Evidence map›Paper›PMID 28772310›Full record

ArticleJAMA otolaryngology-- head & neck surgery2017

Development and Initial Validation of a Consumer Questionnaire to Predict the Presence of Ear Disease.

Samantha J Kleindienst, David A Zapala, Donald W Nielsen, James W Griffith, Dania Rishiq, Larry Lundy, Sumitrajit Dhar

Erratum issuedAbstract read
In one paragraph

Article in JAMA otolaryngology-- head & neck surgery, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
1.1field-weighted citation impact, top 24% 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

10 citing papers in PubMed, 17 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Audiologic Assessment.Seminars in hearing · 2022
    Review
  6. Article
  7. Errors in Items and Algorithm in Questionnaire Used in Validation Study.JAMA otolaryngology-- head & neck surgery · 2018
    Article
  8. Errors in Questionnaire Scoring Algorithm.JAMA otolaryngology-- head & neck surgery · 2018
    Article
  9. Article
  10. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors at 2 institutions in 1 country.

Samantha J KleindienstDivision of Audiology, Mayo Clinic Arizona, Scottsdale.
David A ZapalaDepartment of Otorhinolaryngology, Mayo Clinic, Jacksonville, Florida.
Donald W NielsenDon Nielsen Consulting, LLC, Dublin, Ohio.
James W GriffithDepartment of Medical Social Sciences, Northwestern University, Chicago, Illinois.
Dania RishiqDepartment of Otorhinolaryngology, Mayo Clinic, Jacksonville, Florida.
Larry LundyDepartment of Otorhinolaryngology, Mayo Clinic, Jacksonville, Florida.
Sumitrajit DharRoxelyn and Richard Pepper Department of Communication Sciences and Disorders, Northwestern University, Evanston, Illinois.
Jacksonville College · USNorthwestern University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Importance: The already large population of individuals with age- or noise-related hearing loss in the United States is increasing, yet hearing aids remain largely inaccessible. The recent decision by the US Food and Drug Administration to not enforce the medical examination prior to hearing aid fitting highlights the need to reengineer consumer protections when increasing accessibility. A self-administered tool to estimate ear disease risk would provide disease surveillance without posing an unreasonable barrier to hearing aid procurement. Objective: To develop and validate a consumer questionnaire for the self-assessment of risk for ear diseases associated with hearing loss. Design, Setting, and Participants: The questionnaire was developed using established methods including expert opinion to validate and create questions, and cognitive interviews to ensure that questions were clear to respondents. Exploratory structural equation modeling, logistic regression, and receiver operating characteristic curve analysis were used to determine sensitivity and specificity with blinded neurotologist opinion as the criterion for evaluation. Patients 40 to 80 years old with ear or hearing complaints necessitating a neurotologic examination and a control group of participants with a diagnosis of age- or noise-related hearing loss participated at the Departments of Otorhinolaryngology and Audiology of Mayo Clinic Florida. Main Outcomes and Measures: Sensitivity and specificity of the prototype questionnaire to identify individuals with targeted diseases. Results: Of 307 participants (mean [SD] age, 62.9 [9.8] years; 148 [48%] female), 75% (n = 231) were enrolled with targeted disease(s) identified on neurotologic assessment and 25% (n = 76) with age- or noise-related hearing loss. Participants were randomly divided into a training sample (80% [n = 246; 185 with disease, 61 controls]) and a test sample (20% [n = 61; 46 with disease, 15 controls]). Using a simple scoring method, a sensitivity of 94% (95% CI, 89%-97%) and specificity of 61% (95% CI, 47%-73%) were established in the training sample. Applying this cutoff to the test sample resulted in 85% (95% CI, 71%-93%) sensitivity and 47% (95% CI, 22%-73%) specificity. Conclusions and Relevance: This is the first self-assessment tool designed to assess an individual's risk for ear disease. Our preliminary results demonstrate a high sensitivity to disease detection. A further validated and refined version of this questionnaire may serve as an efficacious tool for improving access to hearing health care while minimizing the risk for missed ear diseases.

Indexed as

Diagnostic Self EvaluationSurveys and QuestionnairesAgedFemaleHearing AidsHearing LossHumansLogistic ModelsMaleMiddle AgedPredictive Value of TestsRisk AssessmentROC Curve

Identifiers

PMID28772310
PMCPMC5710257
OpenAlexW2743936422

What OpenQuestion holds

Textmetadata
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.