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Does Symptom Linkage Density Predict Outcomes in Cognitive Therapy for Recurrent Depression?
Journal of Psychopathology and Behavioral Assessment ( IF 2.118 ) Pub Date : 2021-08-17 , DOI: 10.1007/s10862-021-09914-y
Jeffrey R Vittengl 1 , Lee Anna Clark 2 , Michael E Thase 3 , Robin B Jarrett 4
Affiliation  

Acute-phase cognitive therapy (CT) is an efficacious treatment for major depressive disorder (MDD), but how CT helps patients is incompletely understood. As a potential means to clarify CT mechanisms, we defined “symptom linkage density” (SLD) as a patient’s mean time-lagged correlation among nine depressive symptoms across 13 weekly assessments. We hypothesized that patients with higher SLD during CT have better outcomes (treatment response, and fewer symptoms after response), and we explored whether SLD correlated with other possible CT processes (growth in social adjustment and CT skills).

Data were drawn from two clinical trials of CT for adult outpatients with recurrent MDD (primary sample n = 475, replication sample n = 146). In both samples, patients and clinicians completed measures of depressive symptoms and social adjustment repeatedly during CT. In the primary sample, patients and cognitive therapists rated patients’ CT skills. After CT, responders were assessed for 32 (primary sample) or 24 (replication sample) additional months to measure long-term depression outcomes.

Higher SLD predicted increases in social adjustment (both samples) and CT skills (primary sample) during CT, CT response (both samples), and lower MDD severity for at least 2 years after CT response (both samples). Analyses controlled patient-level symptom means and variability to estimate SLD’s incremental predictive validity.

These novel findings from two independent samples with longitudinal follow-up require further replication and extension. SLD may reflect or facilitate generalization of CT skills, improvement in social functioning, or other processes responsible for CT’s shorter and longer term benefits.



中文翻译:

症状关联密度是否可以预测复发性抑郁症认知治疗的结果?

急性期认知疗法 (CT) 是一种有效的治疗重度抑郁症 (MDD) 的方法,但尚不完全了解 CT 如何帮助患者。作为阐明 CT 机制的潜在方法,我们将“症状连锁密度”(SLD) 定义为患者在 13 周评估中九种抑郁症状之间的平均时滞相关性。我们假设在 CT 期间 SLD 较高的患者有更好的结果(治疗反应,反应后症状较少),并且我们探讨了 SLD 是否与其他可能的 CT 过程(社会适应和 CT 技能的增长)相关。

数据来自两项针对复发性 MDD 成人门诊患者的 CT 临床试验(主要样本n  = 475,复制样本n  = 146)。在这两个样本中,患者和临床医生在 CT 期间反复完成了抑郁症状和社会适应的测量。在初级样本中,患者和认知治疗师评估患者的 CT 技能。CT 后,对反应者进行了 32(主要样本)或 24(复制样本)额外月的评估,以衡量长期抑郁症的结果。

较高的 SLD 预测 CT 期间社会适应(两个样本)和 CT 技能(主要样本)、CT 反应(两个样本)的增加,以及 CT 反应后至少 2 年的较低 MDD 严重程度(两个样本)。分析受控的患者水平症状均值和变异性,以估计 SLD 的增量预测有效性。

这些来自两个具有纵向随访的独立样本的新发现需要进一步复制和扩展。SLD 可以反映或促进 CT 技能的普遍化、社会功能的改善或负责 CT 的短期和长期利益的其他过程。

更新日期:2021-08-19
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