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The Functional Condition and Physical Mobility among Patients Provided with Long-Term Institutional Care

2016· article· pl· W2562776040 on OpenAlexaboutno aff
Ilona Kuźmicz, Tomasz Brzostek, Maciej Górkiewicz

Bibliographic record

VenueJagiellonian University Repository (Jagiellonian University) · 2016
Typearticle
Languagepl
FieldHealth Professions
TopicGlobal Health Care Issues
Canadian institutionsnot available
Fundersnot available
KeywordsLong-term careMedicineFunctional Independence MeasureGerontologyActivities of daily livingTerm (time)Physical therapyCognitionPsychologyPsychiatry

Abstract

fetched live from OpenAlex

Introduction.The increase of dysfunction in the functional condition and a decrease in physical mobility lead to independence limitation and increased demand for health care services.Aim of the study.The aim of the research was to evaluate the association between functional condition and physical mobility and selected demographic variables of patients provided with long-term institutional care.Material and methods.The study group consisted of persons provided with long-term institutional care.The following standardized research tools were used in this study: the Cognitive Assessment Scale, the Edmonton Functional Assessment Tool and the Barthel Index.Results.Studies have shown that with increasing dysfunction of the functional condition of mobility decreases patients.The analysis showed no significant correlation of functional condition with age and gender of the respondents.Conclusions.The results indicate a need systematic assessment of the functional condition of patients, which determines adjustment of care to the capabilities and needs of the patients.

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)0.000
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.010
GPT teacher head0.244
Teacher spread0.234 · 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 designObservational
Domainnot available
GenreEmpirical

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
Published2016
Admission routes1
Has abstractyes

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