title: Time-invariant and time-varying predictors of depression symptoms in primary care patients.
abstract: OBJECTIVE
  The aims of this study were to examine correlates of depression symptoms, baseline predictors of change in depression symptoms, and time-varying predictors of depression symptoms in a primary care sample.
  
  
  METHODS
  In this study, we assessed depression symptoms and other variables at 3 time points over the course of 6 months in 103 primary care patients with elevated depression symptoms at baseline. Data collection occurred from May 2004 to September 2007.
  
  
  RESULTS
  Individuals with lower income levels and those who were not married had a poorer course of depression, as assessed by Center for Epidemiologic Studies Depression Scale score, over time. Several variables fluctuated in concert with depression symptoms within individuals over time. As depression symptoms improved, family functioning, problem-solving, pain, and general health perceptions also improved. A multivariate analysis showed that problem-solving and general health perceptions predicted significant (P < .001) unique variance in fluctuations in depression symptoms within individuals.
  
  
  CONCLUSIONS
  Care management programs for primary care depression may benefit from the inclusion of psychosocial interventions that directly target variables closely linked to depression, such as problem-solving and general health perceptions. In addition, special efforts must be made to help depressed individuals with low income and less social support.
authors.affiliation: Warren Alpert Medical School of Brown University, Providence, Rhode Island, USA. Luebelacker@butler.org
authors.forename: Lisa A
authors.initials: LA
authors.lastname: Uebelacker
authors.forename: Risa B
authors.initials: RB
authors.lastname: Weisberg
authors.forename: David R
authors.initials: DR
authors.lastname: Strong
authors.forename: Marcia
authors.initials: M
authors.lastname: Smith
authors.forename: Ivan W
authors.initials: IW
authors.lastname: Miller