Comparing severity and qualitative facets of depression between eating disorders and depressive disorders: Analysis of routine data.

BACKGROUND: While it is know that depressive symptoms are common in eating disorders (EDs), it is unclear whether these symptoms differ from those in depressive disorders (DDs) with regard to severity and quality. METHODS: Beck Depression Inventory II (BDI-II) scores at admission to treatment of 4.895 inpatients with a unipolar DD and 3.302 inpatients with an ED were compared by means of independent t-tests and Cohen's d effect sizes with regard to: (1) overall severity (BDI-II total score), (2) six facets of depression identified by non-metric multidimensional scaling of the German BDI-II validation sample, and (3) individual items. RESULTS: (1) The two groups did not differ with regard to the BDI-II total score. (2) There was no difference in the facet Depressive Core Symptoms. Patients with DDs had higher scores for Diminished Activation (d = 0.40) and patients with EDs had higher scores for Negative View of Self (d = 0.40). (3) Patients with DDs showed higher score on the item Loss of Energy (d = 0.48), while patients with EDs sored higher on Self-Dislike (d = 0.48) and Changes of Appetite (d = 0.48). CONCLUSIONS: Depression in EDs seems to be as severe as in DDs and may show similar core aspects (e.g., Sadness, Loss of Pleasure). Qualitative differences suggested that individual additional symptoms of depression need to be differently addressed in therapy. The pronounced Negative View of Self in EDs is in line with the "core low self-esteem", a central component of the prevalent transdiagnostic model of EDs.

The predictive power of subgroups: an empirical approach to identify depressive symptom patterns that predict response to treatment.

BACKGROUND: Depression research has been trying to improve the response rates to treatments by identifying a valid set of differential predictor variables. Potential candidates have been proposed, one of which were different subtypes of depression. However, the results on the predictive quality of subtypes on treatment are conflicting. METHODS: The analyzed data consisted of Hamilton Depression Rating Scales (HAM-D17) of 879 depressive inpatients, which were recruited in a naturalistic multicenter study. Mean length of stay was 9.9 weeks. In a first step, a Latent Class Analysis (LCA) was conducted to classify the patients into smaller groups. In a second step, the class variable was included in a Linear Mixed Effects model to predict the same patients' response to treatment. RESULTS: Five classes were obtained from LCA, showing substantially different symptom profiles. One of the classes, with a symptom profile similar to melancholic depression, showed substantially slower response to treatment (i.e., estimated time to remission; 11.3 weeks) than the remaining classes in the study (6.6-8.6 weeks). LIMITATIONS: The applied measurement instrument, the HAM-D17, did not include items for two additional, frequently found subtypes of depression: psychotic and atypical depression. Thus, these subtypes could not emerge in the LCA. Furthermore, there was no systematic variation of treatment in the data. Thus, a differential effect of the classes on treatment could not be measured. CONCLUSIONS: The classification of patients according to their symptom profiles seems to be a potent predictor for treatment response. However, the obtained symptom patterns are not completely congruent with the theoretically proposed subgroups. Against the background of the results, dividing melancholic depression in a rather cognitive and vegetative subtype may be promising.

Activation as an overlooked factor in the BDI-II: a factor model based on core symptoms and qualitative aspects of depression.

An adequate assessment of depression has been of concern to many researchers over the last half-century. These efforts have brought forth a manifold of depression rating scales, of which the Beck Depression Inventory (BDI) is 1 of the most commonly used self-assessment scales. Since its revision, the item structure of the BDI-II has been examined in many factor analytic studies, yet it has not been possible to achieve a consensus about the underlying factor structure. Recent findings from a nonmetric multidimensional scaling (NMDS) analysis (Bühler, Keller, & Läge, 2012) of the German norming sample of the BDI-II emphasized a structure with different qualitative aspects of depression, which suggested that the existing factor models do not adequately represent the data. The NMDS results were reviewed, and on the basis of these findings, a different factor model is proposed. In contrast to the common factor models in the literature, the presented model includes an additional factor, which is associated with the activation level of the BDI-II symptoms. The model was evaluated with a 2nd sample of patients diagnosed with a primary affective disorder (N = 569) and obtained good fit indices that even exceeded the fit of the most reliable factor model (Ward, 2006) described in the literature so far. Furthermore, emphasis is placed on the methodological question of how factor models may be derived from the results of NMDS analyses.

