Developing the Driving and Dementia Roadmap: a knowledge-to-action process
Bibliographic record
Abstract
OBJECTIVES: Despite three decades of research, gaps remain in meeting the needs of people with dementia and their family/friend carers as they navigate the often-tumultuous process of driving cessation. This paper describes the process of using a knowledge-to-action (KTA) approach to develop an educational web-based resource (i.e. toolkit), called the Driving and Dementia Roadmap (DDR), aimed at addressing some of these gaps. DESIGN: Aligned with the KTA framework, knowledge creation and action cycle activities informed the development of the DDR. These activities included systematic reviews; meta-synthesis of qualitative studies; interviews and focus groups with key stakeholders; development of a Driving and Dementia Intervention Framework (DD-IF); and a review and curation of publicly available resources and tools. An Advisory Group comprised of people with dementia and family carers provided ongoing feedback on the DDR's content and design. RESULTS: The DDR is a multi-component online toolkit that contains separate portals for current and former drivers with dementia and their family/friend carers. Based on the DD-IF, various topics of driving cessation are presented to accommodate users' diverse stages and needs in their experiences of decision-making and transitioning to non-driving. CONCLUSION: Guided by the KTA framework that involved a systematic and iterative process of knowledge creation and translation, the resulting person-centered, individualized and flexible DDR can bring much-needed support to help people with dementia and their families maintain their mobility, community access, and social and emotional wellbeing during and post-driving cessation.
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 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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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 | 0.001 |
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 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".