mHealth-supported hearing care for adults in communities : evaluating an innovative service-delivery model

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dc.contributor.advisor Swanepoel, De Wet
dc.contributor.coadvisor Mahomed-Asmail, Faheema
dc.contributor.coadvisor Eikelboom, Robert
dc.contributor.postgraduate Frisby, Caitlin
dc.date.accessioned 2023-12-18T07:43:21Z
dc.date.available 2023-12-18T07:43:21Z
dc.date.created 2024-04
dc.date.issued 2023-08-31
dc.description Thesis (PhD (Audiology))--University of Pretoria, 2023. en_US
dc.description.abstract Hearing loss is a major global health concern, with prevalence rates expected to increase in the coming years. Although hearing loss affects individuals globally, a significant portion of individuals with hearing loss reside in low- and middle-income countries (LMICs) where hearing healthcare services are limited or non-existent. The combination of task-shifting to community healthcare workers (CHWs), supported by innovative technologies such as mobile health (mHealth), has been highlighted as a priority to enhance access to point-of-care services and community-based care. This research project aimed to evaluate a mHealth-supported hearing care model for adults in communities facilitated by CHWs and constituted four studies. Increasing use of mHealth approaches to improve access, scalability, penetration, quality, and convenience of health services has been demonstrated. However, a comprehensive assessment of the range of mHealth use for hearing healthcare across the care continuum and from a global perspective has not been undertaken. Study One of this research project aimed to identify and describe the published research in mHealth-supported hearing healthcare services across the continuum of care. Three databases (Scopus, MEDLINE (PubMed), and Web of Science) were searched, following the Joanna Briggs Institute Reviewers Manual guidelines. A total of 146 articles were included, with high-income countries accounting for 56% of the contributions, upper-middle-income countries with 32%, lower-middle-income countries with 8%, and low-income countries with 4%. The identified articles covered various aspects of hearing healthcare, including promotion (2%), screening (39%), diagnosis (35%), treatment (10%), and support (14%) for hearing loss. In terms of mHealth use, high-income countries were more prevalent in diagnosis (62% vs 38%), treatment (67% vs 33%), and support (82% vs 18%) compared to low- and middle-income countries (LMICs), except for screening (64% vs 36%). Relatively few studies focused on hearing health promotion across all income brackets. The results of this study demonstrate the potential of mHealth-supported hearing healthcare services globally. However, rigorous implementation evaluations are still necessary, particularly in LMICs. Study Two aimed to validate smartphone-facilitated in-situ audiometry with noise-attenuating ear cups facilitated by CHWs. This study comprised of four experiments, including determining the maximum permissible ambient noise levels (MPANLs), assessing inter-device reliability, evaluating clinical threshold accuracy, and performance in real-world settings. Results showed that MPANLs for in-situ hearing aids were higher than standard headphones (24 to 47.3 dB) across all frequencies. The second experiment indicated that inter-device reliability was high, with all inter-device differences across all intensities and frequencies less than 3 dB. Frequency output was consistent and differed less than 0.7% between devices. Experiments 3 and 4 revealed that automated in-situ audiometry has a high level of accuracy compared to clinical audiometry. Most thresholds (85.2% and 83.3%) were within 10 dB of thresholds obtained in the sound booth and a community setting, respectively. Test-retest reliability was also acceptable for both settings, with and ICC of 0.85 to 0.93 in a soundproof booth and 0.83 to 0.97 in a community setting. The findings of this study conclude that smartphone-facilitated in-situ audiometry is a reliable and valid approach for community-based testing. Study Three aimed to evaluate the feasibility of a community-based rehabilitation model providing hearing aids to adults in low-income communities using CHWs supported by mHealth technologies. Hearing aid outcomes were measured and analysed using a quantitative approach (IOI-HA) with illustrative open-ended questions. Data was collected through initial face-to-face interviews, telephone interviews, and face-to-face visits post-fitting. Responses to open-ended questions were analysed using inductive thematic analysis. Out of the 152 adults in the community who reported having hearing difficulties, CHWs successfully tested 148 individuals during home visits. A total of 40 adults qualified for hearing aid fittings based on the inclusion criteria, with 19 of them being fitted bilaterally with hearing aids. Positive outcomes and minimal challenges in handling the devices were reported 45 days after the fitting and were still maintained at the six-month follow-up. Most participants (73.7%) fitted with hearing aids were still using them at the six-month follow-up. Implementing a hearing healthcare service-delivery model facilitated by CHWs in low-income communities is thus feasible. Utilising mHealth technologies, CHWs can enable scalable service-delivery models, offering the potential for enhanced accessibility and affordability in low-income settings. Study Four aimed to evaluate the feasibility of a mHealth acclimatisation and support program supported by CHWs in low-income communities. An application-based acclimatisation and support program was adapted and translated for use in LMICs. Twenty messages were sent over a 45-day period. Participants were contacted to collect their feedback 45 days and six months after the program's initiation. Inductive thematic analysis was employed. The majority (78.9%; 15/19) received the program through WhatsApp, while 21.1% (4/19) received it via SMS. Participants described the program as helpful, supportive, informative, sufficient, and clear during both follow-ups. The mHealth acclimatisation and support program demonstrated the feasibility and potential benefits of assisting first-time hearing aid users in low-income communities. Implementing scalable mHealth-support options can enhance access to hearing care and improve overall outcomes for these individuals. The results of this research project highlighted the feasibility of innovative hearing healthcare service-delivery models facilitated by CHWs using mHealth to improve access and affordability of hearing services in LMICs. Trained CHWs can successfully provide a range of hearing healthcare services, including hearing assessments, hearing aid fittings, and assistance with acclimatisation and support. The lack of hearing healthcare services and professionals is a persistent barrier in LMICs. Strategies, including decentralisation through task-shifting, are feasible (as demonstrated by Studies Three and Four) and should be prioritised to improve access. en_US
dc.description.availability Unrestricted en_US
dc.description.degree PhD (Audiology) en_US
dc.description.department Speech-Language Pathology and Audiology en_US
dc.description.faculty Faculty of Humanities en_US
dc.description.sdg SDG-10: Reduces inequalities en_US
dc.identifier.citation * en_US
dc.identifier.doi 10.25403/UPresearchdata.24792801 en_US
dc.identifier.other A2024 en_US
dc.identifier.uri http://hdl.handle.net/2263/93793
dc.language.iso en en_US
dc.publisher University of Pretoria
dc.rights © 2023 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria.
dc.subject UCTD en_US
dc.subject Community-based hearing health en_US
dc.subject mHealth en_US
dc.subject Low- and middle-income countries en_US
dc.subject In-situ audiometry en_US
dc.subject Community healthcare workers en_US
dc.title mHealth-supported hearing care for adults in communities : evaluating an innovative service-delivery model en_US
dc.type Thesis en_US


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