Achieving eating independence in an acute stroke ward: Developing a collaborative care plan
Bibliographic record
Abstract
Aim: This article outlines the development and implementation of a collaborative feeding care plan (FCP) for stroke patients in an acute stroke ward. The aim of this pilot study was to evaluate the impact of an ecological intervention to improve eating independence in an acute stroke ward environment. Methods: An action research approach comprising seven stages—determine the initial problem, develop the care plan, act, reflect and monitor progress, evaluate, reflect, and refine plan—was used to track environmental changes during the development and implementation of the FCP in an acute stroke ward in an Australian regional hospital. During the evaluation phase, six allied health staff completed a survey on the FCP. The staff also completed an observation assessment integrating the Eating Disability Scale, Functional Independence Measure and Canadian Occupational Performance Measure with 12 participants with acute stoke (participants with FCP=6; participants without FCP=6). Results: The FCP group showed significant improvements in upper limb independence (p=0.046), when comparing mean admission scores (3.5±0.97) with discharge scores (4.17±2.14). Clinically significant improvements in levels of collaboration between health professionals were also demonstrated. Conclusions: The changes in team collaboration and the patient's upper limb independence indicate how environmental change can influence acute stroke patient outcomes. It is recommended that this study be expanded to further explore the effect of ecological interventions and change.
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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 | 0.012 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".