Literature DB >> 21846812

Development and validation of a screening questionnaire for noise-induced hearing loss.

M Rosso1, R Agius, N Calleja.   

Abstract

BACKGROUND: An audiometric health surveillance programme can be perceived to be a relatively costly exercise and employers, especially in developing countries, might therefore be reluctant to undertake this. A questionnaire might be a cheaper alternative. AIMS: To develop a questionnaire to help determine the prevalence of noise-induced hearing loss (NIHL) in the vernacular (language) of a developing country and to validate it against an audiometric standard.
METHODS: A questionnaire was developed, translated and administered in a face-to-face interview. Otoscopic examination was followed by conventional pure-tone audiometry (at 0.25, 0.5, 1, 2, 4 and 8 kHz) for both ears of each respondent. The questionnaire responses were compared to the audiometric standard.
RESULTS: Two hundred and fifty workers from three companies (two printing and one woodworking) participated in this study. The sensitivity of the hearing loss questionnaire in detecting noise-induced hearing loss was 32%, while its specificity was 79%. There was an evidence to suggest good agreement (r = 0.523) between the total number of years worked in noisy jobs and NIHL (P < 0.05).
CONCLUSIONS: The questionnaire developed in this study was found to have an unacceptably low sensitivity for noise-induced hearing loss and therefore cannot be a valid substitute for audiometry. Pure tone industrial audiometry needs to be used more widely than currently in developing countries.

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Year:  2011        PMID: 21846812     DOI: 10.1093/occmed/kqr059

Source DB:  PubMed          Journal:  Occup Med (Lond)        ISSN: 0962-7480            Impact factor:   1.611


  2 in total

1.  Prediction of hearing loss among the noise-exposed workers in a steel factory using artificial intelligence approach.

Authors:  Mohsen Aliabadi; Maryam Farhadian; Ebrahim Darvishi
Journal:  Int Arch Occup Environ Health       Date:  2014-11-29       Impact factor: 3.015

2.  Empirical estimation of the grades of hearing impairment among industrial workers based on new artificial neural networks and classical regression methods.

Authors:  Maryam Farhadian; Mohsen Aliabadi; Ebrahim Darvishi
Journal:  Indian J Occup Environ Med       Date:  2015 May-Aug
  2 in total

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