Part III: Measuring hearing-critical job tasks 135 2009). Despite the increased effort that has been invested to develop valid tests and models to assess the functional ability of speech communication, there is only limited evidence on how to assess an employees’ ability to detect acoustic warning signals. A computational model has been developed to predict the detectability of warning signals in noise based on the acoustic characteristics of the signal and the noise, as well as the hearing status of an individual or a group (Zheng et al., 2003). However, there is limited evidence for the validity of this model, and the model tends to underestimate warning signal detectability (Van der Hoek-Snieders et al., 2021). This might be due to the fact that this model has been developed to specify the optimal acoustic characteristics of warning signals rather than for assessing if an individual is capable of performing the job-specific, hearing-critical tasks. Since a valid model for assessing signal detectability is lacking and pure-tone audiometry has been shown to be a poor predictor of signal detection in noisy environments, it has been proposed to use real-world simulation tests instead (Tufts et al., 2009). A simulation test can be developed with audio recordings of a specific workplace. We have developed a signal detection test based on audio recordings of Dutch locomotive cabins. Before this signal detection test can be implemented as part of the auditory fitness for job assessment of locomotive engineers, the clinimetric properties of the test should be determined (De Vet et al., 2003). Reliability is important when a test is used to discriminate between individuals because reliability is defined as the ability of a test to differentiate among subjects despite measurement error. For evaluative instruments, agreement parameters are also required. Agreement reflects the degree to which scores or ratings are identical when assessed in repeatedmeasurements (Kottner et al., 2011). In addition, it is important to know whether a test measures what it intends to measure. Therefore, the validity should be determined. The construct ‘the ability to detect acoustic warning signals in the acoustic environment of a train cabin’ is examined with the signal detection test. To examine the construct validity of the test, it should be compared with a gold standard. However, as no gold standard is present at this moment, construct validity can be assessed by testing hypotheses about the relations between the signal detection test and related constructs (De Vet et al., 2011). Since the clinimetric properties of the signal detection test are not yet determined, we aimed to evaluate the reliability, agreement, and construct validity in a population of Dutch locomotive engineers.
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