Montreal Cognitive Assessment Scores Do Not Associate With Communication Challenges Reported by Adults With Alzheimer's Disease or Parkinson's Disease
Bibliographic record
Abstract
PURPOSES: Screening for cognitive-communication challenges in people with Alzheimer's disease (AD) or Parkinson's disease (PD) may benefit from multiple kinds of information about the client (e.g., patient-reported, performance-based). The purposes of this report are (a) to describe, using recently published score range descriptors (e.g., "mild," "moderate"), the patient-reported communication challenges of people with AD or PD using the Communicative Participation Item Bank (CPIB) and the Aphasia Communication Outcome Measure (ACOM); and (b) to examine the relationships between the performance-based Montreal Cognitive Assessment (MoCA), a cognitive screener, and patient-reported CPIB and ACOM scores. METHOD: Participants were a convenience sample of 49 community-dwelling adults with AD or PD. Participants completed the measures in person as part of a larger assessment battery. RESULTS: MoCA total scores ranged from 7 to 28. CPIB T-scores fell in the following ranges: 31% were "within normal limits," 57% reflected "mildly" restricted participation, and 12% reflected "moderately" restricted participation. ACOM T-scores fell in the following ranges: 50% were either "within normal limits" or reflected "mild" impairment, 29% reflected "mild-moderately" impaired functional communication, and 21% reflected "moderately" impaired functional communication. There were only weak and nonsignificant correlations between T-scores on the ACOM or CPIB and scores on the MoCA, and there were no group differences on the ACOM or CPIB between individuals who screened positive versus negative on the MoCA. CONCLUSION: When screening individuals with AD or PD, patient-reported communication challenges seem to be complementary to information provided by the MoCA and perhaps most useful in screening for mild communication challenges.
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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 | 0.001 | 0.010 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".