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Record W7010304561

Influencia de la musicoterapia en la depresión del paciente esquizofrénico en el área de Rehabilotación Exchilpinilla Socabaya, Arequipa - 2018.

2018· dissertation· es· W7010304561 on OpenAlexaboutno aff

Bibliographic record

Venuerenati · 2018
Typedissertation
Languagees
FieldPsychology
TopicMusic Therapy and Health
Canadian institutionsnot available
Fundersnot available
KeywordsPoison controlContext (archaeology)Schizophrenia (object-oriented programming)Scale (ratio)
DOInot available

Abstract

fetched live from OpenAlex

La presente investigación titulada Influencia de la Musicoterapia en la Depresión del paciente esquizofrénico en el Área de Rehabilitación Exchilpinilla, Socabaya Arequipa, tuvo como objetivo general en determinar la influencia de la musicoterapia en la depresión del paciente esquizofrénico en el Área de Rehabilitación Exchilpinilla Socabaya, Arequipa 2018. Se trabajó con una población censal de 93 pacientes, en los cuales se utilizó la técnica de la observación, que consistió en el registro sistemático válido y confiable de comportamiento y/o conducta que manifestaron los pacientes. Ademas en calidad de instrumento, la Escala de Depresión de Calgary, desarrollado específicamente para valorar el nivel de depresión en la esquizofrenia, diseñada por D.Addington, J.Addington y B. Schissel; en el año 1990. La Escala de Depresión de Calgary para la Esquizofrenia (CDSS) es un instrumento válido para medir los síntomas depresivos en los esquizofrénicos crónicos y la Guía de observación directa de la musicoterapia que consta de 4 ítems en donde se muestra las características de la musicoterapia. Los resultado encontrados del 93.55% demuestra la influencia positiva de la musicoterapia en la rehabilitación de la depresión en los pacientes que demuestran esquizofrenia.

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)0.001
metaresearch head score (Gemma)0.004
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 score0.045
Threshold uncertainty score0.089

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.012
GPT teacher head0.365
Teacher spread0.353 · 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
Published2018
Admission routes1
Has abstractyes

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