Understanding the relationship between age and information-seeking in the context of COVID-19
Bibliographic record
Abstract
Abstract Socioemotional selectivity theory proposes that older adults engage in less information-seeking than younger adults as future time perspective becomes more limited and expansive goals are prioritized less. However, gathering information is crucial in emergencies like the COVID-19 pandemic, especially for older adults, who are particularly vulnerable to the virus. This study aims to better understand the association between age and information-seeking patterns during the current pandemic. Two hundred and sixty-six participants (age range = 18 – 84, Mage = 38.86, female = 77.06%, received postsecondary education = 83.08%, born in Canada = 73.68%) completed an online study between May and August 2020. We found that older age was associated with more information-seeking time (b = .45, SE = .16, p < .001). We then investigated whether perceived worries of getting COVID-19 might provide insights into this association. Findings point to a partial mediation with a significant direct effect (b = .37, SE = .16, p = .02, 95% bootstrap CI=[.07, .68]), a marginally significant indirect effect (b = .08, SE = .04, p = .06, 95% bootstrap CI=[-.003, .18]) and a significant total effect (b = .46, SE = .16, p < .001, 95% bootstrap CI=[.14, .77]). That is, older adults engaged in more information-seeking than younger adults in contexts in which information-seeking was personally relevant as indicated by perceived worries. These findings shed light on key correlates of information-seeking in older adulthood and highlight the importance for government and health organizations to make suitable information accessible for older adults.
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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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 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".