Life Satisfaction Index among Elderly People Residing in Gorgan and Its Correlation with Certain Demographic Factors in 2013
Bibliographic record
Abstract
BACKGROUND: Aging is a universal phenomenon that will present itself as a dominant social and welfare challenge. AIM: This study was to examine life satisfaction among people residing in Gorgan and its correlation with certain demographic factors in 2013. METHODS: A total of 250 elder people were selected for the study through the convenience sampling during 4 months. Data collected through life satisfaction index-A (LSIA). This instrument consists of 5 subscales, including, zest for life, resolution and fortitude, congruence between desired and achieved goals, positive self-concept and mood tone. The Multiple Linear Regression analysis was used in order to determine factors influencing the overall LSIA. RESULTS: The overall LSIA score was 22.1 ± 7.5 with the maximum and minimum mean scores pertaining to the resolution and fortitude (6.1 ± 2.5) and the positive self-concept (3.1 ± 1.2) subscales, respectively. Level of education, type of living and gender were variables influencing the overall LSIA (P<0.05). CONCLUSION: Given the overall LSIA, it appears that future plans for this age group should be seriously revised along with cultural plans for promoting reverence for old age in the general public.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.001 | 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".