Abstract
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.
Aims To use meta-regression to identify 'active ingredients' in collaborative care models for depression in primary care.
Method Studies were identified using systematic searches of electronic clatabases. 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 maybe useful in examiningactive ingredients' in complex interventions in mental health.
Declaration of interest None.
| Original language | English |
|---|---|
| Pages (from-to) | 484-493 |
| Number of pages | 10 |
| Journal | British Journal of Psychiatry |
| Volume | 189 |
| DOIs | |
| Publication status | Published - Dec 2006 |
Keywords
- RANDOMIZED CONTROLLED-TRIAL
- DISSEMINATING QUALITY IMPROVEMENT
- IMPROVING PRIMARY-CARE
- COST-EFFECTIVENESS
- DISEASE MANAGEMENT
- MAJOR DEPRESSION
- PHARMACIST INTERVENTION
- ALLOCATION CONCEALMENT
- COMMUNITY PHARMACISTS
- PUBLISHED REPORTS