Running head: APP MENTORSHIP 1 Mentorship Matters: Understanding the Impact of Mentorship for Advanced Practice Providers Deb White Arizona State University APP MENTORSHIP 2 Abstract Nurse practitioners and physician assistants, collectively termed advanced practice providers (APPs), report a lack of onboarding and professional support which has been shown to lead to job dissatisfaction, high turnover rates, professional attrition, and gaps in patient care; wasting billions of healthcare dollars and falling short of the Quadruple Aim. A time-honored, integral means of support in many industries is mentorship. This is a dynamic, evolving relationship between an experienced professional and a novice professional that promotes knowledge application, systems navigation, organizational socialization and personal role integration. Unfortunately, healthcare organizations have been slow to adopt mentorship, as evidenced by the paucity of studies on mentorship programs in health care, and APP turnover rates twice that of physicians. This evidenced-based project expands on the limited existing studies regarding the associations between mentorship and organizational commitment, as well as explores the desired characteristics of quality mentors and perceived barriers to APP mentorship. A survey of multispecialty APPs at an oncology practice within a larger, multi-state integrated healthcare delivery system reveals access to mentors and time are the biggest barriers. The most desired mentorship characteristics are professional knowledge and motivational support. Career development through mentorship can increase job satisfaction and retention, as well as improve the quality of care provided by APPs. By strengthening the professional foundations, patients will benefit with continuity of care, improved quality measures, and efficient systems communication reaching the Quadruple Aim targets. Keywords: mentor, mentorship, advanced practice provider, nurse practitioner, physician assistant, turnover, job satisfaction, organizational commitment APP MENTORSHIP 3 Mentorship Matters: Understanding the Impact of Mentorship for Advanced Practice Providers The increased number of aging, chronically-ill, and underserved populations are challenging existing healthcare provider shortages. The use of nurse practitioners (NPs) and physician assistants (PAs) is an established means to help address those shortages (Essary et al., 2018; Ewing & Hinkley, 2013; Harrington, 2011; Hooker & Everett, 2012; Swan, Ferguson, Change, Larson, & Smaldone, 2015). Advanced practice provider (APP) is an inclusive term to describe both NPs and PAs whom are increasingly employed by healthcare organizations, yet do not receive adequate professional on-boarding support. Healthcare organizations have established orientation programs for recently hired registered nurses, including time-period adaptations for newly graduated nurses; while physicians have lengthy residency programs. Being relatively recent solutions to the provider gaps in the healthcare industry, APPs experience frequent role expectation changes with little collegial or organizational support during times of transition (Harrington, 2011; Hooker & Everett, 2012; Hill & Sawatzky, 2011). This lack of support can lead to job dissatisfaction, high organizational turn-over rates, professional attrition, and gaps in patient care, either due to unfilled APP positions or poorly integrated providers; creating additional cost burdens for the nation’s already financially strained healthcare system. (DeMilt, Fitzpatrick, & McNulty, 2010; Essary et al., 2018; Faraz, 2017; Harrington, 2011; Hill & Sawatzky, 2011; MacLellan, Levett-Jones, & Higgins, 2017). Problem Statement Role transitions are recognized times of stress for professional identity, organizational integration, and meeting quality standards (Faraz, 2017; Harrington, 2011; Hooker, Kuilman, & Everett, 2015). The APP workforce is projected to increase between 30% and 70% within seven years (Hoff, Carabetta, & Collinson, 2017; National Commission on Certification of Physician APP MENTORSHIP 4 Assistants (NCCPA), 2017; Poghosyan, Liu, Shang, & D'Aunno, 2017). With approximately 30,000 APP graduates entering the workforce annually it is imperative that these providers receive robust on-boarding and support if they are to meet expectations of providing high-quality care to patients with chronic and complex health care problems and remain in their professional role (American Association of Nurse Practitioners, 2017; NCCPA, 2017; MacLellan et al., 2015). Frequent turn-over wastes valuable healthcare dollars, and administrative time and supplies. The estimated cost to replace a single provider can be up to $1.3 million; lost revenue from a vacant position and reduced revenue for up to two years must be added to the costs of recruitment, certification/background verification, and orientation (Heil, Culhane, & Munkner, 2015; Rosenfield, 2018). Not accounted for in that $1.3 million is the cost of patient dissatisfaction, remaining provider “burn-out”, decreased efficiency of over-burdened staff, and unnecessary or incorrect testing that often occurs during staffing gaps. The turnover rate for APPs is 12.6%, over twice that of physicians (Anderson, 2012; Bureau of Labor Statistics, 2016; Cejka, 2014). The Institute for Healthcare Improvement’s (IHI) Triple Aim initiative is a global framework to help organizations decrease cost, improve quality, and increase access of healthcare services for all populations (IHI, 2018). Expanding the Triple Aim by including clinician satisfaction acknowledges the impact of provider needs on overall patient outcomes (Bodenhemer & Sinsky, 2014; Essary et al., 2018; IHI, 2017). To be on target with the Quadruple Aim, organizations must address low retention rates, inadequate system integration, provider and patient dissatisfaction, and failure to meet quality outcome standards. Purpose and Rationale A Japanese proverb states “better than a thousand days of diligent study is one day with a great mentor” (Pillemer & Rheaume, 2013). While one day is certainly not equivalent to years of APP MENTORSHIP 5 study, the value of a great mentor in the socialization, knowledge application, systems navigation, and personal role support of novice professional or employee is invaluable and as important as didactic study (DeMilt et al., 2010; Faraz, 2017; Farnese, Bello, Livi, Barbieri, & Gubbiotti, 2016; MacLellan et al., 2015; Manzi et al., 2017). Experienced APPs can help newly employed peer clinicians with organizational integration, professional identity, and systems thinking which will decrease role transition stress, increase job satisfaction and organizational commitment, and reduce turnover, thus saving millions of healthcare dollars (Anderson, 2012; Essary et al., 2018; Heil et al., 2015; Horner, 2017). Ensuring that the newly hired APP is supported through mentorship also increases the likelihood the APP will value mentoring and help on-board others, keeping the costs of healthcare turnover low. It is imperative to develop a definition of mentorship, and how mentorship differs from orientation, preceptorship, collaborative relationship, or physician oversight. In addition to defining mentorship, potential benefits of mentorship for both the APP and the healthcare organization, as well as tools to develop quality mentoring skillsets will be presented. Background and Significance Mentorship Issues and Impact Mentorship is a dynamic, evolving relationship between an experienced professional and a novice professional; the mentor serves as a trusted counselor, professional role model, confidant, friend, and protector (Gerhart, 2012; Harrington, 2011; Horner, 2017; Olivero, 2014; Race & Skees, 2010, Ragins & Kram, 2007). The mentor gains validation of clinical experience, value to the organization, peer recognition, and leadership skills in addition to increased personal reflection and professional growth (DeMilt et al., 2011; Horner & Eley, 2017; Olivero, 2014; Race & Skees, 2010). Other terms are often used interchangeably, though incorrectly, to describe APP MENTORSHIP 6 a mentor/mentee relationship. One of the most common is preceptor, which is defined as a teacher or trainer who also provides evaluation to superiors regarding the novice professional’s performance (Gerhart, 2012; Race & Skees, 2010). This supervisory evaluation role limits the protector and confidant aspects of mentorship. The preceptor role is also linked to the orientation period. Orientation is not a relationship, it is a process of training a new employee and introducing them to the organization, while it may involve an experienced employee and new employee, it is a task focused process as opposed to the dynamic, mutual relationship that characterizes mentorship (Gerhart, 2012; Ragins & Kram, 2007). All PAs and some NPs practice with an overseeing or collaborating physician. While this physician can be a good source of information and support, it is not a mentor role; it is a regulatory, supervisory role with power over the novice’s employment (Ewing & Hinkley, 2013; Gerhart, 2012). While the roles performed by either a preceptor or collaborating physician have benefits, they lack the robust career-building and professional growth provided through quality mentorship. Job Satisfaction and Staff Turnover Turnover is costly to healthcare; reducing turnover helps organizations meet the Quadruple Aim, thus improving population outcomes