Development of a self-directed learning resource on the prevention, identification, and management of postoperative delirium for nurses working in acute surgical settings
Bibliographic record
Abstract
Background: Postoperative delirium (POD) is a sudden decline in cognitive function that presents following surgical intervention and may result in confusion, inattention, and agitation. This syndrome is often under-recognized and under-treated in postoperative clinical settings. Contributing to this issue is the lack of formal education for nurses about POD. Purpose: To develop a self-directed learning resource focused on the prevention, identification, and management of POD for nurses working in acute surgical settings. Methods: 1) an integrative literature review, 2) an environmental scan of available resources from hospitals within Atlantic Canada and reputable websites, 3) consultation interviews with key stakeholders, and 4) the development of the self-directed learning resource. Results: Findings from the methods established the need for the learning resource. The literature revealed that POD is a substantial issue and there is a knowledge gap for nurses on this topic. The effectiveness of education programs for nurses, use of validated screening tools, and implementation of prevention and management protocols were also noted. The environmental scan resulted in several reputable online resources that are relevant to POD care. Consultation interviews reinforced the demand for the resource and highlighted the learning needs of the nursing staff. The self-directed learning resource was developed based on these findings. The six modules within the resource are: 1) Overview of POD, 2) Prevention of POD, 3) Early Identification of POD, 4) Management of POD, 5) Patient and Family Education, and 6) Self-Care and Stress Management. Within the modules there are case studies, reflection exercises, documentation tips, and videos about POD. Conclusion: The aim of the learning resource is to educate staff nurses working in postoperative settings so they can provide evidence-informed nursing care. The learning resource will ideally be made available within the organization’s learning management system.
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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 | 0.007 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".