Evidence map›Paper›PMID 38130265›Full record

ArticleLaryngoscope investigative otolaryngology2023

Physician views of artificial intelligence in otolaryngology and rhinology: A mixed methods study.

Annapoorani Asokan, Conner J Massey, Caroline Tietbohl, Kurt Kroenke, Megan Morris, Vijay R Ramakrishnan

Open access · goldAbstract read
In one paragraph

Article in Laryngoscope investigative otolaryngology, 2023. 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
0.8field-weighted citation impact, top 21% 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, 21 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Review
  4. Review
  5. Auditory and Psychological Impacts of Tympanoplasty in Chronic Suppurative Otitis Media Patients: A Mixed-Methods Study.Indian journal of otolaryngology and head and neck surgery : official publication of the Association of Otolaryngologists of India · 2024
    Article
  6. Autonomous Robotic Systems in Otolaryngology-Head and Neck Surgery.Otolaryngologic clinics of North America · 2024
    Review
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
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

6 authors at 4 institutions in 1 country.

Annapoorani AsokanDepartment of Internal Medicine USC/LA General Medical Center Los Angeles California USA.ORCID https://orcid.org/0000-0003-1550-6349
Conner J MasseyDepartment of Otolaryngology-Head & Neck Surgery University of Colorado School of Medicine Aurora Colorado USA.
Caroline TietbohlDepartment of Family Medicine University of Colorado School of Medicine Aurora Colorado USA.
Kurt KroenkeIndiana University School of Medicine Indianapolis Indiana USA.
Megan MorrisQualitative and Mixed Methods Research Core, Adult and Child Center for Outcomes Research Delivery Science (ACCORDS) University of Colorado School of Medicine Aurora Colorado USA.
Vijay R RamakrishnanRegenstrief Institute, Inc. Indianapolis Indiana USA.
Outcomes Research Consortium · USRegenstrief Institute · USLAC+USC Medical Center · USUniversity of Colorado Denver · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: The study aimed to investigate otolaryngologists' knowledge, trust, acceptance, and concerns with clinical applications of artificial intelligence (AI). Methods: This study used mixed methods with survey and semistructured interviews. Survey was e-mailed to American Rhinologic Society members, of which a volunteer sample of 86 members responded. Nineteen otolaryngologists were purposefully recruited and interviewed until thematic saturation was achieved. Results: Seventy-six respondents (10% response rate) completed the majority of the survey: 49% worked in academic settings and 43% completed residency 10 or fewer years ago. Of 19 interviewees, 58% worked in academic settings, and 47% completed residency 10 or fewer years ago. Conclusion: Few physicians have experience with AI technologies but expect rapid adoption in the clinic, highlighting the urgent need for clinical education and research. Otolaryngologists are most receptive to AI "augmenting" physician expertise and administrative capacity, with respect for physician autonomy and maintaining relationships with patients. Level of Evidence: Level VI, descriptive or qualitative study.

Indexed as

artificial intelligencechronic rhinosinusitismachine learningpatient satisfactionqualitative research

Identifiers

PMID38130265
PMCPMC10731489
OpenAlexW4388068251

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.