with less cost while improving patient and provider satisfaction (Anderson, 2012; Bodenheimer & Sinksy, 2014; Essary et al., 2018; Heil et al., 2015; Horner & Eley, 2017; IHI, 2017; IHI, 2018). Providers who have a strong professional self-identity and feel supported by an organization are much less likely to leave (Faraz, 2016; Gerhart, 2012; Hooker et al., 2015). While mentorship alone does not solve other factors of job satisfaction, such as autonomy, workloads, benefits, and work environment, mentors can help novice APPs gain the self-confidence needed for autonomy, provide practical advice on APP MENTORSHIP 7 managing workloads, and provide an avenue to the socialization needed in the work environment (Faraz, 2016; Farnese et al., 2016; Race & Skees, 2010). Mentorship in an Urban Healthcare System A multispecialty oncology practice that is part of a larger, multi-state integrated healthcare delivery system (IHDS) recently implemented a structured orientation specifically for APPs that is modifiable depending on an APPs prior oncology experience. It has shown initial success and is being examined for implementation in other specialties of the IHDS (Dean, 2017). Further examination of the recently implemented orientation program revealed a gap for increasing the APP workforce; currently practicing APPs feeling uncomfortable and ill-prepared to orient new APPs, especially recent graduates. The oncology clinic is expanding its patient base as well as opening new satellite clinics creating more APP job openings yet few of the current staff are willing to on-board the new personnel. Moving from the expert registered nurse to novice NP or entering into healthcare for the first time as a PA, while navigating the nuances of independent advanced practice in a healthcare system based on the medical-model is challenging; requiring strong professional self-identity, social skills, and organizational support. These are facets that cannot be taught in a didactic fashion but must be learned and practiced under the guidance of a more experienced peer, known as a mentor (Hill & Sawatzky, 2011; Hooker et al., 2015; Horner, 2017; Manzi et al., 2017; Olivero, 2014). Recognizing the mentorship gap, an evidenced based project was designed to examine barriers to mentorship, desired mentor characteristics, and discover potential relationships between organizational commitment and various facets of mentorship and onboarding; with the ultimate goal to support and encourage a mentorship culture in the organization. This led to the following PICO question: APP MENTORSHIP 8 “For APPs (P), how does a mentorship program (I) compared to the lack of mentorship (C) affect turnover and job satisfaction (O)?” Critical Appraisal of the Literature Literature Review Healthcare, particularly nursing, lags behind other industries such as teaching and business management when it comes to supporting and growing the next generation; as evidenced by the paucity of literature found. A preliminary search of PubMed, Cochrane, and CINHAL databases revealed a limited number of articles (approx. 40), few of which were research studies, on NP mentoring. Expanding the search parameters to include nurses and PAs revealed a few more results (approx. 80; Appendix A). However, in comparison to the amount of results returned when searching mentorship in the fields of teaching, engineering, and management (over 1,600; over 56,000 if thesis and dissertations are included) it is apparent there is a research gap in APP mentorship (Appendix B). Even the thesis and dissertations for APPs demonstrate a lack of research as only 9,096 papers were discovered (Appendix C). Postgraduate fellowship or residency programs, which are increasingly popular in large healthcare organizations, are another method of providing support and orientation to newly hired APPs; however, these programs lack standardization and there is no published evidence regarding their efficacy (Bush & Lowery, 2016). Adding the terms “fellowship” or “residency” to the search criteria appeared to provide several thousand additional resources (Appendix D). Interestingly, this search as well as the Cochrane Database search (Appendix A) highlights the lack of standard concrete definitions for the terms mentor, residency, and fellowship. These terms are used in patient therapy and patient support programs, as well as to describe orientation programs. APP MENTORSHIP 9 Mentorship for the APP is an understudied subject with ill-defined, inconsistent terminology and little data driven research. Many editorials, opinions, and program evaluations were found in the literature search, but few high-quality studies were discovered. Thus, studies of mentorship’s contribution to professional retention and job satisfaction in other industries must be explored. Search Strategies PubMed, CINHAL, MEDLINE, and PsycINFO were searched for evidence-based data limited to peer-reviewed articles published between January 2010 and December 2018. Only two results were found that encompassed mentor or mentorship, job satisfaction, turnover, and APPs. Since APP is not common industry term, search terms included APRN, advanced practice registered nurse, nurse practitioner, and physician assistant. Depending on the healthcare database, searching for mentor or mentorship, job satisfaction and turnover yielded 21 to 36 results which focused on healthcare leadership and registered nurses (Appendix E). Given the similar working environment of these roles to the APP, high quality studies from this search can provide insight into mentorship’s role in turnover and APP job satisfaction. While PsycINFO covers some of the behavioral aspects of business, ABI/INFORM is a comprehensive business, management, and trade journals database that was used to search for research regarding mentor or mentorship, job satisfaction and turnover in other disciplines. With over 1,700 per reviewed articles published since 2010, it was necessary to further refine this search. Review of the types of articles initially retrieved led to including research, statistical analysis, studies, or new employees, while excluding supervisors, training, workplace diversity, expatriate employees, and students; resulting in a manageable 79 articles to examine for evidence that might be applicable across industries (Appendix F). APP MENTORSHIP 10 The ERIC Database was searched for studies of mentorship in academia. Depending on the combination of terms, 4 to 33 peer–reviewed studies published since 2010 were returned (Appendix F). The APP/patient/healthcare organization relationship aligns with the teacher/student/school relationship, potentially making results from these studies applicable to the APP. Ten high-quality research studies from four different industries, were chosen for evaluation of mentorship’s effect on job satisfaction and turnover; five from healthcare, two from business management, two from education and one from corrections (Appendix G). While corrections or the penal branch of the justice system may seem very unrelated to healthcare, both industries have high-stress roles, rapidly changing micro and macro environments, and involve multiple confidentiality regulations (Farnese et al., 2016). Synthesis Research on mentorship began to flourish after Kram’s 1983 in-depth qualitative study of 18 mentor-protégé pairs; however, 35 years later there are still no significant experimental or longitudinal studies (Allen & Eby, 2010). This was reflected in the 10 studies compiled, all were rated as level VI evidence with quality design and data interpretation (Appendix G). Organizational Commitment. Eight of the nine quantitative studies used survey tools which have been determined to be reliable and valid for examining the variables of job satisfaction, organizational commitment, and turnover intent. Meyer and Allen’s (1991) Three Component Model of Employee Commitment Scale (MATCMEC) is the dominant tool to measure organizational commitment to predict turnover (Jaros, 2007). The instrument uses a 7point Likert scale to measure three domains: affective or desire/emotional, normative or moral/obligatory, and continuance or cost/benefit aspects of organizational commitment and was APP MENTORSHIP 11 used across three industries in the studies examined. Additionally, the Misner Nurse Practitioner Job Satisfaction Scale created in 2001 specifically to examine NP’s job satisfaction using a 6point Likert scale for 44 items regarding a working environment, including benefits, training, policies, advancement, and interdisciplinary relationships (Horner, 2017). The Misner scale was used in three of the five healthcare studies. All studies consistently demonstrate an inverse relationship between job satisfaction and organizational commitment to turnover intention. Mentorship Measures. When examining mentorship, the tools used were less standardized, but the questions were similar across instruments. Six of the studies also included areas for comment, which adds to the richness of construct themes. The most commonly used mentorship measurement tool was Scandura and Ragin’s (1993) Mentorship Functions Questionnaire (MFQ9) and its lengthier original 15 item version, the Multidimensional Mentoring Measure (Castro, Scandura, & Williams, 2004). Using a 5-point Likert scale the mentorship relationship is evaluated in the domains of role modeling, career support, and psychosocial support. Cronbach's α of 0.96 was replicated in the studies using MFQ9. One study