Piloting a patient navigation programme for individuals living with dementia, their care partners and members of the care team: protocol for a mixed-methods evaluation
Bibliographic record
Abstract
INTRODUCTION: Internationally, the number of individuals living with dementia continues to rise. Individuals living with dementia, their care partners and their care team face many barriers and challenges to accessing dementia care resources and supports. One solution to address the multifaceted care needs of this population is patient navigation (PN). METHODS AND ANALYSIS: This protocol describes the implementation and evaluation plan for a pilot PN programme in New Brunswick (NB) Canada for individuals living with dementia, their care partners and care providers. This project will include two components: (1) an in-person PN programme called Navigating Dementia NB/ Naviguer la démence NB and (2) two virtual peer-to-peer navigational support groups. The PN programme will be codesigned with stakeholders including researchers, patient partners, clinicians and health system managers. Patient navigators will be housed at six primary care sites across the province and the services will be offered in English and French. We will conduct a mixed-methods evaluation to explore the characteristics and experiences of participants who enrol in the PN programme and the navigational support groups, as well as the facilitators and barriers to implementation. Data collection will include navigation charts, Facebook analytics, as well as postintervention surveys, semistructured interviews and focus groups. All participants will provide written informed consent to take part in the intervention and have their data collected for research and evaluation purposes. Demographic data will be analysed using frequency and central tendency measures, while qualitative data from interviews and focus groups will undergo thematic analysis. Content analysis will be used to analyse posts published to the Facebook groups. The evaluation will assess the programme's effectiveness in the short and medium terms, evaluating its ability to achieve the intended outcomes. ETHICS AND DISSEMINATION: This study has been approved by the research ethics boards at the University of New Brunswick, Université de Moncton, Horizon Health Network and Vitalité Health Network. Knowledge translation activities (eg, presentations at local, national and international conferences; publications for open-access journals; reports and lay summaries) will be undertaken to share the findings from this pilot project with diverse stakeholders, such as decision-makers, health system managers, clinicians and the general public.
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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 | 0.107 | 0.063 |
| Meta-epidemiology (narrow) | 0.005 | 0.004 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.006 | 0.005 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.046 | 0.008 |
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".