Student Competition (Clinical/Best Practice Implementation) ID 1974598
Bibliographic record
Abstract
Background/Objective Rehabilitation after spinal cord injury (SCI) is a life-long process with individuals accessing care in a variety of settings, including centres without SCI-specific services (i.e., non-SCI-specialized centres). Activity-based Therapy (ABT) is a relatively new neurorestorative approach that involves intensive, task-specific movement practice below the level of injury. This study aimed to understand current knowledge, perceptions, and use of ABT by physical and occupational therapists at non-SCI-specialized centres. Design/Methods A qualitative exploratory study using semi-structured interviews was conducted. The Theoretical Domains Framework was used to develop an interview guide that queried therapists’ experiences providing SCI rehabilitation, perceptions of ABT and ABT implementation. Canadian therapists who worked with at least one SCI patient in the last 18 months and practiced at non-SCI-specialized centres participated. Interviews were audio-recorded, transcribed verbatim and analyzed using interpretive description. Results Four physical and three occupational therapists from acute, inpatient, long-term care and outpatient settings participated. Three themes were determined: 1) Perceived challenges of working with SCI in non-SCI-specialized centres, 2) Current therapy techniques used and 3) Desire for ABT knowledge and implementation strategies specific to non-SCI-specialized centres. It was identified that participants were unknowingly incorporating some components of ABT in their practice. Participants emphasized challenges to ABT implementation, such as knowledge gaps, and expressed a keenness to learn more about ABT. Conclusions Current implementation of ABT in non-SCI-specialized centres is limited, with a variety of challenges and therapist needs identified. Tailoring ABT education to therapists at non-SCI-specialized centres may increase implementation of ABT at these centres.
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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 | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.742 | 0.481 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".