Does a champion-led implementation toolkit have the potential to improve aphasia guideline adherence? Results from a feasibility study
Bibliographic record
Abstract
PURPOSE: Active implementation efforts are needed to reduce evidence-practice gaps in post-stroke aphasia services. One potential solution is a comprehensive toolkit incorporating evidence-based implementation tools, led by trained Change Champions. We explored the feasibility, acceptability, and potential effectiveness of a prototype toolkit to improve speech-language pathologists' practice. METHOD: = 12 speech-language pathologists). Two Change Champions completed training then selected tools to support provision of written aphasia-friendly information for 3 months. Outcome measures included: a) Pre-post medical record audits, b) pre-post behavioural-determinants surveys, and c) post-study clinician focus groups. Data were analysed using descriptive statistics and non-parametric tests for quantitative data and content analysis for qualitative data, then integrated using a convergent interactive approach. RESULT: Clinicians perceived the toolkit was feasible and acceptable, and highlighted the benefit of Change Champions and resources in facilitating change. Post-implementation written aphasia-friendly information provision increased by 60% (p = 0.005) and most (12/14) targeted barriers improved, suggesting the toolkit with Change Champion support had the potential to improve practice. CONCLUSION: The champion-led implementation toolkit prototype was feasible and acceptable, improving guideline-recommended aphasia care. Result support further development of a theory-informed, tailorable implementation toolkit to improve aphasia services.
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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 | 0.007 | 0.005 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".