How College Students Used Information From Institutions of Higher Education in the United States During COVID-19: Web-Based Cross-Sectional Survey Study
Notice bibliographique
Résumé
BACKGROUND: The start of the COVID-19 pandemic resulted in the implementation of nonpharmaceutical interventions by US institutions of higher education at an unprecedented level. During the backdrop of an emerging pandemic, younger adults (eg, college students) had an overall lower risk for severe outcomes for SARS-CoV-2, making this population a potential source of transmission for age groups with high susceptibility and negative health outcomes. We examine how college students' level of concern for COVID-19 was influenced by different sources of information, their living status, income level, and other demographic identifiers and its association with prevention behavior change. OBJECTIVE: We sought to examine the level of concern, defined as the extent to which the participant would take corrective action to mitigate contracting or spreading the virus (to family or friends) by using personal protective equipment such as a face mask, practicing social distancing, and following other public health recommendations, among college students during the COVID-19 pandemic. METHODS: A cross-sectional, web-based survey was conducted in 2021 among 185 college students aged 18-41 years, with most living in New York City and the United States (n=134, 72.4%). Out of 185 college students, 94 provided their zip codes, with 51 of those college students indicating they lived in New York City areas. The participants completed the survey via a QR code. Study participants who did not complete the full survey or were not college students in any US college or university were excluded. Analyses were conducted using R (version 4.2.2; R Foundation for Statistical Computing). RESULTS: Of 185 respondents participated in the study, 25 (13.5.%) used emails from their schools, 51 (27.6%) used mainstream media, and 109 (58.9%) used social media and other sources to obtain information about COVID-19. Of the 109 participants who learned about the pandemic from social media, 91 (83.5%) were concerned; however, only 63% (32/51) and 60% (15/25) of the participants who sourced information from mainstream media and their schools' email, respectively, were concerned. Further, the participants who received information from social media and other sources were about 3 times more likely to be concerned about COVID-19 than participants who received information from the university via email (P=.036; OR=3.07, 95% CI: 1.06-8.83).. CONCLUSIONS: College students who received information from social media and other sources were more likely to be concerned about COVID-19 than students who received information from their school via emails.
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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 | 0,002 | 0,007 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,002 | 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) | 0,003 | 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 ».