Readiness for scale up following effectiveness-implementation trial: results of scalability assessment of the Community Partnership Program for diabetes self-management for older adults with multiple chronic conditions
Bibliographic record
Abstract
BACKGROUND: Implementation research should assess the feasibility of scale up to bridge the evidence-practice gap for integrated care programs in the prevention and management of chronic conditions. Scalability assessment is the first critical step of scale up to determine the potential suitability of a promising health program to be adopted into routine practice and the fit of the program within local contexts. The Community Partnership Program (CPP), an integrated care intervention for older adults with diabetes and multiple chronic conditions, was designed at the outset with scale up in mind, and evaluated in an implementation-effectiveness randomized controlled trial across three Canadian provinces. The final phase of this program of research was to assess scalability and determine the critical factors and next steps for the development of a scale up plan. METHODS: Multiple methods were used to assess the scalability of the CPP including collection and analysis of publicly available documents, synthesis of qualitative and quantitative evidence from studies of the CPP, semi-structured interviews with key informants, feedback and recommendations arising from working group meetings and knowledge exchange workshops to discuss and rate the scalability of the program. Data collection and analysis was informed by the Intervention Scalability Assessment Tool (ISAT); developed to support practitioners and policy makers in conducting systematic assessments of the suitability of health interventions for population scale-up in high-income countries. RESULTS: Overall, the CPP received high scalability ratings from participants. A phased, horizontal implementation and scale up process was recommended, facilitating local adaptations, on-going program evaluation, and accumulation of evidence. Challenges to scale up were identified, including the need for further evidence of program effectiveness in other diverse settings and populations, and designated funding and adequate health human resources. CONCLUSIONS: Participants agreed the CPP meets the needs of many older adults with diabetes and multiple chronic conditions; however, they suggested further tailoring of the program to support different ethnocultural groups and targeting the CPP to older adults with higher needs. The scalability assessment process was a practical method to generate concrete strategies to facilitate the uptake of the CPP into practice. TRIAL REGISTRATION: Clinical Trials.gov Identifier NCT03664583. Registration date: September 10, 2018.
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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 | 0.070 | 0.107 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".