Patients’ perspectives and experiences on physiotherapy care for knee osteoarthritis: A qualitative study
Bibliographic record
Abstract
ObjectiveTo explore the perspectives and experiences of patients with knee osteoarthritis regarding physiotherapy care management in Hong Kong.DesignQualitative study using semi-structured, individual interviews.SettingCommunity.ParticipantsPatients age 50 years or older with knee osteoarthritis, purposively recruited.InterventionFace-to-face semi-structured interviews were conducted with patients who had completed a physiotherapy rehabilitation programme in the past six months.Main MeasuresA 21-question interview guide encouraged participants to discuss their physiotherapy management, experiences, and recommended interventions, covering all non-pharmacological treatments outlined in local clinical guidelines. Questions also explored factors influencing adherence to care during and after physiotherapy. Interviews were audio-recorded, transcribed verbatim, and analysed thematically.ResultsFourteen patients participated. Five key themes emerged: (a) navigating pain and management strategies; (b) adapting daily life and the impact of knee osteoarthritis on activities; (c) complexities of treatment and the need for personalised care; (d) the role of exercise and mobility; and (e) barriers to access and resources. While patients reported receiving various physiotherapy interventions, gaps were noted in aquatic therapy, neuromuscular training, weight management, and assistive devices. Barriers included limited access, financial constraints, and lack of home exercise equipment. Although participants valued physical activity, maintaining an exercise routine was challenging.ConclusionsA comprehensive, patient-centred approach is essential for effective physiotherapy care for knee osteoarthritis in Hong Kong. Addressing practical barriers and integrating patient feedback can enhance the accessibility and impact of evidence-based interventions.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".