Factors Influencing Quality of Life and Longevity in Elderly People, Phrae City, Thailand
Bibliographic record
Abstract
The purpose of this descriptive research was to study the factors that influence the quality of life (QOL) and longevity of the elderly in Thailand. The sample was made up of 280 elderly people in Phrae province, Thailand. The research found that (1) the QOL of the elderly in Phrae province was overall at a good level of 66.30%, (2) the factors that have significant influence on the QOL of the elderly at the p value = .01 are healing and exercise factors which are able to jointly predict the QOL of the elderly in Phrae Province by 12.2% (R2 = .122), and (3) from the structured interviews of 10 elderly people aged 80 years and older, it was found that diet, exercise, stress reduction, and healing are factors that allow the elderly to live for an average of 80 years which is above the average age of Thai people (the average age for men is 71.8 years old and for women is 78.6 years old).
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".