Persons With Diabetes and General/Family Practitioner Perspectives Related to Therapeutic Inertia in Type 2 Diabetes Mellitus Using Qualitative Focus Groups and the Theoretical Domains Framework: Results From the MOTION Study
Bibliographic record
Abstract
OBJECTIVES: Therapeutic inertia in type 2 diabetes (T2DM) is the failure to receive timely treatment intensification as indicated according to T2DM treatment guidelines. Multifactorial causes of therapeutic inertia in T2DM have been documented at the level of persons with diabetes (PwD), health-care providers and health-care systems. METHODS: We developed a 3-part mixed-methods research program, called the Moving to Overcome Therapeutic Inertia Obstacles Now in T2DM (MOTION) study, to inform the development of strategies to address therapeutic inertia in T2DM. We present the results from focus groups with the following objectives: 1) understanding PwD and general practitioner/family practitioner (GPFP) determinants of behaviour related to treatment intensification using the Theoretical Domains Framework (TDF); and 2) identifying the sources of behaviours contributing to therapeutic inertia in T2DM, as proposed by the Behaviour Change Wheel (BCW). Two focus groups with PwD and 4 with GPFPs were conducted. Transcripts from the focus groups were coded independently by 2 investigators to identify themes, then mapped to TDF domains and linked using the BCW. RESULTS: For PwD, the most commonly coded TDF domains were intentions, goals, knowledge, beliefs about consequences and social influences. For GPFPs, the most common domains were intentions, environmental context and resources and social/professional role and identity. The BCW identified that PwD interventions should include reflective motivation, psychological capability and social opportunity; GPFP interventions should include physical opportunity, social opportunity and reflective motivation. CONCLUSIONS: Comprehensive strategies that target both PwD and GPFP barriers would encourage a more collaborative approach toward treatment intensification decisions and reducing therapeutic inertia.
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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 | 0.014 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".