Robert L Folmer1,2, Jay Vachhani1, Garnett P McMillan1,3, Charles Watson4, Gary R Kidd5, M Patrick Feeney1,2. 1. National Center for Rehabilitative Auditory Research, Portland VA Medical Center, Portland, OR. 2. Department of Otolaryngology, Oregon Health & Science University, Portland, OR. 3. Department of Preventive Medicine, Oregon Health & Science University, Portland, OR. 4. Communication Disorders Technology, Inc., Bloomington, IN. 5. Indiana University, Bloomington, IN.
Abstract
BACKGROUND: The sooner people receive treatment for hearing loss (HL), the quicker they are able to recognize speech and to master hearing aid technology. Unfortunately, a majority of people with HL wait until their impairments have progressed from moderate to severe levels before seeking auditory rehabilitation. To increase the number of individuals with HL who pursue and receive auditory rehabilitation, it is necessary to improve methods for identifying and informing these people via widely accessible hearing screening procedures. Screening for HL is the first in a chain of events that must take place to increase the number of patients who enter the hearing health-care system. New methods for hearing screening should be readily accessible through a common medium (e.g., telephone or computer) and should be relatively easy and quick for people to self-administer. PURPOSE: The purpose of this study was to assess a digits-in-noise (DIN) hearing screening test that was delivered via personal computer. RESEARCH DESIGN: Participants completed the Hearing Handicap Inventory for Adults (HHIA) questionnaire, audiometric testing in a sound booth, and computerized DIN testing. During the DIN test, sequences of three spoken digits were presented in noise via headphones at varying signal-to-noise ratios (SNRs). Participants entered each three-digit sequence they heard using an on-screen keypad. STUDY SAMPLE: Forty adults (16 females, 24 males) participated in the study, of whom 20 had normal hearing and 20 had HL (pure-tone average [PTA] thresholds for 0.5, 1, 2, and 4 kHz >25 dB HL). DATA COLLECTION AND ANALYSIS: DIN SNR and PTA data were analyzed and compared for each ear tested. Receiver operating characteristic curves based on these data were plotted. A measure of overall accuracy of a screening test is the area under the receiver operating characteristic curve (AUC). This measures the average true positive rate across false positives at varying DIN SNR cutoffs. Larger values of the AUC indicate, on average, more accurate screening tests. HHIA responses were analyzed and compared to PTA and DIN SNR results using Pearson correlation statistics. RESULTS: HHIA scores were positively correlated with audiometric PTA and DIN SNR results (p < 0.001 for all correlations). For an HL criterion of one or more frequencies from 0.25 to 8 kHz >25 dB HL, the AUC for the DIN test was 0.95. When a criterion of hearling level was set at one or more frequencies from 0.25 to 8 kHz >20 dB HL, the AUC for the DIN test was 0.96. CONCLUSIONS: The computer version of the DIN test demonstrated excellent sensitivity and specificity for our sample of 40 participants. AUC results (≥0.95) suggest that this DIN test administered via computer should be very useful for adult hearing screening. American Academy of Audiology
BACKGROUND: The sooner people receive treatment for hearing loss (HL), the quicker they are able to recognize speech and to master hearing aid technology. Unfortunately, a majority of people with HL wait until their impairments have progressed from moderate to severe levels before seeking auditory rehabilitation. To increase the number of individuals with HL who pursue and receive auditory rehabilitation, it is necessary to improve methods for identifying and informing these people via widely accessible hearing screening procedures. Screening for HL is the first in a chain of events that must take place to increase the number of patients who enter the hearing health-care system. New methods for hearing screening should be readily accessible through a common medium (e.g., telephone or computer) and should be relatively easy and quick for people to self-administer. PURPOSE: The purpose of this study was to assess a digits-in-noise (DIN) hearing screening test that was delivered via personal computer. RESEARCH DESIGN:Participants completed the Hearing Handicap Inventory for Adults (HHIA) questionnaire, audiometric testing in a sound booth, and computerized DIN testing. During the DIN test, sequences of three spoken digits were presented in noise via headphones at varying signal-to-noise ratios (SNRs). Participants entered each three-digit sequence they heard using an on-screen keypad. STUDY SAMPLE: Forty adults (16 females, 24 males) participated in the study, of whom 20 had normal hearing and 20 had HL (pure-tone average [PTA] thresholds for 0.5, 1, 2, and 4 kHz >25 dB HL). DATA COLLECTION AND ANALYSIS: DIN SNR and PTA data were analyzed and compared for each ear tested. Receiver operating characteristic curves based on these data were plotted. A measure of overall accuracy of a screening test is the area under the receiver operating characteristic curve (AUC). This measures the average true positive rate across false positives at varying DIN SNR cutoffs. Larger values of the AUC indicate, on average, more accurate screening tests. HHIA responses were analyzed and compared to PTA and DIN SNR results using Pearson correlation statistics. RESULTS: HHIA scores were positively correlated with audiometric PTA and DIN SNR results (p < 0.001 for all correlations). For an HL criterion of one or more frequencies from 0.25 to 8 kHz >25 dB HL, the AUC for the DIN test was 0.95. When a criterion of hearling level was set at one or more frequencies from 0.25 to 8 kHz >20 dB HL, the AUC for the DIN test was 0.96. CONCLUSIONS: The computer version of the DIN test demonstrated excellent sensitivity and specificity for our sample of 40 participants. AUC results (≥0.95) suggest that this DIN test administered via computer should be very useful for adult hearing screening. American Academy of Audiology
Authors: Bamini Gopinath; Julie Schneider; Louise Hickson; Catherine M McMahon; George Burlutsky; Stephen R Leeder; Paul Mitchell Journal: Maturitas Date: 2012-04-20 Impact factor: 4.342
Authors: Robert L Folmer; Gabrielle H Saunders; Jay J Vachhani; Robert H Margolis; George Saly; Bevan Yueh; Rachel A McArdle; Lawrence L Feth; Christina M Roup; M Patrick Feeney Journal: J Am Acad Audiol Date: 2021-06-01 Impact factor: 1.245
Authors: Sam Denys; Jan De Laat; Wouter Dreschler; Michael Hofmann; Astrid van Wieringen; Jan Wouters Journal: Trends Hear Date: 2019 Jan-Dec Impact factor: 3.293