A-76 Specificity of the Repeatable Battery for the Assessment of Neuropsychological Status Digit Span as a Validity Indicator in Patients with Mild Cognitive Impairment and Dementia
Bibliographic record
Abstract
Abstract Objective The current study sought to examine the specificity of Digit Span (DS) scaled score from the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) as a performance validity test (PVT) in older adults with Mild Cognitive Impairment (MCI) or dementia. Method Archival data were utilized and included 195 patients (mean age = 72.8; mean education = 13.2) who underwent outpatient neuropsychological evaluations. Cases that had missing data, did not meet criteria for a neurocognitive disorder, or whose performance was deemed invalid were excluded. Participants were classified according to their evaluation diagnosis of MCI (n = 72; mean RBANS total score = 86.8) or dementia. Those diagnosed with dementia were divided by MoCA performance and categorized as mild dementia (n = 90; MoCA≥15; mean RBANS Total Score = 71.0) or moderate dementia (n = 33; MoCA < 15; mean RBANS Total Score = 55.9). Scaled score frequencies were analyzed to calculate specificity for each group. Results An RBANS DS scaled score of ≤4 occurred infrequently in older adults with MCI and mild dementia, resulting in specificity values of 0.93 and 0.90, respectively. In moderate dementia, specificity fell to 0.68 when using a scaled score of ≤4, with a cutoff of ≤2 required to maintain adequate specificity. Conclusions Findings suggest utility of RBANS DS scaled score as a PVT in dementia evaluations provided use of appropriate cutoffs. A more stringent cutoff was required in examinees with moderate dementia relative to patients with MCI and mild dementia. Future research should examine the RBANS DS sensitivity to invalid performance, as well as DS specificity across specific etiologies of MCI and dementia.
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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 | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".