‘It’s a Dance Between Managing Both’: a qualitative study exploring perspectives of persons with knee osteoarthritis and type 2 diabetes mellitus on the impact of osteoarthritis on diabetes management and daily life
Bibliographic record
Abstract
OBJECTIVES: Type 2 diabetes (T2DM) and knee osteoarthritis (OA) commonly co-occur and epidemiologic studies suggest concomitant symptomatic knee OA increases the risk of T2DM complications. We sought to explore the experiences and perspectives of individuals' living with both symptomatic knee OA and T2DM, with a focus on the impact of OA on T2DM management and daily life. DESIGN: We conducted qualitative semistructured telephone interviews with persons living with T2DM and knee OA. We inductively coded and analysed interview transcripts, informed by interpretative description. SETTING: We recruited participants from a community arthritis self-management programme and an academic hospital's family medicine clinic in Ontario, Canada. PARTICIPANTS: We included 18 participants who had a physician diagnosis of both T2DM and knee OA, with variation age, gender, and duration of T2DM and knee OA. RESULTS: Participants with T2DM described how concomitant painful and disabling knee OA made it difficult to engage in physical activity, negatively impacting blood glucose control. Joint pain itself, associated sleep disturbance and emotional distress were also seen to affect blood glucose control. Beyond diabetes management, the impact of OA-related pain and functional limitations on nearly all aspects of daily life led participants to view their OA as important. Despite this, many participants described that their health professionals paid little attention to their OA, which left them to self-manage. Balancing both conditions also required navigating a medical system that provided piecemeal care. CONCLUSIONS: Individuals with T2DM view symptomatic knee OA as an important barrier to both T2DM management and overall well-being, yet are frequently met with insufficient support from health professionals. Greater recognition and management of knee OA in persons with T2DM could help improve patient-centred care and potentially disease outcomes.
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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 | 0.016 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.014 | 0.014 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.003 | 0.006 |
| 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".