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Record W2780406101

Cognitive and Occupationally-based Assessments in Acute Care: For Individuals with Acquired Brain Injury

2017· article· en· W2780406101 on OpenAlexvenueaboutno aff
Jillian Harrison, Stephanie Lenk, Brooke Logan

Bibliographic record

VenueSound Ideas (University of Puget Sound) · 2017
Typearticle
Languageen
FieldMedicine
TopicCerebral Palsy and Movement Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsAcquired brain injuryCognitionMedicinePsychologyIntensive care medicineMedical emergencyPsychiatryPhysical therapyRehabilitation
DOInot available

Abstract

fetched live from OpenAlex

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.016
metaresearch head score (Gemma)0.072
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.016
Threshold uncertainty score0.084

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.072
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0030.003
Science and technology studies0.0010.001
Scholarly communication0.0030.003
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.021
GPT teacher head0.316
Teacher spread0.294 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2017
Admission routes2
Has abstractyes

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