Training of tonal similarity ratings in non-musicians: a "rapid learning" approach.

Although cognitive music psychology has a long tradition of expert-novice comparisons, experimental training studies are rare. Studies on the learning progress of trained novices in hearing harmonic relationships are still largely lacking. This paper presents a simple training concept using the example of tone/triad similarity ratings, demonstrating the gradual progress of non-musicians compared to musical experts: In a feedback-based "rapid learning" paradigm, participants had to decide for single tones and chords whether paired sounds matched each other well. Before and after the training sessions, they provided similarity judgments for a complete set of sound pairs. From these similarity matrices, individual relational sound maps, intended to display mental representations, were calculated by means of non-metric multidimensional scaling (NMDS), and were compared to an expert model through procrustean transformation. Approximately half of the novices showed substantial learning success, with some participants even reaching the level of professional musicians. Results speak for a fundamental ability to quickly train an understanding of harmony, show inter-individual differences in learning success, and demonstrate the suitability of the scaling method used for learning research in music and other domains. Results are discussed in the context of the "giftedness" debate.

Exploring the structure of psychopathological symptoms: a re-analysis of AMDP data by robust nonmetric multidimensional scaling.

This paper investigates the structure of psychopathological symptoms. Based on AMDP symptom profiles, a symptom space was calculated by robust nonmetric multidimensional scaling (NMDS) and the symptom structures of a sample dating from 1980 and a sample from 2002/2003 were compared. The method of NMDS presented in this study allows results from other studies to be confirmed and complemented. The symptom factors identified in the past by factor-analytic studies were replicated as clusters in two-dimensional symptom maps. Additionally, some theoretically assumed clusters of symptoms were detected that were not found in previous factor analysis approaches. From the results, which are depicted in a continuous space, new insights can be gained, especially with regard to questions of categorical and dimensional classifications. The comparison of the structural aspects of the symptomatology across more than two decades resulted in only small divergences and allows conclusions to be drawn about the stability of these structures and consequently of the symptom clusters and dimensions.

Combining the categorical and the dimensional perspective in a diagnostic map of psychotic disorders.

We introduce a diagnostic map that was calculated by robust non-metric multidimensional scaling based on AMDP symptom profiles of patients with schizophrenic and affective disorders to demonstrate a possibility to combine the categorical and the dimensional perspective at the same time. In the diagnostic map, a manic, a depressive, and a non-affective cluster clearly emerged. At the same time, the mania dimension (r = 0.82), the depression dimension (r = 0.68), and the apathy dimension (r = 0.74) showed high multiple regression values in the map. We found substantial overlaps of the diagnostic groups with regard to the affective spectrum but irrespective of the ICD-10 classification. Within this sample, we found the association and quality of mood symptoms to be a structuring principle in a diagnostic map. We demonstrate that this approach represents a promising way of combining the categorical and the dimensional perspective. As a practical implementation of these findings, a multidimensional diagnostic map could serve as an automated diagnostic tool based on psychopathological symptom profiles.

Creating a map of psychiatric patients based on psychopathological symptom profiles.

BACKGROUND: In the current debate about the categorical or dimensional classification of mental disorders many fruitful methods to illustrate one or the other aspect are employed, and suggestions are made to combine the two perspectives. METHODS: We present such an approach to combine both perspectives at the same time. Based on psychopathological AMDP-symptom profiles, a map of psychiatric patients was calculated by robust nonmetric multidimensional scaling (NMDS). RESULTS: The sample from the Ludwig-Maximilians University in Munich included the records of patients, who were admitted and discharged in 2002 and 2003 with a diagnosis of either paranoid schizophrenia, (F20.00, N = 24), bipolar affective disorder, current episode manic without psychotic symptoms (F31.1, N = 32) or severe depressive episode without psychotic symptoms (F32.2, N = 78). In the resulting map of patients we found a clear categorical distinction according to the diagnostic groups, but also high regression values of AMDP-syndromes (manic syndrome: r = 0.83, depressive syndrome: r = 0.68, and paranoid-hallucinatory syndrome, r = 0.62). DISCUSSION: The map of psychiatric patients presents an approach to consider the categorical and dimensional aspects at the same time. We were able to identify meaningful delineations between diagnostic clusters as well as continuous transitions. This method allows the whole psychopathological profile of each individual patient to be considered and also to identify misdiagnosed cases at a glance.

