Enhancing ethical practice and critical reflection by the sTimul experience in a care ethics lab: Evaluation of the sTimul-experience
Bibliographic record
Abstract
Introduction: A three-year European project focused on ethical practice in health and social care. Its key objective was to enhance dignity in care through transformational learning as a result of the sTimul-experience. In the sTimul-experience, health and social care professionals adopted a patients’ role for 24 hours, while nursing students provided them care. Aim: The aim of this evaluation study was to examine and evaluate the sTimul-experience. Method: A tailored evaluation based on the first and third level of Kirkpatrick's Four Levels of Evaluation of educational programs was defined. Specifically designed questionnaires were completed by participants of the sTimul-experience. Results: Evaluation-scores varied between a modest satisfaction on the appropriateness of materials provided during the preparation process, to a high satisfaction on coaching during the reflection sessions. The degree the global sTimul experience impacted professional practice scored 7.6. Participants from the UK and France reported highest satisfactory scores. For the majority of the time student-trainers and facilitators worked within the formulated guidelines. Discussion: After the sTimul-experience, participants reported changes in their personal view on patients situations, underlining the transformative learning in the sTimul-experience. The sTimul-experience broke existing orientations participants had on what it is to be dependent. Participants changed their mental models towards dignity and what is good care. Conclusion: The sTimul-experience had a serious impact on participants practices. A synthesis of the findings of all the evaluation data clearly demonstrated the relevance of ‘a structured and comprehensive preparation’, ‘the importance of being a simulant by remaining in profile/role’, and ‘the importance of having different stages of reflection throughout the sTimul-experience’. This paper presents both qualitative as well as quantitative descriptive insights in the evaluation of transformative learning in the sTimul process, whereas until now no publications with a mixed evaluation design exist. Future studies can use our insights in the development of instruments to evaluate transformational learning by simulation in ethics.
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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 | 0.013 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".