Rasch Analysis of the Global Appraisal of Individual Needs in the City of São Paulo
Bibliographic record
Abstract
INTRODUCTION: Approximately 5% of the global population used an illicit drug in 2013. Regarding licit drugs, alcohol is responsible for the occurrence of approximately 200 diseases, among them depression. In addition to health impairments, alcohol is also implicated in many acts of violence. This study aimed to measure the properties of the Rasch model of the Portuguese version of the Global Appraisal of Individual Needs-Short Screener based on evidence obtained during care for users of alcohol and other drugs. METHOD: To collect the data, 128 interviews were held at the Psychosocial Care Center for Alcohol and Other Drugs in the state capital, during which the scale was applied. RESULTS: The Rasch model revealed that the subscales of the instrument were appropriate, with all items having mean infit and outfit values from 0.5 to 1.5, considered optimal for measurement. There was no evidence of differential performance for gender. Substance use and crime and violence items presented redundancy for severity measures. CONCLUSION: Given the need for validated instruments for use in Brazil, it is encouraging that the Portuguese version of the scale was valid for the Rasch model. The results are consistent with studies using the other American, Brazilian, and Canadian versions of the instrument.
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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 | 0.004 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".