Hearing Aid Directionality with Binaural Processing

The fact that two ears are better than one is well-established. The human auditory system integrates information from both ears providing benefits in terms of loudness, localization, sound quality, noise suppression, speech clarity and listening in noise. The ability to selectively attend to particular sounds, like a single voice among many talkers, is one of the most amazing and significant benefits of binaural hearing.

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Hearing Aid Selection and Fitting Tips Gleaned from Recent Research

The first thing I would like to talk about is the Acceptable Noise Level (ANL) test that was developed at the University of Tennessee, based on the research of Anna Nabelek dating back to 1991. For those of you who are not familiar with this test, here is a quick review of how it works: The test usually is conducted bilaterally in the sound field, not under earphones. You first determine the patient’s most comfortable listening level (MCL) for continuous discourse. The standard material is a travelogue about Arizona. It’s a loudness task, not a speech recognition task, so the actual speech material doesn’t matter too much.

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Hearing Aid Directionality with Binaural Processing

The fact that two ears are better than one is well-established. The human auditory system integrates information from both ears providing benefits in terms of loudness, localization, sound quality, noise suppression, speech clarity and listening in noise. The ability to selectively attend to particular sounds, like a single voice among many talkers, is one of the most amazing and significant benefits of binaural hearing.

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Hearing Aid Selection and Fitting Tips Gleaned from Recent Research

The first thing I would like to talk about is the Acceptable Noise Level (ANL) test that was developed at the University of Tennessee, based on the research of Anna Nabelek dating back to 1991. For those of you who are not familiar with this test, here is a quick review of how it works: The test usually is conducted bilaterally in the sound field, not under earphones. You first determine the patient’s most comfortable listening level (MCL) for continuous discourse. The standard material is a travelogue about Arizona. It’s a loudness task, not a speech recognition task, so the actual speech material doesn’t matter too much.

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Hearing Aid Directionality with Binaural Processing

The fact that two ears are better than one is well-established. The human auditory system integrates information from both ears providing benefits in terms of loudness, localization, sound quality, noise suppression, speech clarity and listening in noise. The ability to selectively attend to particular sounds, like a single voice among many talkers, is one of the most amazing and significant benefits of binaural hearing.

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Hearing Aid Selection and Fitting Tips Gleaned from Recent Research

The first thing I would like to talk about is the Acceptable Noise Level (ANL) test that was developed at the University of Tennessee, based on the research of Anna Nabelek dating back to 1991. For those of you who are not familiar with this test, here is a quick review of how it works: The test usually is conducted bilaterally in the sound field, not under earphones. You first determine the patient’s most comfortable listening level (MCL) for continuous discourse. The standard material is a travelogue about Arizona. It’s a loudness task, not a speech recognition task, so the actual speech material doesn’t matter too much.

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Measuring motivation using the transtheoretical (stages of change) model: A follow-up study of people who failed an online hearing screening.

Measuring motivation using the transtheoretical (stages of change) model: A follow-up study of people who failed an online hearing screening.

Int J Audiol. 2016 May 20;:1-7

Authors: Ingo E, Brännström KJ, Andersson G, Lunner T, Laplante-Lévesque A

Abstract
OBJECTIVE: Acceptance and readiness to seek professional help have shown to be important factors for favourable audiological rehabilitation outcomes. Theories from health psychology such as the transtheoretical (stages-of-change) model could help understand behavioural change in people with hearing impairment. In recent studies, the University of Rhode Island change assessment (URICA) has been found to have good predictive validity.
DESIGN: In a previous study, 224 Swedish adults who had failed an online hearing screening completed URICA and two other measures of stages of change. This follow-up aimed to: (1) determine prevalence of help-seeking at a hearing clinic and hearing aid uptake, and (2) explore the predictive validity of the stages of change measures by a follow-up on the 224 participants who had failed a hearing screening 18 months previously.
STUDY SAMPLE: A total of 122 people (54%) completed the follow-up online questionnaire, including the three measures and questions regarding experience with hearing help-seeking and hearing aid uptake.
RESULTS: Since failing the online hearing screening, 61% of participants had sought help. A good predictive validity for a one-item measure of stages of change was reported.
CONCLUSIONS: The Staging algorithm was the stages of change measure with the best ability to predict help-seeking 18 months later.

