The predictive validity of the MoCA‐LD for assessing mental capacity in adults with intellectual disabilities
Bibliographic record
Abstract
BACKGROUND: Mental capacity assessments currently rely on subjective opinion. Researchers have yet to explore the association between key cognitive functions of rational decision making and mental capacity classifications for people with intellectual disabilities. METHOD: Sixty-three adults completed the Montreal Cognitive Assessment, which yielded estimates of their overall cognitive ability (MoCA-LD) as well as their memory, attention, language and executive functioning. Differences in scores were explored for those who had, and lacked, capacity, and logistic regression was used to test the predictive validity of each measure. RESULTS: There were significant differences between both groups for all measures. Logistic regression identified MoCA-LD as a significant predictor of capacity assessment outcomes. ROC curve analysis provided novel, evidence-based benchmarks to help guide clinical practice based on MoCA-LD scores. CONCLUSION: This study offers a foundation for more objective approaches to mental capacity assessment. This demonstrates that assessments of cognitive ability can yield information that is helpful for mental capacity evaluations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.048 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.006 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| 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 teacher head, 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".