used Noe’s (1998) Mentoring Function Scale (MFS), which is designed specifically for assigned mentors, has an equally high reliability, and has been tested in multiple languages (Noe, 1988; Ho, Kwon, Park, Yoon & Kim, 2017). Two of the three studies directly measuring mentorship and job satisfaction found a significantly positive relationship, and a third study showed a positive association although it did not reach level of significance (Appendix H). Six of the studies found that mentorship increased organizational commitment and decreased turnover intention. Limitations of existing research. Despite high validity and reliability of the tools used, they are based on recall and self-reporting which can create biased results. In four of the five APP MENTORSHIP 12 healthcare studies, some of the participants were recalling information from three to 25 years prior. While the recalled information may be accurate, it can also be influenced by the process of experience. The healthcare related surveys were comprised of 91% females, which is consistent with the general population of NPs, but approximately one third of PAs are male (NCCPA, 2017). This disparity could make the studies less generalizable to men; however, Pathak and Srivastava’s (2017) study, and Ragins and Cotton’s (1991) Perceived Barriers to Mentorship (PBM), as well as many studies in the general literature, found no difference in gender with regards to mentorship experiences and expectations. Discussion Collectively, these studies show that mentorship can increase job satisfaction and organizational commitment, which in turn will reduce turnover, regardless of the industry. The majority of the studies showed that the type of mentorship program did not differ significantly on the outcomes of turnover or job satisfaction; however, two studies found that structured mentorship programs provided significantly more benefit than informal mentoring arrangements. The challenges of mentorship, either formal or informal, were discussed by three of the studies although no data analysis of these concepts was performed. Current literature was unable to define the highest quality forms of mentorship, what specific skills produce optimal outcomes, and how these factors impact organizational commitment. However, the overall evidence, regardless of discipline, demonstrates that mentorship is effective at improving job satisfaction and organizational commitment, reducing role ambiguity, richly socializing the novice, and promoting career growth of both the mentor and mentee, which in turn creates stronger organizations and reduces unnecessary turnover costs. One study was able to associate mentorship for rural providers with improved population APP MENTORSHIP 13 outcomes and reduced healthcare costs, supporting the idea that mentorship is a protentional method to aid in meeting the Quadruple Aim. Theoretical Framework and Evidence-Based Practice Model Theoretical frameworks are groups of concepts designed to explain or predict an aspect of human or organizational behavior or activity (Melnyk & Fineout-Overholt, 2015). The Theory of Organizational Socialization is a gold-standard of social theory and uses six tactical dimensions to predict and ultimately manage a new employee’s acclimation into the organization (Saks, Uggerslev, & Fassina, 2007). Each tactic falls along a continuum between a custodial role response and an innovative role response which can determine how an employee relates to the organization throughout a career (Tuttle, 2002; Saks et al., 2007). Content tactics range from sequential to random and fixed to variable and cover such concepts as timetables, sequential steps, and process schedules. Context tactics are distributed along a collective to individual and formal to informal continuum and include the concepts of grouping, experiences, segregation, and recognition. Social tactics apply to concepts of role modeling, individualism, and conformity; and range from serial to disjunctive and investiture to divestiture (Saks et al., 2007). A mentor uses role modeling, and career and psychosocial support techniques to help the mentee successfully navigate the bipolar continuums of each tactic to understand the content, context, and social aspect of the new position to become an integrated team member (Ragins & Kram, 2007). Van Maanen & Schein’s (1979) Theory of Organizational Socialization’s six tactics of socialization parallel the concepts in the MATCMEC, MFQ9, and Multidimensional Mentoring Measure, providing congruity in collection and evaluation of data and outcomes (See Appendix I for representative diagrams). APP MENTORSHIP 14 An evidence-based practice (EBP) model guides the application of a theoretical framework and evidence synthesis into practice settings. The Stevens Star Model of Knowledge Transfer is designed to cope with limited volumes and types of research, the mismatch of knowing and doing, and the challenges of sustaining innovative changes (Melnyk & FineoutOverholt, 2015). The limited amount of APP mentorship research requires knowledge from other industries be adapted to healthcare. As many authors have stated, people acknowledge the value of mentorship, businesses recognize its ability to increase job satisfaction, and employees desire this type of support, yet very few organizations have mentorship programs in place; a definite mismatch of knowledge and action (Ragins & Kram, 2007; Allen & Eby, 2010; Harrington, 2011; & Gerhart, 2012). The Stevens Star Model is circular in nature allowing fluid movement among the five components of discovery, evidence summary, translation to guidelines, practice integration, and outcome evaluation. Mentorship is a conceptual construct that remains broad, complex, yet vague despite the scrutiny, debate, and critique of various industry experts and scholars (Allen & Eby, 2010). These conceptual challenges are intensified when transferring the construct to healthcare; necessitating a non-structured model that incorporates various types of knowledge needed to understand mentorship’s impact on job satisfaction and turnover when developing a program to promote mentoring among APPs. Project Design Purpose As the literature search revealed, there is a gap in understanding the qualities of strong mentors in healthcare and how mentorship impacts job satisfaction, organizational commitment, and turnover. This gap also fails to fully answer, but hints at the possibility that mentorship could help meet the Quadruple Aim goals to decrease cost, improve quality, increase access of APP MENTORSHIP 15 healthcare services for all populations, and enhance providers’ work experience. Based on the results of the literature review and the needs of the IHDS the original PICO question was modified to create the design of the evidenced-based project. The following three questions were formulated to analyze the gaps experienced during on-boarding of APPs: 1. What do experienced APPs perceive as barriers to serving as a mentor? 2. What attributes create a quality, effective mentoring relationship? 3. Does mentorship support improve the organizational commitment of the APPs? A survey to answer these questions was developed and results were analyzed for correlations, themes, and gaps in current practice. The results of the gap analysis and mentorship evidence will be combined to create mentorship tools or courses to improve the on-boarding and long-term organizational commitment of APPs employed by the IHDS. If APP mentorship effects mirror that seen in other disciplines it is expected that productivity will increase, and costs will decrease. Project Methods Survey Design. Two standardized instruments discussed in the literature review and synthesis were included in the gap analysis. The MATCMEC was used to gain insight into the APPs perspectives of the affective, normative, and continuance aspects of organizational commitment. The MATCMEC, available free of charge for academic users, was obtained from the University of Western Ontario (https://www.employeecommitment.com/) on April 11, 2018. The MFQ9 was used to obtain data regarding the APPs perspectives of the mentoring domains of role modeling, career support, and psychosocial support. Permission to use was obtain from Dr. Teresa Anne Scandura on July 16, 2018. APP MENTORSHIP 16 A third validated mentorship instrument, the PBM, was also included in the project survey. The PBM uses a 7-point Likert scale to determine perceived barriers across five factors: 1. Access to mentors, 2. Fear of initiating, 3. Willingness of mentors, 4. Approval of others, and 5. Misinterpretation. The PBM was validated using a principal components factor analysis with varimax ration. Results of that analysis reveals a Cronbach's α ranging from 0.83 to 0.93 depending on the specific factor (Ragins & Cotton, 1991). Permission to use the PBM was obtained from Dr. Bella Rose Ragins on July 16, 2018. Permission letters can be viewed in Appendix J. The survey tool also included demographics such age, gender, profession, employment history, and professional, educational, and mentoring experience (Appendix K, pp. 1-5). Four open-ended questions were placed throughout the survey to allow the respondents to share descriptive information regarding mentorship. Custom ranking questions based on the MFQ9 domains of role modeling, career support, and psychosocial support sought to determine the most valued characteristic of each domain (Appendix K, p. 12). Five custom Likert-scale