17 Evidence based practice education for healthcare professions – an international multidisciplinary perspective
Bibliographic record
Abstract
Objectives To ascertain current practice and provision of EBP education across healthcare professions at undergraduate, postgraduate and continuing professional development programme levels for the purpose of making key recommendations to healthcare educators and policy makers in relation to ‘best practice’ for EBP education. Method Three distinct but interlinked phases of research were conducted. In phase 1, a desktop rapid review was undertaken to provide a contextualised succinct synthesis of literature relating to the competencies and programme components associated with EBP education. In phase 2, interviews with experts (n=5) in evidence based practice education were conducted to ascertain current and nuanced information on EBP education from an international perspective (Australia, New Zealand, Canada, United Kingdom). In Phase 3,a descriptive, cross-sectional, national, online survey was undertaken to capture and describe baseline data relating to the current provision and practice of EBP education to healthcare professionals at third level institutions and professional training/regulatory bodies in Ireland. Results A narrative synthesis of 83 empirical studies revealed that participation in any form of EBP education has beneficial effects across all EBP competencies with the most apparent positive trend derived from multi-modal teaching and learning interventions. Analysis of EBp expert interview data provided definitive advice in relation to: (i) EBP curriculum considerations; (ii) Teaching EBP and (iii) Stakeholder engagement in EBP education. Representation from 11 healthcare professions across academic levels was obtained from the national survey conducted in Phase 3. A considerable amount of EBP activity throughout health profession education was apparent, with strong recognition of the need for EBP principles and processes within curricula to achieve core professional competencies. However, effectively embedding EBP throughout health education curricula requires further strategic development. Conclusions Despite positive attitudes towards EBP and a predominant recognition of its necessity for the delivery of quality and safe healthcare, its consistent translation at the point of care remains elusive. An examination of current discourse between academic and clinical educators across healthcare professions is required to progress a ‘real world’ pragmatic approach to the integration of EBP education which has meaningful relevance to students and engenders active engagement from educators, clinicians and policy-makers alike.
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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 | 0.092 | 0.139 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.003 | 0.010 |
| Scholarly communication | 0.021 | 0.012 |
| Open science | 0.004 | 0.012 |
| Research integrity | 0.013 | 0.012 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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".