponding national percentiles from a representative, US sample¹⁹ are shown in Table 3. Overall, 44.6% of children reported poor GH, 8.6% poor FR, 9.3% severe fatigue, and 7.6% severe stress. Parent proxy reports categorized children as 43.7% with poor GH, 15.5% poor FR, 20.4% severe fatigue, and 14.4% severe stress.

Table 3.

Parent Proxy and Self-Report Patient-Reported Outcomes Measurement Information System Measures

PROMIS^® Measure^a	Parent proxy, T-score			Child self-report, T-score
PROMIS^® Measure^a	n	Mean (SD), National percentile	Poor/severe,^b n (%)	n	Mean (SD), National percentile	Poor/severe,^b n (%)
Pediatric Global Health Scale	1372	37.3 (8.6), 10	599 (43.7)	527	38.4 (7.6), 15	235 (44.6)
Pediatric Family Relationships Scale	1366	49.2 (9.2), 43	211 (15.5)	523	47.0 (9.6), 40	45 (8.6)
Fatigue	1366	53.0 (7.6), 86	279 (20.4)	525	51.1 (7.2), 85	49 (9.3)
Stress	1365	53.1 (8.8), 61	197 (14.4)	525	52.8 (8.0), 61	40 (7.6)

For Global Health and Family Relationships scales, higher T-score and percentile correspond to better function. For fatigue and stress, lower T-score and percentile correspond to better function. The national percentiles were obtained from a study of PROMIS measures in a nationally representative, US sample.¹⁹

Poor global health/family relationships refer to ≤5th percentile and severe fatigue/stress refers to ≥95th percentile.

PROMIS, Patient-Reported Outcomes Measurement Information System; SD, standard deviation.

Among dyads, in a subset, both reported poor GH (32.2%), poor FR (3.8%), severe fatigue (6.0%), or severe stress (5.3%). There were significant child–parent proxy differences (p < 0.01 for all), and kappa coefficients showed slight to fair agreement (0.13–0.39).

PRO Measures: Relationship With Child and Family Characteristics

Child and family characteristics associated with reported poor GH and poor FR are summarized in Table 4. By parent proxy report, the odds of a child having poor GH were significantly higher for adolescents compared with school-age children [adjusted odds ratio (aOR) 1.81, 95% confidence interval (CI) 1.44–2.27], as were the odds of poor FR (aOR 2.19, 95% CI 1.59–3.02).

Table 4.

Predictors of Patient-Reported Outcomes Assessed by Patient-Reported Outcomes Measurement Information System Measures

Predictor	PROMIS measure, parent proxy (n = 1379)		PROMIS measure, child self-report (n = 530)
Predictor	Unadjusted	Adjusted^a	Unadjusted	Adjusted^b
Poor global health, OR (95% CI)
Child age 12–18 vs. 5–11 years	1.82 (1.46–2.27)	1.81 (1.44–2.27)	—	—
Child female vs. male^c	1.17 (0.94–1.45)	1.04 (0.82–1.32)	1.54 (1.06–2.25)	1.41 (0.93–2.14)
Parent female vs. male	1.50 (1.12–2.00)	1.48 (1.09–2.02)	1.02 (0.59–1.77)	1.01 (0.56–1.82)
Child race and ethnicity^d
African American, Non-Hispanic	1.54 (1.17–2.02)	1.29 (0.97–1.73)	1.36 (0.89–2.07)	1.14 (0.71–1.84)
Asian/Pacific Islander	1.57 (0.70–3.52)	1.71 (0.75–3.93)	0.75 (0.18–3.12)	0.45 (0.09–2.34)
Latino or Hispanic	1.03 (0.77–1.37)	1.08 (0.80–1.45)	1.27 (0.79–2.06)	1.08 (0.64–1.83)
Other	1.29 (0.83–2.01)	1.19 (0.75–1.88)	1.44 (0.74–2.81)	1.36 (0.65–2.85)
Multiple-parent household^e	0.63 (0.51–0.79)	0.69 (0.55–0.88)	0.80 (0.56–1.13)	0.89 (0.60–1.33)
Other residents in the household	0.96 (0.74–1.24)	—	1.05 (0.69–1.60)	—
Other children in the household	1.16 (0.92–1.46)	—	1.24 (0.84–1.82)	—
Multiple households	1.32 (1.00–1.73)	1.43 (1.07–1.91)	1.64 (1.02–2.66)	1.62 (0.93–2.79)
Poor family relationships, OR (95% CI)
Child age 12–18 vs. 5–11 years	2.20 (1.62–2.99)	2.19 (1.59–3.02)	—	—
Child female vs. male^c	1.07 (0.79–1.44)	1.02 (0.74–1.41)	0.93 (0.48–1.78)	0.74 (0.36–1.53)
Parent female vs. male	1.19 (0.80–1.78)	1.16 (0.75–1.79)	1.06 (0.40–2.85)	0.97 (0.34–2.76)
Child race and ethnicity^d
African American, Non-Hispanic	1.52 (1.05–2.21)	1.31 (0.88–1.93)	1.64 (0.75–3.55)	1.22 (0.49–3.00)
Asian/Pacific Islander	0.89 (0.26–3.06)	0.92 (0.26–3.26)	4.17 (0.74–23.46)	4.71 (0.74–30.07)
Latino or Hispanic	1.13 (0.76–1.69)	1.01 (0.66–1.54)	1.28 (0.51–3.19)	1.55 (0.58–4.13)
Other	1.38 (0.77–2.48)	1.29 (0.71–2.35)	1.46 (0.44–4.82)	1.63 (0.47–5.73)
Multiple-parent household^e	0.64 (0.47–0.86)	0.75 (0.54–1.03)	0.52 (0.28–0.97)	0.36 (0.17–0.74)
Other residents in the household	0.98 (0.69–1.39)	—	0.78 (0.35–1.72)	—
Other children in the household	0.90 (0.66–1.23)	—	1.05 (0.53–2.10)	—
Multiple households	1.31 (0.92–1.86)	1.46 (1.00–2.11)	1.91 (0.92–3.95)	1.48 (0.64–3.45)

