{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,30]],"date-time":"2026-04-30T12:26:07Z","timestamp":1777551967697,"version":"3.51.4"},"reference-count":9,"publisher":"SAGE Publications","license":[{"start":{"date-parts":[[2026,2,1]],"date-time":"2026-02-01T00:00:00Z","timestamp":1769904000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,2,1]],"date-time":"2026-02-01T00:00:00Z","timestamp":1769904000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"funder":[{"DOI":"10.13039\/100007865","name":"University of Texas Medical Branch","doi-asserted-by":"publisher","award":["NA"],"award-info":[{"award-number":["NA"]}],"id":[{"id":"10.13039\/100007865","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["DIGITAL HEALTH"],"published-print":{"date-parts":[[2026,2]]},"abstract":"<jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>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.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We analyzed 921 publicly available Reddit posts referencing \u201cpropofol\u201d 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.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Two coders achieved strong agreement (Cohen's \u03ba\u2009=\u20090.82). 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 (\n                      <jats:italic toggle=\"yes\">r<\/jats:italic>\n                      \u2009=\u2009\u22120.19). Four thematic clusters emerged: clinical sedation and medication questions; provider professionalism and ethics; veterinary use and animal care; and exam stress or career anxiety.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>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.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1177\/20552076261434056","type":"journal-article","created":{"date-parts":[[2026,3,14]],"date-time":"2026-03-14T05:46:06Z","timestamp":1773467166000},"update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":0,"title":["Understanding anesthesia anxiety: A mixed-methods analysis of propofol discourse on reddit"],"prefix":"10.1177","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0009-0003-9682-365X","authenticated-orcid":false,"given":"James R.","family":"Burmeister","sequence":"first","affiliation":[{"name":"Oakland University William Beaumont School of Medicine"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"John K.","family":"Jung","sequence":"additional","affiliation":[{"name":"University of Texas Medical Branch"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-5544-0594","authenticated-orcid":false,"given":"Ismail","family":"Zazay","sequence":"additional","affiliation":[{"name":"University of Texas Medical Branch"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Roy G.","family":"Soto","sequence":"additional","affiliation":[{"name":"Corewell Health William Beaumont University Hospital"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","published-online":{"date-parts":[[2026,3,13]]},"reference":[{"key":"e_1_3_3_2_2","doi-asserted-by":"publisher","DOI":"10.1021\/acsptsci.4c00745"},{"key":"e_1_3_3_3_2","doi-asserted-by":"publisher","DOI":"10.4103\/ija.ija_232_24"},{"key":"e_1_3_3_4_2","doi-asserted-by":"publisher","DOI":"10.1111\/add.70022"},{"key":"e_1_3_3_5_2","article-title":"Reddit user age, gender, and key demographics statistics (2025 data)","author":"Connell AF","unstructured":"Connell AF. Reddit user age, gender, and key demographics statistics (2025 data). Adam Connell 2025 Apr 28. Accessed 2025 Jul 18. https:\/\/adamconnell.me\/reddit-statistics\/","journal-title":"Adam Connell"},{"key":"e_1_3_3_6_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-76452-3_25"},{"key":"e_1_3_3_7_2","doi-asserted-by":"publisher","DOI":"10.1007\/s10115-024-02214-3"},{"key":"e_1_3_3_8_2","doi-asserted-by":"publisher","DOI":"10.1145\/3633070"},{"key":"e_1_3_3_9_2","first-page":"1052","article-title":"A comparative review of deep learning techniques on the classification of irony and sarcasm in text","volume":"5","author":"Ravikoshi L","year":"2024","unstructured":"Ravikoshi L, Palokangas S. A comparative review of deep learning techniques on the classification of irony and sarcasm in text. IEEE Trans Affect Comput 2024; 5: 1052\u20131066.","journal-title":"IEEE Trans Affect Comput"},{"key":"e_1_3_3_10_2","doi-asserted-by":"publisher","DOI":"10.1186\/s12904-024-01612-2"}],"container-title":["DIGITAL HEALTH"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1177\/20552076261434056","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/full-xml\/10.1177\/20552076261434056","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1177\/20552076261434056","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,28]],"date-time":"2026-04-28T17:56:28Z","timestamp":1777398988000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/10.1177\/20552076261434056"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,2]]},"references-count":9,"alternative-id":["10.1177\/20552076261434056"],"URL":"https:\/\/doi.org\/10.1177\/20552076261434056","relation":{},"ISSN":["2055-2076","2055-2076"],"issn-type":[{"value":"2055-2076","type":"print"},{"value":"2055-2076","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,2]]},"article-number":"20552076261434056"}}