Health information use by patients with systemic lupus erythematosus (SLE) pre and during the COVID-19 pandemic
Notice bibliographique
Résumé
OBJECTIVE: We conducted an international survey of patients with SLE to assess their access, preference and trust in various health information sources pre-COVID-19 and during the COVID-19 pandemic. METHODS: Patients with SLE were recruited from 18 observational cohorts, and patients self-reporting SLE were recruited through five advocacy organisations. Respondents completed an online survey from June 2020 to December 2021 regarding the sources of health information they accessed in the 12 months preceding (pre-11 March 2020) and during (post-11 March 2020) the pandemic. Multivariable logistic regressions assessed factors associated with accessing news and social media post-11 March 2020, and self-reporting negative impacts from health information accessed through these sources. RESULTS: Surveys were completed by 2111 respondents; 92.8% were female, 76.6% had postsecondary education, mean (SD) age was 48.8 (14.0) years. Lupus specialists and family physicians were the most preferred sources pre-11 March 2020 and post-11 March 2020, yet were accessed less frequently (specialists: 78.5% pre vs 70.2% post, difference -8.3%, 95% CI -10.2% to -6.5%; family physicians: 57.1% pre vs 50.0% post, difference -7.1%, 95% CI -9.2% to -5.0%), while news (53.2% pre vs 62.1% post, difference 8.9%, 95% CI 6.7% to 11.0%) and social media (38.2% pre vs 40.6% post, difference 2.4%, 95% CI 0.7% to 4.2%) were accessed more frequently post-11 March 2020 vs pre-11 March 2020. 17.2% of respondents reported negative impacts from information accessed through news/social media. Those outside Canada, older respondents or with postsecondary education were more likely to access news media. Those in Asia, Latin America or younger respondents were more likely to access social media. Those in Asia, older respondents, males or with postsecondary education in Canada, Asia or the USA were less likely to be negatively impacted. CONCLUSIONS: Physicians, the most preferred and trusted sources, were accessed less frequently, while news and social media, less trusted sources, were accessed more frequently post-11 March 2020 vs pre-11 March 2020. Increasing accessibility to physicians, in person and virtually, may help reduce the consequences of accessing misinformation/disinformation.
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 | 0,001 | 0,006 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
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 ».