Thinking Beyond COVID-19: How Has the Pandemic Impacted Future Time Horizons?
Bibliographic record
Abstract
Older age is reportedly protective against the detrimental psychological impacts of the COVID-19 pandemic, consistent with the theory that reduced future time extension (FTE) leads to prioritization of socioemotional well-being. We investigated whether depression severity and pandemic-related factors (regional severity, threat, social isolation) reduce FTE beyond chronological age and whether these relationships differ between younger and older adults. In May 2020, we recruited 248 adults (younger: 18-43 years, older: 55-80 years) from 13 industrialized nations. Multigroup path analysis found that depression severity was a better predictor of FTE than the reverse association in both age groups, suggesting an affective foreshortening of future time. In both age groups, older age was protective against depression severity, and younger age was associated with heightened vulnerability to the negative impacts of pandemic-related factors. Future research should consider the complex interrelationships between FTE, age, and depression severity and the potential impacts of the broader psychosocial milieu.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".