Collaborative care for depression in primary care. Making sense of a complex intervention: systematic review and meta-regression.
BACKGROUND
The management of depression in primary care is a significant issue for health services worldwide. "Collaborative care" interventions are effective, but little is known about which aspects of these complex interventions are essential.


OBJECTIVE
To use meta-regression to identify "active ingredients" in collaborative care models for depression in primary care.


METHODS
Studies were identified using systematic searches of electronic databases. The content of collaborative care interventions was coded, together with outcome data on antidepressant use and depressive symptoms. Meta-regression was used to examine relationships between intervention content and outcomes.


RESULTS
There was no significant predictor of the effect of collaborative care on antidepressant use. Key predictors of depressive symptom outcomes included systematic identification of patients, professional background of staff and specialist supervision.


CONCLUSIONS
Meta-regression may be useful in examining "active ingredients" in complex interventions in mental health.
Bower
Peter
P
National Primary Care Research and Development Centre, University of Manchester, Manchester M13 9PL, UK. peter.bower@manchester.ac.uk
Gilbody
Simon
S
Richards
David
D
Fletcher
Janine
J
Sutton
Alex
A
D003866:Depressive Disorder / Q000175:diagnosis / Q000628:therapy*; D006801:Humans; D007400:Interprofessional Relations; D008605:Mental Health Services / Q000592:standards*; D010348:Patient Care Team / Q000592:standards*; D011320:Primary Health Care / Q000592:standards*; D016896:Treatment Outcome