Age Differences in Positive Event Appraisals during COVID-19: Evidence from a Daily Diary Study
Bibliographic record
Abstract
Abstract Multiple studies suggest that community-dwelling older adults are psychologically resilient in the face of the COVID-19 pandemic. Notably, during the initial weeks of the COVID-19 outbreak, older age was associated with engaging in more daily positive events (Klaiber et al., 2021, Journal of Gerontology: Psychological Sciences). We followed up on these findings by exploring age differences in positive event appraisals during the COVID-19 pandemic. During the 7-day diary study conducted between March and August 2020, 1036 participants (mean age = 45.95, SD = 16.04, range = 18-91) reported their positive events in nightly surveys. If at least one positive event occurred, participants rated their appraisals of the event on the following dimensions: importance, calmness, happiness, gratitude, personal responsibility, and control. Older adults (60 years+) rated their positive events to be more personally important and felt more calm and happy during these events, compared to younger (18-39 years) and middle-aged adults (40-59 years). Furthermore, older adults felt more grateful during positive events compared to younger but not middle-aged adults. There were no age differences in feelings of control or personal responsibility for positive events. These findings highlight the importance of daily positive events for older adults during a time of major stress. In line with theories on adult development, daily positive event processes in older adults are characterized by valuing positive and meaningful social connections, as well as a greater degree of positive event-specific emotions such as feeling calm, happy, and grateful.
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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 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".