A novel hybrid scale for the assessment of cognitive and executive function: The Free‐Cog
Bibliographic record
Abstract
BACKGROUND: Scales measuring cognitive and executive functions are integral to the assessment and management of patients with suspected cognitive impairment. Some of the most commonly used cognitive tests are now subject to copyright restrictions. Furthermore, no existing scale assesses both executive and cognitive abilities. AIMS: We aimed to develop and validate a novel hybrid scale for use in clinical practice which integrate measures of cognition and executive abilities ('Free-Cog'). METHODS: The instrument was devised through a national collaboration including health professionals, those with lived experience of dementia and researchers. Following ethics committee approval, the Free-Cog was assessed in 25 real-world clinical settings across England, Wales and Scotland. It was compared to three other cognitive tests routinely administered in clinical practice: the Mini-Mental State Examination (MMSE), the Montreal Cognitive Assessment (MOCA), and the Addenbrooke's Cognitive Examination (ACE). RESULTS: The Free-Cog was tested in 960 patients with clinical diagnoses of dementia, Mild Cognitive Impairment (MCI), and normal controls. Similar to the MMSE, MOCA and ACE, it discriminated well between the three groups (p < 0.001). It correlated well with the other instruments. Using a receiver operating characteristic curve analysis, Free-Cog achieved an Area Under Curve of 0.94 for dementia versus controls, 0.80 for MCI versus controls and 0.77 for dementia versus MCI. A version of the tool adapted for telephone consultation, the Tele Free-Cog, also discriminated well between patient groups. CONCLUSIONS: Free-Cog is a non-proprietary, empirically derived, concise assessment. Uniquely, it combines cognitive and executive function questions in the one instrument. It could be used to inform the assessment of people presenting with cognitive impairment and is available to anyone interested in trialling it.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".