Evaluating the impact of a national geriatric mental health ECHO educational program on healthcare providers’ practice
Bibliographic record
Abstract
Project Extension for Community Healthcare Outcomes (ECHO) enables healthcare providers to share knowledge and best practices via telementoring. The ECHO model builds provider capacity and improves care for patients with a variety of health conditions. This study describes a Canada-wide National ECHO pilot project in the area of geriatric mental health and reports on the program's impact on providers' care practices. A mixed-methods approach was used to analyze surveys completed by participating healthcare providers. Program evaluation measured satisfaction, achievement of learning objectives, awareness of issues related to geriatric mental health, and comfort and self-efficacy working with older adults. The program led to a statistically significant increase in participants' awareness of issues related to support for older adults with mental illness and comfort and self-efficacy in managing these patients in their own practice. The National ECHO pilot project was successful in building healthcare providers' capacity to care for older adults with mental health issues and positively impacting their practice. These findings support using the ECHO model to provide ongoing geriatric mental health education for clinicians from across Canada and beyond.
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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 | 0.012 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".