Comparing the Oxford Digital Multiple Errands Test (OxMET) to a real-life version: convergence, feasibility, and acceptability.
Bibliographic record
Abstract
The Oxford Digital Multiple Errands Test (OxMET), a validated computer tablet-based executive function task, has the potential to inform rehabilitation and discharge decisions. The aim of the present study was to assess the convergence, acceptability, and feasibility of the OxMET compared to the validated and in-person Multiple Errands Test Home Version (MET-Home). The present study sampled 97 participants (47 stroke survivors, 50 neurologically healthy control participants). Stroke survivors were on average 515 days post-stroke. All participants completed the OxMET and the MET-Home, the Montreal Cognitive Assessment (MoCA), and questionnaires on activities of daily living, depression, mobility, and disability. We examined convergence, acceptability, and feasibility of both METs. We analysed qualitative feedback about both METs. Using age, education, sex, mobility, disability, mood, MoCA score, technology usage, stroke severity, and time since stroke as predictors, there were no predictors of OxMET completion. MET-Home completion was predicted by sex B= 0.18, p=.03, mobility level B= 0.13, p=.02, and MoCA score B= 0.24, p=.02. MET-Home accuracy was predicted by Age B= -0.04, p= .03, sex B= -.98, p= .03, mRS B= -0.63, p= .04, and MoCA score B= .26, p<.001. OxMET accuracy was predicted by MoCA score B=.41, p<.001. MET-Home accuracy was significantly related to multiple OxMET metrics (r>=.30 & p<.006). Qualitative feedback indicated that the OxMET was easy and fun and had less cognitive/non-cognitive barriers compared to the MET-Home, but that the MET-Home was more challenging and interesting. Both MET task scores are moderately related, providing good convergent validity. The OxMET digital administration provides a more acceptable and inclusive assessment, especially to people with mobility restrictions and more severe stroke.
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.458 | 0.082 |
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; both teacher heads agree on what is shown here.
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".