Psychometric functions for pure tone intensity discrimination: Slope differences in school-aged children and adults
Psychometric functions for pure tone intensity discrimination: Slope differences in school-aged children and adults
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DOI：
10.1121/1.3050273
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发表时间：
2009-02-01
影响因子：
2.4
通讯作者：
Grose, John H.
中科院分区：
文献类型：
--
作者：
Buss, Emily;Hall, Joseph W., III;Grose, John H.
先前关于学龄儿童纯音强度辨别的工作得出结论，儿童可能比成人具有更高水平的内部噪声[J. Acoust. Soc. Am. 120，2777-2788（2006）]。如果是真的，这将意味着心理测量功能的斜率是浅的儿童比成人，预测，在本实验中进行了测试。听力正常的儿童（5-9岁）和成人进行了测试，在两个阶段的协议。第一阶段使用跟踪程序估计71%正确的强度歧视与门控500赫兹纯音和65分贝的声压级标准水平。这些轨迹的平均值和标准差用于识别每个观察者的一组五个信号水平。在实验的第二阶段，在这五个水平上估计正确率。与这些数据相适应的心理测量功能显着浅的儿童比成人，预测的内部噪音假说。来自两个测试阶段的数据与模型一致，其中性能基于稳定的心理测量函数，灵敏度受心理测量函数斜率限制。在观察者之间的斜率和阈值之间的关系密切符合一个简单的信号检测模型的预测。(C)2009年美国声学学会。[DOI 10.1121/1.3050273]
Previous work on pure tone intensity discrimination in school-aged children concluded that children might have higher levels of internal noise than adults for this task [J. Acoust. Soc. Am. 120, 2777-2788 (2006)]. If true, this would imply that psychometric function slopes are shallower for children than adults, a prediction that was tested in the present experiment. Normal hearing children (5-9 yr) and adults were tested in a two-stage protocol. The first stage used a tracking procedure to estimate 71% correct for intensity discrimination with a gated 500 Hz pure tone and a 65 dB sound pressure level standard level. The mean and standard deviation of these tracks were used to identify a set of five signal levels for each observer. In the second stage of the experiment percent correct was estimated at these five levels. Psychometric functions fitted to these data were significantly shallower for children than adults, as predicted by the internal noise hypothesis. Data from both stages of testing are consistent with a model wherein performance is based on a stable psychometric function, with sensitivity limited by psychometric function slope. Across observers the relationship between slope and threshold conformed closely to predictions of a simple signal detection model. (C) 2009 Acoustical Society of America. [DOI: 10.1121/1.3050273]