questions were included regarding barriers of productivity requirement, role expectations, and teaching experience that were mentioned in the healthcare literature (Appendix K, p.18). Two custom Likert-scale questions were included to gauge the APPs interest in potential mentoring programs (Appendix K, p. 19.). The above described questions and validated instruments were combined into one on-line survey to be administered through SurveyMonkey (Appendix K). Due to the length of the survey, the ability to stop and restart the survey was established using email addresses which were encrypted into SurveyMonkey and blinded to all project investigators. This encryption method also allowed SurveyMonkey to send automatic reminders at established intervals. APP MENTORSHIP 17 Ethics and Recruitment. The survey, project timeline, consent, IHDS support letters, and project presentation were submitted to the Arizona State University Institutional Review Board. The project was determined to be exempt on 9/24/18 (Appendix L). A brief presentation explaining the project and providing instructions on survey completion was given to the APPs within the multispecialty oncology practice at the IHDS on November 12, 2018. The presentation was an agenda item on the regular bi-monthly APP meeting. The APPs were given the opportunity to ask questions regarding the project or survey instructions. The following day all APPs employed by the practice (n=54) were emailed a link to the secure, anonymous on-line SurveyMonkey survey. The link remained active for six weeks, with two reminder emails automatically generated by SurveyMonkey for non-initiated or incomplete surveys. Data Analysis. Upon closure of the on-line survey on December 31, 2018 the data was downloaded to IBM’s SPSS program for analysis. No personal or identifying data, including IP addresses or emails, was download from SurveyMonkey. SPSS was used to run correlations, and descriptive statistics to examine the relationships of experience, education, and role with mentorship and organizational commitment. Outcomes Survey Results Demographics. Twenty-four APPs responded to email invitation and completed at least some portion of the survey, resulting in a response rate of 40%. Six surveys had missing data in some of Likert scale questions; the missing data was accounted for using intent to treat. The responding APPs’ age ranged from 26 to 63 years of age with an average of 42 years of age (SD = 9.37). There were three male respondents (12.5%) and 21 female respondents (87.5%). Over half of the sample had greater than 4 years of APP experience (58.3%, n = 14); leaving 41.7% APP MENTORSHIP 18 (n= 10) of the sample with less than 4 years of APP experience. Nurse practitioners comprised 70.8% (n = 17) of sample and PAs comprised 29.2% (n = 7) of the sample. NPs reported an average of 8.65 (SD = 7.88) years of RN experience, with years of RN experience ranging from 3 to 28 years. The majority of APPs (79.2%, n = 19) had advanced practice experience with at least one other employer; while 20.8% (n= 5) of the APPs had only worked with the IHDS since receiving their advance practice license (see Appendix M, Table 1M for additional demographic frequencies). Mentorship Experiences. Seven APPs (29.2%) stated they had no experience with mentorship, while 66.7% (n=16) reporting having an APP mentor at some point during their career and nine (37.5%) had served as a mentor during their APP career. The vague yet complex definition of mentorship is demonstrated by the fact 1/5 of the respondents (20.8%, n=5) felt that a mentor was the same as a preceptor. There was a wide variety of types of mentorship experienced, but informal relationships (54.2%, n=13) within the same organization (41.7%, n=10) was the most common. Table 2M (Appendix M) displays the complete mentorship perception and experiences data. The PBM includes a seven-point Likert scale that ranges from strongly disagree to strongly agree, giving a total score range of 19 to 133, with the lower scores corresponding to fewer perceived barriers to mentorship. The perceived barrier scores for the APPs at this organization ranged from 19 to 70, with a mean of 50.49 (SD=13.35). Access to mentors was scored as the greatest barrier, with the respondent range matching the total possible scores in this section, 4 to 28 and a mean of 16.05 (SD=6.03). Five potential barriers specific to APP mentorship were evaluated by a seven-point Likert scale that ranged from strongly disagree to strongly agree. Productivity requirements (M =3.28, APP MENTORSHIP 19 SD= 1.35) and role expectations (M =3.06, SD= 1.23) were more slightly prominent barriers than the mentoring (M =3.00, SD= 1.22) or teaching (M =2.61, SD= 0.89) skills of the APP (Table 5M, Appendix M). Mentorship Qualities. The rankings of specific characteristics within the domains of role modeling, career development, and psychosocial support can be seen in Appendix M, Figure 1M. Clinical skills (n=8) and teaching skills (n=6) were shared the highest ranking in the role modeling domain. In the area of career development professional knowledge (n=15) was clearly the highest-ranking desired attribute. The psychosocial domain also had clearly favored attribute of motivational support (n=14). Similar education (n=15) in the career development domain and same gender (n=12) in the psychosocial domain were clearly the least valued mentorship characteristics. The MFQ9 includes a seven-point Likert scale that ranges from strongly disagree to strongly agree, providing a total score range of 9 to 63, with higher scores corresponding to positive values in the functions of mentorship. The APPs scores ranged from 36 to 59, with a mean of 43.32 (SD=6.41). The individual domains, career development, psychosocial support, and role modeling showed nearly equal means at 14.16 (SD=6.41), 14.42 (SD=6.41), and 14.74 (SD=6.41), respectively. The total possible score for the domain levels are 3 to 21. Career development’s range was 9 to 21, psychosocial support showed the narrowest range at 12 to 18, and role modeling had a range of 11 to 21. Organizational Commitment. Employees with strong affective organizational commitment (OCA) scores are most often high performing employees who are committed to organizational growth and success. The normative/moral domain (OCN) score reflects the employee’s feelings of obligation to the organization and tend to represent moderately strong performers. A high score in the continuance/cost domain (OCC) can indicate the employee is APP MENTORSHIP 20 staying only to avoid loss of income or benefit. Research has associated high scores in this domain with bare minimum performance. The responding APPs’ OCA scores ranged from 2.50 to 6.25 on a 7-point Likert scale, with an average score of 4.86 (SD =0.98). OCN scores ranged from 2.25 to 5.88 on a 7-point Likert scale, with an average score of 4.26 (SD =0.99). OCC scores ranged from 2.38 to 5.50, with an average score of 3.89 (SD =0.93). Data Interpretation To answer the project questions, the statistical analyses include descriptive statistics (Appendix M, Tables 1M and 2M), and the inferential statistics of Spearman and Pearson correlations. The correlations table for the PBM can be found in Appendix M, Table 3M. The correlations for the MATCMEC can be found in Appendix M, Table 4M. Qualitative data obtained from open ended responses was analyzed for common themes. What do experienced APPs perceive as barriers to serving as a mentor? A mean total perceived barriers score of 50.49 out of 133 indicates the APPs in this survey perceived the overall barriers to mentorship at the IHDS as low. Years at the IHDS (r = -.417, p = .04), total MFQ9 (r = -.351, p = .09) and OCA (r = -.469, p = .02) demonstrate an inverse moderate correlation to perceived barriers. Since increasing years at an organization reduces perceived barriers to mentorship, but years of experience as an APP or RN shows no correlation, the involvement of an organization in building a mentorship culture be a positive benefit for the highest performing employees. The qualitative, open-ended question, which was placed prior to any PBM Likert scale questions: “Please share your thoughts in the box below on what barriers you feel are present when considering mentorship for the APP,” provided additional insight. Fifteen of the respondents (62.5%) answered this question; of those 11 (73%) stated time was the major barrier. APP MENTORSHIP 21 Comment details referenced daily schedule already too busy and lack of dedicated mentoring time. Three of the respondents stated that the organization needs to support mentorship and provide opportunities for APPs to interact outside of the daily patient schedule. Role, scope of practice differences, and location of care (inpatient vs. outpatient) were also mentioned by the APPs as barriers to mentorship. Healthcare literature often mentions productivity requirements of providers can have negative impacts on involvement or activities outside of direct patient care. For this IHDS, most APPs slightly disagreed with the statement that productivity requirements (M = 3.28) or role expectations (M = 3.06) were barriers to their ability to mentor. What attributes create a quality, effective mentoring relationship? Analysis of the mentor characteristics rankings shows that in the domain of role modeling, clinical skills (M =2.11, SD= 1.15) are the most desired attribute followed by teaching (M =2.42, SD= 1.43), organizational