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Record W4399854081 · doi:10.3928/01484834-20240404-01

Evaluating the Effectiveness of Empathy-Based Education in Undergraduate Nursing: A Scoping Review

2024· review· en· W4399854081 on OpenAlexaff
Eva Peisachovich, Elizabeth Viernes Sombilon, Naida L. Graham, Nureen Ladha, Celina Da Silva

Bibliographic record

VenueJournal of Nursing Education · 2024
Typereview
Languageen
FieldMedicine
TopicEmpathy and Medical Education
Canadian institutionsYork University
Fundersnot available
KeywordsEmpathyNursingPsychologyNurse educationMedical educationMEDLINEMedicinePolitical scienceSocial psychology

Abstract

fetched live from OpenAlex

This article has been amended to include factual corrections. An error was identified subsequent to its original publication. This error was acknowledged on page 6, volume 64, issue 1. The online article and its erratum are considered the version of record. Background: Empathy is an essential trait in nursing practice that improves the quality of patient care. Nursing curricula that incorporate empathy-based experiential learning (i.e., hands-on educational experiences and reflections designed to foster and develop emotional intelligence) promote students' self-awareness and confidence when providing care to patients. This scoping review examined studies that explored the effects of educational interventions on the development of empathy in undergraduate nursing students. Method: Searches were conducted in MEDLINE using keywords related to nursing education and translated into CINAHL, EMBASE, and ERIC databases. Results: A total of 6,238 studies were identified. After duplicate and unrelated articles were excluded, 18 publications were considered for this review. Sixteen studies concluded empathy interventions were effective, five indicated the need for further research, and two implicated a need for standardization in empathy-evaluation tools. Conclusion: This review endorses the effectiveness of educational interventions and supports their implementation to promote empathy in undergraduate nursing students. [ J Nurs Educ . 2024;63(6):367–371.]

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 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)0.006
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.776
Threshold uncertainty score0.958

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.157
GPT teacher head0.566
Teacher spread0.408 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

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

Citations11
Published2024
Admission routes1
Has abstractyes

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