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Record W3118942399 · doi:10.1186/s12912-021-00543-0

Evaluation of a delirium awareness podcast for undergraduate nursing students in Northern Ireland: a pre−/post-test study

2021· article· en· W3118942399 on OpenAlexfundno aff
Gary Mitchell, Jessica Scott, Gillian Carter, Christine Brown Wilson

Bibliographic record

VenueBMC Nursing · 2021
Typearticle
Languageen
FieldMedicine
TopicIntensive Care Unit Cognitive Disorders
Canadian institutionsnot available
FundersQueen's UniversityQueen's University Belfast
KeywordsDeliriumMedicineTest (biology)Nursing researchNursingDescriptive statisticsIntervention (counseling)PsychologyPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: Delirium is a common disorder affecting several people in primary, secondary, and tertiary settings. The condition is frequently under-diagnosed leading to long-lasting physical and cognitive impairment or premature death. Despite this, there has been limited research on the impact of innovative approaches to delirium education amongst undergraduate nursing students. The aim of this study was to evaluate the effect of a delirium awareness podcast on undergraduate nursing student knowledge and confidence related to the condition in Northern Ireland. METHODS: The intervention was a 60-min delirium awareness podcast, available throughout May 2020, to a convenience sample of year one undergraduate nursing students (n = 320) completing a BSc Honours Nursing degree programme in a Northern Ireland University. The podcast focused on how nursing students could effectively recognise, manage, and prevent delirium. Participants had a period of 4 weeks to listen to the podcast and complete the pre and post questionnaires. The questionnaires were comprised of a 35-item true-false Delirium Knowledge Questionnaire (DKQ), a 3-item questionnaire about professional confidence and a 7-item questionnaire evaluating the use of podcasting as an approach to promote knowledge and confidence about delirium. Data were analysed using paired t-tests and descriptive statistics. RESULTS: Students improved across all three core areas in the post-test questionnaire, demonstrating improvements in knowledge about symptoms of delirium (7.78% increase), causes and risk factors of delirium (13.34% increase) and management of delirium (12.81% increase). In relation to perceived confidence, students reported a 46.50% increase in confidence related to recognition of delirium, a 48.32% increase in relation to delirium management and a 50.71% increase their ability to communicate about delirium. Both questionnaires were statistically significant (P < 0.001). The final questionnaire illustrated that nursing students positively evaluated the use of podcast for promoting their knowledge and confidence about delirium and 96.32% of nursing students believed that the podcast met their learning needs about delirium. CONCLUSIONS: A 60-min podcast on delirium improved first year student nurse knowledge about delirium. Nursing students also expressed that this approach to delirium education was effective in their learning about the condition.

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)0.010
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: Non-randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.016
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 head0.051
GPT teacher head0.399
Teacher spread0.348 · 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 designNon-randomized trial
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".

Quick stats

Citations35
Published2021
Admission routes1
Has abstractyes

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