Biopsychosocial determinant of quality of life of older adults in Pakistan and Canada
Bibliographic record
Abstract
Background: The rapidly rising average age of the older adults has brought various global healthcare challenges. A core challenge is how to enhance their quality of life (QoL). Objective: The objective of the current study was to test the significance of biopsychosocial determinants of quality of life of older adults in Pakistan and Canada. Methodology: A cross-sectional survey was carried out on a conveniently approached purposive sample of 1,005 older adults (Pakistani = 557 and Canadian = 448) of age range between 60 years and 80 years. The data were collected via demographic datasheet, World Health Organization Quality of Life Brief Scale, Health and Lifestyle Questionnaire, General Self-Efficacy Scale, Rosenberg Self-Esteem Scale, and Berlin Social Support Scale. Results: = .27, and.68) quality of life of older adults in Pakistan and Canada, respectively, after controlling the demographic variables. Significant differences were found between Pakistani and Canadian older adults on biopsychosocial factors: Canadian older adults scored significantly higher on health and lifestyle, self-efficacy, and quality of life, and older adults in Pakistan scored significantly higher on self-esteem and social support. Conclusion: A significant amount of better QoL of older adults can be achieved through enhancing the biopsychosocial correlates of their QoL, both in Pakistan and Canada.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".