knowledge (M =3.21, SD= 1.36), bedside mannerisms (M =3.47, SD= 1.39), and time management (M =3.79, SD= 1.13). Even though the major barrier to mentorship from qualitative responses was time, time management ranked the lowest of desired role modeling characteristics; 37% (n=7) of the APPs completing the rankings put time management 5th (lowest) and no one ranked it 1st (highest). The domain of career development had the most closely grouped responses. The desired characteristics were professional knowledge (M =1.42, SD= 0.96), goal setting (M =2.84, SD= 0.90), networking (M =3.00, SD= 1.20), providing challenges to the mentee (M =3.11, SD= 1.10), and having similar educational backgrounds (M =4.63, SD= 0.83). Although similar educational backgrounds was ranked the lowest, two qualitative responses did indicate that NPs APP MENTORSHIP 22 and PAs or acute care NPs and outpatient NPs differ in both education and scopes of practice and therefor are not effective mentors for each other. In the domain of psychosocial support, the ranking of desired characteristics from most valued to least valued were motivational support (M =1.95, SD= 1.55), emotional support (M =2.47, SD= 0.77), friendship (M =3.11, SD= 1.05), availability after work (M =3.32, SD= 1.16), and being of the same gender (M =4.16, SD= 1.47). Does mentorship support improve the organizational commitment of the APPs? In this small sample, there was a weak inverse correlation of the OCA with provision of a mentor on hire (r = -.133, p = .54), which is an unexpected finding. It is possible that more recent hires are the only ones provided mentors and thus have not yet developed feelings of strong organizational commitment. However, having ever had an APP mentor showed a moderate positive association with OCA (rs = .333, p = .11). The MFQ9 scores demonstrated a moderate association with the OCA (r = .380, p = .07) and OCN (r = .352, p = .09) scores, indicating that mentorship is valued by higher performing employees who are committed to the organization. Additional observations. Two questions using a seven-point Likert scale that ranged from strongly disagree to strongly agree were included in the survey to determine the APPs interest in mentorship programs to build skills (M =5.44, SD= 1.15) or form relationships (M =5.50, SD= 1.03). Although most APPS felt their mentoring or teaching skills were not a barrier to mentorship, they expressed a strong desire for programs for skills and opportunities to building mentoring relationships. Teaching experience showed a weak moderate positive correlation with having been an APP mentor (rs = .367, p = .08), and OCN score (rs = .352, p = .09). Teaching experience also showed a weak inverse relationship with having had an APP mentor (rs =- .296, p = .16). Perhaps APP MENTORSHIP 23 the lack of a mentor is what spurred the involvement in teaching or perhaps a prior teaching experience gave the impression a mentor was not needed. It was assumed that teaching experience would reflect higher MFQ9 scores and this was not seen in the project results, as only a weak correlation (rs = .141, p = .51) was found. Evidence Translation to Build Mentorship Consistent with other mentorship studies, many correlations were observed, but lacked statistical significance. This is attributed to factors such as the recall bias of survey instruments and the complex nature of relationships and organizational commitment; as well as the illdefined, various concepts of mentorship. However, valuable insight into the needs and desires of the APP can be determined from this project. Overcoming the barriers of access and time, and providing opportunities for mentors and mentees to interact are key components needed to build a mentoring culture. This can be accomplished using virtual meetings outside of the established bi-monthly APP meetings (Shaw & Fulton, 2015). The IHDS has many educational and regulatory trainings that staff are required to attend throughout the year; thoughtful scheduling of the mentor/mentee pairs for this training meets multiple goals. Participation in organizational community events also offers opportunities for mentors and mentees to interact while building professional relationship bonds (Olivero, 2014; Shaw & Fulton, 2015). Specific education or resources on mentoring can be incorporated into the bi-monthly meetings to reinforce the organizational support of a mentorship. One APP stated “organizations do not encourage mentorship,” which highlights healthcare’s lack of a mentoring culture, as opposed to what is common in the management and education industries. The role differences between PAs and NPs presents mentoring challenges when the IHDS considers them interchangeable, as one respondent stated “there are no peers that do my job.” APP MENTORSHIP 24 This reflects the idea that a mentor must be identical just more experienced; however, mentors can come from a variety of backgrounds and be effective. Mentors can focus on various aspects of professional development and multiple mentors enrich the systems thinking a novice is learning (Allen & Eby, 2010; Olivero, 2014).The IHDS‘s current practice of providing an “APP partner” for role specific knowledge and support is a viable way to address this challenge and improve the APPs understanding of the mentorship construct. Another common assumption is that the mentor/mentee pair should be of the same gender. This could compound the NP and PA differences as most NPs are female and most PAs are male. However, the results of this project and the existing literature show that gender is not perceived barrier to developing mentoring relationships. The results of this gap analysis indicate a mentorship program or resource that provides motivational support, professional role modeling, and clinical knowledge in such a way that it is not perceived as a time burden and is accessible by APPs across locations would be welcomed. There are existing meetings that can incorporate mentoring information as well as increase opportunities for interactions. Technology can be used for both synchronous and asynchronous meetings so the resource fits easily into busy schedules. Just as the IDHS’s recent formal orientation has expanded from oncology to other specialties, this resource could be adaptable to other departments within the IDHS. Given the variety of practice settings at the IDHS, this resource could also be used large hospitals with multiple resources, small practices with only a few providers, and healthcare academia. To improve integration of mentorship into healthcare, the APP mentees should have the opportunity to understand the didactic concept of mentorship, experience mentoring relationships, and practice the skills of quality mentoring during the basic educational process. The project data is APP MENTORSHIP 25 not be limited to use by APPs; it can be used by various stakeholders in healthcare. Human resources personnel can use the information on organizational commitment, expectations, and turnover to support the value of robust on-boarding programs that include mentorship. Quality improvement departments can expand the data review to look at billing corrections, ordering errors, and patient satisfaction scores between groups of novice APPs before the mentor program and after implementation of the mentor program. Organizations can use the study data and mentor program as a recruitment tool. Mentor recognition provides the organization with a means to increase retention of its strongest APPs. The small sample size and unique characteristics of the organization limit the generalizability of these results to all healthcare organizations. The APPs at this IDHS do not have productivity requirements associated with their income; for organizations with productivity based salary structures the barrier results could be different. The respondents scored high in organizational commitment, indicating these employees are the high performers, who are more likely to participate in organizational activities outside the role minimums which can skew the results regarding the mentoring of needs of employees scoring high in the OCC. Additional areas for study include longitudinal career paths, patient outcomes related to a mentorship program, and patient care costs for mentored and non-mentored APPs. To meet the goals of the Quadruple Aim, healthcare organizations and providers must adapt the evidence from other professional disciplines; as well as conduct research, obtain data, and develop programs to serve as a benchmark for the growth of APP mentorship. Conclusion Mentorship has the potential to increase the APP’s job satisfaction, which will strengthen organizational commitment and reduce turnover, potentially saving millions of healthcare dollars APP MENTORSHIP 26 spent on recruiting and training providers. Subsequently, a well-mentored APP will be a more effective, integrated provider, further reducing healthcare costs, creating a self-propagating mentorship culture, and improving patient outcomes. Patients will be the ultimate beneficiary of well-mentored APPs with high levels of job satisfaction and organizational commitment, through highly efficient teamwork, clear organizational communication, meeting (even exceeding) quality measures, and continuity of care. APP MENTORSHIP 27 References Allen, T.D., & Eby, L.T. (2010). The Blackwell handbook of mentoring: A multiple perspective approach [Kindle Edition]. West-Sussex, United Kingdom: Wiley-Blackwell. Retrieved from Amazon.com American Association of Nurse Practitioners. (2017). More than 234,000 licensed nurse practitioners in the United States [Press Release]. Retrieved from https://www.aanp.org/192-press-room/2017-press-releases/2098-more-than-234-000licensed-nurse-practitioners-in-the-united-states Anderson, C. (2012). 