Process evaluation of team-based care in people aged >65 years with type 2 diabetes mellitus
Bibliographic record
Abstract
OBJECTIVE: The prevalence of type 2 diabetes mellitus (T2DM) is increasing globally and there is critical need develop interventions to improve health outcomes among older people. The Group Appointments in Primary Care (GAP) study was a randomised controlled trial designed to test the efficacy of a group and team-based medical visit programme to lower haemoglobin A1c among patients with T2DM. We aimed to understand the barriers and facilitators to implement the GAP intervention within a primary care setting, with an emphasis on patient experience. RESEARCH DESIGN AND METHODS: This was a qualitative exploratory study. Data were gathered from semistructured interviews conducted with the first cohort of GAP study participants (n=15) at baseline and intervention completion. GAP participants were aged >65, diagnosed with T2DM and from one primary care clinic. The interview questions identified the patient perspectives and factors relating to their attendance at seven group medical visits that were part of the intervention programme. Data were analysed using framework analysis. RESULTS: We identified four themes that captured participants' experiences: (1) Education: learning with professionals, learning with one another; (2) Social Support: common interests, common problems; (3) Setting: ease of location, ease of conversation and (4) Impact: expectations met, empowerment gained. The GAP intervention increased participants' self-reported diabetes literacy and self-management skills. CONCLUSIONS: We learnt that: accessible community centres, not primary care offices, were the ideal location for GAP; the consistent leadership of the primary care physician was valued by participants; and, the content related to exercise and healthy diet were viewed as impactful. Also, learning was achieved through content delivered by clinical experts, and by T2DM experts with lived experience-the GAP peers. Our findings highlight the important role of group learning. TRIAL REGISTRATION NUMBER: NCT02002143.
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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 | 0.067 | 0.093 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| 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".