Effects of neuregulin-1 genetic variation and depression symptom severity on longitudinal patterns of psychotic symptoms in primary care attendees.

A better understanding of the factors associated with psychotic symptoms could aid early identification and treatment of psychotic disorders. Previous studies have typically utilized cross-sectional study designs and have focused on individuals with psychotic disorders. Thus, examination of promising correlates of psychotic symptoms using longitudinal designs among more broadly defined populations is warranted. Two such correlates are neuregulin-1 (NRG1) genotypic variation and depression symptom severity. Both NRG1 and depression symptom severity have cross-sectional evidence for an association with psychosis but their affect on longitudinal patterns of psychotic symptoms and their potential interaction effects are less clear. Using repeated measures analysis of variance and covariance we modeled the main and interaction effects of NRG1 genotypic variation and depressive symptom severity on longitudinal psychotic symptom patterns in 301 primary care attendees assessed annually over 4 years. One-fifth (19.9%) of the participants reported one or more psychotic symptoms over the 4-year assessment period. We observed a curvilinear (i.e., cubic) association between depression symptom severity at baseline and longitudinal patterns of psychotic symptoms but did not observe a main effect for NRG1 genotypic variation on psychotic symptom patterns. However, NRG1 rs6994992 genotype moderated the curvilinear association between depression symptom severity and psychotic symptom patterns. Specifically, depression symptom severity had less of an effect on longitudinal psychotic symptoms among carriers of the rs6994992 TT genotype compared to CC and CT carriers. Our findings suggest a curvilinear association between depression symptom severity and longitudinal patterns of psychotic symptoms that is moderated by NRG1 genotype.

Individual and area factors associated with general practitioner integration in Australia: a multilevel analysis.

The further integration of primary care within the wider health system is an imperative for reform in all countries. The aim of this paper is to determine the factors associated with general practitioner (GP) integration using the GP Integration Index which has been recently developed and is demonstrating good reliability. The analysis is based on a database derived from an Australia-wide mail questionnaire survey of 1874 GPs drawn from a 20% stratified random sample of 123 Divisions of General Practice (47.8% adjusted response rate). The GP Integration Index measures the level of GPs' integration with the health care system based upon a description of their own behaviour. It consists of nine GP integration factors, and their two associated higher-order factors-Primary Care Management (PCM) and Community Health Role (CHR)-as well as five GP integration enabling factors. A multivariate multilevel analysis was undertaken. An explanatory model for both PCM and CHR was tested based on the GP integration factors as well as general practice, GP and regional characteristics. CHR and PCM were most strongly associated with GP integration enabling factors (mainly at the individual-level) and, for CHR only, with urban-rural location (mainly at the area-level). The most important single explanatory variable for both PCM and CHR was the GP integration enabling factor, "Knowledge of local resources." The important explanatory variables were those reflecting the way GPs work, rather than their broad 'classification' within individual or GP-setting groupings. Based on these results, some revision to the proposed model was necessary. We conclude that processes of care factors (as compared to structure of care factors) are more important in relation to GP integration than previously recognised. Future policy initiatives to promote GP integration should focus on programs to improve GP's knowledge of local resources.