Dementia ECHO: Evaluation of a telementoring programme to increase dementia knowledge and skills in First Nations-led health services
Bibliographic record
Abstract
INTRODUCTION: High rates of dementia among Australian First Nations' peoples have resulted in an increased demand for dementia knowledge and skills among the primary health care professionals in these communities. The Dementia Extension for Community Healthcare Outcomes (ECHO) program aims to be a culturally safe way of increasing local health workforce capacity by facilitating dementia knowledge, skills and confidence among primary care professionals in First Nations community settings. Dementia ECHO is based on the international evidence-based telementoring programme, Project Extension for Community Healthcare Outcomes. Every Dementia ECHO session is delivered by videoconference and comprises a specialist-led presentation and a case discussion from a primary care health service participant. The aims of this study were to assess the uptake and reach of Dementia ECHO; examine the perceived importance of dementia care and dementia education among Aboriginal and Torres Strait Islander Community Controlled Health Service staff; and evaluate the potential impact of Dementia ECHO on health service staff pertaining to dementia knowledge, confidence to provide dementia care and professional isolation. METHOD: Dementia ECHO service activity data maintained by the programme providers was reviewed to determine uptake and reach. A pre-implementation survey examined Aboriginal and Torres Strait Islander Community Controlled Health Service staff perspectives on the importance of dementia education and the priority of a range of health issues. After each Dementia ECHO session, a brief online survey gathered quantitative and qualitative data regarding the potential impact of the session. RESULTS: = 10) were placed as the top priority. The brief post-session feedback provided 44 complete survey responses demonstrating: perceived improvement in dementia knowledge and skills (88.4%); increased confidence to provide dementia care (83%); and a reduction in professional isolation (88%). CONCLUSION: Dementia ECHO addresses a gap in dementia education that is much needed in health professionals with increasing numbers of First Nations people living with dementia. This current study shows that attending an evidence-based telementoring programme, such as Dementia ECHO, can increase dementia knowledge and confidence to care for someone living with dementia and their families.
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".