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Record W4310032161

Factores de vulnerabilidad en adolescentes y su relación con el consumo de alcohol

2017· article· es· W4310032161 on OpenAlexaff
Estuardo J. Monjes-Ávila

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2017
Typearticle
Languagees
FieldSocial Sciences
TopicSocial Sciences and Policies
Canadian institutionsLockheed Martin (Canada)
Fundersnot available
KeywordsPsychologyHumanitiesArt
DOInot available

Abstract

fetched live from OpenAlex

En este estudio se analizan los principales factors de vulnerabilidad que influyen en el hábito de consumo de alcohol en adolescentes entre 15 y 19 años de las instituciones educativas privadas de nivel de diversificado. Se realizó un estudio cuantitativo analítico transversal en seis instituciones educativas privadas (Colegios Valladolid, San Sebastián, El Deber, de Señoritas Santa Inés, San José de los Infantes e Instituto Tecnológico de Computación) durante los meses de junio y julio del 2017 en los municipios de Guatemala y Mixco, Guatemala, con una muestra de 416 estudiantes. El 65% ha consumido bebidas alcohólicas durante el último año. Sobre los que sí han consumido bebidas alcohólicas, el 64.6% es menor de 18 años, el 80% pertenece al sexo masculino, el 42% tiene familiares en primer grado que consumen alcohol de manera patológica, el 76% refiere que es habitual el consumo de bebidas alcohólicas en reuniones sociales, el 87% de los consumidores no considera que la legislación que prohíbe la venta de bebidas alcohólicas a menores de 18 años sea un impedimento para consumir bebidas alcohólicas. Las variables que presentaron asociación significativa fueron: el factor cultura y normas y el factor contexto del consumo de alcohol, los cuales pueden servir de predictores del consumo. El valor predictivo de consumo de alcohol con las variables indicadas, fue de 81.2%.

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)0.006
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Open science, 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 score0.087
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0050.003
Scholarly communication0.0130.004
Open science0.0100.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.000

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 head0.293
GPT teacher head0.622
Teacher spread0.330 · 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
Published2017
Admission routes1
Has abstractyes

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