PMID: 27206679 [PubMed - as supplied by publisher]

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Clinical validation of automated audiometry with continuous noise-monitoring in a clinically heterogeneous population outside a sound-treated environment.

Clinical validation of automated audiometry with continuous noise-monitoring in a clinically heterogeneous population outside a sound-treated environment.

Int J Audiol. 2016 May 20;:1-7

Authors: Brennan-Jones CG, Eikelboom RH, Swanepoel W, Friedland PL, Atlas MD

Abstract
OBJECTIVE: Examine the accuracy of automated audiometry in a clinically heterogeneous population of adults using the KUDUwave automated audiometer.
DESIGN: Prospective accuracy study. Manual audiometry was performed in a sound-treated room and automated audiometry was not conducted in a sound-treated environment.
STUDY SAMPLE: 42 consecutively recruited participants from a tertiary otolaryngology department in Western Australia.
RESULTS: Absolute mean differences ranged between 5.12-9.68 dB (air-conduction) and 8.26-15 dB (bone-conduction). A total of 86.5% of manual and automated 4FAs were within 10 dB (i.e. ±5 dB); 94.8% were within 15 dB. However, there were significant (p < 0.05) differences between automated and manual audiometry at 250, 500, 1000, and 2000 Hz (air-conduction) and 500 and 1000 Hz (bone-conduction). The effect of age (≥55 years) on accuracy (p = 0.014) was not significant on linear regression (p > 0.05; R(2) =( ) 0.11). The presence of a hearing loss (better ear ≥26 dB) did not significantly affect accuracy (p = 0.604; air-conduction), (p = 0.218; bone-conduction).
CONCLUSIONS: This study provides clinical validation of automated audiometry using the KUDUwave in a clinically heterogeneous population, without the use of a sound-treated environment. Whilst threshold variations were statistically significant, future research is needed to ascertain the clinical significance of such variation.

PMID: 27206551 [PubMed - as supplied by publisher]

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Measuring motivation using the transtheoretical (stages of change) model: A follow-up study of people who failed an online hearing screening.

Measuring motivation using the transtheoretical (stages of change) model: A follow-up study of people who failed an online hearing screening.

Int J Audiol. 2016 May 20;:1-7

Authors: Ingo E, Brännström KJ, Andersson G, Lunner T, Laplante-Lévesque A

Abstract
OBJECTIVE: Acceptance and readiness to seek professional help have shown to be important factors for favourable audiological rehabilitation outcomes. Theories from health psychology such as the transtheoretical (stages-of-change) model could help understand behavioural change in people with hearing impairment. In recent studies, the University of Rhode Island change assessment (URICA) has been found to have good predictive validity.
DESIGN: In a previous study, 224 Swedish adults who had failed an online hearing screening completed URICA and two other measures of stages of change. This follow-up aimed to: (1) determine prevalence of help-seeking at a hearing clinic and hearing aid uptake, and (2) explore the predictive validity of the stages of change measures by a follow-up on the 224 participants who had failed a hearing screening 18 months previously.
STUDY SAMPLE: A total of 122 people (54%) completed the follow-up online questionnaire, including the three measures and questions regarding experience with hearing help-seeking and hearing aid uptake.
RESULTS: Since failing the online hearing screening, 61% of participants had sought help. A good predictive validity for a one-item measure of stages of change was reported.
CONCLUSIONS: The Staging algorithm was the stages of change measure with the best ability to predict help-seeking 18 months later.

PMID: 27206679 [PubMed - as supplied by publisher]

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Clinical validation of automated audiometry with continuous noise-monitoring in a clinically heterogeneous population outside a sound-treated environment.

Clinical validation of automated audiometry with continuous noise-monitoring in a clinically heterogeneous population outside a sound-treated environment.

