Educational Needs of Patients Undergoing Total Joint Arthroplasty
Bibliographic record
Abstract
PURPOSE: To identify the educational needs of adults who undergo total hip and total knee replacement surgery. METHODS: A qualitative research design using a semi-standardized interviewing method was employed. A purposive sampling technique was used to recruit participants, who were eligible if they were scheduled to undergo total hip or total knee replacement or had undergone total hip or total knee replacement in the previous 3 to 6 months. A comparative contrast method of analysis was used. RESULTS: Of 22 potential participants who were approached, 15 participated. Five were booked for upcoming total hip or total knee replacement and 10 had undergone at least one total hip or total knee replacement in the previous 3 to 6 months. Several themes related to specific educational needs and factors affecting educational needs, including access, preoperative phase, surgery and medical recovery, rehabilitation process and functional recovery, fears, and expectations counterbalanced with responsibility, emerged from the interviews. CONCLUSIONS: Educational needs of adults who undergo total hip and knee replacement surgery encompass a broad range of topics, confirming the importance of offering an all-inclusive information package regarding total hip and total knee replacement.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".