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
Bibliographic record
Abstract
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 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 | 0.014 | 0.053 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".