OR significant at p < 0.05, shown in bold.

Adjusted for child age, child gender, parent gender, child race and ethnicity, multiple-parent household, and multiple households.

Adjusted for child gender, parent gender, child race and ethnicity, multiple-parent household, and multiple households.

Child gender excludes the “other” category due to small sample size.

Reference group for race and ethnicity is “White/Caucasian, non-Hispanic” and excludes the “Native American or Aleut” category due to small sample size.

Reference group is single-parent household.

CI, confidence interval; OR, odds ratio.

A multiple-parent household was associated with significantly lower odds of poor FR by child self-report (aOR 0.36, 95% CI 0.17–0.74) and of poor GH by parent proxy report (aOR 0.69, 95% CI 0.55–0.88). Parents were also significantly more likely to report the child having poor GH and poor FR when a child spent time in multiple households (Table 4).

Parents were more likely to report the child having severe fatigue when the parent was female (aOR 2.29, 95% CI 1.46–3.58), the child was an adolescent (aOR 2.31, 95% CI 1.74–3.06), and when other children were in the home (aOR 1.37, 95% CI 1.01–1.87). Similarly, parents were more likely to report a child having severe stress when the parent was female (aOR 1.89, 95% CI 1.15–3.10) and when the child was an adolescent (aOR 2.09, 95% CI 1.52–2.88).

However, parents were significantly less likely to report a child with severe stress (aOR 0.48, 95% CI 0.32–0.73) or severe fatigue (aOR 0.69, 95% CI 0.49–0.97) when his/her race and ethnicity category was non-Hispanic Black compared with non-Hispanic White. In adjusted analyses, no child or family characteristics were significantly associated with severe fatigue or stress by self-report.

Discussion

As a chronic childhood condition that may adversely affect multiple domains of HRQOL, pediatric obesity is a condition for which PROs can offer valuable insights for patient care. Our study offered a comprehensive look at PROMIS measures by self-report and parent proxy across a pediatric network of tertiary care PWMP. Almost two-thirds of eligible parents and more than half of eligible children participated, demonstrating the ability to collect PROs in a clinical setting. This satisfied the overall HWN goal, demonstrating that at least 50% participation was feasible in the context of routine care delivery.

However, there was variability in participation across sites. While the majority of sites met the goal for parent recruitment, only half met the adolescent goal. Site size and workflow, as well as methods and resources for screening and recruitment, contributed to the feasibility at individual sites and are considerations for implementation in future work. Although survey administration time was not collected, based on prior studies, expected completion time was ∼5 minutes.^21,22

The pragmatic nature of the study, including the waiver of consent, brief nature of the survey, inclusion of survey content that was meaningful to families and clinicians, and integration of survey administration into the clinical workflow, reflects the potential relevance for translation to clinical practice.

In our sample, nearly half of the children (44.6%) and parents (43.7%) reported poor GH for the child. Studies have demonstrated impaired GH on PROMIS measures among children with special health care needs,²³ behavioral health diagnoses,²⁴ asthma,²⁴ diabetes,^24,25 inflammatory bowel disease,²⁵ and cystic fibrosis.²⁵ Obesity appears to have a similar impact on a family's perception of a child's GH.

This provides further support to the literature demonstrating poorer quality of life across multiple domains among children with obesity, especially those in clinical settings and with greater obesity severity.^26,27 This underscores the value of GH as an important health indicator to measure and address in children with obesity.

There were also some significant discrepancies between child and parent proxy reports similar to reports with PROMIS²⁸ and among children with obesity.^26,27,29 Such differences reinforce the importance of understanding both child and parent perspectives in delivering optimal health care for conditions such as obesity, which rely on family-centered treatment.

Our study also explored the association of the child and family characteristics with PROs. Nearly 9% of children reported poor FR. In addition, children living in multiple-parent households, just under 60% of the sample, had significantly lower odds of poor GH by parent proxy report and of poor FR by self-report. Related, children spending time in multiple households had significantly higher odds of poor GH and poor FR by parent report.

