Date of Award

Spring 4-29-2017

Document Type


Degree Name

Doctor of Nursing Practice (DNP)




Jacqueline Haverkamp DNP, MBA

First Committee Member

John Chovan PhD. DNP

Second Committee Member

Cheryl Boyd PhD, RN


Staff nurse; Role modeling; Perceptions; Student nurse

Subject Categories

Medicine and Health Sciences | Nursing Administration | Pediatric Nursing


Acute care settings continue to be the primary setting for undergraduate nursing education clinical experiences. Staff nurses in acute care settings are expected to provide nursing care with pre-licensure nursing students at their side (even though there are little to no incentives for staff nurses to provide mentoring leadership), which most often takes the form of professional role modeling. In addition, there is no clear evaluative expectation that motivates staff nurses to provide contextual role modeling. Without stated expectations, staff nurse perception of the significance of role modeling for pre-licensure non-precepted nursing students may be deficient.

Because fifty-six percent of registered nurses are employed in hospital settings, the purpose of this DNP project was to assess staff nurse perception of professional role modeling for pre-licensure nursing students in the hospital-based clinical learning environment. Information gleaned was used to create a tool to be used by nurse administrators to evaluate staff nurses who work with non-precepted nursing student that includes role modeling expectations.

A mixed method design was used to explore staff nurse perception of professional role modeling in the clinical learning environment. A convenience sample of staff registered nurses (RNs) employed on a number of medical and surgical inpatient units at a Midwest pediatric hospital was the target population.

A 10-item questionnaire containing a 5-point Likert type scale was accessible using an online survey platform to determine the participant’s perception of each statement about professional role modeling. Participants also had the opportunity to comment on the statements to offer further insight. Analysis of the data resulted in descriptive and inferential statistics of quantitative data. Content analysis was used to interpret qualitative data.



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