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Uso de drogas en estudiantes de una universidad de El Salvador y su relación con el maltrato durante la niñez

2015· article· pt· W2261798820 on OpenAlexaff
Cristina Juárez de Amaya, Robert B. Mann, Hayley A. Hamilton, Pat Erickson, Bruna Brands, Norman Giesbrecht, Maria da Glória Miotto Wright, Francisco Cumsille, Jaime Sapag, Akwatu Khenti

Bibliographic record

VenueTexto & Contexto - Enfermagem · 2015
Typearticle
Languagept
FieldSocial Sciences
TopicYouth, Drugs, and Violence
Canadian institutionsCentre for Global Health ResearchPublic Health OntarioUniversity of TorontoCentre for Addiction and Mental Health
Fundersnot available
KeywordsHumanitiesPsychologyArt

Abstract

fetched live from OpenAlex

O objetivo do estudo foi examinar a relação entre o uso e o abuso de drogas e maus-tratos durante a infância em estudantes universitários na cidade de San Salvador, El Salvador. Trata-se de estudo exploratório, de corte transversal, com uma amostra de 272 estudantes. Os resultados indicaram que 43% (118) dos alunos relataram ter consumido drogas em algum momento da vida; as drogas mais utilizadas nos últimos 12 meses foram álcool (14%), maconha (9,3%) e tabaco (7%). Os abusos físico e verbal foram os tipos mais comuns de abuso e, menos frequente, porém existente, foi o abuso sexual. Ter amigos que usam drogas foi um fator de risco para o uso e abuso de drogas. Existe uma relação direta entre o uso/abuso de drogas e o abuso físico na infância, sendo essa associação estatisticamente significantiva (<0.005).

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)0.005
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.237
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.228
GPT teacher head0.460
Teacher spread0.232 · 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 teacher head, not a consensus.

Study designQualitative
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

Citations2
Published2015
Admission routes1
Has abstractyes

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