Assessing nursing students’ e−health literacy and foresights to global health challenges during COVID−19 restrictions: A cross-sectional study with a machine learning approach

This study aims to assess the e-health literacy and foresights to global health challenges of nursing students during the COVID19 restrictions. As the healthcare environment becomes more digitalized, understanding how nursing students perceive and prepare for global health challenges during the COVI...

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Veröffentlicht in:Nurse education in practice Jg. 81; S. 104179
Hauptverfasser: KUPCU, Cisem, BODUR, Gonul, KUCUKKAYA, Aycan, GOKTAS, Polat
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Scotland Elsevier Ltd 01.11.2024
Elsevier Limited
Schlagworte:
Ability
Adult
Artificial intelligence
Challenges
Chronic illnesses
Collaboration
College students
Councils
COVID-19
COVID-19 restrictions
Cross-Sectional Studies
Curricula
E-health literacy
Education
Education, Nursing, Baccalaureate
Educational Strategies
Female
Gender pay gap
Global Health
Global health challenges
Globalization
Health care industry
Health disparities
Health education
Health Literacy
Health Promotion
Health services
Humans
International Organizations
Literacy
Machine Learning
Male
Medical education
Mental health services
Midwifery
Migration
Nurses
Nursing
Nursing education
Nursing students
Pandemics
Primary Health Care
Public health
Quantitative analysis
Restrictions
Skills
Statistical analysis
Statistical methods
Students
Students, Nursing - psychology
Students, Nursing - statistics & numerical data
Surveys and Questionnaires
Turkey
Young Adult
Turkey
Nursing students
Global health challenges
Educational strategies
COVID-19 restrictions
Machine learning
E-health literacy
ISSN:1471-5953, 1873-5223, 1873-5223
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Zusammenfassung:This study aims to assess the e-health literacy and foresights to global health challenges of nursing students during the COVID19 restrictions. As the healthcare environment becomes more digitalized, understanding how nursing students perceive and prepare for global health challenges during the COVID19 restrictions and e-health literacy is crucial for customizing educational strategies to enhance their capabilities. A descriptive and correlational study design was employed. The study included 310 nursing students from six universities in Istanbul, Turkey, encompassing both state and foundation institutions. Data were collected via online surveys, including an Information Form, a Foresight Form for Global Health Challenges and an E−Health Literacy Scale. The study extended beyond conventional statistical analysis by incorporating a tree-based ML model, specifically a Random Forest classifier, to identify complex patterns and relationships affecting e−health literacy and global health perceptions. The analysis indicated that e−health literacy levels among nursing students are significantly shaped by their academic year, participation in global health courses and engagement with international health organizations. ML techniques pinpointed the ability to discern high−quality online health resources as a pivotal skill, emphasizing the need for nursing curricula to focus on advanced critical evaluation skills. The findings stress the necessity of integrating critical evaluation and information−seeking skills into nursing education to equip students for the complexities of a globalized health landscape.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
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ISSN:1471-5953
1873-5223
1873-5223
DOI:10.1016/j.nepr.2024.104179