Our findings are similar to those of Forrest et al,²⁴ who reported lower PROMIS GH scores among children from single-caregiver households, and provide further support to the well-established relationship between single-caregiver households and worse child physical and mental health outcomes across multiple domains,^30,31 including obesity.^32–34

As described in the pediatric obesity literature^35,36 and supported by our HWN parent stakeholders, caregivers have an important role in providing children with the support and environment essential to promoting health, including implementing healthy lifestyle behaviors. These findings also underscore the importance of counseling to support family communication, relationships, and consistency between households for implementing lifestyle goals as a key component of pediatric weight management.

Other salient findings were that adolescents had worse PROs, a finding previously noted for the PROMIS GH scale.^13,24 Severe stress and fatigue among children were also less likely to be reported by a parent when the child had non-Hispanic Black compared with non-Hispanic White race and ethnicity. As our study was not specifically intended to assess differences in PROs across racial and ethnic groups, further work is needed to understand the impact of social determinants of health, including social and structural factors,³⁷ on PROs for families impacted by obesity.

Strengths of the study include the use of HWN to assess PROs by self- and parent proxy report across a network with geographic and patient heterogeneity and the collaboration among multiple stakeholders to develop an assessment tool that was meaningful for both families and clinicians. The findings remain highly relevant to pediatric weight management, especially given the impact of COVID-19 on obesity,^38–40 mental health,^41,42 and families,^43,44 and are of value given the size and scope of the sample.

The study does have limitations. The survey was intentionally short based on feedback from the patient and parent stakeholders. As a result, only a single item was used to assess stress and fatigue. Furthermore, some measures of socioeconomic status such as income or parental education, which may be associated with worse PROMIS scores,²⁴ were not included. Furthermore, a decision was made during the codesign process to simplify race and ethnicity categories for the purposes of the survey. However, there may be differences in PROs that are not described in our study because of how race and ethnicity were categorized. In addition, clinical data, including BMI, were not available for linkage to the survey data in this analysis.

Conclusions

In conclusion, a survey for PROs was developed and implemented across a network of tertiary care PWMP with input from patients and families. Results showed impaired GH assessed by both parent proxy and self-report and potential associations between family context and PROs. Further work can build on this exploratory effort to evaluate how monitoring PROs as part of comprehensive management for pediatric obesity may inform patient care and monitoring of patient progress.

Footnotes

Impact Statement

This study demonstrated the feasibility of collecting patient-reported outcomes (PROs) in tertiary care pediatric weight management programs (PWMP). Results suggest that family context may be associated with the health perspectives of the patient and caregiver. Future work may build on this pilot to show how PROs can inform clinical care in PWMP.

Acknowledgments

The authors would like to thank all the patient and family collaborators, the PEDSnet HWN project team, including the staff at the DCC, and the study participants. The authors would also like to thank the coinvestigators from the PEDSnet HWN: Sandra Hassink, MD, Nemours Children's Hospital, DE; Lenna Liu, MD, MPH, Seattle Children's Hospital; and Robert Siegel, MD, Cincinnati Children's Medical Center.

Authors' Contributions

E.T.R. was involved in conceptualization, methodology, formal analysis, supervision, and writing—original draft (lead); E.R.E. was involved in methodology, data curation, project administration, formal analysis, and writing—original draft; I.E., M.A.H., N.C.H., S.K., G.K., C.L., and S.K. were involved in conceptualization, methodology, supervision, and writing—review and editing; E.M.S. was involved in methodology, program administration, and writing—original draft; T.-L.T.P. and J.M.S. were involved in conceptualization, methodology, supervision, and writing—original draft; L.N.W. was involved in conceptualization, supervision, and writing—review and editing; K.A.Z. was involved in conceptualization, methodology, and writing—original draft; and C.B.F. was involved in methodology, supervision, funding acquisition, and writing—review and editing. All authors approved the final manuscript as submitted and agree to be accountable for all aspects of the work.

Disclaimer

The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Funding Information

The HWN was part of PEDSnet. PEDSnet is a Clinical Data Research Network in PCORnet^®, the National Patient-Centered Clinical Research Network, an initiative funded by the Patient-Centered Outcomes Research Institute (PCORI). PEDSnet's participation in development of PCORnet was partially funded through a PCORI award, 1306-01556. Dr. Lannon received funding from the PCORI PEDSnet award to support her work on this project. Dr. Phan receives support from the Eunice Kennedy Shriver National Institute of Child Health and Human Development of the National Institutes of Health (award No. K23HD083439).

Author Disclosure Statement

E.T.R. was previously the Site Principal Investigator for clinical trials sponsored by Merck and Astra Zeneca. E.R.E. is a current employee of Merck Sharp & Dohme LLC, a subsidiary of Merck & Co., Inc., Rahway, NJ, USA. E.M.S. is a current employee of Janssen of Johnson and Johnson. All other authors have no competing financial interests.

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