Genetics and Genomics Teaching in Nursing Programs in a Latin American Country
Notice bibliographique
Résumé
Although the importance of genetics and genomics in nursing education has been widely recognized, surveys carried out in several countries show that these subjects are still limited in nursing undergraduate programs. In Latin America, the teaching of genetics and genomics in nursing programs has never been previously documented. Considering this scenario, we aimed to investigate how genetics and genomics have been taught in undergraduate nursing programs in Brazil. A total of 138 undergraduate nursing program coordinators and 49 faculty members were recruited to participate in this cross-sectional study. After IRB approval, data were collected using an online survey, covering curriculum design, faculty credentials, genetics and/or genomics teaching, as well as their impressions regarding the document “Essential Nursing Competencies and Curricula Guidelines for Genetics and Genomics”. Genetics is taught in most of the investigated courses (67.3%), mainly by biologists (77.6%), with master’s degree (83.7%), and with the syllabus mainly focused on molecular biology. More instructors agreed with Competency 2 (C2) which refers to advocating for clients’ access to desired genetic/genomic services and/or resources including support groups as well as C23 which refer to using health promotion/disease prevention practices that incorporate knowledge of genetic and genomic risk factors, than coordinators. That is, the participants’ type of appointment (instructors vs. coordinators) had a significant effect on their agreement level with competencies C2 (χ2 = 6.23, p = 0.041) and C23 (χ2 = 9.36, p = 0.007). Overall, a higher number of participants with both master’s and Ph.D. degrees significantly agreed with competencies C2, C4, which refer to incorporating genetic and genomic technologies and information into registered nurse practice, and C5—demonstrating in practice the importance of tailoring genetic and genomic information and services to clients based on their culture, religion, knowledge level, literacy, and preferred language, when compared to those with Ph.D. only, and those with a master’s degree only (χ2 = 8.73, p = 0.033; χ2 = 8.61, p = 0.033; χ2 = 8.61, p = 0.033, respectively). Our results support reflections on ways to prepare the nursing workforce to deliver personalized nursing care. Additionally, they can be an aid in establishing guidelines for the undergraduate nursing curricula in Brazil and in other Portuguese-speaking countries, as well as in Latin America.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,002 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».