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Retrieved from https://prodcmsstoragesa.blob.core.windows.net/uploads/files/2016StatisticalProfileofCer tifiedPhysicianAssistants.pdf Noe, R. (1988). An investigation of the determinants of successful assigned mentoring relationships. Personnel Psychology, 41, 457-479. Retrieved from http://login.ezproxy1.lib.asu.edu/login?url=https://search-proquestcom.ezproxy1.lib.asu.edu/docview/1304559368?accountid=4485 Olivero, O.A. (2014). Interdisciplinary mentoring in science [Kindle Edition]. New York, NY: Elsevier, Inc. Retrieved from Amazon.com Pathak, D., & Srivastava, S. (2017). Understanding the role of demographic diversity on mentoring and job satisfaction: A study on managers in information technology (IT) industry in India. South Asian Journal of Management, 24(2), 41-64. Retrieved from Retrieved from http://login.ezproxy1.lib.asu.edu/login?url=https://search-proquestcom.ezproxy1.lib.asu.edu/docview/1938167227?accountid=4485 Pillemer, K., & Rheaume, C. (2013). Leading the way: The busy nurse’s guide to supervision in long-term care (3rd ed). Delmar-Cengage Learning: Clifton Park NY. Poghosyan, L., Liu, J., Shang, J., & D'Aunno, T. (2017). Practice environments and job satisfaction and turnover intentions of nurse practitioners: Implications for primary care workforce capacity. Health Care Management Review, 42, 162-171. doi: 10.1097/HMR.0000000000000094 Pogodzinski, B. (2015). Administrative context and novice teacher-mentor interactions. Journal of Educational Administration, 53, 40-65. doi: 10.1108/jea-06-2013-0073. APP MENTORSHIP 33 Race, T.K., & Skees, J. (2010). Improving outcomes through mentorship on all levels of nursing. Critical Care Nursing Quarterly, 33, 163-174. Ragins, B.R., & Cotton, J.L. (1991). Easier said than done: Gender differences in perceived barriers to gaining a mentor. Academy of Management Journal, 34, 939-951. Ragins, B.R., & Kram, K.E. (2007). The Handbook of Mentoring at Work: Theory, Research, and Practice. Thousand Oaks, CA: Sage Publications. Rosenfield, J. (2018). Calculating the financial costs of physician burnout. Medical Economics [blog]. Retrieved from https://www.medicaleconomics.com/medical-economicsblog/calculating-financial-costs-physician-burnout Saks, A.M., Uggerslev, K.L., & Fassina, N.E. (2007). Socialization tactics and newcomer adjustment: A meta-analytic review and test of a model. Journal of Vocational Behavior, 70, 413-446. doi: 10.1016/j.jvb.2006.12.004 Shaw, M.E., & Fulton, J. (2015). Mentorship in healthcare ( 2nd ed). [Kindle edition]. Cumbria, CA: M&K Publishing Swan, M., Ferguson, S., Change, A., Larson, E., & Smaldone, A. (2015). Quality of primary care by advanced practice nurses: a systematic review. International Journal for Quality in Health Care, 27, 396-404. doi: 10.1093/intqhc/mzv054 Tuttle, M. (2002). A review and critique of Van Maanen and Schein's "Toward a Theory of Organizational Socialization and Implications for Human Resource Development. Human Resource Development Review, 1, 66-90 Running head: APP MENTORSHIP 34 Appendix A Preliminary Searches of PubMed, Cochrane, and CINHAL Databases Figure 1A. PubMed Searches APP MENTORSHIP Figure 2A. Cochrane Searches This search highlights the generalized use of the word mentor, especially when combined with satisfaction. Many of the articles retrieved were related to medication or therapy programs that paired patients who had a chronic disease with newly diagnosed patients. 35 APP MENTORSHIP Figure 3A. CINAHL Searches 36 APP MENTORSHIP 37 Appendix B Mentorship in Teaching or Business Management Databases Figure 1B. ProQuest Database Searches APP MENTORSHIP 38 Appendix C APP Mentorship in Dissertation and Thesis Database Figure 1C. ProQuest Dissertation and Thesis Database APP MENTORSHIP 39 Appendix D Search of CINHAL Database Figure 1D. CINHAL Search including Residency Programs This search also reflects the widespread and varied use of the words residency or fellowship, as well as the popularity of registered nurse residency programs. Running head: APP MENTORSHIP 40 Appendix E Final Search of Healthcare Databases Figure 1E. Final PubMed search Figure 2E. Final CINHAL search APP MENTORSHIP Figure 3E. Final MEDLINE and PsycINFO search 41 Running head: APP MENTORSHIP 42 Appendix F Final Search of Business Management and Education Databases Figure 1F. ABI/INFORM Database Search Figure 2F. ERIC Database Search APP MENTORSHIP 43 Appendix G Mentorship Research Studies Evaluation Summary Table 1G. Evaluation Table Citation 1 Theory/ Conceptual Framework Design/ Method Sample/ Setting Major Variables & Definitions Measurement/ Instrumentation Data Analysis Findings/ Results Horner, D. (2017). Mentoring: Positively influencing job satisfaction and retention of new hire nurse practitioners. Watson’s Caring Model (1988) Cross-Sectional Survey- Mixed methods, Convenience Sample N=69 n=37 IV1-M IV2 -MQ DV- JS MNPJSS – 2001Cronbach's α 0.96(entire scale) 0.79 to 0.94 (subscales). One-way ANOVA Cross tabulation M = +JS 4.4 vs 4.39 Purpose: Does M positively influence NP JS? P=NS Reg Setting: PC, H Variables: YNP, YRN, Sp, D, G, E NST MQ OEQ 27% provided M at hire Of 73% w/o M, 100% would have liked M Level/Quality of Evidence; Decision for practice/ application to practice LOE: VI Demographics generalizable to NPs, not PAs. Any form or length of M perceived as valuable Weakness: Small, regional study, recall Funding: NS based –2/3 M themes participants on Exclusion – -constructive Bias: none their job over 3 other APPs feedback years. Lots of -shared knowledge %, 𝑥𝑥 , and -encouraged tables, but -availability unable to Key: A-Autonomy; adm-administration; ATS-Anticipated Turnover Scale; C-certified; CCS-Cross Sectional Survey; D-Degree; DV-dependent variable; FNP-Family Nurse Practitioner; FM-Formal Mentoring; G-Gender; H-Hospital; IM-Informal Mentoring; IV-independent variable; JS-Job Satisfaction; M-mentor/mentorship; mmonths of practice; MATCMEC-Meyers & Allen’s Three Component Model of Employee Commitment; MBI-Maslach Burnout Inventory; MF-Mentoring Functions; MFQ9-Mentoring Functions Questionnaire; MMM-Multidimensional Mentoring Measure; MNPJSS-Misner Nurse Practitioners Job Satisfaction Survey; MQMentorship Quality; N-number of sample size; n-number of final participants; NP-Nurse Practitioner; NS-Not Stated; NST-Nonstandard Tool; Ntl-National; OCOrganizational Commitment; OEQ-Open-Ended Questions; OSI -Organizational Socialization Inventory; P-Power; PA- Physician Assistant; PC-Primary Care; QMRSQuality of Mentoring Relationship Scale; RA-Role Ambiguity; RAS-Role Ambiguity Scale; rec-recruitment; Reg-Regional; RN-Registered Nurse; sig-significant; SpSpecialty; SSQ6-Social Support Questionnaire Short Version; TI-Turnover Intent; WLC-Work-Life Conflict; Y-Years of Practice; Country: USA Inclusion- C NP, English Speaking 100% rate M beneficial APP MENTORSHIP 44 Citation 2 Theory/ Conceptual Framework Design/ Method Sample/ Setting Major Variables & Definitions Measurement/ Instrumentation Data Analysis Faraz, A. (2016). Novice nurse practitioner workforce transition and turnover intention in primary care. NS (3-compenent model or TCM) Descriptive CSS, online rec & adm, Convenience sample of accredited Master’s programs graduates N=293 n=177 IV-JS, A, RA DV- TI 80%P w/ 5% sig =131 Variables: YRN, D, M, G, Sp MNPJSS -2001Cronbach's α 0.96(entire scale) 0.79 to 0.94 (subscales). Hierarchical multiple regression analysis Country: USA Funding: NS Bias: Purpose: 1. Describe individual characteristics, role acquisition & JS of NPs. 2. Identify factors of successful Y1 and TI. Ntl Setting: PC, Inclusion YNP - 3m1y Exclusion NS ATS – Cronbach's α per developer 0.84, per 2010 meta analysis w/ RN 0.89 per DeMilt study 0.68 SSQ6 Cronbach's α 0.90-0.93 RAS Cronbach's α 0.84 Reasons for Not M -productivity demands -too many residents -specialty practice calculate correlations IV – A p=.001 LOE: VI Adequate sample size. States balance of M & A needed. RA needs M. Findings/ Results IV – RA p=.03 R2=0.476 MNPJSS = 𝑥𝑥 4.43 moderate JS M -no sig impact on TI or JS Level/Quality of Evidence; Decision for practice/ application to practice Weakness: State distribution not reported, could impact A and thus JS and TI 77% desired M or residency Key: A-Autonomy; adm-administration; ATS-Anticipated Turnover Scale; C-certified; CCS-Cross Sectional Survey; D-Degree; DV-dependent variable; FNP-Family Nurse Practitioner; FM-Formal Mentoring; G-Gender; H-Hospital; IM-Informal Mentoring; IV-independent variable; JS-Job Satisfaction; M-mentor/mentorship; mmonths of practice; MATCMEC-Meyers & Allen’s Three Component Model of Employee Commitment; MBI-Maslach Burnout Inventory; MF-Mentoring Functions; MFQ9-Mentoring Functions Questionnaire; MMM-Multidimensional Mentoring Measure; MNPJSS-Misner Nurse Practitioners Job Satisfaction Survey; MQMentorship Quality; N-number of sample size; n-number of final participants; NP-Nurse Practitioner; NS-Not Stated; NST-Nonstandard Tool; Ntl-National; OCOrganizational Commitment; OEQ-Open-Ended Questions; OSI -Organizational Socialization Inventory; P-Power; PA- Physician Assistant; PC-Primary