Translation and adaptation of the Bipolar Prodrome Symptom Scale-Retrospective: Patient Version to Brazilian portuguese
Bibliographic record
Abstract
BACKGROUND: Bipolar disorder (BD) is a chronic and often severe mental disease, associated with a significant burden in affected individuals. The characterization of a premorbid (prodromal) period and possible development of preventive interventions are recent advances in this field. Attempts to characterize high-risk stages in BD, identifying symptoms prior to the emergence of a first manic/hypomanic episode, have been limited by a lack of standardized criteria and instruments for assessment. The Bipolar Prodrome Symptom Scale-Retrospective (BPSS-R), developed by Correll and collaborators, retrospectively evaluates symptoms that occur prior to a first full mood episode in individuals with BD. OBJECTIVE: To describe the translation and adaptation process of the BPSS-R to Brazilian Portuguese. METHOD: Translation was conducted as follows: 1) translation of the scale from English to Brazilian Portuguese by authors who have Portuguese as their first language; 2) merging of the two versions by a committee of specialists; 3) back-translation to English by a translator who is an English native speaker; 4) correction of the new version in English by the author of the original scale; 5) finalization of the new version in Brazilian Portuguese. RESULTS: All the steps of the translation process were successfully accomplished, resulting in a final version of the instrument. CONCLUSIONS: The Brazilian Portuguese version of the BPSS-R is a potentially useful instrument to investigate prodromal period of BD in Brazil.
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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 | 0.006 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".