METHODS: An observational cross-sectional design was used in a sample (N = 67) of help-seeking youth (ages 13 to 18, inclusive) experiencing depressive symptoms. The MFQ was administered verbatim to youth by a research analyst over the phone. Youth were then grouped into subthreshold-to-mild or moderate-to-severe depression severity categories based on scores received on the Kiddie Schedule for Affective Disorders and Schizophrenia-Depression Rating Scale. Receiver Operating Characteristic curve analyses were conducted, with area under the curve (AUC) and Youden Index (J) as primary indices. We hypothesized that the lower limit of the 95 % confidence interval for the area under the curve would be ≥0.70.
RESULTS: The primary analysis yielded an AUC of 0.85 (95 % CI: 0.763-0.947) and an optimal cut-off of ≥43 (J = 0.60, positive predictive value = 91.4 %, negative predictive value = 62.5 %, sensitivity = 72.7 %, specificity = 87.0 %).
CONCLUSIONS: Our study collected a small sample, and as such cannot identify how subgroup classification (e.g., based on race or gender) may moderate outcomes. Further, unknown measurement error of the predictor and reference variable measures can bias the estimates.
CONCLUSIONS: Our preliminary findings highlight the potential for the MFQ to support clinical decision-making relevant to adolescents experiencing varying severities of depressive symptoms in secondary care settings.
方法:在寻求帮助的青年(13至18岁,包括在内)的样本中使用了观察性横断面设计。MFQ是由研究分析师通过电话逐字发给年轻人的。然后,根据情感障碍的Kiddie时间表和精神分裂症抑郁量表上收到的分数,将青少年分为亚阈值至轻度或中度至重度抑郁严重程度类别。进行了接收器工作特性曲线分析,以曲线下面积(AUC)和约登指数(J)为主要指数。我们假设曲线下面积的95%置信区间下限为≥0.70。
结果:初步分析得出的AUC为0.85(95%CI:0.763-0.947),最佳临界值≥43(J=0.60,阳性预测值=91.4%,阴性预测值=62.5%,灵敏度=72.7%,特异性=87.0%)。
结论:我们的研究收集了一个小样本,因此无法识别子组分类的方式(例如,基于种族或性别)可能会缓和结果。Further,预测变量和参考变量度量的未知测量误差可能会使估计产生偏差。
结论:我们的初步发现强调了MFQ支持与在二级护理环境中经历不同程度的抑郁症状的青少年相关的临床决策的潜力。