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Medición de la satisfacción en las residencias de personas mayores de la campiña sur de Córdoba (España)

2011· article· en· W39602982 on OpenAlexfundno aff
Joaquín Jesús Blanca Gutiérrez, Manuel Linares Abad, María Luisa Grande Gascón

Bibliographic record

VenueEvidentia: Revista de enfermería basada en la evidencia · 2011
Typearticle
Languageen
FieldMedicine
TopicAging, Health, and Disability
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of WaterlooGovernment of Ontario
KeywordsHumanitiesPersonaArt

Abstract

fetched live from OpenAlex

Introduccion: el concepto de satisfaccion podemos explicarlo como la diferencia entre las expectativas y la atencion real que se le proporciona al paciente. Si bien su estudio se ha sistematizado en entornos como los Hospitales y los centros de salud, su uso no esta tan extendido en el ambito de las residencias de personas mayores. Objetivo: mediante este trabajo, pretendemos estudiar la percepcion subjetiva de satisfaccion de las personas mayores que viven institucionalizadas. Metodologia: estudio de tipo cuantitativo, descriptivo y transversal, realizado mediante encuesta en las 6 residencias de personas mayores de la comarca de la campina sur de Cordoba (Espana). Estudiamos variables de tipo socio-demografico (sexo, edad, no de hijos, tiempo viviendo en la residencia, estado civil y nivel de independencia) y la puntuacion obtenida con respecto a la satisfaccion de los participantes. Resultados y Conclusiones: La percepcion subjetiva de la satisfaccion de las personas mayores institucionalizadas del area de estudio es notablemente alta, con respecto al entorno fisico, los cuidados recibidos y la interaccion social. Hay diferencias estadisticas a favor del grupo de hombres frente al de mujeres. No hay tales diferencias entre el grupo de personas validas frente a asistidas

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.049
Threshold uncertainty score0.098

Distilled classifier scores by category (both heads)

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 integrity0.0010.000
Insufficient payload (model declined to judge)0.0070.001

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 head0.020
GPT teacher head0.325
Teacher spread0.305 · 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
Published2011
Admission routes1
Has abstractyes

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