European Portuguese version of the Mini-BESTest: a cross-cultural adaptation and psychometric measurements in individuals with sensorimotor impairments
Bibliographic record
Abstract
Purpose This study aimed to translate and cross-culturally adapt the Mini-BESTest into European Portuguese and to evaluate its psychometric properties in individuals with sensorimotor impairments.Material and Methods A cross-sectional cross-cultural adaptation and validation study was conducted according to the COSMIN guidelines and the STROBE statement. The study included 100 participants with sensorimotor impairments who were able to walk 6 m. Cronbach’s alpha and item-total correlations were used to assess internal consistency. Interpretability was assessed by examining floor and ceiling effects and skewness. To investigate construct validity, Spearman correlation coefficients and Bland-Altman analysis were performed to compare the Berg Balance Scale and the Mini-BESTest Inter- and intra-rater reliability were assessed by calculating the ICC, SEM and MDC based on video recordings of the participants during the Mini-BESTest assessments.Results The European Portuguese Mini-BESTest showed good internal consistency (Cronbach’s α = 0.892) and no significant floor or ceiling effects. Excellent inter- and intra-rater reliability (ICC = 0.97) were also demonstrated, with MDC of 2.58 and 2.57, respectively. Furthermore, this instrument showed a significant correlation with the BBS (r = 0.902). Bland-Altman analysis showed small absolute differences.Conclusion The European Portuguese Mini-BESTest is comparable to the original English version in terms of validity and reliability and is therefore highly recommended for use by Portuguese-speaking professionals to assess postural control.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".