Care; QMRSQuality of Mentoring Relationship Scale; RA-Role Ambiguity; RAS-Role Ambiguity Scale; rec-recruitment; Reg-Regional; RN-Registered Nurse; sig-significant; SpSpecialty; SSQ6-Social Support Questionnaire Short Version; TI-Turnover Intent; WLC-Work-Life Conflict; Y-Years of Practice; APP MENTORSHIP 45 Citation 3 Theory/ Conceptual Framework Design/ Method Sample/ Setting Major Variables & Definitions Measurement/ Instrumentation Data Analysis Findings/ Results DeMilt, D. (2011). Nurse practitioners’ job satisfaction and intent to leave current positions, the nursing profession, and the nurse practitioner role as a direct care provider. NS (3-compenent model or TCM) Descriptive CSS, Convenience Sample of those who approached rec table at ntl conference N=35,000 n=254 IV-JS DV- TI t-test P=NS Variables: YRN, YNP, D, MNPJSS -2001Cronbach’s α 0.96(entire scale) 0.79 to 0.94 (subscales). IV JS MNPJSS = 𝑥𝑥 4.05 +TI 𝑥𝑥 4.63 -TI p <.001 Country: USA Funding: NS Purpose: Describe NP JS effect on TI Ntl Setting: PC, H Inclusion YNP->6m Excluded – nonworking, or not in direct patient care ATS – Cronbach’s α per developer 0.84, per this study 0.68, per 2010 meta analysis w/ RN 0.89 Reasons for leaving job 19% lack of colleague relationship 20% little practice control 22% not valuable team member Level/Quality of Evidence; Decision for practice/ application to practice LOE: VI Sig finding of dissatisfaction increasing intent to leave. 2/3 of reasons could be helped with M Weakness – Participating NPs may have had unknown motivation to approach booth/participate Bias: selfselected participants Key: A-Autonomy; adm-administration; ATS-Anticipated Turnover Scale; C-certified; CCS-Cross Sectional Survey; D-Degree; DV-dependent variable; FNP-Family Nurse Practitioner; FM-Formal Mentoring; G-Gender; H-Hospital; IM-Informal Mentoring; IV-independent variable; JS-Job Satisfaction; M-mentor/mentorship; mmonths of practice; MATCMEC-Meyers & Allen’s Three Component Model of Employee Commitment; MBI-Maslach Burnout Inventory; MF-Mentoring Functions; MFQ9-Mentoring Functions Questionnaire; MMM-Multidimensional Mentoring Measure; MNPJSS-Misner Nurse Practitioners Job Satisfaction Survey; MQMentorship Quality; N-number of sample size; n-number of final participants; NP-Nurse Practitioner; NS-Not Stated; NST-Nonstandard Tool; Ntl-National; OCOrganizational Commitment; OEQ-Open-Ended Questions; OSI -Organizational Socialization Inventory; P-Power; PA- Physician Assistant; PC-Primary Care; QMRSQuality of Mentoring Relationship Scale; RA-Role Ambiguity; RAS-Role Ambiguity Scale; rec-recruitment; Reg-Regional; RN-Registered Nurse; sig-significant; SpSpecialty; SSQ6-Social Support Questionnaire Short Version; TI-Turnover Intent; WLC-Work-Life Conflict; Y-Years of Practice; APP MENTORSHIP 46 Citation 4 Theory/ Conceptual Framework Design/ Method Sample/ Setting Major Variables & Definitions Measurement/ Instrumentation Data Analysis Findings/ Results BartleyDaniele., P. (2014). Family nurse practitioner mentoring relationships’ impact on organizational commitment. Kram’s (1985 Mentoring Theory, Meyer & Allen’s (1997) Organizational Commitment Model CSS N= 1500 n=403 n M=203 n w/oM=178 IV1-M IV2 -MQ IV3-MF IV4-IM/FM DV- OC MATCMEC – Cronbach’s α affective 0.85 continuance 0.79 normative 0.73 Variables: MFQ9 Cronbach’s α 0.91 0.82-0.85 (subscales) ANOVA, MANOVA, descriptive analysis, Pearson’s correlations IV1 M Affective p = .003 Continuance p = Nsig Normative p = 0.14 IV2 MQ Affective p < .001 Continuance p = Nsig Normative p = 0.11 IV3 MF Affective p < .001 Continuance p = Nsig Normative p = Nsig IV4 IM/FM Affective p = .029 Continuance p = Nsig Normative p = 0.30 Country: USA Funding: NS Bias: none Postal/Email survey of AANP members Purpose: Determine M, MQ, MF’s effect on OC P=127 Ntl Setting: PC FNP Inclusion – Y1, fulltime employment Exclusion – dual C QMRS Cronbach’s α 0.88 Level/Quality of Evidence; Decision for practice/ application to practice LOE: VI M increases affective & normative OC, Nsig of continuance OC maybe related to challenges in TTP. Format of mentoring less important than presence of mentoring. Weakness: Recall based, average 9 yrs of practice, M NP maybe more likely to respond. Only FNP included, maynot apply to specialities. Maynot apply to DNP (3% of study size) Key: A-Autonomy; adm-administration; ATS-Anticipated Turnover Scale; C-certified; CCS-Cross Sectional Survey; D-Degree; DV-dependent variable; FNP-Family Nurse Practitioner; FM-Formal Mentoring; G-Gender; H-Hospital; IM-Informal Mentoring; IV-independent variable; JS-Job Satisfaction; M-mentor/mentorship; mmonths of practice; MATCMEC-Meyers & Allen’s Three Component Model of Employee Commitment; MBI-Maslach Burnout Inventory; MF-Mentoring Functions; MFQ9-Mentoring Functions Questionnaire; MMM-Multidimensional Mentoring Measure; MNPJSS-Misner Nurse Practitioners Job Satisfaction Survey; MQMentorship Quality; N-number of sample size; n-number of final participants; NP-Nurse Practitioner; NS-Not Stated; NST-Nonstandard Tool; Ntl-National; OCOrganizational Commitment; OEQ-Open-Ended Questions; OSI -Organizational Socialization Inventory; P-Power; PA- Physician Assistant; PC-Primary Care; QMRSQuality of Mentoring Relationship Scale; RA-Role Ambiguity; RAS-Role Ambiguity Scale; rec-recruitment; Reg-Regional; RN-Registered Nurse; sig-significant; SpSpecialty; SSQ6-Social Support Questionnaire Short Version; TI-Turnover Intent; WLC-Work-Life Conflict; Y-Years of Practice; APP MENTORSHIP 47 Citation 5 Theory/ Conceptual Framework Design/ Method Sample/ Setting Major Variables & Definitions Measurement/ Instrumentation Data Analysis Findings/ Results Kim, J. (2017). Work-life conflict of married and childless single female workers. NS (Organizational Culture Theory, Work-Family Conflict Construct) CSS N= 325 n=288 P=NS MATCMEC Cronbach’s α affective 0.85 continuance 0.79 normative 0.73 t-test linear regression, hierarchical moderated regressions IV1-M p < .001 Purpose: Examine M role OC, WLC, in a maledominated culture IV1-M IV2-WLC DV- OC Country: S. Korea Funding: NS Bias: None Citation 6 Theory/ Conceptual Framework Design/ Method Pathak, D. (2017). Understanding the role of Kram’s (1985) Mentoring Theory CSS Natl Setting: 6 companies w/ >1000 employees Inclusion: Female Exclusion: Male, single Female w/children Variables: E, Y employed, Age, Marital status Ahmad’s (2011) WLC Cronbach’s α 0.74 Noe’s (1988) MF Scale Cronbach’s α = 0.92 0.79-0.85 (subscales) IV2-WLC p < .001 -role model work-life balance & professionalism -gender/role definitions Sample/ Setting Major Variables & Definitions Measurement/ Instrumentation Data Analysis Findings/ Results N= 200 n=200 IV1-M DV- JS MMM Cronbach’s α = 0.93 Regression analysis, ttest, Tukey’s IV1-M R= 0.74; p > .0.05 P=NS Level/Quality of Evidence; Decision for practice/ application to practice LOE: VI WLC negatively impacts OC, but M mitigates it. The presence of M increases OC. Female NP, 2/3 physicians are male Weakness: Overall education less, and culture different from US Level/Quality of Evidence; Decision for practice/ application to practice LOE: VI Employees need both autonomy Key: A-Autonomy; adm-administration; ATS-Anticipated Turnover Scale; C-certified; CCS-Cross Sectional Survey; D-Degree; DV-dependent variable; FNP-Family Nurse Practitioner; FM-Formal Mentoring; G-Gender; H-Hospital; IM-Informal Mentoring; IV-independent variable; JS-Job Satisfaction; M-mentor/mentorship; mmonths of practice; MATCMEC-Meyers & Allen’s Three Component Model of Employee Commitment; MBI-Maslach Burnout Inventory; MF-Mentoring Functions; MFQ9-Mentoring Functions Questionnaire; MMM-Multidimensional Mentoring Measure; MNPJSS-Misner Nurse Practitioners Job Satisfaction Survey; MQMentorship Quality; N-number of sample size; n-number of final participants; NP-Nurse Practitioner; NS-Not Stated; NST-Nonstandard Tool; Ntl-National; OCOrganizational Commitment; OEQ-Open-Ended Questions; OSI -Organizational Socialization Inventory; P-Power; PA- Physician Assistant; PC-Primary Care; QMRSQuality of Mentoring Relationship Scale; RA-Role Ambiguity; RAS-Role Ambiguity Scale; rec-recruitment; Reg-Regional; RN-Registered Nurse; sig-significant; SpSpecialty; SSQ6-Social Support Questionnaire Short Version; TI-Turnover Intent; WLC-Work-Life Conflict; Y-Years of Practice; APP MENTORSHIP demographic diversity on mentoring and job satisfaction: A study on managers in information technology (IT) industry in India. (Organizational Culture Theory) 48 Purpose: Understand the relationship between M and JS, and diversity’s role in M satisfaction and JS Ntl Setting: Private IT sector companies with mentor policies, managers, Variables: G, Age, Management Level NST JS (modified/combined 2 scales) multiple comparisons M - No gender differences Country: India Funding: NS Bias: None Citation 7 Theory/ Conceptual Framework Design/ Method Sample/ Setting Major Variables & Definitions Measurement/ Instrumentation Data Analysis Findings/ Results DeAngelis, K. (2013). The impact of preservice preparation and early career support on novice teachers’ career intentions and decisions. NS (Organizational Development Theory, Career Cycles Theory) CSS & Longitudinal administrative data N= 2,221 n= 1,159 IV1-M IV2 -MQ DV- TI NST survey – collaboration of school systems Purpose: Examine interactions of preservice preparation and career support on Reg Setting: Y1 teachers public school Descriptive statistics, MANOVA, predicated probabilities IV1-M