Decision Models and Technology Can Help Psychiatry Develop Biomarkers.

Why is psychiatry unable to define clinically useful biomarkers? We explore this question from the vantage of data and decision science and consider biomarkers as a form of phenotypic data that resolves a well-defined clinical decision. We introduce a framework that systematizes different forms of phenotypic data and further introduce the concept of decision model to describe the strategies a clinician uses to seek out, combine, and act on clinical data. Though many medical specialties rely on quantitative clinical data and operationalized decision models, we observe that, in psychiatry, clinical data are gathered and used in idiosyncratic decision models that exist solely in the clinician's mind and therefore are outside empirical evaluation.

Integrating Behavioral Health and Primary Care in Two New Jersey Federally Qualified Health Centers.

This column describes a unique model for integrating behavioral health services into two New Jersey federally qualified health centers (FQHCs). The pilot project, funded by a private foundation grant, offers a lens for exploring the distinct challenges and opportunities faced by FQHCs serving diverse populations. The behavioral health services provided through this project were comprehensive, including behavioral health care, chronic disease management, and computerized cognitive-behavioral therapy.

Stuttering, induced fluency, and natural fluency: a hierarchical series of activation likelihood estimation meta-analyses.

Developmental stuttering is a speech disorder most likely due to a heritable form of developmental dysmyelination impairing the function of the speech-motor system. Speech-induced brain-activation patterns in persons who stutter (PWS) are anomalous in various ways; the consistency of these aberrant patterns is a matter of ongoing debate. Here, we present a hierarchical series of coordinate-based meta-analyses addressing this issue.