“It’s a Chronic, Vicious Cycle”: Diabetes Health-care Professionals’ Perceptions of the Impact of Knee Osteoarthritis on Type 2 Diabetes Management
Bibliographic record
Abstract
OBJECTIVES: Type 2 diabetes (T2D) and knee osteoarthritis (OA) frequently co-occur, and concomitant knee OA increases risk for diabetes complications. Despite this, OA is frequently undertreated. Diabetes health-care professionals' (HPs') perceptions of the impact of knee OA in people with T2D may impact how it is addressed in clinical practice. We aimed to understand how diabetes HPs perceive the impact of knee OA on diabetes management and outcomes. METHODS: In this qualitative study we performed a secondary analysis of semistructured interviews with 18 diabetes HPs (primary care providers, endocrinologists, and diabetes educators) in Ontario, Canada. Transcripts were inductively coded and thematically analyzed. RESULTS: We developed 3 themes: 1) Patients commonly raise OA-related concerns during diabetes appointments; 2) Impact of OA on diabetes management; and 3) Conscious disconnect between perceived patient and HP priorities. Diabetes HPs recognized that knee OA commonly co-occurred in their patients. Most HPs perceived that OA has deleterious effects on diabetes management through physical inactivity, as well as other mechanisms. Despite observing OA's impact on their patients, most participants did not address OA due to the focussed structure of diabetes appointments, "single-problem" appointments, and culture of siloed care. CONCLUSIONS: Diabetes HPs recognized the high prevalence of knee OA in their patients and its deleterious effects on diabetes management, although OA management was usually not prioritized. This highlights a missed opportunity in optimizing care for people with T2D. Implementing strategies to promote OA care during diabetes visits may improve disease outcomes for both conditions.
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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 | 0.012 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 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".