The Oral Trail Making Test: Effects of Age and Concurrent Validity
Bibliographic record
Abstract
The oral version of the Trail Making Test (OTMT) is a neuropsychological measure that provides an assessment of sequential set-shifting without the motor and visual demands of the written TMT (WTMT). Originally purposed to serve as an oral analog of the WTMT, the OTMT provides a means to evaluate patients with physical restrictions. However, formal validity studies and available normative data remain sparse. In a sample of healthy adults (n = 81), a strong correlation was observed between OTMT-B and its written counterpart (r = .62), but the correlations were weak between OTMT-A and either written version of the TMT. OTMT-B was significantly correlated with age but not with education or gender, whereas OTMT-A was not significantly correlated with demographic factors. The WTMT to OTMT ratios observed in the current study were generally lower than previously reported and varied across age groups, suggesting that the recommended use of a uniform conversion factor to predict one performance based on the other should be cautiously undertaken. Normative data that have been stratified by age are provided as well as suggestions for using both versions of the TMT in tandem to better elucidate the nature of cognitive deficits and to aid in the localization of cerebral dysfunction.
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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 | 0.008 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".