What matters to patients following total knee arthroplasty? A grounded theory of adapting to a knee replacement
Bibliographic record
Abstract
BACKGROUND: Globally the volume of total knee arthroplasty (TKA) is on the rise, reflecting aging populations, an associated increase in treatment of osteoarthritis, and a desire for improved quality of life. There is evidence that as high as 15 to 20% of patients are not satisfied with their TKA results and efforts need to be made to improve these rates. This study set out to identify what patients consider important when reflecting on TKA satisfaction, to pave the way to identifying service transformation opportunities that will enhance patient-centred care and satisfaction with this procedure. METHODS: Twenty-seven TKA recipients were recruited in the province of British Columbia, Canada. Semi-structured interviews were conducted about participants' experience and satisfaction with TKA, three to four years post-surgery. Grounded theory was employed to analyze participants' stories about what was front of mind when they reflected on satisfaction with their new knee. RESULTS: Participants described their post-TKA knee in terms its adequacy: how it felt and worked, and how it matched their pre-surgical expectations. The central element of their stories was the process of adapting, which gave rise to their perceptions of adequacy. Adapting comprises the patient experience of physically integrating and cognitively accepting their new knee. Patterns of adapting reflect the level of the new knee's achieved adequacy and the straightforwardness of the adapting process. DISCUSSION: The conceptualization of adequacy and the process of adapting allow a patient-centred understanding of what patients experience following TKA. For participants who did not readily achieve the adequacy they had anticipated, the challenges they experienced during adapting dominated their stories. Participants' adapting stories afford key insights into how the health care system could adjust to better support TKA patients, and improve rates of satisfaction with this procedure. CONCLUSIONS: The process of adapting lends itself to system intervention in support of enhanced post-TKA outcomes and satisfaction. These interventions could include the development of a care model including long-term clinical support for patients whose knees do not achieve desired results on schedule, and collaborating with patients to set and manage reasonable expectations about how their post-TKA knee will feel and function.
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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 | 0.031 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.011 | 0.033 |
| Scholarly communication | 0.010 | 0.009 |
| Open science | 0.004 | 0.007 |
| Research integrity | 0.004 | 0.008 |
| 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".