The importance of informational, clinical and personal support in patient experience with total knee replacement: a qualitative investigation
Bibliographic record
Abstract
BACKGROUND: Total knee arthroplasty (TKA) is the most frequently performed joint replacement surgery in North America. Patient perspectives on TKA have been investigated in various ways, including finding as many as 20% of TKA patients are dissatisfied with their surgical outcomes. Understanding the patient experience with TKA broadly and in relation to patient satisfaction is a key gap in existing literature. METHODS: We report on the qualitative component of a mixed methods prospective cohort study examining patient experience and satisfaction post-TKA for adults in British Columbia, Canada. Data collection consisted of 45 in-depth interviews about individuals' knee surgery experiences conducted eight months after surgery. Analysis consisted of thematic coding by multiple coders. RESULTS: Participants' descriptions of their TKA experiences were primarily concerned with support, or the provision of aid and assistance. Support was insufficient when their expectations of support were not met; unmet support expectations led to an overall negative TKA experience. Support operated in three key domains: (1) informational support, (2) clinical support, and (3) personal support. Key sources of informational and clinical support included pre-optimisation clinics, surgeons, and physiotherapists. Key topics for informational support included pain, pain management, and recovery trajectories. Personal support was provided by family, friends, other TKA patients, employers, and themselves. CONCLUSIONS: Patient needs and expectations for support are shaped both before and after TKA surgery. Patients with an overall positive TKA experience had improvement in their knee pain, stiffness or functioning post-TKA, had their major expectations and needs for support met during their TKA recovery, and believed that any significant future expectations or needs for ongoing support would be adequately met. In contrast, patients with an overall negative TKA experience had at least one major expectation or need for support not met during their TKA recovery, even in cases where they had good TKA outcomes. Suggested interventions to improve the experience of persons receiving TKA include an expanded patient navigator model, revised pre-surgery educational materials, particularly around pain expectations and management, and comprehensive sharing of other patients' TKA experience.
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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 | 0.014 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.009 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.005 |
| 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".