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Classifying Symptom Change in Eating Disorders: Clinical Significance Metrics for the Change in Eating Disorder Symptoms ScaleHwang, Anthony D. 12 July 2010 (has links) (PDF)
Despite well-established diagnostic measures and measures of specific dimensions of eating disorder symptomatology, little work has been done to develop a brief, comprehensive, and valid measure for assessing change in eating disorder symptoms. Further, empirically-supported change indices to assess treatment progression and outcome have not yet been developed. The Change in Eating Disorder Symptoms Scale (CHEDS) is a new comprehensive measure designed to assess progress and change during treatment in persons with diagnoses on the eating disorder spectrum. Previous studies have demonstrated the subscale structure, reliability, and validity of the CHEDS. This study determined clinically significant change criteria for the CHEDS to complement the studies that have supported the CHEDS as a reliable and valid measure of eating disorder symptomatology. The CHEDS was also compared to a life functioning scale, the Clinical Impairment Assessment. A reliable change index (RCI) was developed, which generated an inferential statistic that estimates the magnitude of change in a score necessary for a change score to be considered statistically reliable. A cutscore was also developed, which differentiates between functional and dysfunctional populations, between eating disordered clinical subjects and non-clinical subjects. Trajectories were identified using hierarchical linear modeling methods for use in conjunction with clinical significance criteria to aid in the tracking of symptoms during treatment, treatment decision-making, and tailoring treatment according to expected and observed progress. The clinical significance change criteria were then applied to the clinical sample to determine change patterns descriptive of recovered, reliable improvement, deterioration, and no change. Finally, a scoring program with clinical significance change criteria and trajectory analyses for total and subscale scores was developed.
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