Newcastle University, Institute of Neuroscience, Newcastle upon Tyne, UK.
Newcastle University, Institute of Neuroscience, Newcastle upon Tyne, UK; Department of Psychology, Eberhard Karls University, Tübingen, Germany.
Compr Psychiatry. 2014 Jul;55(5):1310-21. doi: 10.1016/j.comppsych.2014.03.002. Epub 2014 Mar 21.
Bipolar disorders (BDs) are often not recognised with potentially drastic consequences for the individuals and their families. In clinical practice self-reports can be used to screen to enhance recognition. We therefore present a systematic review of the screening properties for the Hypomania Checklist (HCL-32).
A systematic literature search was conducted to identify all relevant studies looking at the screening properties of the HCL-32 in adults.
Out of 196 papers 21 papers reported data on 22 independent samples. We narratively reviewed these studies. Weighted estimated Sensitivity was 80% regardless of whether a BD diagnosis was compared to unipolar depression or any other non-bipolar diagnosis. Specificity indicated that the HCL-32 was better when comparing BD to unipolar depression (65.3%) than to any other diagnostic category (57.3%). Fewer studies provided estimates for predictive powers, leading to less reliable overall estimates for these indicators.
Despite some limitations, using the HCL-32 as a first screening in patients seeking help for depression can be recommended, but should never be used on its own for diagnosing. Future research should examine whether screening properties can be improved by developing an algorithm incorporating the negative consequences reported for different areas in the HCL-32.
双相情感障碍(BDs)经常未被识别,这可能对个体及其家庭产生严重后果。在临床实践中,可以使用自我报告进行筛查以提高识别率。因此,我们对 Hypomania Checklist(HCL-32)的筛查特性进行了系统评价。
进行了系统的文献检索,以确定所有研究 HCL-32 在成年人中筛查特性的相关研究。
在 196 篇论文中,有 21 篇论文报告了 22 个独立样本的数据。我们对这些研究进行了叙述性综述。无论将 BD 诊断与单相抑郁或任何其他非双相诊断进行比较,加权估计的敏感性均为 80%。特异性表明,HCL-32 在将 BD 与单相抑郁(65.3%)进行比较时优于任何其他诊断类别(57.3%)。较少的研究提供了预测能力的估计值,因此这些指标的总体估计值不太可靠。
尽管存在一些局限性,但可以推荐在寻求抑郁治疗的患者中使用 HCL-32 作为初步筛查,但绝不能单独用于诊断。未来的研究应检验通过开发一种算法来改善筛查特性的可能性,该算法将纳入 HCL-32 中不同领域报告的负面后果。