Evidence map›Paper›PMID 41836612›Full record

ArticleDigital health

Understanding anesthesia anxiety: A mixed-methods analysis of propofol discourse on reddit.

James R Burmeister, John K Jung, Ismail Zazay, Roy G Soto

Abstract read
In one paragraph

Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

James R BurmeisterDepartment of Foundational Medical Studies, Oakland University William Beaumont School of Medicine, Rochester, MI, USA.ORCID https://orcid.org/0009-0003-9682-365X
John K JungJohn Sealy School of Medicine, University of Texas Medical Branch, Galveston, TX, USA.
Ismail ZazayJohn Sealy School of Medicine, University of Texas Medical Branch, Galveston, TX, USA.ORCID https://orcid.org/0009-0001-5544-0594
Roy G SotoAttending Anesthesiologist, Residency Program Director, Department of Anesthesiology, Corewell Health William Beaumont University Hospital, Royal Oak, MI, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Propofol is widely used in procedural sedation and general anesthesia, but often provokes anxiety among patients and some providers. This study investigates the emotional and thematic landscape of propofol-related discourse on Reddit, a major online health information platform. Methods: We analyzed 921 publicly available Reddit posts referencing "propofol" and related sedation terms using a mixed-methods approach. Sentiment analysis was performed with TextBlob and complemented by manual thematic coding. Posts were categorized by subreddit, sentiment, and topic. Descriptive statistics and correlation analyses examined relationships between sentiment, word count, and subreddit type. Results: Two coders achieved strong agreement (Cohen's κ = 0.82). Half of posts were neutral, whereas 30% were negative and 20% were positive. Negative sentiment was most common in patient-focused subreddits such as r/colonoscopy (38%), while provider forums like r/anesthesiology were more neutral or analytical. Among posts, 52% were patient-authored, 28% provider-authored, and 20% unclear. Patients more often expressed anxiety and confusion, while providers discussed clinical dilemmas and ethical issues. Higher word count was weakly correlated with more negative sentiment ( Conclusion: Reddit reveals emotionally rich propofol discourse, spanning patient fears and provider uncertainties. Analysis using digital health frameworks such as affective publics and the Technology Acceptance Model highlights opportunities for improved patient communication, education, and digital tool design. Limitations include platform demographic bias and limited generalizability. These findings offer a methodological foundation and conceptual framework for future digital health research and sentiment-aware clinical tools.

Indexed as

anesthesiaanxietyhealth communicationnatural language processingpatient participationPropofolsocial media

Identifiers

PMID41836612
PMCPMC12988267

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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.