Evaluation of a co-produced delirium awareness programme for undergraduate nursing students in Northern Ireland: a pre-test/post-test study
Bibliographic record
Abstract
Abstract Background Delirium is recognised internationally as a common disorder that causes acute deterioration in a person’s cognitive abilities. Healthcare professionals play a key role in the early identification and management of delirium and effective education can support timely recognition and treatment. There is currently a lack of research exploring the delirium education provided to undergraduate nursing students. The aim of this study was to evaluate the effectiveness of a co-produced delirium awareness programme on undergraduate nursing students in Northern Ireland. Methods The intervention was a 2-h delirium workshop, delivered in April 2019, to a convenience sample of year one undergraduate nursing students ( n = 206) completing a BSc Honours Nursing degree programme in a Northern Ireland University. The workshop focused on four core elements: defining delirium, reflecting on practice, recognition of delirium and management of delirium. Participants completed a 35-item true-false Delirium Knowledge Questionnaire (DKQ) at baseline and post intervention using Socrative, a cloud-based student response system. In addition, students also completed a short questionnaire at baseline and post-workshop, designed by the authors, to ascertain perceived confidence about caring for people with delirium. Data were analysed using paired t-tests and descriptive statistics. Results In the DKQ, Scores were normally distributed around the mean at baseline (71.89%) and post intervention (81.89%). Students improved across all three core areas in the post-test questionnaire, demonstrating improvements in knowledge about symptoms of delirium (7.32% increase), causes and risk factors of delirium (17.91% increase) and management of delirium (5.72% increase). In relation to perceived confidence, students reported a 60.20% increase in confidence related to recognition of delirium, a 49.51% increase in relation to delirium management and a 45.04% increase their ability to communicate about delirium. Both questionnaires were statistically significant ( P < 0.01). Conclusions A 2-h workshop on delirium improved first year student nurse knowledge about delirium. Nursing students expressed that this approach to delirium education enabled collective thinking about how knowledge could be transferred into individual practises. Students also stated that learning incorporating the voice of the person who has experienced delirium, was an effective and powerful way to deliver education.
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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 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".