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Record W4387668169 · doi:10.56712/latam.v4i4.1250

Empatía y estrés académico en estudiantes del IX y X ciclo de la carrera de Enfermería de la Universidad Norbert Wiener, 2023

2023· article· es· W4387668169 on OpenAlexaboutno aff
Yessenia Milagros Osco Rojas, Rodolfo Amado Arévalo Marcos

Bibliographic record

VenueLATAM Revista Latinoamericana de Ciencias Sociales y Humanidades · 2023
Typearticle
Languagees
FieldPsychology
TopicStress and Burnout Research
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPsychologyPhilosophy

Abstract

fetched live from OpenAlex

Determinar la relación entre la empatía y estrés académico en estudiantes del IX y X ciclo de la carrera de Enfermería de la Universidad Norbert Wiener, 2023. Se desarrolló una metodología hipotético-deductivo, de enfoque cuantitativo, tipo aplicada con diseño no experimental, de nivel descriptivo correlacional de corte transversal; con una muestra de 150 estudiantes, donde se aplicó los instrumentos “Empatía de Toronto (TEQ)” que mide la variable Empatía y el “Inventario SISCO”, que mide el estrés académico. En el análisis descriptivo se enfocó en lo más resaltante, se obtuvo que el 34.0% presento una Empatía alta para un estrés académico moderado, el 12.7% de empatía baja para un estrés académico moderado, por otro lado también se demostró que existe una relación entre empatía y estrés académico, a través de una significancia estadística (p=0.001), a su vez se encontró una correlación positiva baja (rho=0.167) en los estudiantes del IX y X ciclo de la carrera de Enfermería de la Universidad Norbert Wiener. Se determinó que los internos del IX y X ciclo de la carrera de Enfermería de la Universidad Norbert Wiener, poseen un alto nivel de empatía a pesar de estar pasando por un estrés académico moderado.

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)0.004
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.124
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.003
Science and technology studies0.0020.004
Scholarly communication0.0010.000
Open science0.0020.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.039
GPT teacher head0.388
Teacher spread0.349 · 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; both teacher heads agree on what is shown here.

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
Published2023
Admission routes1
Has abstractyes

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