A Longitudinal Study on Multidimensional Resilience to Physical and Psychosocial Stress in Elderly Mexicans
Bibliographic record
Abstract
Objectives: To identify trajectories of depression and daily disability in the context of serious falls and widowhood and to predict those trajectories before the events occurred. Methods: Longitudinal data were used from the Mexican Health and Aging Study. Trajectories were estimated using latent class growth analysis. Internal and socio-ecological resources were analyzed as predictors of the trajectories. Results: Unfavorable (worsening of symptoms and chronic high symptoms) and favorable (improvement of symptoms and stable low symptoms (resistance)) trajectories were identified. Favorable trajectories were more likely for daily disability. Persons who showed resistance in depression also tended to show resistance in daily disability. Net worth, cognition, and subjective well-being were early predictors for most trajectories. Discussion: Besides resistance, individuals rather show different co-occurring trajectories in the studied outcomes. While some factors could be identified that lead to favorable trajectories in both stressful contexts, the study also shows the necessity for context-specific research and praxis.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 | 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".