Design, implementation, and evaluation of a knowledge translation intervention to increase organ donation after cardiocirculatory death in Canada: a study protocol
Bibliographic record
Abstract
BACKGROUND: A shortage of transplantable organs is a global problem. There are two types of organ donation: living and deceased. Deceased organ donation can occur following neurological determination of death (NDD) or cardiocirculatory death. Donation after cardiocirculatory death (DCD) accounts for the largest increments in deceased organ donation worldwide. Variations in the use of DCD exist, however, within Canada and worldwide. Reasons for these discrepancies are largely unknown. The purpose of this study is to develop, implement, and evaluate a theory-based knowledge translation intervention to provide practical guidance about how to increase the numbers of DCD organ donors without reducing the numbers of standard NDD donors. METHODS: We will use a mixed method three-step approach. In step one, we will conduct semi-structured interviews, informed by the Theoretical Domains Framework, to identify and describe stakeholders' beliefs and attitudes about DCD and their perceptions of the multi-level factors that influence DCD. We will identify: determinants of the evidence-practice gap; specific behavioural changes and/or process changes needed to increase DCD; specific group(s) of clinicians or organizations (e.g., provincial donor organizations) in need of behaviour change; and specific targets for interventions. In step two, using the principles of intervention mapping, we will develop a theory-based knowledge translation intervention that encompasses behavior change techniques to overcome the identified barriers and enhance the enablers to DCD. In step three, we will roll out the intervention in hospitals across the 10 Canadian provinces and evaluate its effectiveness using a multiple interrupted time series design. DISCUSSION: We will adopt a behavioural approach to define and test novel, theory-based, and ethically-acceptable knowledge translation strategies to increase the numbers of available DCD organ donors in Canada. If successful, this study will ultimately lead to more transplantations, reducing patient morbidity and mortality at a population-level.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".