The Hip Instructional Prehabilitation Program for Enhanced Recovery (HIPPER) as an eHealth Approach to Presurgical Hip Replacement Education: Protocol for a Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: Osteoarthritis (OA), leading to hip replacement (THR), is a primary contributor to global mobility impairment. In 2018, more than 59,000 THR surgeries were performed in Canada. Health promotion education, such as prehabilitation, is vital to optimizing surgical outcomes. OBJECTIVE: This study aims to evaluate the feasibility of the Hip Instructional Prehabilitation Program for Enhanced Recovery (HIPPER), an eHealth approach to prehabilitation education. METHODS: A single-blind (assessor-blind), 2-arm, feasibility randomized controlled trial will be conducted. We will recruit 40 (HIPPER group, n=20; control group, n=20) older adults with hip OA and on a waitlist for a THR. The HIPPER intervention consists of 12 online, interactive modules. The control group will receive the current standard practice consisting of 2 online educational sessions lasting 2 hours each (webinars). Feasibility outcomes (eg, recruitment and retention rates) will be evaluated. RESULTS: Recruitment started in March 2021. As of April 20, 2021, 18 participants were recruited. All 18 completed T1 measures. Only 1 participant has been scheduled to have a surgery and therefore has been scheduled to complete T2 measures. The remainder of the participants are waiting to be notified of their surgery date. This project was funded by a Canadian Institutes of Health Research Project Grant. Our institute's research ethics board approved this study in November 2016. CONCLUSIONS: Results will lead to refinement of the HIPPER protocol in order to evaluate a standardized and geographically accessible prehabilitation program. TRIAL REGISTRATION: ClinicalTrials.gov NCT02969512; https://clinicaltrials.gov/ct2/show/NCT02969512. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/29322.
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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 | 0.036 | 0.032 |
| Meta-epidemiology (narrow) | 0.006 | 0.004 |
| Meta-epidemiology (broad) | 0.014 | 0.006 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.007 | 0.009 |
| Insufficient payload (model declined to judge) | 0.087 | 0.012 |
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".