Defense Date
7-23-2019
Graduation Date
Fall 12-20-2019
Availability
One-year Embargo
Submission Type
dissertation
Degree Name
PhD
Department
Nursing
School
School of Nursing
Committee Chair
Joan Lockhart
Committee Member
Rebecca Kronk
Committee Member
James Schreiber
Committee Member
Anne Thomas
Keywords
Nurse Practitioner, Delphi, Nurse Practitioner Competencies, Competency Based Education
Abstract
Background: Competency-based education (CBE) has been recommended for nurse practitioner (NP) education. To implement CBE, existing NP core competencies need to be reduced in number and refined.
Purpose: This study refined and reduced redundancy in the National Organization of Nurse Practitioner Faculties (NONPF) and American Association of Colleges of Nursing (AACN) NP core competencies through the consensus of experts in NP practice. This study used the current NP Core Competencies (NONPF, 2017), the Essentials of Doctoral Education for Advanced Nursing Practice (AACN, 2006), and the Common Advanced Practice Registered Nurse Doctoral-Level Competencies,(AACN, 2017a)as these documents are the competencies accredited NP programs commonly use in curriculum development. The primary aim of this study was to determine the relevancy of these competencies; a secondary aim was to ensure that the final competencies were clear and measurable.
Methods: A Delphi approach was used to reach consensus among an expert panel who reviewed the core competencies via an online questionnaire. Descriptive statistics were used to calculate median and interquartile ranges; content analysis was conducted with qualitative data.
Results: Consensus was reached after three rounds and resulted in 49 final core competencies.
Implications for Practice: This study provides the NP community with a manageable list of relevant, clear, and measurable competencies that faculty members can use to implement CBE in their programs.
Language
English
Recommended Citation
Chan, T. (2019). Determining Nurse Practitioner Core Competencies Utilizing A Delphi Approach (Doctoral dissertation, Duquesne University). Retrieved from https://dsc.duq.edu/etd/1831