Item-level Informant Discrepancies Between Children and Their Parents on the PROMIS® Pediatric Scales
Published in: Quality of Life Research, v. 24, no. 8, Aug. 2015, p. 1921-1937
Posted on RAND.org on November 23, 2015
OBJECTIVE: The study objective was to describe the individual item-level discrepancies between children ages 8–17 years and their parents for the PROMIS® pediatric scales. Contextual effects on item-level informant discrepancies for the pediatric pain interference items were further analyzed conditional on whether the child, the parent, or anyone else in the household experienced chronic pain. METHODS: Parallel pediatric self-report and parent proxy-report items were completed by approximately 300 parent–child dyads depending on form assignment and individual nonresponse. Agreement between parent and child responses to individual items was measured using the polychoric correlation coefficient and weighted κ. The Chi-square test of symmetry was utilized for a comparison of the pattern of parent–child item discrepancies on the response scales, and the differences between the child and parent responses on the 1–5 item response scale are summarized. RESULTS: A continuum of higher item-level parent–child discrepancies was demonstrated starting with peer relationships, anger, anxiety, and depressive symptoms, followed by progressively lower parent–child discrepancies for energy, fatigue, asthma impact, pain interference, upper extremity, and mobility items. Parent–child discrepancies for pain interference items were lower in the context of chronic pain either in the child or in the parent. CONCLUSIONS: Parent–child item-level discrepancies were lower for more objective or visible items than for items measuring internal states or less observable items measuring latent variables such as peer relationships and fatigue. Future research should focus on the child and parent characteristics that influence domain-specific item-level discrepancies, and under what conditions item-level parent–child discrepancies predict child health outcomes.