Case Complexity as a Guide for Psychological Treatment Selection
Case Complexity as a Guide for Psychological Treatment Selection
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DOI：
10.1037/ccp0000231
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发表时间：
2017-09-01
影响因子：
5.9
通讯作者：
McMillan, Dean
中科院分区：
文献类型：
--
作者：
Delgadillo, Jaime;Huey, Dale;McMillan, Dean
目的：尽管对于如何定义心理护理的复杂性还没有达成共识，但有些病例被认为更加复杂且难以治疗。本研究提出了一种精算、数据驱动的方法，根据复杂案例的个体特征来识别复杂案例。方法：1,512 名接受低强度和高强度心理治疗的患者的临床记录被分为 2 个随机子样本。使用具有最佳缩放比例的惩罚（Lasso）回归在 1 个子样本中估计了预测治疗后抑郁症（患者健康问卷 - 9；Kroenke、Spitzer 和 Williams，2001）和焦虑症（广泛性焦虑症 - 7；Spitzer、Kroenke、Williams 和 Lowe，2006）症状的可靠且临床显着改善 (RCSI) 的预后指数。在第二个（交叉验证）子样本中，使用基于 PI 的算法将患者分类为标准 (St) 或复杂 (Cx) 病例。使用逻辑回归对接受不同强度治疗的 Cx 病例之间的 RCSI 率进行比较。结果：与 Cx 病例相比，St 病例的 RCSI 发生率显着更高（OR = 1.81 至 2.81）。如果 Cx 病例最初被分配到高强度（相对于低强度）干预措施，则往往会获得更好的抑郁结果（OR = 2.23）；焦虑也观察到类似的模式，但比值比 (1.74) 没有统计学意义。结论：复杂病例可以及早发现，并配合高强度干预措施以改善预后。这篇文章的公共卫生意义是什么？针对抑郁和焦虑问题进行心理治疗后，复杂病例往往预后不良。提出了一种定义复杂性的基于证据的模型，以指导治疗师将患者与不同强度的治疗相匹配。研究结果表明，这种个性化的治疗选择方法可以为复杂病例带来更好的结果，并且可以改进仅根据临床判断做出的决策。
Objective: Some cases are thought to be more complex and difficult to treat, although there is little consensus on how to define complexity in psychological care. This study proposes an actuarial, data-driven method of identifying complex cases based on their individual characteristics. Method: Clinical records for 1,512 patients accessing low-and high-intensity psychological treatments were partitioned in 2 random subsamples. Prognostic indices predicting post-treatment reliable and clinically significant improvement (RCSI) in depression (Patient Health Questionnaire-9; Kroenke, Spitzer, & Williams, 2001) and anxiety (Generalized Anxiety Disorder-7; Spitzer, Kroenke, Williams, & Lowe, 2006) symptoms were estimated in 1 subsample using penalized (Lasso) regressions with optimal scaling. A PI-based algorithm was used to classify patients as standard (St) or complex (Cx) cases in the second (cross-validation) subsample. RCSI rates were compared between Cx cases that accessed treatments of different intensities using logistic regression. Results: St cases had significantly higher RCSI rates compared to Cx cases (OR = 1.81 to 2.81). Cx cases tended to attain better depression outcomes if they were initially assigned to high-intensity (vs. low intensity) interventions (OR = 2.23); a similar pattern was observed for anxiety but the odds ratio (1.74) was not statistically significant. Conclusions: Complex cases could be detected early and matched to high-intensity interventions to improve outcomes.What is the public health significance of this article?Complex cases tend to have a poor prognosis after psychological treatment for depression and anxiety problems. An evidence-based model of defining complexity is proposed to guide therapists in matching patients to treatments of differing intensity. The findings indicate that this personalized method of treatment selection could lead to better outcomes for complex cases and could improve upon decisions that are informed by clinical judgment alone.