Face validity of the youth Multiple Errands Test (yMET) in the community: A focus group and pilot study
Bibliographic record
Abstract
Introduction During late adolescence and early adulthood, maturation of cognitive functions including executive functions are occurring. The multiple errands test is an assessment of real-world executive functions and, to date, non-virtual reality multiple errands test research has focused primarily on adults with acquired brain injury in hospital settings. There is poor evidence across multiple errands test studies for content and face validity and limited studies in the community. This study aimed to explore multiple errands test face validity for typically developing youth (age 16–24 years) and describe their community setting performance on a youth multiple errands test. Methods A youth focus group ( N = 5) was conducted to explore perceptions of the multiple errands test. From their input, the youth multiple errands test was developed and pilot tested ( N = 9) in a shopping mall. Results Two themes emerged from focus group analysis and limited changes, relevant to youth, were made to develop the youth multiple errands test. The focus group and pilot study found the youth multiple errands test was acceptable and cognitively challenging for youth, with older youth performing better than younger youth. Overall youth multiple errands test performance suggests similarities to healthy adults in previous studies. Conclusion Findings must be interpreted with caution since the sample was small, but preliminary results indicate that future studies with the youth multiple errands test are feasible and warranted.
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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 | 0.021 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".