Final evaluation of the “Making Health Choices” advance care planning in aged care project
Bibliographic record
Abstract
Published literature suggests that advance care planning (ACP) activity in aged-care homes is inconsistent and often of poor quality. There are few published reports of the effectiveness of formal training and implementation of ACP in aged-care homes. The Respecting Patient Choices Program piloted a training and implementation model in 19 aged-care homes in Victoria, Australia in 2010-11. The model required selected aged-care home nurses and management staff to attend 3 workshops over a 6-month period and complete pre and post-workshop tasks. The workshops included didactic and experiential teaching, discussions and role plays. Model evaluation included ACP documentation audits, in addition to pre and post implementation surveys to examine aged-care home ACP policies and practices, and staff knowledge, attitudes and behaviours around ACP. Key results were as follows: Measurement Pre-training (%) Post-training (%) P value % of staff reporting the existence of written policies on ACP in aged-care homes. 53 100 0.008 % of aged-care homes. which discuss medical treatment options with resident/family 42 100 0.016 % of aged-care homes which discuss “things that matter most about life and living” with resident 8 92 0.009 % of aged-care homes reporting that ACP information is used effectively within the facility. 33 100 0.013 % of staff reporting that ACP is carried out “well/very well” within their aged-care home. 25 100 0.009 Mean staff score on ACP knowledge test [SD] 4.4 [1.1] 5.7 [0.9] 0.001 The available data suggests that the RPC model of ACP in aged-care homes succeeded in training staff and implementing ACP.
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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) | 0.001 | 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 | 0.000 |
| 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".