Damian Läge’s research while affiliated with University of Zurich and other places

Judgments and decisions under uncertainty are frequently linked to a prior sequential search for relevant information. In such cases, the subject has to decide when to stop the search for information. Evidence accumulation models from social and cognitive psychology assume an active and sequential information search until enough evidence has been accumulated to pass a decision threshold. In line with such theories, we conceptualize the evidence threshold as the “desired level of confidence” (DLC) of a person. This model is tested against a fixed stopping rule (one-reason decision making) and against the class of multi-attribute information integrating models. A series of experiments using an information board for horse race betting demonstrates an advantage of the proposed model by measuring the individual DLC of each subject and confirming its correctness in two separate stages. In addition to a better understanding of the stopping rule (within the narrow framework of simple heuristics), the results indicate that individual aspiration levels might be a relevant factor when modelling decision making by task analysis of statistical environments.

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.

In this paper, two studies are reported in which children’s ability to distinguish reality from fantasy was investigated. In Experiment 1, children of different ages made pairwise comparisons of 12 pictures of fictional figures and 3 photographs of real people by evaluating on a 6-point scale how easily these figures could meet each other. The results revealed that fantasy/reality distinction develops with age: 7-8-year-olds showed a fundamental categorical distinction (comparable to that of adults) whereas 3-4-year-olds treated the real world like one of many worlds. In Experiment 2, we took an individual differences approach and tested 116 4-5-year-olds who performed the same fantasy task. In addition, they were presented with theory-of-mind tasks and tests measuring non-verbal intelligence and language skills. The results showed that, after statistically controlling for age, non-verbal intelligence, and language skills, theory-of-mind abilities still significantly contributed to the prediction of fantasy understanding.

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.

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. (PsycINFO Database Record (c) 2014 APA, all rights reserved).

In standardisierten psychopathologischen Inventaren werden die Ausprägungen von Symptomen erfasst, die entweder für bestimmte Kategorien von psychischen Störungen oder für die Psychopathologie allgemein bezeichnend sind. Bislang werden diese detaillierten Befunde, die routinemässig bei Patienten erhoben werden, allerdings mit nur wenigen aggregierten Kennzahlen beschrieben, womit ein Grossteil an systematischer Information verlorengeht. Egli, Riedel, Möller, Strauss und Läge (2009) haben das Verfahren der Patientenkarten vorgeschlagen – Eine NMDS-Analyse der psychopathologischen Befunde –, mithilfe derer ein hoher Grad an symptomatischer Detailinfor-mation aus den psychopathologischen Inventaren erhalten bleibt. Die Autoren diskutierten diese Patientenkarten allerdings primär im Hinblick auf die Statusdiagnostik. Im vorliegenden Manuskript wird der Vorschlag von Egli et al. (2009) aufgegriffen und die Möglichkeiten für einen Einsatz der Patientenkarten in der Verlaufsdiagnostik diskutiert. Besonderer Fokus wird auf die methodischen Komplikationen bei der lokalen Interpretation von NMDS-Lösungen gelegt, welche für die Anwendung der Patientenkarten von hoher Wichtigkeit sind. Ein Ansatz zur lokalen Optimierung der Patientenkarten wird aufgezeigt und mit den etablierten NMDS-Algorithmen verglichen. Die lokale Interpretierbarkeit der Patientenkarten bei Verwendung des neuen Ansatzes ist vielversprechend, denn sie übersteigt sowohl in der 2- als auch in der 3-dimensionalen NMDS-Lösung diejenige der etablierten Algorithmen.

An adequate assessment of depression has been a concern to many researches over the last half-century. These efforts have brought forth a manifold of depression rating scales, of which one of the most commonly used self-assessment scales is the Beck Depression Inventory (BDI). Since its revision by Beck, Steer, and Brown (1996), the item structure of the BDI-II has been examined in many factor analyses, both, exploratory and confirmatory. Yet, a consensus about the underlying factor structure could not be achieved.Aim/objectivesThe present study was conducted to reexamine the item structure based on robust Nonmetric Multidimensional Scaling (NMDS). The NMDS solution allows for evaluating the diverging results from the factor analyses conducted so far.Methods The norm sample of the German version of the BDI-II was used (Hautzinger, Keller, & Kühner, 2006), which consisted of N = 266 patients diagnosed with a major depressive disorder.ResultsThe NMDS solution emphasized a facet oriented structure and revealed the insufficiency of the factor analyses to adequately capture the data.Conclusions Based on the NMDS solution, we propose an item structure consisting of a depressive core syndrome, surrounded by five specific facets (Figure 1). The core syndrome measures the severity of the depression mainly, whereas the five facets pronounce different qualities inherent to depression.[Figure 1]

Theoretischer Hintergrund: Das BDI-II deckt mit 21 Depressionssymptomen die Breite der Depression ab und ist geeignet, die Symptomstruktur der Depression zu erforschen. Eine Vielzahl an faktorenanalytischen Studien erbrachte aber bislang keinen Konsens. Fragestellung: Nonmetrische Multidimensionale Skalierung (NMDS) soll daher die divergierenden Resultate einordnen und ein Modell der Symptomstruktur schaffen. Methode: Mittels NMDS wird die Symptomstruktur des BDI‐II (N = 266 Depressive) in einen 2‐dimensionalen Raum abgebildet. Ergebnisse: Die NMDS‐Lösung legt eine Facettenstruktur nahe, welche von den faktorenanalytischen Modellen bislang unzulänglich erfasst wird. Schlussfolgerungen: Neben einem generellen Kernsyndrom finden sich fünf spezifische Facetten (verminderte Aktivierung, psychovegetative Symptome, gesteigerte Aktivierung, Hoffnungslosigkeit und negative Einstellung zum Selbst), die die Heterogenität der Symptomatik innerhalb der Depression aufzeigen und damit die Existenz von Subtypen in der Depression nahelegen.