Bibliographic record
Abstract
Objective:To investigate the predictors of Subjective Well-being(SWB) in widowed elders.Methods:A total of 292 widowed elders who living in communities were selected by interval sampling.The subjects were interviewed with the Memorial University of Newfoundland Scale of Happiness,Cornell Medical Index(CMI),Coping Style Questionnaire,Social Support Rating Scale and a self-made questionnaire.The data was analyzed by independent-sample t-test,one-way ANOVA and Structural Equation Modeling.Results:The males reported higher Subjective Well-being than the females [(25.5±5.7)vs.(22.8±6.9),P0.01].CMI,problem-solving,withdrawal,social supports using,subjective social support were significantly correlated with SWB(the regression weight were-0.358,0.567,-0.469,0.320 and 0.152 respectively).Problem-solving,self-abuse,help-seeking,social supports using,subjective social support were significantly correlated with SWB(the regression weight were 0.124,-0.087,0.091,0.049 and 0.098 respectively).Structural Equation Modeling analysis showed that problem-solving had maximal positive effect on SWB,social supports using and subjective social secondly(the regression weight were 0.691,0.369 and 0.250 respectively);withdrawal had maximal negative effect on SWB(the regression weight was-0.469).Conclusion:Lack of social supports is a risk factor of low subjective well-being in widowed elders,and adaptive coping style have positive effect on SWB.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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 teacher head, 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".