Protocol for the development of versions of the Montreal Cognitive Assessment (MoCA) for people with hearing or vision impairment
Bibliographic record
Abstract
INTRODUCTION: Hearing and vision impairments are highly prevalent among older adults and impact commonly used cognitive assessment tools for the identification of dementia. Adaptations of such tests for people with hearing or vision impairment have not been adequately validated among populations with such sensory impairment. METHODS AND ANALYSIS: We will develop two versions of the Montreal Cognitive Assessment (MoCA) for people with acquired hearing impairment (MoCA-H) or vision impairment (MoCA-V). The MoCA-H and MoCA-V will exclude the existing MoCA items that are presented in spoken or visual format, respectively, and include new suitably adapted items. Participants (n=792) with combinations of hearing, vision and cognitive impairment will complete standard or adapted versions of the MoCA across three language sites (English, French and Greek). Development of the MoCA-H and the MoCA-V will be based on analysis of adapted and standard MoCA items following model-based development to select the combination of items for the MoCA-H and MoCA-V that provide optimal sensitivity and specificity for detection of dementia. ETHICS AND DISSEMINATION: The study has received ethical approval from respective centres in the UK, France, Greece and Cyprus. The results of the study will be disseminated through peer-reviewed publication, conference presentations, the study website (https://www.sense-cog.eu/), the SENSE-Cog Twitter account (@sense_cog) and the MoCA test website (https://www.mocatest.org/). The main outputs of the study will be versions of the MoCA that are appropriate for use with adults with acquired hearing or vision impairment and will contribute significantly to the clinical care of older people.
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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 | 0.061 | 0.079 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.005 | 0.009 |
| Insufficient payload (model declined to judge) | 0.108 | 0.044 |
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".