Development and validation of a questionnaire assessing discrepancy between patients’ pre‐surgery expectations and abilities and post‐surgical outcomes following knee replacement surgery
Bibliographic record
Abstract
PURPOSE: The discrepancy between patient-desired outcomes and achievable functional outcomes is a source of patient dissatisfaction. This paper reports development and validation of a questionnaire to assess this discrepancy in patients undergoing knee replacement surgery. METHODS: The initial questionnaire (Knee Surgery Perception Questionnaire, KSPQ) comprised two parts. Part A, assessed patients' perception of their current level of function and pain, and Part B, assessed patients' desired outcomes of the surgery. Validation was carried out for Part A and then applied to Part B using a one-factor congeneric model and was tested in 185 patients preceding surgery. A discrepancy score between patients' expectations and desired outcome (Part B) and their perception of current function (Part A) was also calculated. Pearson correlations were used between the KSPQ total score and subscales and other knee-specific questionnaires to determine construct validity. RESULTS: The final best set of models included four items for each subscale with a Chi-square value of 7.3 (n.s). The subscales and the total KSPQ showed significant strong to moderate correlations with knee-specific questionnaires. The discrepancy score in each subscale and the overall score showed relatively large discrepancy between patients' expectations and their perception of current function; with higher discrepancy score reported for pain and walking. CONCLUSION: The KSPQ is a valid questionnaire to assess patients' expected and desired outcomes of knee replacement surgery and their perception of their current abilities and function, and discrepancy between these. The KSPQ now requires further investigation at different stages of recovery following surgery. LEVEL OF EVIDENCE: III.
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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 | 0.011 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".