Examining Technological Applications Used for the Cognitive Assessment and Rehabilitation of Concussed Individuals: A Rapid Review
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 use of technological applications for cognitive assessment and rehabilitation is growing, yet tools specifically targeting cognition in concussed individuals remain underexplored. This rapid review examined technologies used for cognitive assessment and/or rehabilitation following concussion. Specific objectives were to identify (1) cognitive domains targeted, (2) participant populations recruited, (3) quality of assessment or therapeutic impact, and (4) user involvement in application design. A structured search across three databases yielded 16 articles analyzing 21 applications. Four (25%) focused primarily on cognition, while the remainder addressed multiple domains. Most applications assessed cognition, and study populations frequently included athletes and military members/veterans. Only two (12.5%) studies reported user feedback on application design. Findings suggest a need for broader requirements of concussed civilians to improve representativeness, and for future research to prioritize the development of applications targeting cognitive rehabilitation in concussed populations.
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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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