ABSTRACT

Objective:

Psychotherapy randomized trials rarely have tested for the best fitting model for time effects. We examined the fit of different statistical models for examining time when repeated assessments of depressive symptoms are the primary outcome.

Method:

We used data from three studies comparing psychotherapy treatments for major depressive disorder. Outcome measures were self-report ratings for Study 1 (N = 237) and Study 2 (N = 100) and clinician ratings for Study 3 (N = 120) of depressive symptoms measured at every session (Studies 1 and 2) or monthly (Study 3). We examined the fit of the following time patterns: linear, quadratic, cubic, log transformation of time, piece-wise linear, and unstructured.

Results:

In Study 1, a log-linear model had the best fit (Δ Akaike information criterion [AICc] = 7.5). In Study 2, all models had essentially no support (Δ AICcs > 10) in comparison to the best fitting model, which was the unstructured model. In Study 3, the cubic model had the best fit, but it was not significantly better than a log-linear (Δ AICc = 3.5) or unstructured model (Δ AICc = 2.5).

Conclusions:

Trials should routinely compare different time models, including an unstructured model, when repeated measures of depressive symptoms are the primary outcome.

中文翻译：

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随机心理社会干预试验中抑郁症状的重复评估：分析症状随时间变化的最佳实践

摘要

客观的：

心理治疗随机试验很少测试时间效应的最佳拟合模型。当抑郁症状的重复评估是主要结果时，我们检查了不同统计模型的拟合度。

方法：

我们使用了三项比较重度抑郁症心理治疗的研究数据。结果测量是研究 1（ N  = 237）和研究 2（N  = 100）的自我报告评级以及研究 3（N  = 120）的临床医生对每次治疗（研究 1 和 2）或每月测量的抑郁症状的评级（研究 3)。我们检查了以下时间模式的拟合：线性、二次、立方、时间的对数变换、分段线性和非结构化。

结果：

在研究 1 中，对数线性模型具有最佳拟合（Δ Akaike 信息标准 [AICc] = 7.5）。在研究 2 中，与最佳拟合模型（非结构化模型）相比，所有模型基本上都没有支持（ΔAICcs > 10）。在研究 3 中，三次模型的拟合效果最好，但并不明显优于对数线性模型 (Δ AICc = 3.5) 或非结构化模型 (Δ AICc = 2.5)。

结论：

当抑郁症状的重复测量是主要结果时，试验应定期比较不同的时间模型，包括非结构化模型。