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Fatores associados à autonomia pessoal em idosos: revisão sistemática da literatura

2021· review· pt· W3137017068 on OpenAlexaboutno aff
Gabriela Carneiro Gomes, Rafael da Silveira Moreira, Tuíra Oliveira Maia, Maria Angélica Bezerra dos Santos, Vanessa de Lima Silva

Bibliographic record

VenueCiência & Saúde Coletiva · 2021
Typereview
Languagept
FieldHealth Professions
TopicHealth, Nursing, Elderly Care
Canadian institutionsnot available
Fundersnot available
KeywordsAutonomyGerontologyPsychologySocial psychologyScopusMedicineMEDLINEPolitical science

Abstract

fetched live from OpenAlex

The scope of this article is to identify factors associated with personal autonomy among the elderly. It is a systematic review of analytical epidemiological studies selected from the PubMed, Web of Science, Scopus and Lilacs databases, without time and language constraints. The search located 3,435 articles and selection was conducted in two phases: reading of abstracts and entire articles, with inclusion and exclusion criteria, by two independent reviewers, resulting in seven selected studies. The risk of bias was assessed using the Newcastle-Ottawa Scale protocol. All studies included were of sectional design and analyzed autonomy from the perspective of the perception of increased autonomy. The instruments used were the Hertz Perceived Entity of Autonomy Scale and the Chinese version of Perceived Enactment of Autonomy Scale. The factors associated with the autonomy of the elderly identified were grouped by functionality, family relations, interpersonal relations, life perception, satisfaction with health services, demographic factors, schooling, general health status and quality of life. The study of personal autonomy among the elderly presented a multifactorial and biopsychosocial character, although it is a recent theme in which further research with more detailed scientific evidence is necessary.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.039
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.022
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.039
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0070.005
Bibliometrics0.0220.022
Science and technology studies0.0010.001
Scholarly communication0.0040.003
Open science0.0020.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.089
GPT teacher head0.429
Teacher spread0.340 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

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

Citations33
Published2021
Admission routes1
Has abstractyes

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