The structure-based expert model of the mental disorders--a validation study.

BACKGROUND: In an earlier study, our research group presented an alternative approach to measuring knowledge about mental disorders by constructing a structure-based expert model of the ICD-10 mental disorders. This article presents a validation of this expert model by measuring the emergence of such knowledge structures in psychotherapy students. SAMPLING AND METHODS: The participants of a continuing education program in cognitive behavioral psychotherapy rated a selection of mental disorders based on their phenomenological similarity. The similarity judgments of each student were translated by nonmetric multidimensional scaling (NMDS) into a cognitive map. In a quasi-longitudinal section design, the maps of the students of the first to the fourth year of training were compared with each other and with an expert map (the expert model) of experienced therapists. RESULTS: The discrepancies of the trainee maps compared with each other and with the expert map significantly decreased with increasing training level. CONCLUSIONS: The convergence of the students' maps towards the expert model indicates that the structural knowledge about mental disorders of experienced therapists can also be found to be emerging in psychotherapy students. This finding supports the validity of the expert model and may reflect a general knowledge-structuring principle of the mental disorders. In spite of the statistical significance found, in view of the small number of participants in the third and fourth years of training, the results should be treated with caution and should be regarded as first indicators which need further confirmation.

A structure-based expert model of the ICD-10 mental disorders.

BACKGROUND: Many authors have highlighted that a classificatory system such as the ICD-10 or the DSM-IV should attempt to integrate categorical as well as dimensional aspects rather than relying only on a categorical distinction. METHODS: In the current study, a method is presented that allows both perspectives to be considered. Based on their clinical experience, 20 therapists were asked to rate a selection of ICD-10 mental disorders in terms of their similarity. The resulting data were processed by nonmetric multidimensional scaling on individual basis as well as mean basis and a cluster analysis. RESULTS: From a categorical point of view, the resulting mean cognitive map and the cluster analytic groups showed a good concordance with the ICD-10 F groups. Additionally, analogies to the critical observations with regard to the classification systems could be observed. From the dimensional point of view, there were two dimensions found (cognition and psychosis) which showed high correlations in the mean map. CONCLUSIONS: The method presented in this study offers an opportunity to account for dimensional as well as categorical aspects of classification by exploring the structure of the ICD-10 mental disorders directly from the point of view of therapists and thus creating the basis for an expert model.

Mapas políticos: a relevância do nível de formaçäo para a estrutura subjetiva do panorama político brasileiro / Political maps: the educational dependency of the brazilian political lanscape's subjective structure

Examina o conhecimento político das camadas da populaçäo que possuem diferentes níveis de instruçäo através do modelo dos mapas políticos. O método da classificaçäo hierárquica revela relaçöes subjetivas de semelhanças entre partidos e políticos brasileiros. Traduz tais relaçöes em estruturas geométricas, por meio da escala multidimensional näo-métrica (Nonmetric Multidimensional Scaling - NMDS). Comparaçöes entre camadas da populaçäo com diferentes níveis de instruçäo demonstram que pessoas com formaçäo escolar deficiente têm muita dificuldade em classificar as estruturas dos grandes blocos políticos. A comparaçäo com uma investigaçäo feita paralelamente no Chile classifica os resultados num contexto de psicologia cognitiva. Discute também, a relevância do acesso à mídia

Mapas politicos: a relevancia do nivel de formacao para a estrutura subjetiva do panorama politico brasileiro

O conhecimento politico das camadas da producao que posssuem diferentes niveis de instrucao e examinado atraves do modelo dos mapas politico. O modelo da classificacao hierarquica permite revelar relacoes subjetivas de semelhancas entre partidos e politicos brasileiros. Tais relacoes podem ser traduzidas em estruturas geometricas, por meio da escala multidimensional nao-metrica (Nonmetric Multidimensional Scaling - NMDS). Comparacoes entre camadas da populacao com diferentes niveis de instrucao demonstram que pessoas com formacao escolar deficiente tem muita dificuldade em classificar as estruturas dos grandes blocos politicos. A comparacao com uma investigacao feita paralelamente no Chile permite classificar os resultados num contexto de psicologia cognitiva. Alem disso, a relevancia do acesso a midia e discutida.