Post-Traumatic Growth among Older People after the Forced Lockdown for the COVID–19 Pandemic
Bibliographic record
Abstract
We explored post-traumatic growth (PTG) in older adults immediately after the forced lockdown in Spain during March to April, 2020, due to the COVID-19 pandemic. The study also tried to identify the variables that predict PTG, focusing on the experience of COVID, sociodemographic variables, and social resources. In total 1,009 people aged 55 years and older participated in the study and completed an online questionnaire comprising the following elements: The short form of the Post-traumatic Growth Inventory (PTGI-SF), sociodemographic and social resources questions, and their experiences of COVID-19 (if they had been infected themselves or if they had experienced the loss of someone close). Results showed that only a quarter of the participants experienced higher PTG after the forced lockdown, with only age and social resources being correlated with scores on the PTGI-SF. Looking at the strengths that older adults put into action to combat the pandemic and its social and health consequences could be an important consideration when planning future social policies for this and other pandemics.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".