Needs and experiences of postgraduate nursing students in Nigeria during the COVID‐19 pandemic
Notice bibliographique
Résumé
AIM: To explore the experiences and needs of postgraduate nursing students within the Nigerian context. DESIGN: This qualitative study was conducted using a descriptive phenomenological approach. METHOD: Data were collected between February and April 2022 using a purposive sampling method and telephone semi-structured interviews. Colaizzi's method of Qualitative data Analysis was utilized. Twenty-two Nigerian postgraduate nursing students were interviewed. RESULTS: Three themes emerged: challenges of Nigerian postgraduate students before the pandemic, the impact of the pandemic on postgraduate education, and innovations to improve postgraduate education in Nigeria. The challenges include the burden of physical lectures, lack of infrastructure, and poor mentorship of postgraduate nursing students. The impact of the pandemic on postgraduate education includes abrupt disruption of the academic program, a prolonged academic calendar, and a communication gap between students and their research supervisors. Innovations to improve postgraduate nursing education in Nigeria also include adoption and sustainability of e-learning, upgrading post-basic to postgraduate nursing programmes, proper structuring of postgraduate nursing education, commencement of postgraduate nursing programmes in more universities and provision of financial aid for students. Our primary finding is that funding, mentorship and infrastructure were issues peculiar to all the respondents. CONCLUSION: This study concludes that efforts should be made to maintain a seamless educational program by ensuring an uninterrupted flow of learning through virtual means, thereby enhancing effective teaching and learning. IMPLICATIONS: Graduate nursing studies is one of the suggested solutions in the WHO strategic direction for nursing and midwifery globally to achieve Universal Health Coverage . The reason is that nurses can practice with more and better skills in any work setting, thus improving the quality of health care services. Our study provides insights into the experiences of postgraduate students and how these could discourage other nurses who might have thought about furthering their studies. Efforts should be made to provide all the support that these students need, using evidence from this study and similar studies to ensure they have a good learning experience and others can be motivated to learn at the graduate level as well. This will increase the proportion of nurses and midwives honed with better skills to provide more standard quality services that will improve patient care outcomes.
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 | 0,003 | 0,006 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,007 | 0,003 |
| Communication savante | 0,004 | 0,002 |
| Science ouverte | 0,001 | 0,005 |
| Intégrité de la recherche | 0,002 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».