Identifying Determinants of Intervention Sustainability in Cancer Survivorship Care
Bibliographic record
Abstract
Background: Substantial gains could be made in reducing the cancer burden if current scientific evidence was applied in practice. The World Health Organization estimates that, worldwide, one-third of cancer cases could be prevented and another one-third cured if evidence was consistently implemented and sustained in cancer care. However, moving evidence-based interventions into care has proven a significant challenge. Even when interventions are put into practice, they often fail to become integrated into the long-term routines of organizations. This poor sustainability means many patients do not benefit from the best care possible. There is little empirical data on the factors that influence the sustainability of interventions in clinical settings. Aim: To identify the determinants of, and explore the processes that facilitate, sustainability of interventions in cancer care survivorship. Sustainability was defined as the continued use of an intervention and its associated components and/or the continued achievement of the intended benefits after the initial funding or support period. Methods: We first conducted an environmental scan to identify interventions in cancer survivorship care implemented in Canada. This was followed by a literature review to ascertain the evidence base for each intervention and identify those meeting the US National Cancer Institute's criteria for evidence-based interventions. We then recruited key individuals relevant to the evidence-based interventions for semistructured in-depth interviews to explore issues related to their sustainability. Interview data are being analyzed through an inductive grounded theory approach using constant comparative analysis. Results: Twenty-seven individuals participated in the interviews. Preliminary findings reveal five factors that influenced whether, and the extent to which, interventions were sustained in cancer survivorship care. Participants emphasized (1) access to sufficient resources and funding is critical to sustaining interventions after the initial funding period. The ability of a team or organization to (2) evaluate a new intervention and demonstrate its quality and usefulness was often perceived as necessary to obtain continued funding as well as ongoing buy in and support from key stakeholders. In addition, the (3) extent to which the intervention can be adapted, (4) support of senior management, and (5) existence of an on-the-ground champion to continuously promote, adapt, lead, and spread the intervention were perceived as important factors that contribute to an intervention's sustained use. Conclusion: Research into determinants and processes of sustainability is critical to ensure we plan and act in ways that maximize the sustained use of interventions shown to benefit patients and our cancer systems. Issues related to evaluation, adaptability, and ongoing moral and material supports should be considered before, during, and after implementation efforts.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".