Multiple clock drawing scoring systems: simpler is better
Bibliographic record
Abstract
OBJECTIVE: The clock drawing test (CDT) is a widely used cognitive screening tool that has been well accepted among clinicians and patients for its ease of use and short administration time. Although there is ample interest in the CDT as a screening instrument, there remains a range of CDT administration and scoring systems with no consensus on which system produces the most valid results while remaining user friendly. The aims of this review are to synthesize the available evidence on CDT scoring systems' effectiveness and to recommend which system is best suited for use at the clinical frontlines. DESIGN: A Pubmed literature search was carried out from 2000 to 2013 including manual cross-referencing of bibliographies in order to capture studies published after Shulman's comprehensive review published in 2000. A brief summary of all original scoring systems is included, as well as a review of relevant comparative studies. RESULTS: The consensus from multiple comparison studies suggests that increasing the complexity of CDT scoring systems does little to enhance the test's ability to identify significant cognitive impairment. Moreover, increased complexity in scoring adds to the administration time, thereby reducing the test's utility in clinical settings. CONCLUSIONS: In comparing scoring systems, no system emerged as consistently superior in terms of predictive validity. The authors conclude that when scoring the CDT as a screening instrument in a primary/general medicine/community setting, simpler is better, and perhaps qualitative assessment of "normal" versus "abnormal" may be sufficient for screening purposes and the establishment of a baseline for follow-up.
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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 | 0.045 | 0.136 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.012 | 0.013 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.006 | 0.008 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".