Facilitators and obstacles to the use of a cognitive orthosis for meal preparation within the homes of adults with a moderate to severe traumatic brain injury: Informal caregivers and health-care professionals’ perspectives
Bibliographic record
Abstract
A cognitive orthosis named COOK was developed and implemented to facilitate meal preparation for adults with severe traumatic brain injury (TBI) living in an alternative housing unit. This study aimed to explore facilitators and barriers to the potential use and implementation of COOK in a new context (i.e., within the homes of people living with a TBI in the community). For this purpose, 20 stakeholders (e.g., health-care professionals, clinical coordinators, informal caregivers of individuals with TBI) were interviewed. Participants identified various potential benefits of this technology (e.g., improving independence and confidence of people with TBI) and facilitators (e.g., clinical and technical supports, helpful functionalities) that could facilitate the use and implementation of COOK within a home environment. However, numerous questions remained unanswered regarding the logistics surrounding the implementation of such technology. Thus, further studies and modifications are required to facilitate future implementation of this technology among individuals living in their own homes.
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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 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| 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".