520 - Measuring Quality of Life in Children with Medical Complexity
Friday, April 24, 2026
5:30pm - 8:00pm ET
Publication Number: 1500.520
Emily Cramer, Children's Mercy Kansas City, Kansas City, MO, United States; S. Margaret Wright, Children's Mercy Hospitals and Clinics, Kansas City, MO, United States; Luis E.. Sainz y Diaz, Children's Mercy, Kansas City, MO, United States; Isabella Zaniletti, IZ Statistics LLC, Tampa, FL, United States; Jeffrey D. Colvin, Children's Mercy Hospitals and Clinics, Kansas City, MO, United States
Associate Professor Children's Mercy Kansas City Kansas City, Missouri, United States
Background: Measuring quality of life (QOL) for children with medical complexity (CMC) is important for understanding the healthcare needs of CMC and their families as well as delivering consistent, high-quality care. The Cerebral Palsy Quality of Life Questionnaire (CP-QOL) is a well-established, valid tool for measuring quality of life in children with cerebral palsy, but the validity of the tool for the broader population of CMC is unknown. Objective: To evaluate and adapt an existing QOL instrument to the population of children with medical complexity. Design/Methods: Participants were enrolled caregivers in a research repository of CMC receiving primary care at a free-standing children’s hospital. Caregivers completed surveys (n=125), which included child and caregiver demographics, the CP-QOL, and other items. Confirmatory factor analysis (CFA) was used to evaluate the original CP-QOL factor structure. Next, items were examined for response patterns, and items with non-response >20% were deleted. The remaining items were then evaluated for conceptual meaning and regrouped into newly proposed factors and tested using CFA. Items with low factor loadings ( < 0.4) or multidimensionality (e.g. strong loadings with more than 1 factor) were deleted to reduce survey length and increase the validity of remaining factors. The new factor structure was further validated by testing the CFA on a data from a second administration of the survey (n=99). Scale reliability was evaluated using McDonald’s omega. CFA was performed on bootstrapped samples of survey data to increase sample size and reduce error. Results: The majority were aged 6-11 years (74.4%), non-Hispanic white (62.4%), and had ≥4 complex chronic conditions (56.8%) and technology dependence (84.8%) (Table 1). Following the response pattern evaluation, 9 items exceeded the 20% threshold for nonresponse and were deleted. Of the remaining 40 items, 23 (58%) were eliminated for significant overlap or low communality with other scale items. A final 4-factor structure was identified (Table 2). Model fit was adequate (CFI=0.88, SRMR=0.062), and scale reliability on individual subscales ranged from 0.83-0.92, with high overall scale reliability (ω=0.97). The subsequent validation on the second sample also demonstrated acceptable fit (CFI=0.86, SRMR=0.059), and overall scale reliability (ω=0.97).
Conclusion(s): The CP-QOL does not exhibit strong validity for use in the heterogeneous population of children with medical complexity. The proposed modifications provide a shortened version with better validity for this unique population.
