Repeated assessments of depressive symptoms in randomized psychosocial intervention trials: best practice for analyzing symptom change over time.
Repeated assessments of depressive symptoms in randomized psychosocial intervention trials: best practice for analyzing symptom change over time.
复制标题
在随机心理社会干预试验中重复评估抑郁症状:分析症状随时间变化的最佳实践。
DOI:
10.1080/10503307.2022.2073289
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发表时间:
2023
期刊:
影响因子:
--
通讯作者:
ConnollyGibbons,MaryBeth
中科院分区:
文献类型:
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作者:
Crits-Christoph,Paul;Gallop,Robert;Duong,Lang;Zoupou,Eirini;ConnollyGibbons,MaryBeth
ObjectivePsychotherapy 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.MethodWe 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.ResultsIn 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).ConclusionsTrials should routinely compare different time models, including an unstructured model, when repeated measures of depressive symptoms are the primary outcome.