Multidimensional emotional disorders inventory: Reliability and validity in a Spanish clinical sample.

BACKGROUND: The categorical approach to diagnosing mental disorders has been criticized for a number of reasons (e.g., high rates of comorbidity; larger number of diagnostic categories and combination). Diverse alternatives have been proposed using a hybrid or totally dimensional perspective. Despite the evidence supporting use of the Multidimensional Emotional Disorders Inventory (MEDI) for assessing the transdiagnostic dimensions of Emotional Disorders using a dimensional-categorical hybrid approach, no data exist on Spanish clinical samples. The present study explores the validity and reliability of the 49-item MEDI in a clinical sample and provides data for its use. METHODS: A total of 280 outpatients with emotional disorders attended in different Spanish public Mental Health Units in Spain filled out all questionnaires during the assessment phase and the MEDI again one week after. The instruments used evaluate four main constructs: personality, mood, anxiety and avoidance. RESULTS: The nine original factors were confirmed and showed adequate reliability (α: 0.66-0.91) and stability (r = 0.76-0.87). No differences in mean scores by sex were presented in any subscale (p ≥ .07). The MEDI subscales correlated significantly with the scales of each of the selected constructs (0.45 < r < 0.76). LIMITATIONS: The main limitations of this study were the limited sample size and not being able to count on MEDI scores post-transdiagnostic intervention. CONCLUSIONS: The MEDI demonstrates adequate reliability and validity. It allows to assess diverse symptoms efficiently, thus being of interest for clinical studies and practice.

Clinical symptoms and personality traits predict subpopulations of treatment-seeking substance users.

BACKGROUND: The heterogeneity of treatment-seeking substance users represents a challenge, as most studies include participants having problems with specific substances or merge polysubstance users into the same category without considering differences between profiles. Considering the inconsistent literature on predictors of treatment outcomes, this study aimed to identify subpopulations of individuals with substance use disorders (SUDs) and analyze the association among class membership, previous relapses, and treatment retention. METHODS: The study recruited a total of 159 participants (mean age = 40.60, SD = 8.70; 85.5% males) from two treatment facilities (outpatient daycare and inpatient residential centers). The baseline assessment gathered lifetime and current substance use, and personality and psychopathology measures. The study performed a latent class analysis to identify subpopulations of substance users and explored predictors of class membership using a multinomial regression analysis. RESULTS: The study found six different classes of substance users based on their diagnosis and pattern of substance use: class 1 (6.92% of participants): individuals with cannabis as primary substance, alcohol/cocaine as secondary substance and additional use of stimulants or other drugs; class 2 (30.82%): cocaine as primary substance, alcohol as secondary and additional cannabis use; class 3 (20.13%): alcohol as primary substance, cocaine as secondary and additional cannabis use; class 4 (17.61%): cocaine as primary substance, cannabis as secondary and additional alcohol/other drugs use; class 5 (16.35%): alcohol as primary and cannabis as secondary substance; class 6 (8.18%): heroin as primary substance, cocaine as secondary and additional alcohol use. Several traits and clinical symptoms predicted distinct class memberships. Participants pertaining to class 6 presented the highest number of relapses (M = 2.54, SD = 1.56). CONCLUSIONS: These results have several clinical implications. Belonging to class 6 was associated with a greater number of previous relapses. Also, specific psychopathological symptoms and personality traits may impact SUD treatment response, which may help clinicians to guide initial assessment and treatment allocation.