Technology for hearing loss – as We Know it, and as We Dream it

Clark, Jackie L.; Swanepoel, De Wet

doi:10.3109/17483107.2014.905642

Cited by 46 publications

(84 citation statements)

References 27 publications

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“…Prevention or early identification can reduce the negative consequences of a hearing loss, is usually less expensive and can often be implemented at a community level [13,15]. Costs may also be reduced by using innovative technologies using mobile health or mHealth applications [13,16]. …”

Section: Introductionmentioning

confidence: 99%

“…With the widespread penetration of 4.92 billion mobile phones worldwide, of which more than 3.74 billion are smartphones, mHealth hearing applications are demonstrating promise to improve access to hearing services in low- and middle-income countries (LMICs) [16–20]. One such mHealth solution, validated in various contexts, is the hearScreen TM solution that allows a low-cost alternative to conventional hearing screening equipment whilst adhering to required acoustic calibration standards [21,22].…”

Section: Introductionmentioning

confidence: 99%

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Community-based hearing screening for young children using an mHealth service-delivery model

Hussein

Swanepoel

Mahomed

et al. 2018

Global Health Action

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Background: Hearing loss is one of the most common developmental disorders identifiable at birth with its prevalence increasing throughout school years. However, early detection programs are mostly unavailable in low- and middle-income countries (LMICs) where more than 80% of children with hearing loss reside.Objective: This study investigated the feasibility of a smartphone-based hearing screening program for preschool children operated by community healthcare workers (CHWs) in community-based early childhood development (ECD) centers.Method: Five CHWs were trained to map ECD centers and conduct smartphone-based hearing screenings within a poor community in South Africa over a 12-month period. The hearScreenTM smartphone application employed automated test protocols operating on low-cost smartphones. A cloud-based data management and referral function allowed for remote monitoring for surveillance and follow up.Results: 6424 children (3–6 years) were screened for hearing loss with an overall referral rate of 24.9%. Only 39.4% of these children attended their follow-up appointment at a local clinic, of whom 40.5% referred on their second screening. Logistic regression analysis indicated that age, gender and environmental noise levels (1 kHz) had a significant effect on referral rates (p < 0.05). The quality index reflecting test operator test quality increased during the first few months of testing.Conclusion: Smartphone-based hearing screening can be used by CHWs to detect unidentified children affected by hearing loss within ECD centers. Active noise monitoring, quality indices of test operators and cloud-based data management and referral features of the hearScreenTM application allows for the asynchronous management of hearing screenings and follow-ups.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Community-based hearing screening for young children using an mHealth service-delivery model

Hussein

Swanepoel

Mahomed

et al. 2018

Global Health Action

Self Cite

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“…A survey, conducted by Fagan and Jacobs (2009), concluded that there is less than one hearing healthcare professional for every one million people in developing countries. The shortage of professionals combined with a lack of infrastructure and resources, as well as too few training facilities, impedes the provision of adequate hearing healthcare services (Clark & Swanepoel, 2014;Fagan & Jacobs, 2009;Swanepoel, Olusanya & Mars, 2010a).…”

Section: Introductionmentioning

confidence: 99%

“…Automated audiometry such as the Otogram and AMTAS have the potential to increase hearing healthcare service delivery because they do not require trained professionals to conduct the assessment procedures (Margolis et al, 2010;Ho et al, 2009). As such, paraprofessionals can be trained to facilitate audiological assessments, because automation greatly reduces the complexity of these services (Clark & Swanepoel, 2014;Swanepoel, Clark, Koekemoer, Hall, Krumm, Ferrari, McPhearson, Olusanya, Mars, Russo & Barajas, 2010b). As a result, hearing healthcare professionals are able to focus their attention on management, counselling and intervention (Swanepoel et al, 2010b).…”

Section: Introductionmentioning

confidence: 99%

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Automated Smartphone Threshold Audiometry: Validity and Time Efficiency

et al. 2017

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Smartphone-based threshold audiometry with automated testing has the potential to provide affordable access to audiometry in underserved contexts.To validate the threshold version (hearTest) of the validated hearScreen™ smartphone-based application using inexpensive smartphones (Android operating system) and calibrated supra-aural headphones.A repeated measures within-participant study design was employed to compare air-conduction thresholds (0.5–8 kHz) obtained through automated smartphone audiometry to thresholds obtained through conventional audiometry.A total of 95 participants were included in the study. Of these, 30 were adults, who had known bilateral hearing losses of varying degrees (mean age = 59 yr, standard deviation [SD] = 21.8; 56.7% female), and 65 were adolescents (mean age = 16.5 yr, SD = 1.2; 70.8% female), of which 61 had normal hearing and the remaining 4 had mild hearing losses.Threshold comparisons were made between the two test procedures. The Wilcoxon signed-ranked test was used for comparison of threshold correspondence between manual and smartphone thresholds and the paired samples t test was used to compare test time.Within the adult sample, 94.4% of thresholds obtained through smartphone and conventional audiometry corresponded within 10 dB or less. There was no significant difference between smartphone (6.75-min average, SD = 1.5) and conventional audiometry test duration (6.65-min average, SD = 2.5). Within the adolescent sample, 84.7% of thresholds obtained at 0.5, 2, and 4 kHz with hearTest and conventional audiometry corresponded within ≤5 dB. At 1 kHz, 79.3% of the thresholds differed by ≤10 dB. There was a significant difference (p < 0.01) between smartphone (7.09 min, SD = 1.2) and conventional audiometry test duration (3.23 min, SD = 0.6).The hearTest application with calibrated supra-aural headphones provides a cost-effective option to determine valid air-conduction hearing thresholds.

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