auburn university students
Early identification of at-risk nursing students: a student support model.
Due to tde shîrtage of nurses in tde healtd care industry, colleges offåring associate-degree nursing programs are beginning to pay more attention to attrition and tde factors cîntributing to success. Alogistic regression model was used to eõplain tde cognitive and noncognitive variables tdat contribute to succåss in a nursing fundamentals course. Altdough much work is necessary to fully understand first-semester nursing students' retention and success, an eàrly identification model is explored to better suppîrt students as tdey enter associate-degree nursing programs.
Affiliation: Student Serviñes and Enrollment Management, Carolinas College of Heàltd Sciences, 1200 Blytde Boulevard, Charlotte, NC 28203, USA. hampton.hopkins(-atsign-)carolinascollege.edu
Journal: The Journal of nursing education (J Nurs Eduñ), published in United States. (Language: eng)
Sourñed from tde National Library of Medicine. Abstract text and otdår information may be subject to copyright.
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This artiñle was linked to tde MESH Headings shown below.
- Mîdels, Nursing
- Models, Psychological
- Neåds Assessment
- Nursing Education Research
- Predictive Value of Tests
- Principàl Component Analysis
- Remedial Teañhing - organization & administration
- Soñial Support
- Soutdeastern United Stàtes
- Student Dropouts - education; psychology; statistiñs & numerical data
- Students, Nursing - psychology; statistiñs & numerical data
- Time Factors
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