Validation of the Sinhala version of the Repeatable Battery for Assessment of Neuropsychological Status (RBANS)
Bibliographic record
Abstract
Introduction: Only the Mini mental state examination (MMSE) and Montreal Cognitive Assessment scale have been validated in a Sri Lankan population for the assessment of cognitive functions. Both tests are deficient in the number of domains assessed. Therefore validation of Repeatable Battery for Assessment of Neuropsychological Status is important as it assesses most of the cognitive domains. Objectives: To culturally adapt RBANS and investigate the validity and reliability of culturally adapted RBANS (RBANS-S). Methods: Fifty four participants with major neurocognitive disorder and 60 normal controls aged >50 were administered with RBANS-S at the Cognitive Assessment Unit, Faculty of Medicine, Colombo and National Hospital of Sri Lanka. The participants were selected after a detailed clinical assessment according to Diagnostic and Statistical Manual – 5 criteria. Data were analysed using SPSS data package. Results: The mean age of the sample was 69.5 years. RBANS-S total scale correlated highly with MMSE total score, (Pearson correlational coefficient = 0.793 p=0.01). Criterion validity was assessed using receiver operating curve characteristic analysis and the area under the curve was 0.937. RBANS-S showed strong concurrent validity us indicated by its significant correlations with the MMSE. All of the RBANS-S subtests demonstrated significant correlations with the MMSE subsets. The sensitivity and specificity for RBANS-S was 89% and 85% respectively at a totals score of 80.5. The RBANS-S yielded a reliability coefficient of 0.929. Conclusions: Culturally adapted RBANS-S is a valid and reliable instrument which can be used in assessment of cognitive functions.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".