Therapeutic-Use-of-Self as Relational Pedagogy in Occupational Therapy Education: A Qualitative Description Study
Bibliographic record
Abstract
Background. Amid growing calls for relational teaching approaches in higher education to improve student learning outcomes and student and educator well-being, a need remains for effective relational pedagogies. Therapeutic-use-of-self (TUS) is an occupational therapy skill that centers the client–occupational therapist relationship, yet there is a dearth of research exploring its application as a pedagogy. This presents an opportunity for a widely used occupational therapy skill, TUS, to be adapted as a much-needed relational pedagogy. Objective. We explored the experience of TUS as a relational pedagogy in occupational therapy education from educator and student perspectives. Method. This qualitative description study borrowed from the evocative methodology of collaborative autoethnography. We, six researcher–participants, across two Canadian entry-to-practice occupational therapy programs, engaged in five discussions exploring the relationship between participant stories and contexts. Reflective memoing and reflexive thematic analysis were applied for analysis. Findings. Four themes were described: (a) education as transaction, (b) authenticity in learning, (c) experiencing TUS, and (d) relationship as resistance. Conclusion. With an emphasis on authenticity, empathy, power equity, and critical reflexivity, TUS challenges status quo approaches to education. Although neoliberalism challenges the feasibility of relational pedagogy in higher education, TUS holds promise as a relational and critical pedagogy.
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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 | 0.016 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.013 | 0.012 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".