Using activity-based therapy for individuals with spinal cord injury or disease: Interviews with physical and occupational therapists in rehabilitation hospitals
Bibliographic record
Abstract
Objective: To understand if and how physical therapists (PTs) and occupational therapists (OTs) use activity-based therapy (ABT) and its associated technologies for the rehabilitation of individuals living with spinal cord injury or disease (SCI/D) in Canadian rehabilitation hospital settings.Design: Qualitative study.Setting: Through rehabilitation hospitals participating in the Rick Hansen Spinal Cord Injury Registry, we recruited licensed OTs and PTs to participate in focus groups.Participants: Twelve PTs and ten OTs from nine sites across eight provinces participated.Outcome Measures: To inform the development of a semi-structured interview guide, we used the Theoretical Domains Framework. To analyze the data, we used interpretive description.Results: We identified three themes that influenced therapists’ use of ABT and associated technologies for SCI/D rehabilitation. (1) Therapists’ decision-making approach to ABT and technology. Therapist roles, site-specific dynamics and goal setting influenced decision-making. Assuming roles such as mentor, liaison and advocate led to more ABT use. Site-specific dynamics concerned levels of ABT knowledge, teamwork, and staffing. In hospital rehabilitation, there was competition between discharge and neurorecovery goals. (2) Therapist perceived individual factors. Patient factors either increased (i.e. patients’ motivation, self-advocacy) or prevented (i.e. mourning period, tolerance) the likelihood that ABT was introduced by therapists. (3) ABT and equipment access. Technology was used for ABT in a variety of ways. Access was affected by visible (e.g. equipment cost) and invisible barriers (e.g. departmental relations).Conclusions: The use of ABT and its associated technologies in Canadian rehabilitation hospitals is variable. Ongoing education could be offered, and site-specific implementation strategies could be developed, to promote ABT use.
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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 | 0.008 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.010 | 0.007 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".