Programme theory development and formative evaluation of a provincial knowledge translation unit
Bibliographic record
Abstract
BACKGROUND: Research shows a significant gap between healthcare research and evidence-based healthcare policy and practice. Knowledge translation (KT) has an important role in addressing this gap by bolstering evidence-informed healthcare. Canada's Strategy for Patient-Oriented Research (SPOR) is a nationally mandated and supported initiative developed to respond to the gap between research and practice. One aspect of SPOR is the provincial/territorial SUpport for People and Patient-Oriented Research and Trials (SUPPORT) Units, intended to assist local health researchers and systems to reach the goal of improving the quality and quantity of patient-oriented research in Canada. This article presents the programme theory development and a formative evaluation of the KT Platform in Alberta's SPOR SUPPORT Unit. METHODS: We used a mixed-methods approach to develop the KT Platform's programme theory and subsequently conducted the formative evaluation. An extensive needs assessment, comprised of 59 qualitative interviews with researchers and health systems employees in Canada with an interest in KT, served as the basis for our programme theory design. Three years after launching the KT Platform, we hired an evaluation consultant to conduct a formative evaluation of the Platform's programme theory and operations. The evaluation was performed by conducting nine interviews with KT Platform service users (n = 6) and KT experts acting in advisory capacities to the KT Platform (n = 3). RESULTS: The KT Platform developed a '4C Model' as a summary of the Platform's programme theory. This model is designed to meet local needs for capacity-building, a community of practice, consultation services, and contributions to KT science. This suite of services was found to help the local health system implement health evidence with measurable positive health outcomes. However, the community remains hesitant about their capacity as individuals to design and perform important KT activities independently. CONCLUSIONS: With the mandate and support provided by SPOR, the KT Platform was able to design a strong programme theory based on evidence from an extensive needs assessment of the local community. The resulting 4C Model has provided a framework for KT work to assist in improving local health outcomes and can be considered by others designing KT programmes as a useful model to follow. Ongoing monitoring and assessment are required to continue to identify and respond to local needs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.142 | 0.158 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.005 | 0.010 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".