Translation, Cultural Adaptation, and Validation of the Hiligaynon Montreal Cognitive Assessment Tool (MoCA-Hil) Among Patients With X-Linked Dystonia Parkinsonism (XDP)
Bibliographic record
Abstract
Background: X-linked dystonia parkinsonism (XDP) is a neurodegenerative disease endemic to Filipinos with maternal lineage from Panay Island, Philippines. Patients present with dystonia concurrent with or followed by parkinsonism. Non-motor symptoms also predominate, affecting behavior and cognition. We aimed to translate and do cross-cultural adaptation and validation of the Montreal Cognitive Assessment Tool (MoCA) into Hiligaynon (MoCA-Hil), the language spoken in Panay Island, to perform baseline cognitive screening of XDP patients. Methods: Forward translation to Hiligaynon was done by two translators, then back translation of a single version was adapted and approved by a committee. A pilot testing was done yielding the final translated version, which was then tested on 46 XDP patients. The test-retest reliability was measured for 11 patients. The XDP-MDSP (Movement Disorder Society of the Philippines) rating scale was used to assess disease severity. Results: The MoCA-Hil showed an acceptable test-retest reliability [intraclass correlation (ICC) 0.74] and internal consistency (Cronbach’s alpha 0.86 at baseline, 0.81 at 12 weeks). The two subscales with low ICC at 0.09 and 0.21 were delayed recall and orientation, respectively. Conclusion: Translation, cultural adaptation and validation of the MoCA to Hiligaynon was successfully done. This tool may now be used in clinical practice and in research for Hiligaynon-speaking subjects.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".