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Record W2912995687

Percepción subjetiva del tiempo y evaluación del estado emocional de pacientes con enfermedad crónica avanzada

2019· article· es· W2912995687 on OpenAlexaboutno aff
Ana Osorio-Lucena, B. Segura, Rafael Montoya‐Juárez, Ma Paz García

Bibliographic record

VenueEvidentia: Revista de enfermería basada en la evidencia · 2019
Typearticle
Languagees
FieldHealth Professions
TopicNursing care and research
Canadian institutionsnot available
Fundersnot available
KeywordsMoodAnxietyPsychologyIntrospectionDepression (economics)Clinical psychologyEmotional distressHospital Anxiety and Depression ScaleDistressPsychiatry
DOInot available

Abstract

fetched live from OpenAlex

Objectives: Characterizing emotional state and perception over the years in patients with advanced chronic disease, and compare it to Hospital Anxiety and Depression Scale. Methodology: It is a quantitative descriptive and transversal observational study in which we deepen the patient’s emotional state. Based on the administration of a questionnaire to collect demographic and clinical variables, in which the Karnofsky Index, Bayes Time Subjective Perceived Scale, Brief Scale of Introspection of the State of Mind, Scale of Evaluation of Edmonton Symptoms and Hospital Anxiety and Depression Scale. Results: Patients with advanced chronic illness presented anxious and depressive symptomatology’s high levels and a negative mood‘s predominance, existing a correlation between patients’ answers to Hospital Anxiety and Depression Scale and the identified emotional states through the Brief Mood Introspection Scale. Over time, these patients perceive it as slow or very slow, existing interrelation with the presence of anxious and depressive symptomatology. Conclusions: The subjective perception of time and the description of mood using the Brief Mood Introspection Scale can be a good tool for the emotional distress detection.

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)0.015
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.145
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0150.008
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0010.002
Open science0.0030.002
Research integrity0.0020.006
Insufficient payload (model declined to judge)0.0170.010

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 head0.035
GPT teacher head0.421
Teacher spread0.386 · 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
Published2019
Admission routes1
Has abstractyes

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