Background and aims
Muscle dysmorphia (MDM), or bigorexia, is a subcategory of body dysmorphic disorder (BDD), also known as “Adonis Complex” in nonscientific contexts. One of the most used tools to investigate MDM is the Adonis Complex Questionnaire (ACQ). The ACQ is a 13‐item US questionnaire, designed for male subjects only, related to the dissatisfaction and concerns about physical appearance. The aim of the current study was to evaluate the validity of the Italian version of the ACQ.
Methods
The instrument was administered to a sample of 322 male adults, recruited from the general population. We used the maximum‐likelihood confirmatory factorial analysis (CFA), analyzing the covariance matrices with AMOS 24.0, to evaluate the different factorial models proposed in the literature.
Results
The evaluation of the factorial structure of the Italian version of the ACQ demonstrates the greater stability and internal consistency of the two‐factor model, compared to the original three‐factor model. The factors have no correlation with the demographic characteristics of the sample.
Conclusions
The present study confirms the validity and the reliability of the Italian two‐factor version of the ACQ and highlights the general tendency, among Italian males, to have concerns about their own physical appearance with recurring thoughts and eating behaviors finalized to improve it. Our study represents an advance in the use of adequate and reliable instruments to assess concerns about physical appearance in the Italian male population.
The use of observational tools in psychological assessment has decreased in recent years, mainly due to its personnel and time costs, and researchers have not explored methodological innovations like adaptive algorithms in observational assessment. In the present study, we introduce the behavior-driven observation procedure to develop, test, and implement observational adaptive instruments. In Study 1, we use a preexisting observational checklist to evaluate nonverbal behaviors related to psychotic symptoms and to specify the adaptive algorithm’s model. We fit the model to observational data collected from 114 participants. The results support the model’s goodness of fit. In Study 2, we use the estimated model parameters to calibrate the adaptive procedure and test the algorithm for accuracy and efficiency in adaptively reconstructing 58 nonadaptively collected response patterns. The results show the algorithm’s good accuracy and efficiency, with a 40% average reduction in the number of administered items. In Study 3, we used real raters to test the adaptive checklist built with behavior-driven observation. The results indicate adequate intrarater agreement and good consistency of the observed response patterns. In conclusion, the results support the possibility of using behavior-driven observation to create accurate and affordable (in terms of resources) observational assessment tools.
The discovery of psychoanalysis and of psychotropic medications represent two radical events in understanding and treatment of mental suffering. The growth of both disciplines together with the awareness of the impracticality of curing mental suffering only through pharmacological molecules-the collapse of the "Great Illusion"-and the experience of psychoanalysts using psychotropic medications along with depth psychotherapeutic treatment, have led to integrated therapies which are arguably more effective than either modality alone. The authors review studies on the role of pharmacotherapy with psychoanalysis, and the role of the analyst as the prescriber. The psychotic disorders have specifically been considered from this perspective.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.