Int J Audiol. 2016 May 20;:1-7

Authors: Brennan-Jones CG, Eikelboom RH, Swanepoel W, Friedland PL, Atlas MD

Abstract
OBJECTIVE: Examine the accuracy of automated audiometry in a clinically heterogeneous population of adults using the KUDUwave automated audiometer.
DESIGN: Prospective accuracy study. Manual audiometry was performed in a sound-treated room and automated audiometry was not conducted in a sound-treated environment.
STUDY SAMPLE: 42 consecutively recruited participants from a tertiary otolaryngology department in Western Australia.
RESULTS: Absolute mean differences ranged between 5.12-9.68 dB (air-conduction) and 8.26-15 dB (bone-conduction). A total of 86.5% of manual and automated 4FAs were within 10 dB (i.e. ±5 dB); 94.8% were within 15 dB. However, there were significant (p < 0.05) differences between automated and manual audiometry at 250, 500, 1000, and 2000 Hz (air-conduction) and 500 and 1000 Hz (bone-conduction). The effect of age (≥55 years) on accuracy (p = 0.014) was not significant on linear regression (p > 0.05; R(2) =( ) 0.11). The presence of a hearing loss (better ear ≥26 dB) did not significantly affect accuracy (p = 0.604; air-conduction), (p = 0.218; bone-conduction).
CONCLUSIONS: This study provides clinical validation of automated audiometry using the KUDUwave in a clinically heterogeneous population, without the use of a sound-treated environment. Whilst threshold variations were statistically significant, future research is needed to ascertain the clinical significance of such variation.

PMID: 27206551 [PubMed - as supplied by publisher]

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Measuring motivation using the transtheoretical (stages of change) model: A follow-up study of people who failed an online hearing screening.

Measuring motivation using the transtheoretical (stages of change) model: A follow-up study of people who failed an online hearing screening.

Int J Audiol. 2016 May 20;:1-7

Authors: Ingo E, Brännström KJ, Andersson G, Lunner T, Laplante-Lévesque A

Abstract
OBJECTIVE: Acceptance and readiness to seek professional help have shown to be important factors for favourable audiological rehabilitation outcomes. Theories from health psychology such as the transtheoretical (stages-of-change) model could help understand behavioural change in people with hearing impairment. In recent studies, the University of Rhode Island change assessment (URICA) has been found to have good predictive validity.
DESIGN: In a previous study, 224 Swedish adults who had failed an online hearing screening completed URICA and two other measures of stages of change. This follow-up aimed to: (1) determine prevalence of help-seeking at a hearing clinic and hearing aid uptake, and (2) explore the predictive validity of the stages of change measures by a follow-up on the 224 participants who had failed a hearing screening 18 months previously.
STUDY SAMPLE: A total of 122 people (54%) completed the follow-up online questionnaire, including the three measures and questions regarding experience with hearing help-seeking and hearing aid uptake.
RESULTS: Since failing the online hearing screening, 61% of participants had sought help. A good predictive validity for a one-item measure of stages of change was reported.
CONCLUSIONS: The Staging algorithm was the stages of change measure with the best ability to predict help-seeking 18 months later.

PMID: 27206679 [PubMed - as supplied by publisher]

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via IFTTT

Clinical validation of automated audiometry with continuous noise-monitoring in a clinically heterogeneous population outside a sound-treated environment.

Clinical validation of automated audiometry with continuous noise-monitoring in a clinically heterogeneous population outside a sound-treated environment.

Int J Audiol. 2016 May 20;:1-7

Authors: Brennan-Jones CG, Eikelboom RH, Swanepoel W, Friedland PL, Atlas MD

Abstract
OBJECTIVE: Examine the accuracy of automated audiometry in a clinically heterogeneous population of adults using the KUDUwave automated audiometer.
DESIGN: Prospective accuracy study. Manual audiometry was performed in a sound-treated room and automated audiometry was not conducted in a sound-treated environment.
STUDY SAMPLE: 42 consecutively recruited participants from a tertiary otolaryngology department in Western Australia.
RESULTS: Absolute mean differences ranged between 5.12-9.68 dB (air-conduction) and 8.26-15 dB (bone-conduction). A total of 86.5% of manual and automated 4FAs were within 10 dB (i.e. ±5 dB); 94.8% were within 15 dB. However, there were significant (p < 0.05) differences between automated and manual audiometry at 250, 500, 1000, and 2000 Hz (air-conduction) and 500 and 1000 Hz (bone-conduction). The effect of age (≥55 years) on accuracy (p = 0.014) was not significant on linear regression (p > 0.05; R(2) =( ) 0.11). The presence of a hearing loss (better ear ≥26 dB) did not significantly affect accuracy (p = 0.604; air-conduction), (p = 0.218; bone-conduction).
CONCLUSIONS: This study provides clinical validation of automated audiometry using the KUDUwave in a clinically heterogeneous population, without the use of a sound-treated environment. Whilst threshold variations were statistically significant, future research is needed to ascertain the clinical significance of such variation.

