ArticlePLOS digital health2026
Hierarchy and hope: Exploring AI's role in medicine through a thematic analysis of online discourse.
Article in PLOS digital health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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.
Who cites it
1 citing paper in PubMed.
- Generative artificial intelligence in medical education: from knowledge assessment to clinical reasoning and professional competence.Frontiers in medicine · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The healthcare community remains divided on the benefits of artificial intelligence (AI) in medicine. In this qualitative study, we sought to better understand the perceived opportunities and threats of AI among premedical students, medical students, and physicians. We conducted a thematic analysis on Reddit, a social platform where candid opinions are often shared. Posts from the r/premed, r/medicalschool, and r/medicine subreddits were searched using the terms "AI", "chatGPT", "openAI", and "artificial intelligence". We analyzed 2403 comments across 47 threads from December 2022 to August 2023. A coding scheme was developed manually following Braun and Clarke's (2006) framework, and common themes were extracted. The main themes identified centered on AI enhancement versus replacement. Careers perceived to be lower in the medical social hierarchy were considered most at risk of replacement. AI was thought to first replace non-medical jobs, followed by mid-levels, and then primary care and diagnostic specialties, with specialists and surgeons affected last. Some contributors emphasized that AI could never replace a physician's compassion and nuanced clinical judgment. Others viewed AI as a tool to enhance efficiency, particularly in tasks such as studying, note writing, screening, and triage. Although verifying the credentials of commenters on online forums poses a challenge, platforms like Reddit offer a valuable opportunity to understand nuanced attitudes and perceptions regarding AI in medicine. Online forums allow for a unique understanding of the impressions of AI in medicine. While AI was generally well-received, we identified a key finding: a socially hierarchical, biased form of thinking among healthcare professionals. The perpetuation of this biased mindset may contribute to role devaluation, mistrust, and collaboration challenges within healthcare teams-ultimately impacting patient care. To fully leverage AI's potential in medicine, it is critical to acknowledge and address potentially biased perceptions within the healthcare community.
Identifiers
What OpenQuestion holds
Registered trials
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.