Exploring Attitudes and Experiences of People With Knee Osteoarthritis Toward a Self-Directed eHealth Intervention to Support Exercise: Qualitative Study
Bibliographic record
Abstract
BACKGROUND: Knee osteoarthritis (OA) is a highly prevalent and debilitating condition. Exercise is a recommended treatment because of its effectiveness at improving pain and function. However, exercise is underutilized in OA management. Difficulty accessing health care has been identified as a key barrier to exercise uptake. Innovative and scalable methods of delivering exercise treatments to people with knee OA are needed. We developed a self-directed eHealth intervention to enable and encourage exercise participation. The effectiveness of this intervention on pain and function in people with knee OA is being evaluated in a randomized clinical trial. OBJECTIVE: This study aimed to explore the attitudes and experiences of people with knee OA who accessed the self-directed eHealth intervention and the features perceived as useful to facilitate self-directed exercise. METHODS: This was a qualitative study embedded within a randomized controlled trial. Individual, semistructured phone interviews were conducted with 16 people with knee OA who had accessed a 24-week eHealth intervention (website and behavior change SMS program) designed to support exercise participation. Interviews were audiorecorded, transcribed verbatim, and thematically analyzed using an inductive approach. RESULTS: Five themes arose: (1) technology easy to use and follow (website ease of use, SMS ease of use), (2) facilitators to exercise participation (credible OA and exercise information, website features, prescribed exercises simple to do unsupervised, freedom to adapt the exercise to suit needs, influence of other health care experiences), (3) sense of support and accountability (SMS good reminder and prompt, accountable, SMS tone and automation could trigger negative emotions [eg, guilt or shame], inability to contact someone when needed), (4) positive outcomes (knee symptom improvements, confidence to self-manage, encouraged active living), (5) suggestions for real-world application (provided by a health professional preferred, should be provided at subsidized or low out-of-pocket cost). CONCLUSIONS: People with knee OA had mostly positive experiences with and attitudes towards the use of an eHealth intervention that supported exercise participation independent of a health professional. A human connection associated with the eHealth intervention appeared important.
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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".