Fried Eiko I, Nesse Randolph M
University of Leuven, Faculty of Psychology and Educational Sciences, Research Group of Quantitative Psychology and Individual Differences, Tiensestraat 102, 3000, Leuven, Belgium.
School of Life Sciences, Arizona State University, Room 351 Life Sciences Building A, Tempe, AZ, 85287-450, USA.
BMC Med. 2015 Apr 6;13:72. doi: 10.1186/s12916-015-0325-4.
Most measures of depression severity are based on the number of reported symptoms, and threshold scores are often used to classify individuals as healthy or depressed. This method--and research results based on it--are valid if depression is a single condition, and all symptoms are equally good severity indicators. Here, we review a host of studies documenting that specific depressive symptoms like sad mood, insomnia, concentration problems, and suicidal ideation are distinct phenomena that differ from each other in important dimensions such as underlying biology, impact on impairment, and risk factors. Furthermore, specific life events predict increases in particular depression symptoms, and there is evidence for direct causal links among symptoms. We suggest that the pervasive use of sum-scores to estimate depression severity has obfuscated crucial insights and contributed to the lack of progress in key research areas such as identifying biomarkers and more efficacious antidepressants. The analysis of individual symptoms and their causal associations offers a way forward. We offer specific suggestions with practical implications for future research.
大多数抑郁严重程度的衡量标准是基于所报告症状的数量，阈值分数常被用于将个体分类为健康或抑郁。如果抑郁症是一种单一病症，且所有症状都是同样好的严重程度指标，那么这种方法以及基于此的研究结果就是有效的。在此，我们回顾了大量研究，这些研究表明，诸如悲伤情绪、失眠、注意力不集中问题和自杀念头等特定抑郁症状是不同的现象，它们在诸如潜在生物学、对功能损害的影响以及风险因素等重要方面存在差异。此外，特定的生活事件会导致特定抑郁症状的增加，并且有证据表明症状之间存在直接因果联系。我们认为，普遍使用总分来估计抑郁严重程度已经模糊了关键的见解，并导致在识别生物标志物和更有效的抗抑郁药物等关键研究领域缺乏进展。对个体症状及其因果关联的分析提供了一条前进的道路。我们为未来的研究提供了具有实际意义的具体建议。
