Providing Insights into the Challenges of Implementing Activity-Based Therapy in Canada: A Comparative Analysis Using Focus Group Interviews with Key Interest Groups
Bibliographic record
Abstract
Background: Activity-based therapy (ABT) has emerged as a therapeutic approach that may promote neurorecovery and reduce secondary complications in people living with spinal cord injury or disease (SCI/D). In spite of the numerous health benefits, adoption of ABT into practice has been limited across the Canadian care continuum. Objectives: This study aimed to understand the challenges of implementing ABT in Canada for people living with SCI/D through the perspectives of key interest groups. Methods: Researchers, hospital therapists, community trainers, administrators, persons living with SCI/D, and advocates, funders, and policy experts who had knowledge of and/or experience with ABT participated in focus group interviews to share their perspectives on the barriers to ABT practice. Interviews were analyzed using conventional content analysis followed by a comparative analysis across groups. Results: The 48 participants identified six key challenges: (1) challenge of gaps in knowledge/training, (2) challenge of standardizing ABT, (3) challenge of determining the optimal timing of ABT, (4) challenge of defining, characterizing, and achieving high dosage and intensity, (5) challenge of funding ABT, and (6) challenge of measuring participation and performance in ABT. A comparative analysis found some challenges were emphasized by certain groups, such as the cost of ABT for persons with SCI/D, lack of education and training in ABT for therapists and trainers, minimal evidence to develop guidelines for researchers and advocates, and funding ABT programs for administrators. Conclusion: Participants highlighted several challenges that limit ABT practice. Strategies to address these challenges will support successful implementation of ABT in Canada.
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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 | 0.037 | 0.057 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.026 | 0.008 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| 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".