New normative data and convergent validity for the MET-Home revised in English speaking neurologically healthy adults and stroke survivors
Bibliographic record
Abstract
ObjectiveThe Multiple Errands Test - Home (MET-Home) is a home-based standardised assessment of executive dysfunction. We revised the MET-Home to combat low acceptability of two items. We aimed to provide normative data and psychometrically validate the new version. MethodWe compared existing data for the original MET-Home and the revised version. We accounted for covariates of age, education, mobility, disability level, stroke severity and days since stroke in comparisons. We assessed reliability and validity of the revision and provided new normative data, as well as known-group discriminability analysis. We correlated MET-Home with global cognitive functioning (Montreal Cognitive Assessment), basic functioning (Barthel Index), and instrumental activities of daily living (Nottingham Extended Activities of Daily Living scale). ResultsData (N=144) from neurologically healthy participants (n=78, n=44 revised version) and survivors of stroke (n=66, 29 revised version) were analysed. MET-Home versions were not statistically different in accuracy, omissions, or partial completions (all p>.05). MET-Home reliability was high (α=.80). The MET-Home was highly related to global cognitive functioning (r=.56, p<.001), instrumental activities of daily living (r=.46, p<.001) and basic functioning (r=.35, p<.001). New normative data were generated. Known group discriminability using normative cut offs was good and specificity of MET-Home accuracy was high (90% specificity), but sensitivity was low (30% sensitivity). ConclusionThe revised MET-Home is a newly normed and valid tool useful for clinical investigation of executive dysfunction. We encourage use of this revised MET-Home with greater participant acceptability.
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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 | 0.005 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".