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MP21-18 MISCONCEPTIONS ABOUT WOMEN WITH RECURRENT URINARY TRACT INFECTION IN YOUTUBE EDUCATIONAL VIDEOS; INCONGRUENCE WITH AUA GUIDELINES - HEALTH EQUITY FINDINGS

2023· article· en· W4360607964 on OpenAlexaboutno aff
Mostafa Bondok, Lynn Stothers, Andrew Macnab, Vancouver, Mohamed Bandok, Calgary, Emma Dixon, Marcia Trochez, Kelsey Petersen, Rishika Selvakumar

Bibliographic record

VenueThe Journal of Urology · 2023
Typearticle
Languageen
FieldMedicine
TopicPelvic floor disorders treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineEquity (law)Health careFamily medicineLibrary science

Abstract

fetched live from OpenAlex

You have accessJournal of UrologyCME1 Apr 2023MP21-18 MISCONCEPTIONS ABOUT WOMEN WITH RECURRENT URINARY TRACT INFECTION IN YOUTUBE EDUCATIONAL VIDEOS; INCONGRUENCE WITH AUA GUIDELINES - HEALTH EQUITY FINDINGS Mostafa Bondok, Lynn stothers, Andrew Macnab, Vancouver, Canada, Mohamed Bandok, Calgary, Canada, A. Lenore Ackerman, Emma Dixon, Marcia Trochez, Kelsey Petersen, and Rishika Selvakumar Mostafa BondokMostafa Bondok , Lynn stothers Lynn stothers , Andrew MacnabAndrew Macnab , Vancouver Vancouver , Canada Canada , Mohamed BandokMohamed Bandok , Calgary Calgary , Canada Canada , A. Lenore AckermanA. Lenore Ackerman , Emma DixonEmma Dixon , Marcia TrochezMarcia Trochez , Kelsey PetersenKelsey Petersen , and Rishika SelvakumarRishika Selvakumar View All Author Informationhttps://doi.org/10.1097/JU.0000000000003246.18AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Stigmatization of health illness is a threat to health equity. Although case control studies demonstrate that commonly suggested hygiene practices do not decrease the incidence of urinary tract infection (UTI) in women, many patient-education sources promote this misconception, & in doing so risk stigmatizing women with UTIs as 'dirty' or 'unclean'. Objective: To document the quality, veracity, & comprehensiveness of recurrent UTI (rUTI) information on YouTube to increase health care workers' (HCWs) awareness of UTI-related content online, & to identify deficits in understanding, clarify misconceptions & reduce stigmatization risk. METHODS: High-traffic topic search terms were curated by Google Trends to extract 200, of which 45 met inclusion criteria. 5 independent reviewers used a standardized questionnaire based on the AUA rUTI guidelines to assess definition of UTI, marketing content, prophylaxis/prevention strategies, & antibiotic use/stewardship. Statistics: Fleiss kappa (K) assessed Inter-rater reliability (IRR). RESULTS: High variability and incongruency from guideline definitions of UTI (Table 1); the most common prophylactic strategy discussed Cranberry; only 55% discussed increasing fluid intake. Table 2 illustrates commonly recommended hygiene practices: including front to back wiping (25%) K=0.71. 33% promoted other non-evidence-based hygiene practices including expression of uncleanliness of women. CONCLUSIONS: Misleading information for women seeking education on UTI through YouTube is high. Misinformation on hygiene practices is unproductive, & several videos captured HCWs claiming that rUTI results from poor female hygiene practices, creating a health equity concern for women experiencing UTIs. These findings alert HCWs on the need to provide evidence-based recommendations by consulting practice guidelines, such as those provided by the AUA. Source of Funding: n/a © 2023 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 209Issue Supplement 4April 2023Page: e293 Advertisement Copyright & Permissions© 2023 by American Urological Association Education and Research, Inc.MetricsAuthor Information Mostafa Bondok More articles by this author Lynn stothers More articles by this author Andrew Macnab More articles by this author Vancouver More articles by this author Canada More articles by this author Mohamed Bandok More articles by this author Calgary More articles by this author Canada More articles by this author A. Lenore Ackerman More articles by this author Emma Dixon More articles by this author Marcia Trochez More articles by this author Kelsey Petersen More articles by this author Rishika Selvakumar More articles by this author Expand All Advertisement PDF downloadLoading ...

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.073
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.105
Threshold uncertainty score0.352

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.073
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0030.001
Scholarly communication0.0030.003
Open science0.0010.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.1050.012

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.060
GPT teacher head0.388
Teacher spread0.327 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations1
Published2023
Admission routes1
Has abstractyes

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