Developing a Complex Intervention to Improve Knee Osteoarthritis Care in Persons with Type 2 Diabetes
Bibliographic record
Abstract
Knee osteoarthritis is a leading cause of disability, frequently co-occurs in people with type 2 diabetes, and the presence of knee osteoarthritis-related chronic joint pain and functional impairment can challenge optimal type 2 diabetes management. It is thus important to effectively identify and treat knee osteoarthritis in these individuals to improve type 2 diabetes outcomes and quality of life, in addition to osteoarthritis outcomes. Through four inter-related projects and guided by the Medical Research Council framework, this thesis describes the development of a complex intervention to improve the diagnosis and evidence-based treatment of knee osteoarthritis in people with type 2 diabetes. It involved a partnership with Arthritis Society Canada for intervention delivery. The first three projects used qualitative methods to understand determinants of behaviour in stakeholder groups using the Theoretical Domains Framework. The first project identified barriers and enablers to seeking and engaging in osteoarthritis care in people with type 2 diabetes. The second project identified barriers and enablers of diabetes health professionals’ assessment and treatment of knee osteoarthritis in their patients. The third project identified barriers and enablers of arthritis therapists from Arthritis Society Canada considering type 2 diabetes when formulating an osteoarthritis management plan. The fourth project comprehensively described the multi-step process of complex intervention development that combined theories of behaviour change, stakeholder involvement, and existing evidence. Relevant domains identified from stakeholder interviews were mapped to behavioural change techniques to identify potential intervention components. Stakeholder meetings ascertained acceptability and feasibility of proposed intervention components, and a program theory was constructed to inform the implementation of the intervention and its evaluation. The intervention components, incorporating a range of behavioural change techniques at the patient, health professional, and arthritis therapist level, intend to identify persons with knee osteoarthritis within type 2 diabetes care and refer them to Arthritis Society Canada for delivery of evidence-based longitudinal knee osteoarthritis management. Diverse stakeholder input throughout the development allowed co-design of an intervention that appears feasible and acceptable to target users. This thesis lays the foundation for subsequent feasibility testing and evaluation, and ultimately seeks to inform improved care and outcomes for individuals with type 2 diabetes and knee osteoarthritis.
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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 | 0.008 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".