Biomedical subjects

C Hendricks Brown

Publications and source records attributed to C Hendricks Brown.

3 recordsLinked to original sources

PubMed2002

Hierarchical modeling of sequential behavioral data: an empirical Bayesian approach.

The authors review the common methods for measuring strength of contingency between 2 behaviors in a behavioral sequence, the binomial z score and the adjusted cell residual, and point out a number of limitations of these approaches. They present a new approach using log odds ratios and empirical Bayes estimation in the context of hierarchical modeling, an approach not constrained by these limitations. A series of hierarchical models is presented to test the stationarity of behavioral sequences, the homogeneity of sequences across a sample of episodes, and whether covariates can account for variation in sequences across the sample. These models are applied to observational data taken from a study of the behavioral interactions of 254 couples to illustrate their use.

Bayes Theorem↗

PubMed2002

General growth mixture modeling for randomized preventive interventions.

This paper proposes growth mixture modeling to assess intervention effects in longitudinal randomized trials. Growth mixture modeling represents unobserved heterogeneity among the subjects using a finite-mixture random effects model. The methodology allows one to examine the impact of an intervention on subgroups characterized by different types of growth trajectories. Such modeling is informative when examining effects on populations that contain individuals who have normative growth as well as non-normative growth. The analysis identifies subgroup membership and allows theory-based modeling of intervention effects in the different subgroups. An example is presented concerning a randomized intervention in Baltimore public schools aimed at reducing aggressive classroom behavior, where only students who were initially more aggressive showed benefits from the intervention.

Journal Article↗

PubMed2002

Preventing schizophrenia and psychotic behaviour: definitions and methodological issues.

Although schizophrenia onset usually occurs in late adolescence or early adulthood, much research shows that its seeds are planted early in life and that eventual onset occurs at the end of a neurodevelopmental process leading to aberrant brain functioning. This idea, along with the fact that current therapies are far from fully effective, suggests that preventive treatments may be needed to achieve an ideal outcome for schizophrenia patients and those predisposed to the disorder. In this article, we review the methodological challenges that must be overcome before effective preventive interventions can be created. Prevention studies will need to define the target population. This requires the identification of risk factors that will be useful in selecting at-risk people for preventive treatment. We review currently identified risk factors for schizophrenia: genes, psychosocial factors, pregnancy and delivery complications, and viruses. We also review 3 different types of prevention programs: universal, indicated, and selective. For schizophrenia, we distinguish prevention programs that target prodromal cases and those that target the disorder's premorbid precursors. Although those targeting prodromal cases provide a useful framework for early treatment of the disorder, studies of premorbid individuals are needed to design a truly preventive treatment.

Affect↗