Screening for Learning Difficulty Using Teacher Ratings on the Colorado Learning Difficulties Questionnaire

Taylor A Koriakin, M. McCurdy, A. Pritchard, T. A. Zabel, L. Jacobson
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Abstract

The present study examined clinical utility of teacher ratings on the Colorado Learning Difficulties Questionnaire (CLDQ) learning difficulties screening within a referred, school-aged sample ( N =519, 5-18 years). Of this sample, 419 youth had CLDQ reading scale scores from a reading or general education teacher, and 338 had CLDQ math scale ratings from a math or general education teacher. Sensitivity, specificity and receiver operating characteristic (ROC) curves were examined for specific reading and math difficulties (achievement SS<85). Cut-scores were identified to maximize sensitivity (reading: 60–91%; math: 85–89%), but specificity was low (reading: 60–64%, math: 47–48%); AUCs ranged from .70-.87 for reading and .75-.77 for math. Discrimination was comparable in an elementary subsample. Conditional probabilities suggested CLDQ ratings more accurately predicted children without learning difficulties (i.e., true negatives) than with learning difficulties. Parent and teacher ratings were well correlated ( r =.71), but addition of teacher ratings improved classification accuracy and model fit ( p <.001) across domains. Furthermore, CLDQ teacher ratings were helpful in reducing false positives based upon parent ratings alone. Findings suggest teacher ratings via CLDQ can be used to screen children at risk for learning difficulties, with teacher ratings showing added value over and above parent ratings. Subscribe to LDMJ
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使用科罗拉多学习困难问卷的教师评分筛选学习困难
本研究考察了在科罗拉多学习困难问卷(CLDQ)学习困难筛查中教师评分的临床效用,涉及学龄样本(N =519, 5-18岁)。在这个样本中,419名青少年从阅读或通识教育教师那里获得了CLDQ阅读量表评分,338名青少年从数学或通识教育教师那里获得了CLDQ数学量表评分。对特定阅读和数学困难(成就SS<85)的敏感性、特异性和受试者工作特征(ROC)曲线进行检验。确定Cut-scores以最大限度地提高灵敏度(读数:60-91%;数学:85-89%),但特异性较低(阅读:60-64%,数学:47-48%);auc范围从0.70 -。阅读为87分,75分。数学77分。判别在基本子样本中具有可比性。条件概率表明CLDQ评分比有学习困难的儿童更准确地预测了没有学习困难的儿童(即真阴性)。家长和教师评分有很好的相关性(r = 0.71),但教师评分的增加提高了跨领域的分类准确性和模型拟合(p < 0.001)。此外,CLDQ教师评分有助于减少仅基于家长评分的误报。研究结果表明,通过CLDQ进行的教师评级可以用来筛选有学习困难风险的儿童,教师评级显示出比家长评级更高的价值。订阅LDMJ
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