Alcohol use and problems related to the Maxakali indigenous peoples' worldview: a cross-sectional census study
Bibliographic record
Abstract
Abstract Background The objectives of this study were to estimate the prevalence of Alcohol Use and Alcohol-Related Problems (AU & ARP) among the Brazilian Maxakali indigenous people, and to examine how the prevalence varies according to sociodemographic characteristics and their associations with these characteristics. Methods A cross-sectional analytical population-based study was conducted with 1,036 Maxakali aged from nine years. A questionnaire was applied to 66 indigenous leaders who responded about alcohol consumption in 2016 and the negative consequences of this consumption among their friends in their villages. The association between consumption and consequences with the sociodemographic data of respondents was examined by applying the chi-square, Fisher's exact, and cluster analysis tests. Kappa values were calculated to assess the reproducibility of the questionnaire. Results The 12-month prevalence of alcohol use was 39.1%. The usage rate for women (17.3%) was 3.6 times lower than the usage rate for men. Male alcohol use rates increase from 8.1–64% in the age group from 09 to 14 to 15 to 19 years old. The highest proportions of alcohol use among mothers and fathers were found in extended families and associated with the negative consequences of those who use cachaça. On the other hand, nuclear families showed an association of protection against alcohol use in the age group of 9 to 14 years in females. Although alcohol use in females starts from 20 to 24 years of age, the rates of problems related to this use in women surpassed those of men during 25 to 45 years of age. Conclusions With the substantial agreement of reproducibility in the application of the questionnaire, we expect that the ease of application and the predictive power of this tool will allow the detection and monitoring of alcohol use and its consequences in the Maxakali people.
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 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".