Brazilian version of the Brief Screener for Substance and Behavioral Addiction
Bibliographic record
Abstract
Introduction: Excessive and compulsive behaviors, including substance and behavioral addictions, represent a growing global concern. In Brazil, the increasing prevalence of these behaviors underscores the need for effective screening tools to identify individuals at risk. The Brief Screener for Substance and Behavioral Addiction (SSBA) has been recognized internationally for its utility in both clinical assessment and public health surveillance. This study aimed to adapt the SSBA for use in Brazil, with potential applications in other Portuguese-speaking countries. Methods: The adaptation process followed international guidelines for cross-cultural adaptation of psychometric instruments. It included forward translation into Portuguese, back-translation into English, and expert committee review to ensure semantic and conceptual equivalence. A pilot study was conducted to assess clarity and relevance. Subsequently, the Brazilian version of the SSBA was administered to a sample of 450 individuals, comprising both clinical and non-clinical populations. Psychometric analyses evaluated the instrument's reliability, validity, and factorial structure. Results: The Brazilian version of the SSBA demonstrated good internal consistency and satisfactory construct validity across subscales. Confirmatory factor analysis supported the original structure of the instrument, and no major linguistic or cultural adaptations were required. The screener showed strong discriminative power between clinical and non-clinical participants, indicating its effectiveness for identifying individuals at risk for addiction-related disorders. Discussion: The adapted SSBA is a reliable and valid tool for the Brazilian context and may be extended to other Lusophone countries. It provides a brief yet comprehensive screening method suitable for various settings, including clinical practice, research, and community health. The instrument is particularly valuable for health professionals working in addiction prevention, diagnosis, and treatment, supporting early identification and intervention efforts.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".