In the absence of a gold standard

Als er geen gouden standaard bestaat. Een gouden standaard is een meting die valide en zeer betrouwbaar is. Voor psychische problemen bestaan dergelijke gouden standaards meestal niet. Er is bijvoorbeeld veel twijfel over de validiteit van de categorieën van DSM-IV. Als alternatief wordt vaak voorgesteld om dimensionele modellen te gebruiken. Voor hoofdstuk 2 werden verschillende dimensionele modellen van psychopathologie ontworpen en getoetst. Het veel gebruikte model van internalizerende en externalizerende psychopathologie werd aangevuld met problemen die veel voorkomen bij kinderen met ‘autisme-spectrum stoornissen’. In hoofdstuk 3 wordt beargumenteerd dat dergelijke dimensionele modellen een betere basis vormen voor de ontwikkeling van een valide diagnostiek dan de DSM-IV categorieën. Bovendien wordt beschreven hoe een dimensioneel model de basis kan vormen voor het ontwikkelen van bruikbare categorieën voor de klinische praktijk. Verder worden er grote verschillen gevonden tussen informanten (bv. zelf, ouders, leraren) wat betreft de rapportage van symptomen. In hoofdstuk 4 wordt getracht een onderscheid te maken tussen de problemen van een individu en de context en het perspectief van waaruit informanten het individu beoordelen. In hoofdstuk 5 en 6 komen echter verschillende bezwaren tegen deze aanpak naar voren en wordt geconcludeerd dat daadwerkelijke problemen en de wijze van rapporteren hierover niet scherp te onderscheiden zijn. In de discussie worden de verschillende bevindingen gebruikt voor het ontwikkelen van een nieuwe benadering voor het interpreteren van gegevens van meerdere informanten. Deze benadering kan worden gebruikt in onderzoek en klinische praktijk waarin een gouden standaard ontbreekt.

Treatment Utility of Clinical Assessment

The extent to which clinical assessment enhances subsequent treatment benefits for patients has long been controversial, and we suggest specifying and examining more closely the conditions by which assessment can – or cannot - contribute to treatment process and ultimately patient benefit. We argue that this can contribute to more informative research on this very important question, and provide illustrative examples from clinical assessment practice

When and how assessment matters: An update on the Treatment Utility of Clinical Assessment (TUCA)

The Treatment Utility of Clinical Assessment (TUCA) has long been a controversial topic, with arguably more (strong) opinions than relevant, well-designed empirical research. We argue that this question has been tackled too broadly and that a more contextualized approach would likely be more informative. Instead of asking "what is the treatment utility of assessment," we suggest specifying and examining more closely the conditions by which assessment can-or cannot-contribute to treatment process and ultimately patient benefit. To this end, we present a heuristic model for conceptualizing the conditions under which clinical assessment may have treatment utility and illustrate its use by distinguishing four specific classes of assessment-driven interventions. We distinguish direct benefits from assessment from indirect TUCA as two principal pathways, emphasize the importance of having some a priori theory regarding working mechanisms, and stress the requirements of ensuring adequate variability of the presumed mediating variables. These considerations in turn argue for a broader view of pertinent outcome measures, the use of more powerful designs in TUCA research, and the implementation of some form of stepped assessment in clinical practice

Integrating Autism-Related Symptoms into the Dimensional Internalizing and Externalizing Model of Psychopathology. The TRAILS Study

Problems associated with Autism Spectrum Disorder (ASD) occur frequently in the general population and often co-occur with problems in other domains of psychopathology. In the research presented here these co-occurrence patterns were investigated by integrating a dimensional approach to ASDs into the more general dimensional framework of internalizing and externalizing psychopathology. Factor Analysis was used to develop hierarchical and bi-factor models covering multiple domains of psychopathology in three measurement waves of a longitudinal general population sample (N = 2,230, ages 10-17, 50.8 % female). In all adequately fitting models, autism related problems were part of a specific domain of psychopathology that could be distinguished from the internalizing and externalizing domains. Optimal model fit was found for a bi-factor model with one non-specific factor and four specific factors related to internalizing, externalizing, autism spectrum problems and problems related to attention and orientation. Autism-related problems constitute a specific domain of psychopathology that can be distinguished from the internalizing and externalizing domains. In addition, the co-occurrence patterns in the data indicate the presence of a strong general factor

Actor and Partner Effects of Attachment on Relationship Satisfaction and Sexual Satisfaction Across the Genders:An APIM Approach

Previous studies found gender differences in relationship satisfaction and sexuality. We tested gender differences in associations between attachment, a lasting relationship determinant, and two outcomes, relationship and sexual satisfaction. This study improves on earlier research by examining these associations in one Actor-Partner-Interdependence-Model, making direct statistical testing between outcomes possible. Furthermore, a community and a distressed sample (N = 113 heterosexual couples each) were included to attempt replication across samples and to examine clinical implications. In both genders, actor attachment avoidance negatively affected relationship satisfaction and (with one exception) sexual satisfaction. Also in both genders, partner attachment avoidance negatively affected sexual satisfaction. However, whereas partner attachment avoidance influenced female relationship satisfaction, it did not affect male relationship satisfaction. The findings replicated across samples. Clinical implications are discussed

Dimensions of Normal Personality as Networks in Search of Equilibrium: You Can't Like Parties if You Don't Like People

In one currently dominant view on personality, personality dimensions (e.g. extraversion) are causes of human behaviour, and personality inventory items (e.g. I like to go to parties and I like people) are measurements of these dimensions. In this view, responses to extraversion items correlate because they measure the same latent dimension. In this paper, we challenge this way of thinking and offer an alternative perspective on personality as a system of connected affective, cognitive and behavioural components. We hypothesize that these components do not hang together because they measure the same underlying dimension; they do so because they depend on one another directly for causal, homeostatic or logical reasons (e.g. if one does not like people and it is harder to enjoy parties). From this network perspective, personality dimensions emerge out of the connectivity structure that exists between the various components of personality. After outlining the network theory, we illustrate how it applies to personality research in four domains: (i) the overall organization of personality components; (ii) the distinction between state and trait; (iii) the genetic architecture of personality; and (iv) the relation between personality and psychopathology

Dimensions of Normal Personality as Networks in Search of Equilibrium: You Can't Like Parties if You Don't Like People

In one currently dominant view on personality, personality dimensions (e.g. extraversion) are causes of human behaviour, and personality inventory items (e.g. ‘I like to go to parties’ and ‘I like people’) are measurements of these dimensions. In this view, responses to extraversion items correlate because they measure the same latent dimension. In this paper, we challenge this way of thinking and offer an alternative perspective on personality as a system of connected affective, cognitive and behavioural components. We hypothesize that these components do not hang together because they measure the same underlying dimension; they do so because they depend on one another directly for causal, homeostatic or logical reasons (e.g. if one does not like people and it is harder to enjoy parties). From this ‘network perspective’, personality dimensions emerge out of the connectivity structure that exists between the various components of personality. After outlining the network theory, we illustrate how it applies to personality research in four domains: (i) the overall organization of personality components; (ii) the distinction between state and trait; (iii) the genetic architecture of personality; and (iv) the relation between personality and psychopathology. Copyright © 2012 John Wiley & Sons, Ltd