The Practical Approach to Lung Health in South Africa (PALSA) intervention: respiratory guideline implementation for nurse trainers
Bibliographic record
Abstract
AIM: This paper describes the design, facilitation and preliminary assessment of a 1-week cascade training programme for nurse trainers in preparation for implementation of the Practical Approach to Lung Health in South Africa (PALSA) intervention, tested within the context of a pragmatic cluster randomized controlled trial in the Free State province. PALSA combines evidence-based syndromic guidelines on the management of respiratory disease in adults with group educational outreach to nurse practitioners. BACKGROUND: Evidence-based strategies to facilitate the implementation of primary care guidelines in low- to middle-income countries are limited. In South Africa, where the burden of respiratory diseases is high and growing, documentation and evaluation of training programmes in chronic conditions for health professionals is limited. METHOD: The PALSA training design aimed for coherence between the content of the guidelines and the facilitation process that underpins adult learning. Content facilitation involved the use of key management principles (key messages) highlighted in nurse-centred guidelines manual and supplemented by illustrated material and reminders. Process facilitation entailed reflective and experiential learning, role-playing and non-judgemental feedback. DISCUSSION AND RESULTS: Preliminary feedback showed an increase in trainers' self-awareness and self-confidence. Process and content facilitators agreed that the integrated training approach was balanced. All participants found that the training was motivational, minimally prescriptive, highly nurse-centred and offered personal growth. CONCLUSION: In addition to tailored guideline recommendations, training programmes should consider individual learning styles and adult learning processes.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 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 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".