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Effective Components of Collaborative Care for Depression in Primary Care

心理信息 协作护理 医学 数据提取 梅德林 随机对照试验 萧条(经济学) 荟萃分析 科克伦图书馆 系统回顾 家庭医学 物理疗法 初级保健 内科学 政治学 法学 经济 宏观经济学
作者
Hannah Schillok,Jochen Gensichen,Maria Panagioti,Jane Gunn,Lukas Junker,Karoline Lukaschek,Caroline Jung‐Sievers,Philipp Sterner,Lukas Kaupe,Tobias Dreischulte,Mohammed K. Ali,Enric Aragonès,David B. Bekelman,Bea Herbeck Belnap,Robert M. Carney,Lydia Chwastiak,Peter Coventry,Karina W. Davidson,Maria L. Ekstrand,Alison Flehr
出处
期刊:JAMA Psychiatry [American Medical Association]
卷期号:82 (9): 868-868 被引量:11
标识
DOI:10.1001/jamapsychiatry.2025.0183
摘要

Importance Collaborative care is a multicomponent intervention for patients with chronic disease in primary care. Previous meta-analyses have proven the effectiveness of collaborative care for depression; however, individual participant data (IPD) are needed to identify which components of the intervention are the principal drivers of this effect. Objective To assess which components of collaborative care are the biggest drivers of its effectiveness in reducing symptoms of depression in primary care. Data Sources Data were obtained from MEDLINE, Embase, Cochrane Library, PubMed, and PsycInfo as well as references of relevant systematic reviews. Searches were conducted in December 2023, and eligible data were collected until March 14, 2024. Study Selection Two reviewers assessed for eligibility. Randomized clinical trials comparing the effect of collaborative care and usual care among adult patients with depression in primary care were included. Data Extraction and Synthesis The study was conducted according to the IPD guidance of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses reporting guideline. IPD were collected for demographic characteristics and depression outcomes measured at baseline and follow-ups from the authors of all eligible trials. Using IPD, linear mixed models with random nested effects were calculated. Main Outcomes and Measures Continuous measure of depression severity was assessed via validated self-report instruments at 4 to 6 months and was standardized using the instrument’s cutoff value for mild depression. Results A total of 35 datasets with 38 comparisons were analyzed (N = 20 046 participants [57.3% of all eligible, with minimal differences in baseline characteristics compared with nonretrieved data]; 13 709 [68.4%] female; mean [SD] age, 50.8 [16.5] years). A significant interaction effect with the largest effect size was found between the depression outcome and the collaborative care component therapeutic treatment strategy (−0.07; P < .001). This indicates that this component, including its key elements manual-based psychotherapy and family involvement, was the most effective component of the intervention. Significant interactions were found for all other components, but with smaller effect sizes. Conclusions and Relevance Components of collaborative care most associated with improved effectiveness in reducing depressive symptoms were identified. To optimize treatment effectiveness and resource allocation, a therapeutic treatment strategy, such as manual-based psychotherapy or family integration, may be prioritized when implementing a collaborative care intervention.

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