Cognitive and Occupationally-based Assessments in Acute Care: For Individuals with Acquired Brain Injury
Bibliographic record
Abstract
The student researchers collaborated with Marcy Boschee, OTR/L, an occupational therapist practicing in the acute care unit at St. Joseph's Medical Center in Tacoma, WA to investigate two clinical questions: [1] “What evidence is there for the effectiveness of the Montreal Cognitive Assessment (MoCA) in predicting functional cognitive impairment of patients 18-years-old and older in acute care who have sustained an ABI?” and [2] “Which occupationally-based cognitive assessments, feasible to use in the acute care setting, are most effective at predicting functional impairment in patients 18-years-old and older with mild to severe ABI?” A systematic review was conducted and 29 articles were included. The AOTA levels and the Research Pyramid of categorization were used to determine rigor. The findings indicated that the MoCA is not sensitive enough, nor sufficient, in detecting no or mild cognitive impairment. It is therefore recommended that when the MoCA indicates no cognitive impairment, the OT practitioner should administer an occupationally-based cognitive assessment to fully assess the client’s executive functioning abilities.\nThe student researchers analyzed the findings and developed an occupationally-based assessment matrix, supplemented by a decision flowchart. These and the research itself were presented to Marcy and her colleagues in the acute rehabilitation unit at St. Joseph’s Medical Center. In order to best support the implementation of the new information into clinical practice, specific knowledge translation products and activities were offered.\nThe effectiveness of the knowledge translation process was measured through several methods. These included extensive revision processes, post in-service surveys and corresponding analysis, as well as a structured consultation (e.g. follow-up questions) for our collaborating clinician following the in-service itself. It is recommended that St. Joseph’s Medical Center purchase an occupationally-based assessment, as outlined in the assessment matrix, to improve their ability to adequately and effectively assess mild cognitive impairment.
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.
How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".