Associação entre faixa etária e avaliação multidimensional da pessoa idosa residente do município de araras/são paulo/brasil
Bibliographic record
Abstract
OBJECTIVE: To evaluate the impact of age on the multidimensional assessment of elderly persons in Araras/SP/Brazil. METHOD: Multicenter, analytical and quantitative study carried out in Araras/São Paulo/Brazil with elderly people aged 60 years or over and with the cognitive capacity to answer the questionnaire. The scales applied were: Mini Mental State Examination (MMSE), Edmonton Frailty (EFE), Lawton and Brody and Vulnerable Elders Survey - 13 (VES-13), The data were categorized and verified in SPSS (version 23) in a descriptive and inferential (Chi Square; p-value<0.05). Approved by the Ethics and Research Committee (Protocol nº 4,393,230). RESULTS: Sample of 185 elderly people, of which 52.43% were young elderly, 32.43% were moderately elderly and 15.14% were considered elderly. Of the total, 68.10% have some cognitive deficit and of the oldest old, 85.71% have some cognitive deficit; 62.16% have some level of fragility, 57.30% are not vulnerable and 60.54% have some degree of dependence. When analyzing the total number of long-lived elderly people, 75.00% are considered vulnerable. There was a significant association between age group and cognition, frailty, vulnerability and dependence (p<0.001). CONCLUSION: In the sample, it is possible to observe a significant relationship in relation to age range and multidimensional assessment of the elderly, especially in the oldest old. It can be inferred that with advancing age, the individual tends to be susceptible to problems and, therefore, it is important to individualize care and establish decent health conditions, to promote active aging, better quality of life and biopsychosocial well-being.
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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 | 0.004 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".