Beyond Traditional Assessments of Cognitive Impairment: Exploring the Potential of Spatial Navigation Tasks
Bibliographic record
Abstract
INTRODUCTION Alzheimer’s disease affects spatial abilities that are often overlooked in standard cognitive screening tools. We assessed whether the spatial navigation tasks in the Spatial Performance Assessment for Cognitive Evaluation (SPACE) can complement existing tools such as the Montreal Cognitive Assessment (MoCA). METHODS 348 participants aged 21-76 completed the MoCA, SPACE, and sociodemographic- health questionnaires. Regressions were used to predict MoCA scores with risk factors and SPACE tasks as predictors. We also conducted a factor analysis to investigate the relationships among SPACE tasks and the MoCA. RESULTS Regressions revealed significant effects of age, gender, and SPACE tasks. No risk factors for dementia predicted MoCA scores. The factor analysis revealed that MoCA and perspective taking contributed to a separate factor from other navigation tasks in SPACE. Normative data for SPACE are provided. DISCUSSION Our findings highlight the importance of navigation tasks for cognitive assessment and the early detection of cognitive impairment.
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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 | 0.002 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 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".