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Record W4404998845 · doi:10.3390/jcm13237378

Results of a Codesign Process: A Cognition Screening Pathway for Inpatient and Outpatient Settings for Patients Who Are Facing or Have Undergone Lower Limb Amputation

2024· article· en· W4404998845 on OpenAlexaboutno aff
Erinn Dawes, Lyndel Hewitt, Vida Bliokas, Valerie Wilson

Bibliographic record

VenueJournal of Clinical Medicine · 2024
Typearticle
Languageen
FieldEngineering
TopicProsthetics and Rehabilitation Robotics
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineAmputationCognitionPhysical medicine and rehabilitationPhysical therapySurgeryPsychiatry

Abstract

fetched live from OpenAlex

Background/Objectives: Cognition plays a major role in prosthetic rehabilitation success. The ability to identify patients who may have difficulty understanding and adapting to the rehabilitation process is beneficial for clinicians and patients to allow for targeted and appropriate therapy. The research aim was to codesign a process that facilitates routine cognitive screening into the amputee inpatient journey. Methods: A convenience sample of sixteen medical and allied health practitioners from one local health district undertook a codesign process over 10 months from March to November 2023. A combination of virtual and face-to-face data collection occurred. Each of the codesign meetings was audio recorded, following which transcription occurred. Transcripts were reviewed using thematic analysis-based techniques to capture themes and consensus within the group. Results: Two pathways were established for use within one local health district, allowing clinicians to measure the cognition of patients in both inpatient and outpatient settings either before or after they underwent amputation. The newly established pathways provide step-by-step guidance for clinicians, such as how to address contraindicators for testing and providing guidance for subsequent neuropsychological testing. The Montreal Cognitive Assessment (MoCA), both paper based and electronic based, was selected as the cognitive screening tool for implementation. Conclusions: Utilizing codesign as a method for generating a cognitive screening pathway for amputees was successful. The pathways generated should be reviewed for suitability for application in other health settings.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.701
Threshold uncertainty score0.721

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.052
GPT teacher head0.360
Teacher spread0.308 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations2
Published2024
Admission routes1
Has abstractyes

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