Anosognosia in Alzheimer’s Pathology: Validation of a New Measure
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Bibliographic record
Abstract
OBJECTIVE: Two studies were performed to validate a brief measure of cognitive insight and compare it to an empirical model - the Cognitive Awareness Model (CAM). METHOD: A pilot study included 31 (52% male; Mage = 69.42) patients from an outpatient neuropsychological assessment clinic. Seven patients were diagnosed with likely Alzheimer's dementia (AD), 15 mild cognitive impairment (MCI), and 9 no diagnosis (i.e., cognitively normal; CN). The Cognitive Coding Form (CCF) and several other measures were administered. Study 2 entailed archival data extraction of 240 patients (80 CN, 80 MCI, and 80 AD; 53.3% female; Mage = 72.8) to examine whether the CCF predicts memory (Wechsler Memory Scale - IV) and executive functioning (Trail-Making Test B). RESULTS: The pilot study found preliminary evidence of convergent and discriminant validity for the 8-item CCF. Study 2 confirmed that both patient-reported cognitive concerns (F(2,237) = 10.40, p < .001, ω2 = .07, power = .99) and, more strongly, CCF informant-patient discrepancy scores (F(2,237) = 24.52, p < .001, ω2 = .16, power = .99) can distinguish CNs from those with MCI and AD. A regression indicated that depression (5.5%; β = -.38, p < .001) and TMT-B (13%; β = -.43, p < .001), together accounted for 18.5% of the variance in insight (R2 = .19, F(2,219) = 26.10, p < .001), supporting the CAM. CONCLUSIONS: These studies establish an efficient measure of insight with high clinical utility and inform the literature on the role of insight in predicting performance in those with Alzheimer's pathology.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it