Growth curve trajectories of distress in burn patients

Shawn T. Mason, Nida Corry, Neda F. Gould, Nicole Amoyal, Vincent Gabriel, Shelly Wiechman-Askay, Radha Holavanahalli, Sean Banks, Lisa Arceneaux, James A. Fauerbach

Research output: Contribution to journalArticlepeer-review

19 Scopus citations

Abstract

Psychological adjustment after a major burn injury is a significant concern to providers and patients alike. Although efforts have been made to identify associated risk factors, little is known about heterogeneity in the levels or trajectories of adjustment in this population. This study used a novel application of Growth Mixture Modeling to identify subgroups of patients based on their longitudinal self-reported distress using the Brief Symptom Inventory (BSI). Data were drawn from the database of the Burn Model Systems project, a prospective, multisite, cohort study of major burn injury survivors. The BSI was used to assess symptoms in-hospital and at 6, 12, and 24 months postburn. Participants' T scores on the BSIs Global Severity Index provided a continuous measure of psychological distress. Analyses were conducted using participants' Global Severity Index T scores to discern distinct classes of respondents with similar trajectories across the 2-year follow-up. Results from the Growth Mixture Modeling analysis produced an ordered four-class model of psychological recovery from a major burn. Groups represented the equivalent of high, subthreshold, mild, and minimal symptom severity. Covariates significantly affected the intercept and slope of each class, as well as prediction of group assignment. These analyses demonstrate differences between individual recoveries after a major burn. Psychological distress symptoms remain largely stable over time and highlight the psychological vulnerability of this patient population.

Original languageEnglish (US)
Pages (from-to)64-72
Number of pages9
JournalJournal of Burn Care and Research
Volume31
Issue number1
DOIs
StatePublished - Jan 2010

ASJC Scopus subject areas

  • General Medicine

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