Envolvimento com álcool, tabaco e outras substâncias por estudantes universitários
Bibliographic record
Abstract
Introduction: This study aimed to identify the number of students from a higher education institution into the interior of São Paulo state who experienced their entry into alcohol, tobacco and other substances in order to evaluate the occurrence and dependency level on them. Materials and Methods: An extract of a compiling, exploratory, descriptive study under a quantitative approach was conducted in 416 undergraduate students. The data were collected over the third quarter of 2017 by applying a semi-structured questionnaire prepared by the authors in addition to the Triage Questionnaire for Alcohol, Tobacco and other Drugs Use. A descriptive statistical analysis was conducted for data analysis as well as a Pearson’ chi-squared test, according to the instructions for the application of the selected instrument. This study was received and approved by the Research Ethics Committee. Results: The general rates for entry and drug type are 140 (30%) for tobacco derivatives, 303 (66%) for alcohol beverages, 89 (19%) for marijuana, 32 (7%) for cocaine/crack, 24 (5%) for amphetamines or ecstasy, 30 (7%) for inhalant drugs, 45 (10%) for hypnotics/sedatives, 36 (8%) for hallucinogens and 9 (2%) for opioids. Discussion: Students showed to be involved in all types of substances which is linked to flexibility in relation to their use in the university environment and their easy access. Conclusions: Undergraduate students have a real and intense relationship with alcohol, tobacco and other drugs. In addition to this relationship, the risk of addiction to these substances is presented as a major social and healthcare problem.\nComo citar este artigo: Silva DA, Junior RJP, Gomes CFM, Cardoso JV. Envolvimento com álcool, tabaco e outras substâncias por estudantes universitários. Rev Cuid. 2019; 10(2): e641. http://dx.doi.org/10.15649/cuidarte.v10i2.641
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".