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ATTITUDES TOWARDS PEOPLE WITH PROBLEMATIC DRUG USE IN THE CITY OF LOJA, ECUADOR

2019· article· en· W2967840826 on OpenAlexafffund
Cristina Alexandra Delgado, Bruna Brands

Bibliographic record

VenueTexto & Contexto - Enfermagem · 2019
Typearticle
Languageen
FieldMedicine
TopicSubstance Abuse Treatment and Outcomes
Canadian institutionsUniversity of TorontoCentre for Addiction and Mental Health
FundersForeign Affairs and International Trade CanadaGovernment of CanadaUniversidad Técnica Particular de Loja
KeywordsAmbivalenceStigma (botany)Context (archaeology)PsychologyLatin AmericansSocial psychologyMedicinePsychiatryPolitical scienceGeography

Abstract

fetched live from OpenAlex

ABSTRACT Objective: analyze attitudes toward people with problematic drug use in the city of Loja, Ecuador. Method: a quantitative, cross-sectional, preliminary study using survey methodology aimed at collecting data on attitudes towards people with problematic drug use by residents in the city of Loja, Ecuador. The sample size is 121 individuals. This study is part of a multi-center investigation that involves 10 universities and a National Drug Council in Latin America. Results: the results revealed that attitudes toward people with problematic uses of alcohol are positive while attitudes toward people with problematic uses of other drugs such as marijuana and cocaine are ambivalent. It also shows that ambivalence prevails according to the majority of socio-demographic variables, differing in the masculine gender, people in the range of 18-29 years; those who lives with their partner; those who have a higher education than high school who have a positive attitude towards people with problematic uses of alcohol. And the scale that presents the greatest difficulties is the area of personal contact with negative attitudes towards the users of marijuana and cocaine. Conclusion: it is vital to continue researching about stigma, social distance and attitudes towards people who use drugs in the Ecuadorian context, its impact on treatment and social integration and the most appropriate information strategies to avoid stigma.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.261
GPT teacher head0.412
Teacher spread0.152 · 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 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

Citations2
Published2019
Admission routes2
Has abstractyes

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