Comparing the most typical profiles from eating disorder patients before and after treatment.

What is it about?

OBJECTIVES: We investigated differential treatment effects on specific eating disorder (ED) indicators to enhance conclusions about treatment efficacy. METHODS: Profile Analysis via Multidimensional Scaling (PAMS), which identifies core profiles in a population and interprets person profiles with core profile information, was utilized to identify core profiles from a sample of 5177 patients who were repeatedly measured with the EDI-2 at admission and at discharge. To assess differential treatment effects for individual ED indicators, we compared the core profiles at admission with those at discharge. RESULTS: Three core profiles were identified and labeled as: High Body Dissatisfaction with Low Bulimia (Core Profile 1), High Interoceptive Awareness with Low Body Dissatisfaction (Core Profile 2), and High Ineffectiveness with Low Bulimia (Core Profile 3). Treatment had the greatest effects on Core Profile 2. The patients whose profile patterns were similar to that of Core Profiles 1 and 2 were positively related with weight gain. However, treatment was least on Core Profile 3 and the patients whose profile patterns were like that of Core Profile 3 were negatively related with weight gain. CONCLUSIONS: Those patients who fit Core Profile 3 may benefit from different treatment modalities than those that are standard in inpatient settings.

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Why is it important?

Core profiles were estimated in latent dimensions, but we diagnosed individual patients with core profile information. For example, utilizing person correlations, we know how well or poorly each patient's response profile (which is in fact an array of EDI-2 subscores) is related with core profiles. For example, in our Case 1 study, the person correlation with Core Profile 1 was 0.91 but the other correlations were trivial. Then, we know this person would carry the similar characteristics of Core Profile 1 (that had been already labeled and interpreted). However, in our Case 2 study, some patients had similar magnitude correlations with all three core profiles, and then we expect that such patients would carry traits or characteristics appearing in all three core profiles. Since we had 5177 patients, we could assess all of them as shown in Case 1 and Case 2 studies. The Profile Analysis vis Multidimensional Scaling (PAMS) approach demonstrated in the study has a capacity to identify the most typical profiles (so called core profiles) from a population, which is a MACRO approach, but also to assess individual patients in terms of the core profile information as demonstrated in our case studies, which is a MICRO approach.

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