Self-reported strategy generation and implementation in the multiple errands test: A qualitative description
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The Multiple Errands Test (MET) is a naturalistic assessment of executive function. Strategy use during the MET can provide useful information for the development of a cognitive profile and intervention plan in patients with brain injury. However, while observed external strategy use in the MET is well-documented, information about internal strategy use and reference data with healthy controls is limited. Contextual influences on strategy selection in this real-world assessment are also not well understood. This qualitative descriptive study explored the internal and external strategies used during MET performance by cognitively intact adults. Strategies were categorized as planning, checking, and problem solving. When planning, participants simplified and familiarized themselves with MET requirements before developing an action plan. They checked their performance by asking for help and using cues in the physical environment. When problems arose, these were solved through self-talk, comparing alternatives, applying context and modifying their plan. Results highlighted that individuals employ both visible and hidden strategies during the MET. This suggests that reflective discussions with patients following cognitive task engagement may be important, to uncover and understand strategy use, both to inform analysis of performance and guide strategy training.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it