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Evaluation of functional disability and associated factors in the elderly

2019· dataset· en· W6958618446 on OpenAlexaboutno aff

Bibliographic record

VenueFigshare · 2019
Typedataset
Languageen
FieldAgricultural and Biological Sciences
TopicCocoa and Sweet Potato Agronomy
Canadian institutionsnot available
Fundersnot available
KeywordsActivities of daily livingActivities of daily livingSocioeconomic statusSocioeconomic statusPoisson regressionPoisson regressionDepression (economics)Depression (economics)Elderly peopleElderly people

Abstract

fetched live from OpenAlex

Abstract Objective: To estimate the prevalence and self-reported socio-demographic and health factors associated with functional disability in basic and instrumental activities of daily living among the elderly. Method: A cross-sectional study was carried out, based on a representative sample of elderly people receiving care at a reference unit in the north of the state of Minas Gerais. The data were collected in 2015. Demographic and socioeconomic variables, morbidity, hospitalizations in the previous year, frailty (Edmonton Frail Scale), geriatric depression (GDS-15), and functional disability (Katz Index, Lawton and Brody Scales) were analyzed. Multiple analysis was performed using Poisson regression with robust variance. Results: 360 elderly people aged 65 years and over participated in the study. The prevalence of functional disability for Basic Activities of Daily Living was 21.4% while for instrumental activities it was 78.3%. Functional disability in basic activities was higher among elderly males (p=0.03) who had suffered strokes (p=0.00) and were frail (p=0.00), while for instrumental activities it was higher among older elderly persons (p=0.04); who were illiterate (p=0.00), had less than five years of schooling (p=0.02); had depressive symptoms (p=0.00) and were frail (p=0.00). It was lower among elderly persons who lived alone. Conclusion: A high prevalence of functional disability was identified among the elderly for instrumental activities of daily living, demonstrating the need for an effective and immediate approach by health professionals, who should employ preventive care in order to tackle this problem.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.611
Threshold uncertainty score0.895

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.1050.000

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.

Opus teacher head0.132
GPT teacher head0.284
Teacher spread0.152 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreDataset

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".

Quick stats

Citations0
Published2019
Admission routes1
Has abstractyes

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