The patient’s perspective on rehabilitation with wireless accelerometers, activity tracking and motivational feedback following knee replacement: A qualitative study prior to a randomised controlled trial (KneeActivity)
Bibliographic record
Abstract
BACKGROUND: As healthcare systems evolve, individuals are expected to be more involved in managing their health and rehabilitation. A wireless medical accelerometer (SENS motion®) has been developed to collect objective data on physical activity. The number of patients requiring knee replacement is rising, but the motivational effect of medical accelerometers in the rehabilitation after knee replacement remains unexplored. This study aims to employ a user-driven approach to tailor the SENS motion® technology for patients undergoing knee replacement prior to testing the refined technology in a randomised controlled trial. METHODS: The study used a Participatory Design research methodology, emphasising collaboration and user involvement. It was carried out in three sessions, each aimed at refining the SENS motion® system toward the needs of the patient group in focus. The first session involved six healthcare professionals who provided written feed-back. The second and third sessions included testing and subsequent interviews of patients (n = 10). After each session, conducted in iterative processes (plan, act, observe, reflect), SENS motion® system revisions were implemented according to the patient's wishes. The data collected were then analysed using qualitative content analysis. RESULTS: Prior to patient testing, healthcare professionals identified functional and technical errors that required modifications. Patient interviews revealed that (1) there were positive attitudes towards the SENS motion® system, (2) patients were motivated by daily step counts and geographical locations, especially when they were familiar with landmarks, and (3) active involvement of family members was found to be feasible, which contributed to a sense of solidarity during the rehabilitation process. CONCLUSION: This study applied a user-driven approach to customise health technology for postoperative rehabilitation in knee replacement patients. Initially, the technology had both technical and functional problems, but system revisions based on patient feedback improved its acceptance. The refined technology is undergoing testing in a randomised design.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".