Criterion validity of a functional cognitive task in patients with severe traumatic brain injury
Bibliographic record
Abstract
PRIMARY OBJECTIVE: To verify criterion validity of measures from a functional cognitive task (FCT) carried out with patients with severe traumatic brain injury (sTBI) at 2-5 years post-injury. METHODS AND PROCEDURES: Forty-six patients with sTBI took part in a long-term outcome study where the FCT and the Neurobehavioural Rating Scale-Revised (NBRS-R) were administered and the FIM™ instrument was rated. The FCT is a telephone information gathering task for evaluating functional cognitive skills. RESULTS: Ten of 16 measures of the FCT were significantly correlated with similar or related concepts from the NBRS-R. The FIM™ cognitive score and the individual items of this score were significantly correlated with 13 of the FCT measures and with the percentage of amount of information gathered. Internal consistency was good for 13 of 16 measures. Overall, patients generally had mild difficulty on the FCT concepts. CONCLUSION: The FCT can be used with patients with sTBI to evaluate certain aspects of functional cognition. It has good criterion validity and internal consistency, but additional research is required to further measure reliability and its applicability to other severity of TBI and to other phases of recovery.
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 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 | 0.004 | 0.031 |
| 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 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".