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Enregistrement W4225392810 · doi:10.1096/fasebj.2022.36.s1.0r856

Gross Anatomical Knowledge Loss in Fourth‐Year Nursing Students

2022· article· en· W4225392810 sur OpenAlexaff
Yuwaraj Narnaware

Notice bibliographique

RevueThe FASEB Journal · 2022
Typearticle
Langueen
DomaineEngineering
ThématiqueAnatomy and Medical Technology
Établissements canadiensMacEwan University
Organismes subventionnairesnon disponible
Mots-clésComprehensionMedicineKnowledge retentionPsychologyNurse educationMedical educationNursingComputer science

Résumé

récupéré en direct d'OpenAlex

Human anatomy and physiology are considered a cornerstone of health‐related professional education and serve as a prerequisite for future nursing courses (McVicar et al., 2015). Numerous research studies show great difficulty in transferring fundamental knowledge of these courses to clinical and subsequent years of these disciplines (Bhangu et al., 2010; Narnaware and Neumeier, 2020; Narnaware, Y. 2021a). However, most of the knowledge acquisition, transfer/lost, and retention studies have been carried out in medical and allied health students and have been assessed rarely in nursing students. We have previously shown that the second‐and third‐year nursing students lose approximately 29.0% and 31.0% of their second and third‐year anatomical knowledge, retaining about 71.0% and 69.0% within two years (Narnaware and Neumeier, 2020; Narnaware and Neumeier, 2020b). However, anatomical knowledge transfer/loss, retention, and application in fourth‐year nursing students have not been assessed yet. The present study's main objective, therefore, is to assess the anatomical knowledge loss among fourth‐year nursing students and determine if the retention level is organ system‐specific. To evaluate the knowledge loss in fourth‐year nursing students, they were quizzed on eleven anatomy organ systems using the online quizzing system Kahoot. Each Kahoot quiz included nine to eleven knowledge and comprehension level multiple‐choice questions. These scores were compared to first‐year quiz scores on the same content to determine overall knowledge loss over the fourth year. Data were statistically analyzed using SPSS II, and means were compared using two‐way ANOVA. The scores are shown for each organ system by reporting the mean and standard deviation (±SD). Statistical significance was set at P < 0.05 for all tests. The results show that there was a significant decrease in the overall mean score from 83.05 ± 8.34 (± SD) in the first year to 53.9 ± 9.4 (±SD) in the fourth year (P=0.0001) (Figure 1). This equates to a 29.6% loss and 70.4% overall retention of anatomical knowledge over two years. However, there was no significant difference in mean scores between the third‐year and four‐year nursing students. The mean score in fourth‐year nursing students was higher by approximately 3.4% than the third‐year students. System‐specific knowledge loss shown in table 1 was highest for the head and neck lymphatic (55.7%), cranial nerves (44.1%), lymphatic (37.6%), and special senses (37.0%). This system‐specific knowledge loss was followed by the integumentary system (28.2%), vascular system (27.6%), muskulo‐skeletal (26.6%), and nervous system (25.1%). The loss was the lowest for the genitourinary system (21.2%), respiratory system (13.9%), and gastrointestinal system (12.0%). The present study reveals that nursing students lost more knowledge in the fourth‐year than first‐year and comparatively less than third‐year but retained much higher anatomical knowledge than medical and allied health students reported. This study provides knowledge retention for different body systems. It also identifies where nursing students' knowledge retention gaps exist so that those can be addressed by developing a robust interventional strategy for nursing students in the future.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Autre devis · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,684
Score d'incertitude au seuil0,550

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0010,000
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,011
Tête enseignante GPT0,275
Écart entre enseignants0,264 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeAutre devis
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations1
Publié2022
Routes d'admission1
Résumé présentoui

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