The test of time: a history of clock drawing
Bibliographic record
Abstract
OBJECTIVE: The clock drawing test (CDT) has become one of the most widely used cognitive screening instruments in clinical and research settings. Its effectiveness, acceptability, and quick and easy administration have made it a staple for cognitive screening in dementia and a wide range of brain disorders. Despite a spike in popularity since the 1990s, its origins are relatively unknown. The goal of this review is to chronicle its saga and chart its usage over time. METHODS: PsycInfo, Medline, and PubMed literature searches were performed from earliest record to June 2016, in addition to manual cross-referencing of bibliographies, with a focus before 1990. Summary of relevant articles and books up until 1989 is included, as well as clinical applications and surveys that track CDT usage over time. RESULTS: While MacDonald Critchley's well-known textbook from 1953, The Parietal Lobes, is often cited as the first mention of the CDT, its recorded use actually stretches back more than a century to 1915. A review of the literature shows that the CDT began as a test for aphasia-related disorders and constructional apraxia until its entry into contemporary cognitive screening in the 1980s when it primarily became a cognitive screen. Its usage took off in 1989 with over 2000 publications since. CONCLUSIONS: Despite a fairly obscure existence for decades, the CDT has emerged as an effective and ideal cognitive screening instrument for a wide range of conditions. Its use continues to increase, and it has been incorporated into several widely used cognitive screening batteries. Copyright © 2017 John Wiley & Sons, Ltd.
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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 | 0.006 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.014 |
| Scholarly communication | 0.004 | 0.008 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 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".