Acceptability and preliminary effectiveness of a single-arm 12-week digital behavioral health intervention in patients with knee osteoarthritis
Bibliographic record
Abstract
BACKGROUND: Digital health interventions may improve osteoarthritis (OA) management. This study evaluated the acceptability and preliminary effectiveness of a multimodal digital nutrition, exercise, and mindfulness intervention in adults with knee OA. METHODS: Adults with advanced knee OA and an orthopaedic referral were invited to self-enroll in a pragmatic 12-week single-arm intervention. OA-focused nutrition and exercise resources were delivered weekly by email, and secondary components accessed on-demand (web-platform, webinars, and nutrition consultation). Acceptability was assessed by qualitative interview data and completion rates. Preliminary effectiveness on clinical outcomes was assessed by change in health-related quality of life, well-being, mindfulness, self-efficacy, and interest in total knee arthroplasty (TKA) between baseline and 12-weeks. RESULTS: ). Acceptability was demonstrated by positive perceptions of tailored intervention resources. In study completers, health-related quality of life components of pain and physical functioning domains improved at 12-weeks [change in SF36 4.4 (95%CI 0.2-8.6), p = 0.016, and 6.7 (95%CI 2.7-10.7), p < 0.001, respectively]. Self-efficacy for managing daily activities improved [change in PROMIS T-score 4.4 (95%CI 2.8-6.0), p < 0.001]. CONCLUSION: A 12-week digital multimodal intervention for knee OA was acceptable to patients and shows preliminary effectiveness in improving self-efficacy, aspects of quality of life, and decreasing interest in TKA. Digital behavioral interventions for knee OA may be an acceptable approach to improve patient outcomes and OA self-management while potentially reducing utilization of costly health system resources.
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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 | 0.000 | 0.000 |
| 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 | 0.000 |
| 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".