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URBAN RESIDENTS ATTITUDES TOWARDS PEOPLE WITH DRUG ABUSE IN FIVE DISTRICTS OF CONCEPCION COMMUNE, CHILE

2019· article· en· W2964010912 on OpenAlexfundno aff
Patricia Jara Concha, Francisco Cumsille

Bibliographic record

VenueTexto & Contexto - Enfermagem · 2019
Typearticle
Languageen
FieldMedicine
TopicSubstance Abuse Treatment and Outcomes
Canadian institutionsnot available
FundersForeign Affairs and International Trade CanadaUniversidad de Concepción
KeywordsAmbivalenceReligiositySubstance abuseStigma (botany)PsychologySocial psychologyPsychiatryMedicineClinical psychology

Abstract

fetched live from OpenAlex

ABSTRACT Objective: to analyze the attitudes of residents in an urban commune of Concepción, Chile towards people with drug abuse according to drug type, personal experience and socio-demographic variables. Method: descriptive and cross-sectional study that examines the attitude of 121 people of five census districts of commune of Concepción, Chile, regarding who has abuse of four types of drugs: alcohol, marijuana, cocaine and base paste, and its relation with socio-demographic variables, personal experience, drug type, using the Multidimensional Inventory of Attitudes. Results: ambivalent attitudes are observed towards those who abuses of alcohol and marijuana; on the other hand, attitude is negative towards those who abuse of cocaine and base paste. Female gender and religiosity were significantly associated with negative attitudes and young adults presented more ambivalent and less negative attitudes than middle-aged adults and older did. Personal experience is significantly related only if people that abuse of marijuana and cocaine are known. Conclusion: it is concluded that ambivalent and negative attitudes prevail towards people who abuse of drugs, what constitutes an obstacle to access treatment and social integration. It is necessary to keep investigating about attitudes, social distance and personal contact in order to elaborate strategies that allow to address stigma and discrimination towards those who present drug abuse in Chile

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
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 head0.143
GPT teacher head0.399
Teacher spread0.256 · 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 routes1
Has abstractyes

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