Theoretical procedures of the cross-cultural adaptation process of the Child Mania Rating Scale - Parent Version (CMRS-P) for the Brazilian context
Bibliographic record
Abstract
OBJECTIVES: To describe the theoretical procedures employed in the process of cross-cultural adaptation (CCA) for Brazil of the Child Mania Rating Scale - Parent Version (CMRS-P). METHODS: Seven steps were carried out: (1) translations and synthesis; (2) Committee of Judges-I; (3) grammatical review; (4) Committee of Judges-II; (5) semantic analysis (pre-test); (6) back-translation; and (7) discussion with the authors of the original instrument. Participants were two professional translators, 14 experts, a grammar proofreader, and 21 parents/guardians, representatives of the target population. The results were analyzed in terms of the percentage of agreement between evaluators and the content validity coefficient (CVC) and by analysis of comments and suggestions. RESULTS: Grammatical and cultural adjustments were made, in addition to substitution and/or inclusion of words and examples. Adequacy agreement indexes exceeding 86% were achieved and the CVC result for the total scale was excellent (0.95). The pre-test indicated good acceptance and understanding by participants. CONCLUSION: The proposed version proved to be promising for use in the Brazilian context, although further psychometric studies are still needed to prove the scale's validity and reliability.
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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 | 0.083 | 0.117 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".