Fidelity assessment of nurse-led non-pharmacological package of care for knee pain in the package development phase of a feasibility randomised controlled trial based in secondary care: a mixed methods study
Bibliographic record
Abstract
OBJECTIVES: To evaluate fidelity of delivery of a nurse-led non-pharmacological complex intervention for knee pain. SETTING: Secondary care. Single-centre study. STUDY DESIGN: Mixed methods study. PARTICIPANTS: Eighteen adults with chronic knee pain. INCLUSION CRITERIA: Age >40 years, knee pain present for longer than 3 months, knee pain for most days of the previous month, at least moderate pain in two of the five domains of Western Ontario and McMaster Universities Osteoarthritis Index pain scale. INTERVENTIONS: Nurse-led non-pharmacological intervention comprising assessment, education, exercise, use of hot/cold treatments, footwear modification, walking aids and weight-loss advice (if required). OUTCOMES: Primary: fidelity of delivery of intervention, secondary: nurses' experience of delivering intervention. METHODS: Each intervention session with every participant was video recorded and formed part of fidelity assessment. Fidelity checklists were completed by the research nurse after each session and by an independent researcher, after viewing the video-recordings blinded to nurse ratings. Fidelity scores (%), percentage agreement and 95% Confidence Intervals (CI) were calculated. Two semi-structured interviews were conducted with the research nurse. RESULTS: Fourteen participants completed all visits. 62 treatment sessions took place. Nurse self-report and assessor video rating scores for all 62 treatment sessions were included in fidelity assessment. Overall fidelity was higher on nurse self-report (97.7%) than on objective video-rating (84.2%). Percentage agreement between nurse self-report and video-rating was 73.3% (95% CI 71.3 to 75.3). Fidelity was lowest for advice on footwear and walking aids. The nurse reported difficulty advising on thermal treatments, footwear and walking aids, and did not feel confident negotiating achievable and realistic goals with participants. CONCLUSIONS: A trained research nurse can deliver most components of a non-pharmacological intervention for knee pain to a high degree of fidelity. Future research should assess intervention fidelity in a routine clinical setting, and examine its clinical and cost-effectiveness. TRIAL REGISTRATION NUMBER: NCT03670706.
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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 | 0.068 | 0.081 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".