CORRELATES OF COVID VACCINATION UPTAKE AMONG ADULTS WITH SYSTEMIC LUPUS ERYTHEMATOSUS: EMERGING FINDINGS FROM THE 2024-25 RESPIRATORY VIRUS SEASON
Notice bibliographique
Résumé
PV079 / #745 Poster Topic: AS11 - Epidemiology and Public Health Background/Purpose People with systemic lupus erythematosus (SLE) are considered more susceptible to COVID; those who become infected may also experience greater severity and disease consequences. COVID vaccination among people with autoimmune diseases is a public health priority. The current study identifies correlates of uptake of the 2024-25 COVID vaccine formulation among people with SLE. Methods Participants were adults 18 years of age and older diagnosed with SLE who live, work, or seek care in Alabama, Louisiana, and Mississippi recruited between August 23, 2024, and January26, 2025 as part of an ongoing study (n=122). Multivariable logistic regression was used to examine 2024-25 COVID vaccination assessed through self-report. Results Approximately 18% of participants (n=22) reported receiving the most recent COVID vaccine. Satterthwaite t-tests revealed that those reporting more barriers to accessing healthcare—lack of transportation, greater distance, competing demands (work, family), cost, and inadequate insurance—were less likely to report receiving the most recent COVID vaccine (t=3.3, 53.4 df, p<0.01). Similarly, reporting barriers within medical contexts—dislike of their hospital, wait times, confusion with the healthcare system, distrust of their doctor, not feeling listened by their doctor, not believing in the efficacy of treatment, and worry about what would happen at the appointment—was associated with lower self-reported vaccination (t=2.1, 59.6 df, p<0.05). Older age was associated with greater reports of vaccination (t=-2.9, 27.2 df, p<0.01). Multivariable logistic regression models were specified, including barriers to access, medical care barriers, demographic (age, race, relationship status), socioeconomic (income, education, work status), and health characteristics (years since SLE diagnosis, organ damage), as well the time of assessment. In this model, barriers to access (OR 0.4, 95% CI 0.2-1.0, p=0.06) and age (OR 1.1, 95% CI 1.0, 1.1, p=0.5) were associated with COVID vaccination at the trend level. Timing of participant assessment was significant at the p=0.07 level (chi-square 7.1, 3 df). As expected, compared to those assessed in October and earlier, those who participated in subsequent months had greater odds of reporting vaccination, but in a nonlinear fashion (November: OR 4.1; December: OR 37.1; January: OR 17.4). Self-reported vaccination was lower in January compared to December, suggesting that vaccination may taper during this time period. Conclusions This study presents recent findings on uptake of the 2024-25 COVID vaccine among adults with SLE. Results suggest that lessening healthcare barriers, particularly those associated with access such as structural challenges, concerns about cost, and multiple role responsibilities, may facilitate COVID vaccination in this population. Efforts to promote COVID vaccination in the time preceding the release of updated formulations may enhance uptake in earlier months, where we saw the lowest reports of vaccination. We found that self-reported vaccination was lower in January compared to December in our sample, suggesting that continued campaigning in later months of the respiratory virus season may be warranted.
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 | 0,003 |
| 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 | 0,000 |
| 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 ».