Evidence map›Paper›PMID 34683176›Full record

ArticleJournal of personalized medicine2021

Validation of a Personalized Hearing Screening Mobile Health Application for Persons with Moderate Hearing Impairment.

Lok-Yee Joyce Li, Shin-Yi Wang, Jinn-Moon Yang, Chih-Jou Chen, Cheng-Yu Tsai, Lucas Yee-Yan Wu, Te-Fang Wu, Cheng-Jung Wu

Open access · goldAbstract read
In one paragraph

Article in Journal of personalized medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.7field-weighted citation impact, top 33% 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

2 citing papers in PubMed, 9 citations in OpenAlex.

  1. Article
  2. Review
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

8 authors at 6 institutions in 2 countries.

Lok-Yee Joyce LiDepartment of Medicine, Shin Kong Wu-Ho-Su Memorial Hospital, Taipei 111, Taiwan.
Shin-Yi WangDepartment of Nursing, National Taiwan University Hospital, Hsinchu Branch, Hsinchu 300, Taiwan.
Jinn-Moon YangInstitute of Bioinformatics and Systems Biology, National Yang Ming Chiao Tung University, Hsinchu 300, Taiwan.
Chih-Jou ChenMaster Program in School of Nursing, Taipei Medical University, Taipei 110, Taiwan.
Cheng-Yu TsaiDepartment of Civil and Environmental Engineering, Imperial College London, London SW7 2BT, UK.ORCID 0000-0002-1639-4257
Lucas Yee-Yan WuSchool of Medicine, College of Medicine, Taipei Medical University, Taipei 110, Taiwan.
Te-Fang WuDepartment of Otolaryngology-Head and Neck Surgery, Kaohsiung Veterans General Hospital, Kaohsiung 813, Taiwan.
Cheng-Jung WuSchool of Medicine, College of Medicine, Taipei Medical University, Taipei 110, Taiwan.ORCID 0000-0002-7443-2119
National Yang Ming Chiao Tung University · TWTaipei Medical University-Shuang Ho Hospital · TWImperial College London · GBKaohsiung Veterans General Hospital · TWNational Taiwan University Hospital · TWTaipei Medical University · TW

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hearing impairment is a frequent human sensory impairment. It was estimated that over 50% of those aged >75 years experience hearing impairment in the United States. Several hearing impairment-related factors are detectable through screening; thus, further deterioration can be avoided. Early identification of hearing impairment is the key to effective management. However, hearing screening resources are scarce or inaccessible, underlining the importance of developing user-friendly mobile health care systems for universal hearing screening. Mobile health (mHealth) applications (apps) act as platforms for personalized hearing screening to evaluate an individual's risk of developing hearing impairment. We aimed to evaluate and compare the accuracy of smartphone-based air conduction and bone conduction audiometry self-tests with that of standard air conduction and bone conduction pure-tone audiometry tests. Moreover, we evaluated the use of smartphone-based air conduction and bone conduction audiometry self-tests in conductive hearing loss diagnosis. We recruited 103 patients (206 ears) from an otology clinic. All patients were aged ≥20 years. Patients who were diagnosed with active otorrhea was excluded. Moderate hearing impairment was defined as hearing loss with mean hearing thresholds >40 dB. All patients underwent four hearing tests performed by a board-certified audiologist: a smartphone-based air conduction audiometry self-test, smartphone-based bone conduction audiometry self-test, standard air-conduction pure-tone audiometry, and standard bone conduction pure-tone audiometry. We compared and analyzed the results of the smartphone-based air conduction and bone conduction audiometry self-tests with those of the standard air conduction and bone conduction pure-tone audiometry tests. The sensitivity of the smartphone-based air conduction audiometry self-test was 0.80 (95% confidence interval CI = 0.71-0.88) and its specificity was 0.84 (95% CI = 0.76-0.90), respectively. The sensitivity of the smartphone-based bone conduction audiometry self-test was 0.64 (95% CI = 0.53-0.75) and its specificity was 0.71 (95% CI = 0.62-0.78). Among all the ears, 24 were diagnosed with conductive hearing loss. The smartphone-based audiometry self-tests correctly diagnosed conductive hearing loss in 17 of those ears. The personalized smartphone-based audiometry self-tests correctly diagnosed hearing loss with high sensitivity and high specificity, and they can be a reliable screening test to rule out moderate hearing impairment among the population. It provided patients with moderate hearing impairment with personalized strategies for symptomatic control and facilitated individual case management for medical practitioners.

Indexed as

audiometryconductive hearing losshearing impairmentmobile healthsmartphone

Identifiers

PMID34683176
PMCPMC8538050
OpenAlexW3206377334

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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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.