MétaCan
Menu
Back to cohort
Record W4399984448 · doi:10.5430/jnep.v14n10p34

Investigating dyads in nursing education

2024· article· en· W4399984448 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueJournal of Nursing Education and Practice · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicQualitative Research Methods and Applications
Canadian institutionsOttawa HospitalUniversity of Ottawa
Fundersnot available
KeywordsNursingPsychologyMedicine

Abstract

fetched live from OpenAlex

Background: Nursing education faces challenges due to a shortage of nurse educators and nurses in the workforce, prompting programs to expedite training, impacting student and nurse well-being. While standards are high, studies reveal many students feel unprepared. Self-confidence is crucial, affecting clinical performance, as is effective communication, which is pivotal for safe patient care. Dyadic education, involving pairs, is gaining traction for its potential to enhance teamwork and reduce stress.Methods: This study explored dyadic teaching's impact on nursing students' self-confidence, communication, and clinical skills in the context of nursing practicums. A convenience sample of nineteen undergraduate nursing students participated in a survey assessing their experiences in dyads.Results/Conclusions: Findings suggest dyadic teaching fosters greater confidence, reduces stress, and enhances communication. However, limitations, including small sample size and retrospective data collection, underscore the need for further research. Introducing dyadic approaches in nursing curriculums holds promise for optimizing student learning and patient care outcomes.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.775
Threshold uncertainty score0.819

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.332
GPT teacher head0.676
Teacher spread0.344 · 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