Do we need yet another cognitive test? Free-Cog, a novel, hybrid, cognitive screening instrument
Bibliographic record
Abstract
The dementia syndrome encompasses not only cognitive but also functional impairments. This is acknowledged in canonical definitions of dementia (DSM-IV) and major neurocognitive disorder (DSM-5).1 2 However, functional (executive) deficits are not addressed in standard cognitive screening instruments, although they may be more significant for both patients and their carers in terms of their impact on activities of daily living. Traditionally, separate scales have been used to assess cognition and executive function. Free-Cog was developed to assess both cognitive and executive function in a single instrument, hence, a ‘hybrid’ test which combines questions in both domains (accessed at https://www.gmmh.nhs.uk/free-cog).3 The former component assesses traditional measures such as orientation in time and place, memory, calculation, attention, visuospatial function, language and fluency. The latter items are assessed on the basis of responses to a series of themed questions related to activities of daily living, including social functioning, travel, self-care and safety at home. Maximum scores for ‘cognitive function’ and ‘executive function’ are 25 and 5, respectively, giving an overall composite score of 30. Higher scores indicate better function. In this way, it is similar to most other cognitive screening tests such as the Mini-Mental State Examination (MMSE), the Montreal Cognitive Assessment (MoCA) and the Mini-Addenbrooke’s Cognitive Examination (MACE). Free-Cog was initially validated in a proof-of-concept test accuracy study.3 In this index study, a cohort of 960 patients and controls was recruited from multiple memory clinics in the UK, mostly based within psychogeriatric services. The total Free-Cog score and its …
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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 | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.005 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.012 | 0.009 |
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".