A qualitative dominant mixed methods exploration of novel educational material for patients considering total knee arthroplasty
Bibliographic record
Abstract
Purpose To optimize non-operative management and decision making surrounding TKR we created educational whiteboard videos for patients with knee OA. The purpose of this study was to pilot our educational videos with end-users (patients) to determine patients’ experiences and perspectives regarding the content and clarity of videos and to better understand their potential impact on patient’s health behaviour. Materials and methods: This was a mixed methods evaluation, using a qualitative descriptive approach, of patients attending their first consultation with an arthroplasty surgeon for TKR. We conducted in-depth semi-structured interviews with patients. Three members of the research team coded data independently, implementing a thematic analysis. Results: Thirteen participants were included. Participants indicated that the videos enhanced their confidence and clarity surrounding their decision to undergo TKR. The videos also addressed several knowledge gaps in their understanding of OA management. Barriers to uptake of the education were identified including limited access to PTs and the challenge of weight loss. Conclusions: The current educational intervention was valued by patients with knee OA. Implementation of these videos may have important implications for patients, providers, and our health care system.IMPLICATIONS FOR REHABILITATIONPatients with knee OA referred by primary care physicians to arthroplasty surgeons have knowledge gaps that may influence their self-management and decision making surrounding their condition.Educational materials can address these gaps and support patients in their understanding and management of their condition, which may have important downstream implications.Barriers to accessing non-operative care including physiotherapy must be pre-emptively addressed to ensure that enhanced knowledge is met with improved access for patients.
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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 | 0.030 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.006 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".