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Record W3020356820 · doi:10.1186/s12912-020-00427-9

Evaluation of a co-produced delirium awareness programme for undergraduate nursing students in Northern Ireland: a pre-test/post-test study

2020· article· en· W3020356820 on OpenAlexfundno aff
Gary Mitchell, Clare McVeigh, Susan Carlisle, Christine Brown Wilson

Bibliographic record

VenueBMC Nursing · 2020
Typearticle
Languageen
FieldMedicine
TopicIntensive Care Unit Cognitive Disorders
Canadian institutionsnot available
FundersQueen's UniversityQueen's University Belfast
KeywordsDeliriumMedicineIntervention (counseling)Test (biology)NursingNursing managementDescriptive statisticsNursing researchPsychologyPsychiatry

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.011
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.083
GPT teacher head0.408
Teacher spread0.325 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations28
Published2020
Admission routes1
Has abstractyes

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