Older adults during the pandemic: Mental health symptoms are predicted by childhood trauma
Bibliographic record
Abstract
Introduction It has been broadly anticipated that COVID-19 pandemic-related experiences may constitute traumatic stressors in vulnerable populations, and that older adults’ might be especially at risk of experiencing mental health symptoms during the pandemic. Objectives The present study aimed to examine older adults’ psychological distress: posttraumatic stress, Covid-related fears, anxiety, and depression during the pandemic, and the relationship between present distress, defensive functioning, and childhood trauma. We also explored potential differences between younger-older adults (between 65 and 74 years), and older-older adults (75 years and above). Methods Data was collected in a large-scale online survey during the early months of the pandemic, for the present study, we included participants above 65 years old (N = 1,225). Results showed that age, adverse childhood experiences, and overall defensive functioning were all significantly related to posttraumatic stress, anxiety, and depression. Specifically, younger age and more reported childhood adversity were related to higher distress, whereas higher defensive functioning was related to less distress. Covid-related fears were not associated with age. Our final model showed that defensive functioning mediated the relationship between childhood trauma and distress. Conclusions Our results support the relative resilience of older-older adults compared to younger-older adults, as well as the long-lasting impact of childhood adversity through defensive functioning later in life, specifically in times of heightened stress, such as the COVID-19 pandemic. Future studies are warranted to identify further factors affecting defensive functioning as adults age, as well as processes that are associated with resilience in response to stressors in older adulthood. Disclosure No significant relationships.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".