Perceived self-efficacy gained from, and health effects of, a rehabilitation program after hip joint replacement
Bibliographic record
Abstract
OBJECTIVE: To examine whether a routine multidisciplinary inpatient rehabilitation program can increase patient self-efficacy, and to investigate the effects of high self-efficacy at admission, and increases in self-efficacy, on health changes in patients who undergo such rehabilitation after hip joint replacement. METHODS: Participants in this longitudinal study were 1,065 patients who underwent inpatient rehabilitation after hip joint replacement. Questionnaires were administered at admission, discharge, and 6-month followup. The main outcome variables were disability, pain, depressive symptomatology, and self-efficacy to cope with disability and pain. RESULTS: Significant improvements from admission to discharge from the inpatient rehabilitation program in disability, pain, depressive symptoms, and self-efficacy were found. In addition, higher levels of self-efficacy at admission and larger increases in self-efficacy over the course of the program predicted larger health changes (i.e., greater decreases in disability, pain, and depressive symptoms). Results were generally similar for health changes from discharge to 6-month followup. CONCLUSION: A routine multidisciplinary inpatient rehabilitation program after hip joint replacement can result in enhanced self-efficacy.
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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 | 0.002 | 0.009 |
| 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 | 0.001 |
| 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".