Cognitive integration of personal or public events affects mental health: Examining memory networks in a case of natural flooding disaster
Bibliographic record
Abstract
OBJECTIVE: The purpose of this research was to examine whether memories of personal or public events could affect mental health through the way those memories are integrated in memory networks. METHOD: Participants from the general population (N = 224, age mean = 36.62 years, 74% female) were either directly or indirectly personally affected by a natural flooding disaster with moderate consequences or had simply learned about it. A prospective design (during the floods and two months later) was used to examine the impact that such a personal or public event memory could have on their mental health. RESULTS: Results showed that flood-affected individuals reported poorer mental health compared to the unaffected. However, both affected and unaffected individuals who had encoded a current floods-related event in memory as need satisfying or who had embedded such an event in need satisfying memory networks showed better mental health over time. These results held after controlling for the effect of various demographics and dispositional emotion regulation styles. CONCLUSION: Simply learning about public events can impact mental health through the way those events are integrated in memory, which appears as a critical individual difference.
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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 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".