The Role of Time Perspective and Pain Experience in Loneliness of the Elderly
Bibliographic record
Abstract
Focusing on the predictors of loneliness in the elderly is a prerequisite for successful improvement of loneliness. The purpose of this study was to determine the role of time perspective and experience of pain in predicting loneliness. It was a descriptive correlational study. The statistical population consisted of all elderly people over 60 years old in Kermanshah in 2019. 200 elderly members of the Retirement Association were selected through convenience sampling. Zimbardo Time Scale Log (ZTPI), McGill's Revised Inventory (SF-MPQ), and Russell's Loneliness Inventory (UCLA) were used to collect information. The data were analyzed using Pearson's correlation and stepwise multiple regression analysis. Findings indicated a negative and inverse relationship between retrospective-positive, temperamental-pleasure-seeker and the future with loneliness, and there was a positive and direct relationship between the retrospective-negative, experimental-predictive variables and loneliness (P<0/01). The results of the stepwise regression analysis showed that the components of the outlook of retrospective-negative and temperamental-predictive were the most powerful variables for predicting loneliness. Also, emotional pain could predict elderly loneliness. These findings revealed influential concepts in providing care for the elderly and it could be taken in plans and programs to decreases elderly loneliness and increase their well-being.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 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".