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3 results on '"Baltinaite, Giedre"'

1. Mentors' competence in mentoring nursing students in clinical practice: Detecting profiles to enhance mentoring practices

Author

Mikkonen, Kristina, primary, Tomietto, Marco, additional, Tuomikoski, Anna‐Maria, additional, Miha Kaučič, Boris, additional, Riklikiene, Olga, additional, Vizcaya‐Moreno, Flores, additional, Pérez‐Cañaveras, Rosa M., additional, Filej, Bojana, additional, Baltinaite, Giedre, additional, Cicolini, Giancarlo, additional, and Kääriäinen, Maria, additional

Published
2021
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2. Mentors' competence in mentoring nursing students in clinical practice: Detecting profiles to enhance mentoring practices

Author

Universidad de Alicante. Departamento de Enfermería, Mikkonen, Kristina, Tomietto, Marco, Tuomikoski, Anna-Maria, Kaučič, Boris Miha, Riklikiene, Olga, Vizcaya-Moreno, M. Flores, Pérez-Cañaveras, Rosa M., Filej, Bojana, Baltinaite, Giedre, Cicolini, Giancarlo, Kääriäinen, Maria, Universidad de Alicante. Departamento de Enfermería, Mikkonen, Kristina, Tomietto, Marco, Tuomikoski, Anna-Maria, Kaučič, Boris Miha, Riklikiene, Olga, Vizcaya-Moreno, M. Flores, Pérez-Cañaveras, Rosa M., Filej, Bojana, Baltinaite, Giedre, Cicolini, Giancarlo, and Kääriäinen, Maria

Abstract

Aims: To describe the mentoring competence of clinical practice nurse mentors and identify different mentor profiles. Design: Cross-sectional research design, secondary analysis. Methods: An international, cross-sectional study design was performed in five European countries. A total of 1 604 mentors from 33 healthcare organizations participated in the study between 2016–2019. The Mentors' Competence Instrument (MCI), which includes seven sub-dimensions and 44 items, was used to collect data. K-means cluster and binary regression analyses were performed to detect mentor profiles and determine how various factors affect competence, respectively. Results: The K-means cluster analysis identified three distinct profiles: A (n = 926); B (n = 566); and C (n = 85). The profiles showed significantly different values (p < .001) across all seven areas of mentoring competence. In comparison with the other profiles, nurses in profile A were older, had more work experience and were more probably to have completed mentoring-specific training.

Published
2021

3. Mentors' competence in mentoring nursing students in clinical practice: Detecting profiles to enhance mentoring practices.

Author

Mikkonen, Kristina, Tomietto, Marco, Tuomikoski, Anna‐Maria, Miha Kaučič, Boris, Riklikiene, Olga, Vizcaya‐Moreno, Flores, Pérez‐Cañaveras, Rosa M., Filej, Bojana, Baltinaite, Giedre, Cicolini, Giancarlo, and Kääriäinen, Maria

Subjects
CROSS-sectional method, MENTORING, REGRESSION analysis, CLINICAL competence, DESCRIPTIVE statistics, NURSE practitioners, CLUSTER analysis (Statistics), NURSING students, SECONDARY analysis
Abstract

Aims: To describe the mentoring competence of clinical practice nurse mentors and identify different mentor profiles. Design: Cross‐sectional research design, secondary analysis. Methods: An international, cross‐sectional study design was performed in five European countries. A total of 1 604 mentors from 33 healthcare organizations participated in the study between 2016–2019. The Mentors' Competence Instrument (MCI), which includes seven sub‐dimensions and 44 items, was used to collect data. K‐means cluster and binary regression analyses were performed to detect mentor profiles and determine how various factors affect competence, respectively. Results: The K‐means cluster analysis identified three distinct profiles: A (n = 926); B (n = 566); and C (n = 85). The profiles showed significantly different values (p <.001) across all seven areas of mentoring competence. In comparison with the other profiles, nurses in profile A were older, had more work experience and were more probably to have completed mentoring‐specific training. [ABSTRACT FROM AUTHOR]

Published
2022
Full Text
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