Btissame Massoudi1, Floor Holvast2, Claudi L H Bockting3, Huibert Burger4, Marco H Blanker5. 1. University of Groningen, University Medical Center Groningen, Department of General Practice, Groningen, the Netherlands. Electronic address: b.massoudi@umcg.nl. 2. University of Groningen, University Medical Center Groningen, Department of General Practice, Groningen, the Netherlands. Electronic address: f.holvast@umcg.nl. 3. University of Utrecht, Department of Clinical Psychology, Utrecht, the Netherlands; University of Groningen, Department of Clinical Psychology, Groningen, the Netherlands. Electronic address: c.l.h.bockting@uu.nl. 4. University of Groningen, University Medical Center Groningen, Department of General Practice, Groningen, the Netherlands. Electronic address: h.burger@umcg.nl. 5. University of Groningen, University Medical Center Groningen, Department of General Practice, Groningen, the Netherlands. Electronic address: m.h.blanker@umcg.nl.
Abstract
PURPOSE: Psychological interventions are labor-intensive and expensive, but e-health interventions may support them in primary care. In this study, we systematically reviewed the effectiveness and cost-effectiveness of e-health interventions for depressive and anxiety symptoms and disorders in primary care. METHODS: We searched MEDLINE, Cochrane library, Embase, and PsychINFO until January 2018, for randomized controlled trials of e-health interventions for depression or anxiety in primary care. Two reviewers independently screened the identified publications, extracted data, and assessed risk of bias using the Cochrane Collaboration's tool. RESULTS: Out of 3617 publications, we included 14 that compared 33 treatments in 4183 participants. Overall, the methodological quality was poor to fair. The pooled effect size of e-health interventions was small (standardized mean difference = -0.19, 95%CI -0.31 to -0.06) for depression compared to control groups in the short-term, but this was maintained in the long-term (standardized mean difference = -0.22, 95%CI -0.35 to -0.09). Further analysis showed that e-health for depression had a small effect compared to care as usual and a moderate effect compared to waiting lists. One trial on anxiety showed no significant results. Four trials reported on cost-effectiveness. LIMITATIONS: The trials studied different types of e-health interventions and had several risks of bias. Moreover, only one study was included for anxiety. CONCLUSIONS: E-health interventions for depression have a small effect in primary care, with a moderate effect compared to waiting lists. The approach also appeared to be cost-effective for depression. However, we found no evidence for its effectiveness for anxiety.
PURPOSE: Psychological interventions are labor-intensive and expensive, but e-health interventions may support them in primary care. In this study, we systematically reviewed the effectiveness and cost-effectiveness of e-health interventions for depressive and anxiety symptoms and disorders in primary care. METHODS: We searched MEDLINE, Cochrane library, Embase, and PsychINFO until January 2018, for randomized controlled trials of e-health interventions for depression or anxiety in primary care. Two reviewers independently screened the identified publications, extracted data, and assessed risk of bias using the Cochrane Collaboration's tool. RESULTS: Out of 3617 publications, we included 14 that compared 33 treatments in 4183 participants. Overall, the methodological quality was poor to fair. The pooled effect size of e-health interventions was small (standardized mean difference = -0.19, 95%CI -0.31 to -0.06) for depression compared to control groups in the short-term, but this was maintained in the long-term (standardized mean difference = -0.22, 95%CI -0.35 to -0.09). Further analysis showed that e-health for depression had a small effect compared to care as usual and a moderate effect compared to waiting lists. One trial on anxiety showed no significant results. Four trials reported on cost-effectiveness. LIMITATIONS: The trials studied different types of e-health interventions and had several risks of bias. Moreover, only one study was included for anxiety. CONCLUSIONS: E-health interventions for depression have a small effect in primary care, with a moderate effect compared to waiting lists. The approach also appeared to be cost-effective for depression. However, we found no evidence for its effectiveness for anxiety.
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