Adopting a lay navigator training programme in primary care
Bibliographic record
Abstract
Introduction: There is growing interest in the role and use of patient navigators within the health care system. Currently, qualifications and training expectations documented in the literature vary tremendously depending on context and patient population. This paper details the theoretical and pedagogical principles used to develop, implement and evaluate a training programme for lay patient navigators working in a primary care setting. Methods: The planning process involved (a) conducting an educational needs assessment, (b) identifying the theory underpinning the curriculum, (c) developing learning objectives and teaching strategies, (d) formulating evaluation methods, (e) implementing the programme and (f) refining the curriculum based on evaluation feedback and lessons learned. The training programme was first implemented in May 2017 and has evolved over the past 3 years based on our observations and feedback from the programme participants. Results: The training programme involves a total of 25 hours of online and face-to-face education sessions, and ongoing community mentorship from experienced navigators. All training components are rooted in theoretical principles and proven pedagogical approaches. The knowledge, skills and abilities acquired are also tied to core competencies of the role of lay patient navigator. Conclusion: The development of this lay navigator training programme was carefully designed with evidence-based competencies and practical realities to ensure rigour in preparing and supporting navigators’ work in primary care settings.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".