Development and Validation of a Brief Measure of Eating Compulsivity (MEC).

Food addiction is increasingly being recognised as a contributory factor in overweight and obesity. Management of eating compulsivity, a key component of food addiction, may assist greatly in the successful treatment of obesity. Measurement of food addiction and its core characteristic of eating compulsivity is fundamental to increasing understandings of the concept of food addiction, its prevalence among people with and without obesity and its utility within a treatment context. The current study describes the development and initial validation of a brief measure of eating compulsivity that can be used within clinical and research settings to establish a person's level of eating compulsivity. Sixty five participants with a BMI ≥30 (mean BMI 38.1) were recruited from a general population sample within Christchurch, New Zealand. Participants completed the test version of the Measure of Eating Compulsivity (MEC) and the Yale Food Addiction Scale (YFAS) as well as providing self-reported measures of height and weight. The 10-item MEC was developed. This measure was shown to have excellent internal consistency (Cronbach's alpha =.946), based on a single factor accounting for 67.4% of the variance and excellent test-retest reliability (r =.923). MEC10 score was strongly predictive of being categorised as having food addiction based on the YFAS, although not associated with BMI. This brief tool is likely to have high utility in clinical and research settings and requires further validation with a range of populations including those with and without obesity, binge eating disorder and other eating disorders.

Patient predictors of alcohol treatment outcome: a systematic review.

Patient characteristics as predictors of alcohol use disorder treatment outcome were examined on three levels, identifying whether or not variables were significant predictors of drinking-related outcome in univariate analysis, in multivariate analysis, and in multivariate analyses limited to studies including several "key predictors." Also, a model was developed to predict total percentage of variance in treatment outcome accounted for in each study using each of the key predictors and a range of methodological factors. The most consistent univariate predictors were baseline alcohol consumption, dependence severity, employment, gender, psychopathology rating, treatment history, neuropsychological functioning, alcohol-related self-efficacy, motivation, socioeconomic status/income, treatment goal, and religion. When these key predictors were combined into multivariate analyses, baseline alcohol consumption and gender showed substantial reductions in predictive consistency whereas the remaining variables were not greatly affected. The most consistent predictors overall were dependence severity, psychopathology ratings, alcohol-related self-efficacy, motivation, and treatment goal. The two predictor variables most associated with greater variance accounted for in predictive models, when controlling for broader methodological variables, were baseline alcohol consumption and dependence severity. Few predictor variables were examined in more than a third of studies reviewed, and few variables were found to be significant predictors in a clear majority of studies. However, a subset of variables was identified, which collectively could be considered to represent a consistent set of predictors. Too few studies controlled for other important predictor variables. Attempts to synthesize findings were often hampered by lack of agreement of the best measure for predictor variables.