(028) The Impact of Misinformation on Patient Perceptions Undergoing Sexual Health and Other Urological Procedures
Notice bibliographique
Résumé
Abstract Introduction Misinformation and particularly health misinformation, has become rampant in society. Misinformation is defined as the spread of false information irrespective of the intent and has become pervasive due to today’s information channels. The repercussions of misinformation is significant as the World Health Organization declared a COVID-19 ‘infodemic’ in February 2020 as one example in order to combat this phenomenon. The spread of false information among patients has caused for confusion, mistrust with healthcare systems and providers. Although misinformation has been acknowledged on broad scales such as healthcare, there is scarce evidence about the prevalence and effect in certain areas of health and medicine. One particular area of health that may have an inordinate amount of misinformation affecting patient perception is sexual health and urology. Objective The objective of this study was to determine where patients gather information prior to their procedure/consultation and assess their perception as to the reliability of the information. Methods Prior to the consultation/procedure, patients were consented and enrolled to complete a questionnaire consisting of Likert scale, short answer and multiple-choice questions regarding search strategies and perception on misinformation. Demographic, online search strategies and misinformation questions were used to evaluate patient perceptions about general misinformation and the reliability of online information. Cronbach’s alpha was calculated for the Likert questions to assess for internal validity and evaluated on its original five-point scale by a Chi-Square Goodness of Fit Test using R software (v 4.0.3). A p-value < 0.05 was considered statistically significant. Results To date we have enrolled 102 patients. From the survey results, 64.7% patients indicated that they searched up their condition on the internet prior to their consultation/procedure with 86.6% using Google to find relevant information. Short answer questions revealed patients used disease names or descriptive words of their condition when searching for information. Additionally, 40.3% and 43.1% of patients that searched their conditions found the information very reliable or somewhat reliable respectively and was statistically significant. 79.4% and 40.2% of patients spoke with their partner, if applicable, and their friends respectively about their condition. If they did not however, embarrassment to discuss or feeling alone were major reasons to not do so. Patients responded that misinformation is a significant concern when searching up health information. Interestingly, only 4.9% and 56.9% of patients strongly agreed and agreed they were able to identify misinformation and was statistically significant. The majority of patients also strongly agreed or agreed that learning information prior to their appointment affects their relationship with their physician (13.7% and 37.3% respectively). Conclusions Misinformation alters how sexual medicine and urology patients deal with their condition and relationship with their physician. This study is critical to identify areas to create a tailored approach for urologists and sexual medicine specialists to assist in situations where patients may be misinformed about their health. Disclosure No
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,004 | 0,019 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,013 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».