Making the Case for Virtual Osteoarthritis Management Programs
Bibliographic record
Abstract
Rationale: Osteoarthritis (OA) is one of Canada’s most prevalent chronic conditions, resulting in a high burden of disease due to common symptoms of chronic pain, limited function, poor mental health, and decreased quality of life. First-line treatments for OA target pain and quality of life through education, exercise, and weight loss. However, many individuals do not participate in first-line approaches, and known barriers exist to in-person formats. Virtual osteoarthritis management programs (OAMP) have the potential to improve access to treatment and address barriers to in-person formats. Objectives: To understand virtual OAMP that include education and exercises by examining the GLA:DTM Canada transition to virtual formats. The objectives are to: 1) Identify and synthesize available guidance for implementing virtual programs 2) Understand participant and clinician perspectives on virtual GLA:DTM 3) Compare GLA:DTM program outcomes between in-person and virtual or hybrid formats Results: Objective 1: A scoping review demonstrated limited guidance available (six peer-reviewed, six grey literature) for clinicians implementing virtual programs. Collectively guidance suggested clinician training, adjustments to consent, education and exercise components, and completing participant screening and safety checks. Objective 2: Participants’ and clinicians’ perspectives were obtained via qualitative descriptive analysis and identified four main themes: 1) expected and unexpected benefits, 2) drawbacks to virtual programs, 3) program delivery in a virtual world, and 4) shifting and non-shifting perspectives. Overall, participants supported virtual formats, while clinicians remained divided. Objective 3: When compared to virtual formats there were no differences between in-person and virtual/hybrid for pain, quality of life, or self-efficacy. Compared to in-person formats, the virtual format resulted in statistically, but not clinically, lower function scores, and the hybrid format resulted in statistically and clinically fewer chair stand repetitions. Conclusion: Despite limited guidance available on implementation, virtual and hybrid OAMP appear both accepted and generally effective for participants.
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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 | 0.056 | 0.165 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.008 |
| Scholarly communication | 0.016 | 0.020 |
| Open science | 0.005 | 0.015 |
| Research integrity | 0.009 | 0.013 |
| Insufficient payload (model declined to judge) | 0.016 | 0.002 |
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".