Application of a low-cost instrument to identify risk for hearing disorders in a municipal health network.

IF 0.9 Q4 AUDIOLOGY & SPEECH-LANGUAGE PATHOLOGY
CoDAS Pub Date : 2026-08-03 eCollection Date: 2026-01-01 DOI:10.1590/2317-1782/e20250194pt
Monize Menon, Seisse Gabriela Gandolfi Sanches, Alessandra Giannella Samelli
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引用次数: 0

Abstract

Purpose: To evaluate the performance of the PETIT application (automated tablet-based screening) compared with conventional sweep screening in identifying the risk of hearing impairment in school-aged children, using headphones with passive noise cancellation.

Methods: Cross-sectional observational study including 122 children (aged 5 to 8 years) from the public school of Santana de Parnaíba. The following procedures were performed: otoscopy; automated hearing screening via tablet (with Sennheiser HD-280 headphones); and conventional sweep screening. Part of the sample also underwent pure-tone audiometry. Statistical analysis used binomial and binary logistic regression tests, along with the calculation of sensitivity, specificity, and accuracy.

Results: There was significant association between the results of the sweep screening and PETIT, as well as the coefficient of the predictor variable (conventional audiometry) was significant to the performance in the sweep screening. For PETIT, a sensitivity of 85.7%, specificity of 100%, and accuracy of 99.18% were observed.

Conclusion: The results suggest that this tool has promising applicability in schools for identifying children at risk of hearing impairments.

低成本仪器在市政卫生网络中识别听力障碍风险的应用。
目的:评估PETIT应用(基于平板电脑的自动筛查)与传统扫描筛查在识别学龄儿童听力障碍风险方面的性能,使用被动降噪耳机。方法:横断面观察研究,包括122名来自Santana de Parnaíba公立学校的儿童(5至8岁)。进行了以下手术:耳镜检查;通过平板电脑自动筛选听力(配备Sennheiser HD-280耳机);和传统的扫筛。部分样本还进行了纯音测听。统计分析采用二项和二元逻辑回归检验,并计算敏感性、特异性和准确性。结果:扫描筛查的结果与PETIT之间存在显著相关性,预测变量系数(常规听力学)对扫描筛查的表现有显著影响。对PETIT的敏感性为85.7%,特异性为100%,准确性为99.18%。结论:结果表明,该工具在学校识别有听力障碍风险的儿童方面具有良好的适用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CoDAS
CoDAS AUDIOLOGY & SPEECH-LANGUAGE PATHOLOGY-
CiteScore
0.90
自引率
12.50%
发文量
103
审稿时长
30 weeks
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