Agentivité : perspectives des ergothérapeutes quant à leur sentiment de compétence et leurs compétences à la suite d’une formation
Bibliographic record
Abstract
Context: To tackle the systemic injustices experienced by people in vulnerable situations, occupational therapists' agency, i.e. their power to act, is necessary. However, occupational therapists feel ill-equipped to exercise this power, and would like to develop their skills. The general aim of this research was therefore to document occupational therapists' perception of their skills before and after agency training. Methods: We used a mixed sequential explanatory design, comprising a quantitative component consisting of a pre- and post-training self-administered questionnaire and a descriptive qualitative component with group interviews. Results: A total of 103 occupational therapists completed the training between January 19 and October 19, 2019. Their sense of competence improved, especially for those with no prior training in agency. The skills perceived as having developed the most corresponded to the skills deemed a priority for development, namely effective communication, intentional collaboration, and observation and analysis. On the other hand, occupational therapists emphasized that they had not mastered the exercise of these skills in a real-life context. Conclusion: Although continuing education is one way of improving the skills needed to exercise agency, questions remain as to the optimal modalities for ensuring their full and lasting development.
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 | 0.012 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.014 |
| Scholarly communication | 0.013 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".