Assessment of Prorated Scoring of an Abbreviated Protocol for the National Institutes of Health Toolbox Cognition Battery
Bibliographic record
Abstract
OBJECTIVE: To evaluate an abbreviated NIH Toolbox Cognition Battery (NIHTB-CB) protocol that can be administered remotely without any in-person assessments, and explore the agreement between prorated scores from the abbreviated protocol and standard scores from the full protocol. METHODS: Participant-level age-corrected NIHTB-CB data were extracted from six studies in individuals with a history of stroke, mild traumatic brain injury (mTBI), treatment-resistant psychosis, and healthy controls, with testing administered under standard conditions. Prorated fluid and total cognition scores were estimated using regression equations that excluded the three fluid cognition NIHTB-CB instruments which cannot be administered remotely. Paired t tests and intraclass correlations (ICCs) were used to compare the standard and prorated scores. RESULTS: Data were available for 245 participants. For fluid cognition, overall prorated scores were higher than standard scores (mean difference = +4.5, SD = 14.3; p < 0.001; ICC = 0.86). For total cognition, overall prorated scores were higher than standard scores (mean difference = +2.7, SD = 8.3; p < 0.001; ICC = 0.88). These differences were significant in the stroke and mTBI groups, but not in the healthy control or psychosis groups. CONCLUSIONS: Prorated scores from an abbreviated NIHTB-CB protocol are not a valid replacement for the scores from the standard protocol. Alternative approaches to administering the full protocol, or corrections to scoring of the abbreviated protocol, require further study and validation.
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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 | 0.035 | 0.077 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".