The Influence of Expectancies on Pain and Function Over Time After Total Knee Arthroplasty
Bibliographic record
Abstract
OBJECTIVE: Expectancies have a well-documented influence on the experience of pain, responses to treatment, and postsurgical outcomes. In individuals with osteoarthritis, several studies have shown that expectations predict increased pain and disability after total knee replacement surgery. Despite the growing recognition of the importance of expectancies in clinical settings, few studies have examined the influence of expectancies throughout postsurgical recovery trajectories. The objective of the present study was to examine the role of presurgical expectancies on pain and function at 6-week, 6-month, and 1-year follow-ups after total knee arthroplasty. DESIGN AND PARTICIPANTS: Data were collected from patients scheduled for total knee arthroplasty 1 week before surgery and then at 6 weeks, 6 months, and 1 year after surgery. Correlational and multivariable regression analyses examined the influence of expectancies on patients' perceptions of pain reduction and functional improvement at each time point. Analyses controlled for age, sex, body mass index, presurgical pain intensity and function, pain catastrophizing, anxiety, and depression. RESULTS: Results revealed that expectancies significantly predicted pain reduction and functional improvement at 1-year follow-up. However, expectancies did not predict outcomes at the 6-week and 6-month follow-ups. Catastrophizing and depressive symptoms emerged as short-term predictors of postsurgical functional limitations at 6-week and 6-month follow-ups, respectively. CONCLUSIONS: The results suggest that targeting high levels of catastrophizing and depressive symptoms could optimize short-term recovery after total knee arthroplasty. However, the results demonstrate that targeting presurgical negative expectancies could prevent prolonged recovery trajectories, characterized by pain and loss of function up to 1 year after total knee arthroplasty.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".