Mediating effect of coping style between the subjective well⁃being and self⁃perception aging of the elderly in the nursing homes
Bibliographic record
Abstract
ObjectiveTo explore the relationship between subjective well⁃being and self⁃perception aging of the elderly in the nursing homes and the mediating effect of coping styles.MethodsA total of 502 elderly people from 6 nursing homes in Tangshan city were enrolled in this study by using the random sampling method.The survey was conducted using the Brief Aging Perceptions Questionnaire（B⁃APQ），the Simplified Coping Style Questionnaire（SCSQ），and the Memorial University of Newfoundland Scale of Happiness（MUNSH）.ResultsThe B⁃APQ score of the elderly was（52.39±4.53），the MUNSH score was（34.51±9.19），the positive coping score was（12.95±5.28），and the negative coping score was（8.59±2.92）.The self⁃perception aging was negatively correlated with well⁃being and positive coping，and positively correlated with negative coping；happiness was positively correlated with positive coping，and negatively correlated with negative coping.Subjective well⁃being could directly affect the self⁃perception aging level，and it could also indirectly affect the self⁃perception aging level through the mediating effect of coping styles.ConclusionsCoping style played some mediating role in the relationship between subjective well⁃being and self⁃perception aging of the elderly in nursing homes.Nurses in nursing homes could reduce the self⁃perception aging and achieve active aging by improving coping styles and increasing happiness.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".