Evidence map›Paper›PMID 35960191›Full record

ArticleGlobal health action2022

Community-based adult hearing care provided by community healthcare workers using mHealth technologies.

Caitlin Frisby, Robert H Eikelboom, Faheema Mahomed-Asmail, Hannah Kuper, Tersia de Kock, Vinaya Manchaiah, De Wet Swanepoel

Open access · goldAbstract read
In one paragraph

Article in Global health action, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
5.7field-weighted citation impact, top 3% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed, 1 synthesis or guideline pooled it, 31 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 6 institutions in 5 countries.

Caitlin FrisbyDepartment of Speech-Language Pathology and Audiology, University of Pretoria, Pretoria, South Africa.ORCID 0000-0002-9922-2927
Robert H EikelboomDepartment of Speech-Language Pathology and Audiology, University of Pretoria, Pretoria, South Africa.ORCID 0000-0003-2911-5381
Faheema Mahomed-AsmailDepartment of Speech-Language Pathology and Audiology, University of Pretoria, Pretoria, South Africa.ORCID 0000-0002-3666-8331
Hannah KuperInternational Centre for Evidence in Disability, London School of Hygiene & Tropical Medicine, London, UK.ORCID 0000-0002-8952-0023
Tersia de KockhearX Foundation, Pretoria, South Africa.ORCID 0000-0003-2850-1598
Vinaya ManchaiahDepartment of Speech-Language Pathology and Audiology, University of Pretoria, Pretoria, South Africa.ORCID 0000-0002-1254-8407
De Wet SwanepoelDepartment of Speech-Language Pathology and Audiology, University of Pretoria, Pretoria, South Africa.ORCID 0000-0001-8313-1636
University of Pretoria · ZAEar Science Institute Australia · AULondon School of Hygiene & Tropical Medicine · GBSouth African Veterinary Foundation · ZAThe University of Western Australia · AUUniversity of Colorado Hospital · US

Funding

Mobile technologies for delivering hearing care through community health workersR21DC019598 · NIDCD · CINCINNATI CHILDRENS HOSP MED CTR · PI MOORE, DAVID, SWANEPOEL, DEWET · 2022 to 2023
$361k
NIDCD NIH HHS R21 DC019598
6 · The paper itself

Abstract

backgroundThe rising prevalence of hearing loss is a global health concern. Professional hearing services are largely absent within low- and middle-income countries where appropriate skills are lacking. Task-shifting to community healthcare workers (CHWs) supported by mHealth technologies is an important strategy to address the problem.

objectiveTo evaluate the feasibility of a community-based rehabilitation model providing hearing aids to adults in low-income communities using CHWs supported by mHealth technologies.

methodBetween September 2020 and October 2021, hearing aid assessments and fittings were implemented for adults aged 18 and above in two low-income communities in the Western Cape, South Africa, using trained CHWs. A quantitative approach with illustrative open-ended questions was utilised to measure and analyse hearing aid outcomes. Data were 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. The International Outcome Inventory - Hearing Aids questionnaire determined standardised hearing aid outcomes.

resultsOf the 152 adults in the community who self-reported hearing difficulties, 148 were successfully tested by CHWs during home visits. Most had normal hearing (39.9%), 24.3% had bilateral sensorineural hearing loss, 20.9% had suspected conductive hearing loss, and 14.9% had unilateral hearing loss, of which 5.4% had suspected conductive loss. Forty adults met the inclusion criteria to be fitted with hearing aids. Nineteen of these were fitted bilaterally. Positive hearing aid outcomes and minimal device handling challenges were reported 45 days post-fitting and were maintained at six months. The majority (73.7%) of participants fitted were still making use of their hearing aids at the six-month follow-up.

conclusionsImplementing a hearing healthcare service-delivery model facilitated by CHWs in low-income communities is feasible. mHealth technologies used by CHWs can support scalable service-delivery models with the potential for improved access and affordability in low-income settings.

Indexed as

Hearing LossTelemedicineAdultCommunity Health ServicesCommunity Health WorkersDelivery of Health CareHearingHumansCommunity-based rehabilitationcommunity healthHearing losslow- and middle-income countriesmHealthteleaudiology

Identifiers

PMID35960191
PMCPMC9377258
OpenAlexW4290839700

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.