Equality in Hearing Aid Access: A Systematic Review and Meta-analysis
Notice bibliographique
Résumé
Abstract Importance Most people with hearing impairment do not acquire hearing aids, but it is unknown what sociodemographic factors influence access. Objective To systematically review, synthesize and meta-analyze sociodemographic characteristics of people who do and do not acquire hearing aids after hearing loss diagnosis. Data sources We pre-registered the study (PROSPERO: CRD42023428580), and searched MEDLINE, EMBASE, and Web of Science from inception to 27 October 2025. Search terms included hearing aids and cohort study terms. Study selection We included observational studies with participants aged ≥18 years who had hearing loss confirmed through pure-tone audiometry, with any sociodemographic characteristics of those who do and do not access hearing aids. Data extraction and synthesis Using the Meta-analysis of Observational Studies in Epidemiology (MOOSE) guidelines, three authors independently extracted data, assessing study quality using the Newcastle-Ottawa Scale. We calculated ratios of people with hearing loss from each sociodemographic characteristic who acquired hearing aids. We used random effects meta-analyses. Main outcomes and measures Hearing aid acquisition. Results 36 studies including 300,946 people met criteria. Men were more likely to acquire hearing aids than women (n, 287,964; RR, 1.09[1.02-1.17]; I 2 , 98.7%), White people more than other ethnic/racial groups (n, 274,860; RR, 1.26[1.07-1.55]; I 2 , 99.9%), >12 years vs. ≤12 years of education (n, 5,970; RR, 1.17[1.04, 1.32]; I 2 , 79.4%), and pension recipients more than non-recipients (n, 1,678; RR, 1.50 [1.08,2.09], I 2 , 87.4%). There were no differences in hearing aid acquisition by very low household income (≥US$45,000/year vs. 2 , 0%), employment status (currently employed vs. not employed (RR, 0.58[0.34-1.00]; I 2 , 84.2%), relationship status (currently married/partnered vs. not; RR, 0.96[0.87-1.16]; I 2 , 70.0%), living alone vs. with others (RR, 0.82[0.57-1.18]; I 2 , 97.7%) or rural vs. urban areas (RR, 1.20[0.86-1.68]; I 2 , 94.4%). Conclusion and Relevance Underserved groups (women, minorities, those with less education and not receiving pensions) are less likely to get hearing aids, even after hearing testing. Meta-analyses had high heterogeneity, so findings are not generalizable. Some underserved people can access hearing aids, and it is important to further investigate the barriers and enablers. No studies controlled for hearing severity, so findings are limited by confounding by indication. Key Points Question What groups of people with diagnosed hearing loss acquire hearing aids? Finding: Among 300,946 individuals with hearing loss (36 studies), men, those with >12 years of education, pension recipients, and White individuals were more likely to acquire hearing aids. We found no differences based on household income, employment status, relationship status, rural vs. urban areas, and living arrangement. Meaning After accessing hearing services, hearing aid acquisition is related to sex, ethnicity or race, education, and pension status, but no other sociodemographic indicators. Further research is needed about enablers and barriers to obtaining hearing aids for women and ethnic minorities.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,025 | 0,066 |
| Méta-épidémiologie (sens strict) | 0,003 | 0,002 |
| Méta-épidémiologie (sens large) | 0,023 | 0,039 |
| Bibliométrie | 0,008 | 0,009 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,004 | 0,003 |
| Science ouverte | 0,003 | 0,002 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».