萧条(经济学)
心理干预
认知
干预(咨询)
电路培训
临床心理学
医学
心理学
精神科
物理医学与康复
宏观经济学
经济
作者
Xue Zhang,Adam Pines,Patrick Stetz,Andrea Goldstein‐Piekarski,Lan Xiao,Nan Lv,Leonardo Tozzi,Philip W. Lavori,Mark Snowden,Elizabeth M. Venditti,Joshua M. Smyth,Trisha Suppes,Olusola Ajilore,Jun Ma,Leanne M. Williams
出处
期刊:Science Translational Medicine
[American Association for the Advancement of Science (AAAS)]
日期:2024-09-04
卷期号:16 (763)
标识
DOI:10.1126/scitranslmed.adh3172
摘要
Mechanistically targeted behavioral interventions are a much-needed strategy for improving outcomes in depression, especially for vulnerable populations with comorbidities such as obesity. Such interventions may change behavior and outcome by changing underlying neural circuit function. However, it is unknown how these circuit-level modifications unfold over intervention and how individual differences in early circuit-level modifications may explain the heterogeneity of treatment effects. We addressed this need within a clinical trial of problem-solving therapy for participants with depression symptoms and comorbid obesity, focusing on the cognitive control circuit as a putative neural mechanism of action. Functional magnetic resonance imaging was applied to measure the cognitive control circuit activity at five time points over 24 months. Compared with participants who received usual care, those receiving problem-solving therapy showed that attenuations in cognitive control circuit activity were associated with enhanced problem-solving ability, which suggests that this circuit plays a key role in the mechanisms of problem-solving therapy. Attenuations in circuit activity were also associated with improved depression symptoms. Changes in cognitive control circuit activity at 2 months better predicted changes in problem-solving ability and depression symptoms at 6, 12, and 24 months, with predictive improvements ranging from 17.8 to 104.0%, exceeding baseline demographic and symptom characteristics. Our findings suggest that targeting the circuit mechanism of action could enhance the prediction of treatment outcomes, warranting future model refinement and improvement to pave the way for its clinical application.
科研通智能强力驱动
Strongly Powered by AbleSci AI