Modifying the Mini Cog to Screen for Cognitive Impairment in Non-literate Individuals
Bibliographic record
Abstract
Abstract Objectives: The Mini-Cog, a rapid, valid, and reliable screening tool for cognitive impairment, consists of 3-word recall and an executive Clock-Drawing Test (CDT). However, CDT requires at least basic literacy and cultural exposure to analog clocks, conditions not met in many population groups around the world. We developed a modification of the Mini-Cog (MMC) for use with non-literate and literate individuals. Methods: Participants were adults (≥ 60 years) with no neurological diagnosis, with known cognitive impairment due to stroke, Parkinsonism, traumatic brain injury or Alzheimer’s disease, and whose family members were able to read and write. We replaced the CDT with two tasks of everyday life: a serial subtraction task or a multistep performance task. Family members rated the acceptability and feasibility of the Mini-Cog versions using a 6-point scale, and completed a proxy-rated cognitive staging tool, the Dementia Severity Rating Scale (DSRS). Spearman’s rho, Mann- Whitney U and Chi-square tests were used to evaluate group differences and associations between measures. Results: Data were collected from 63 participants (75% ≥ 60 years, 67% non-literate). Literacy was associated with CDT (Chi-square strength 0.9, p < 0.001). Both MMC versions correlated with DSRS in healthy adults and patients (rho 0.6-0.7, p < 0.05). In literate individuals, the acceptability and feasibility of CDT and both alternate distractors were similarly high (5/6). Conclusions: Two alternate distractor tasks may successfully replace CDT in the Mini-Cog. The MMC versions are promising and deserve further study as screening tools for cognitive impairment in larger and more fully characterized samples.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".