PMID: 27206551 [PubMed - as supplied by publisher]

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Measuring motivation using the transtheoretical (stages of change) model: A follow-up study of people who failed an online hearing screening.

Measuring motivation using the transtheoretical (stages of change) model: A follow-up study of people who failed an online hearing screening.

Int J Audiol. 2016 May 20;:1-7

Authors: Ingo E, Brännström KJ, Andersson G, Lunner T, Laplante-Lévesque A

Abstract
OBJECTIVE: Acceptance and readiness to seek professional help have shown to be important factors for favourable audiological rehabilitation outcomes. Theories from health psychology such as the transtheoretical (stages-of-change) model could help understand behavioural change in people with hearing impairment. In recent studies, the University of Rhode Island change assessment (URICA) has been found to have good predictive validity.
DESIGN: In a previous study, 224 Swedish adults who had failed an online hearing screening completed URICA and two other measures of stages of change. This follow-up aimed to: (1) determine prevalence of help-seeking at a hearing clinic and hearing aid uptake, and (2) explore the predictive validity of the stages of change measures by a follow-up on the 224 participants who had failed a hearing screening 18 months previously.
STUDY SAMPLE: A total of 122 people (54%) completed the follow-up online questionnaire, including the three measures and questions regarding experience with hearing help-seeking and hearing aid uptake.
RESULTS: Since failing the online hearing screening, 61% of participants had sought help. A good predictive validity for a one-item measure of stages of change was reported.
CONCLUSIONS: The Staging algorithm was the stages of change measure with the best ability to predict help-seeking 18 months later.

PMID: 27206679 [PubMed - as supplied by publisher]

from #Audiology via ola Kala on Inoreader http://ift.tt/1qCqJUm
via IFTTT

Clinical validation of automated audiometry with continuous noise-monitoring in a clinically heterogeneous population outside a sound-treated environment.

Clinical validation of automated audiometry with continuous noise-monitoring in a clinically heterogeneous population outside a sound-treated environment.

Int J Audiol. 2016 May 20;:1-7

Authors: Brennan-Jones CG, Eikelboom RH, Swanepoel W, Friedland PL, Atlas MD

Abstract
OBJECTIVE: Examine the accuracy of automated audiometry in a clinically heterogeneous population of adults using the KUDUwave automated audiometer.
DESIGN: Prospective accuracy study. Manual audiometry was performed in a sound-treated room and automated audiometry was not conducted in a sound-treated environment.
STUDY SAMPLE: 42 consecutively recruited participants from a tertiary otolaryngology department in Western Australia.
RESULTS: Absolute mean differences ranged between 5.12-9.68 dB (air-conduction) and 8.26-15 dB (bone-conduction). A total of 86.5% of manual and automated 4FAs were within 10 dB (i.e. ±5 dB); 94.8% were within 15 dB. However, there were significant (p < 0.05) differences between automated and manual audiometry at 250, 500, 1000, and 2000 Hz (air-conduction) and 500 and 1000 Hz (bone-conduction). The effect of age (≥55 years) on accuracy (p = 0.014) was not significant on linear regression (p > 0.05; R(2) =( ) 0.11). The presence of a hearing loss (better ear ≥26 dB) did not significantly affect accuracy (p = 0.604; air-conduction), (p = 0.218; bone-conduction).
CONCLUSIONS: This study provides clinical validation of automated audiometry using the KUDUwave in a clinically heterogeneous population, without the use of a sound-treated environment. Whilst threshold variations were statistically significant, future research is needed to ascertain the clinical significance of such variation.

PMID: 27206551 [PubMed - as supplied by publisher]

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