Factors associated with quality of life of Brazilian older adults
Bibliographic record
Abstract
OBJECTIVE: The objective of the study was to explore factors associated with quality of life (QoL) of Brazilian community-dwelling older adults. METHODS: This was a descriptive exploratory cross-sectional study. Data were collected through a household survey. A random sample of 288 older adults from Porto Alegre, Brazil participated in the study. A demographic and health data sheet, the OARS activities of daily living (ADL) scale and the WHOQOL-BREF were administered. RESULTS AND DISCUSSION: The mean age of participants was 71.2 years (SD = 7.5) and 67.4% were female. Using multiple linear regression analysis, with overall QoL as the dependent variable, perceived health status, education level, engagement in physical activity, medical conditions, age group and use of primary health care were significant associated factors. With physical QoL as the dependent variable, significant factors included: perceived health status, medical conditions, education, physical activities and dependence in ADL; with social QoL as the dependent variable, only age group and paid work were significant. In relation to environmental QoL, education and perceived health were significant factors. CONCLUSIONS: The results illustrate the complexity of factors influencing QoL. With a better understanding of these factors, it is possible to plan appropriate health interventions.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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".