How College Students Used Information From Institutions of Higher Education in the United States During COVID-19: Web-Based Cross-Sectional Survey Study
Bibliographic record
Abstract
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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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.005 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".