p < .05 same subject & high MQ Nsig different subject or poor MQ P=NS Variables: G, Sp, same Sp M, IV2 -MQ p < .001 high MQ Nsig poor MQ and support for JS and to increase OC. States need for design of M guides. Service industry employees backbone – JS increases business success Weakness – self-reporting and limited geographic area, outside of US Level/Quality of Evidence; Decision for practice/ application to practice LOE: VI Quality is more important than M availability. Subject specialty improved quality of M. Weakness: Key: A-Autonomy; adm-administration; ATS-Anticipated Turnover Scale; C-certified; CCS-Cross Sectional Survey; D-Degree; DV-dependent variable; FNP-Family Nurse Practitioner; FM-Formal Mentoring; G-Gender; H-Hospital; IM-Informal Mentoring; IV-independent variable; JS-Job Satisfaction; M-mentor/mentorship; mmonths of practice; MATCMEC-Meyers & Allen’s Three Component Model of Employee Commitment; MBI-Maslach Burnout Inventory; MF-Mentoring Functions; MFQ9-Mentoring Functions Questionnaire; MMM-Multidimensional Mentoring Measure; MNPJSS-Misner Nurse Practitioners Job Satisfaction Survey; MQMentorship Quality; N-number of sample size; n-number of final participants; NP-Nurse Practitioner; NS-Not Stated; NST-Nonstandard Tool; Ntl-National; OCOrganizational Commitment; OEQ-Open-Ended Questions; OSI -Organizational Socialization Inventory; P-Power; PA- Physician Assistant; PC-Primary Care; QMRSQuality of Mentoring Relationship Scale; RA-Role Ambiguity; RAS-Role Ambiguity Scale; rec-recruitment; Reg-Regional; RN-Registered Nurse; sig-significant; SpSpecialty; SSQ6-Social Support Questionnaire Short Version; TI-Turnover Intent; WLC-Work-Life Conflict; Y-Years of Practice; APP MENTORSHIP 49 novice teachers’ career intentions Country: USA DV- TI Correlation of M frequency & MQ r=.881 Funding: NS Bias: survey questions filled data gathering needs of school districts Citation 8 Theory/ Conceptual Framework Design/ Method Sample/ Setting Major Variables & Definitions Measurement/ Instrumentation Data Analysis Findings/ Results Pogodzinski, B. (2015). Administrative context and novice teachermentor interactions. NS (Organizational Theory of Leadership, Transformational Theory) Cross-sectional Purposeful sample N= 380 n=184 Purpose: Examine administration’s role in M P=NS IV1-MQ IV2-Adm Climate DV- Job roles DV2-M contact frequency NST MQ MF MBI Cronbach’s α emotional 0.90 depersonalization 0.76 personal accomplishment 0.76 Logistic regression models, ttest IV1-MQ p < .001 DV1- Job roles IV1-MQ p < .05 DV2-M contact frequency IV2-Adm Climate p < .001 DV1- Job roles Country: USA Funding: NS Bias: None Reg Setting: 2 states & 11 school districts – 1 state req. Mx3y, 1 state req. Mx1y Variables: G, Yteaching, IV2-Adm Climate p < .05 DV2-M contact frequency No reason provided for completed TI – could be move out of state or to private school or poor JS Level/Quality of Evidence; Decision for practice/ application to practice LOE: VI Supportive adm climate increases frequency of contact with M. Weakness – other elements of school context could influence results, both states had required formal M programs (1y & 3yrs). Key: A-Autonomy; adm-administration; ATS-Anticipated Turnover Scale; C-certified; CCS-Cross Sectional Survey; D-Degree; DV-dependent variable; FNP-Family Nurse Practitioner; FM-Formal Mentoring; G-Gender; H-Hospital; IM-Informal Mentoring; IV-independent variable; JS-Job Satisfaction; M-mentor/mentorship; mmonths of practice; MATCMEC-Meyers & Allen’s Three Component Model of Employee Commitment; MBI-Maslach Burnout Inventory; MF-Mentoring Functions; MFQ9-Mentoring Functions Questionnaire; MMM-Multidimensional Mentoring Measure; MNPJSS-Misner Nurse Practitioners Job Satisfaction Survey; MQMentorship Quality; N-number of sample size; n-number of final participants; NP-Nurse Practitioner; NS-Not Stated; NST-Nonstandard Tool; Ntl-National; OCOrganizational Commitment; OEQ-Open-Ended Questions; OSI -Organizational Socialization Inventory; P-Power; PA- Physician Assistant; PC-Primary Care; QMRSQuality of Mentoring Relationship Scale; RA-Role Ambiguity; RAS-Role Ambiguity Scale; rec-recruitment; Reg-Regional; RN-Registered Nurse; sig-significant; SpSpecialty; SSQ6-Social Support Questionnaire Short Version; TI-Turnover Intent; WLC-Work-Life Conflict; Y-Years of Practice; APP MENTORSHIP 50 Citation 9 Theory/ Conceptual Framework Design/ Method Sample/ Setting Major Variables & Definitions Measurement/ Instrumentation Data Analysis Findings/ Results Farnese, M. (2016). Learning the ropes: The protective roles of mentoring in a correctional police officers’ socialization process Organizational socialization, Nonaka’s (1994) dynamic model CSS Mailed to University for anonymity N= 396 n=117 IV1-FM DV1- OC DV2-TI Moderated regression models, IV1-FM p =0.27 DV1- OC Purpose: Role of FM on OC & TI Ntl Setting: Multiple correctional facilities MATCMEC Cronbach’s α affective 0.85 continuance 0.79 normative 0.73 Country: Italy Funding: Italian Ministry of Justice Bias: Vested interested in program success P= Variables: G, D, Age Mentorcompleted formal training & not supervisor OSI Cronbach’s α 0.83 IV1-FM p < .001 DV2-TI Level/Quality of Evidence; Decision for practice/ application to practice LOE: VI OSI examines many aspects of M – all subscales sig Formalized training for M OSI indicates M creates culture of training Weakness Self-reporting, small sample size, contractual obligations limit TI Key: A-Autonomy; adm-administration; ATS-Anticipated Turnover Scale; C-certified; CCS-Cross Sectional Survey; D-Degree; DV-dependent variable; FNP-Family Nurse Practitioner; FM-Formal Mentoring; G-Gender; H-Hospital; IM-Informal Mentoring; IV-independent variable; JS-Job Satisfaction; M-mentor/mentorship; mmonths of practice; MATCMEC-Meyers & Allen’s Three Component Model of Employee Commitment; MBI-Maslach Burnout Inventory; MF-Mentoring Functions; MFQ9-Mentoring Functions Questionnaire; MMM-Multidimensional Mentoring Measure; MNPJSS-Misner Nurse Practitioners Job Satisfaction Survey; MQMentorship Quality; N-number of sample size; n-number of final participants; NP-Nurse Practitioner; NS-Not Stated; NST-Nonstandard Tool; Ntl-National; OCOrganizational Commitment; OEQ-Open-Ended Questions; OSI -Organizational Socialization Inventory; P-Power; PA- Physician Assistant; PC-Primary Care; QMRSQuality of Mentoring Relationship Scale; RA-Role Ambiguity; RAS-Role Ambiguity Scale; rec-recruitment; Reg-Regional; RN-Registered Nurse; sig-significant; SpSpecialty; SSQ6-Social Support Questionnaire Short Version; TI-Turnover Intent; WLC-Work-Life Conflict; Y-Years of Practice; APP MENTORSHIP 51 Citation 10 Conceptual Framework Design/ Sample/ Method/Sampling Setting Major Variables Studies & Their Definitions Measurement/ Instrumentation Data Analysis Findings/ Results Manzi, A. (2017). Mentorship & coaching to support strengthening healthcare systems: lessons learned across the five Population Health Implementation & Training (PHIT) partnership projects in subSharan Africa. African Health Initiative Mentorship & Coaching Mixed Method, Semi-structured interviews of key project informants & PHIT project literature review IV=M DV=various health outcomes NST Questionnaire administered in one on one interviews Conceptual Framework -Each system has unique challenges but all show benefit with M -Improved service delivery & quality -Increased leadership & EPB skills -Increased workforce motivation Country: Africa Purpose: Evaluation of M component of PHIT projects to improve quality of care N= NS n=NS Ntl Setting: 5 PHIT project sites that implemented mentorship programs to improve health outcomes Variables: Priority areas, M training, Level/Quality of Evidence; Decision for practice/ application to practice LOE: VI Part of larger study of PHIT, covering 7 years in underserved areas, using a variety of programs and correlated with health outcome measure. Weakness: No demographic data of “key informants”, other factors in PHIT could account for successes Funding: Doris Duke Charitable Foundation Bias: None Key: A-Autonomy; adm-administration; ATS-Anticipated Turnover Scale; C-certified; CCS-Cross Sectional Survey; D-Degree; DV-dependent variable; FNP-Family Nurse Practitioner; FM-Formal Mentoring; G-Gender; H-Hospital; IM-Informal Mentoring; IV-independent variable; JS-Job Satisfaction; M-mentor/mentorship; mmonths of practice; MATCMEC-Meyers & Allen’s Three Component Model of Employee Commitment; MBI-Maslach Burnout Inventory; MF-Mentoring Functions; MFQ9-Mentoring Functions Questionnaire; MMM-Multidimensional Mentoring Measure; MNPJSS-Misner Nurse Practitioners Job Satisfaction Survey; MQMentorship Quality; N-number of sample size; n-number of final participants; NP-Nurse Practitioner; NS-Not Stated; NST-Nonstandard Tool; Ntl-National; OCOrganizational Commitment; OEQ-Open-Ended Questions; OSI -Organizational Socialization Inventory; P-Power; PA- Physician Assistant; PC-Primary Care; QMRSQuality of Mentoring Relationship Scale; RA-Role Ambiguity; RAS-Role Ambiguity Scale; rec-recruitment; Reg-Regional; RN-Registered Nurse; sig-significant; SpSpecialty; SSQ6-Social Support Questionnaire Short Version; TI-Turnover Intent; WLC-Work-Life Conflict; Y-Years of Practice; APP MENTORSHIP 52 Appendix H Mentorship Research Studies Synthesis Summary Table 1H. Synthesis Table Author/Year Industry Healthcare Business Educational Correctional Horner 2017 Faraz 2016 DeMilt 2011 BartleyDaniele 2014 69/37 293/177 35K/254 1500/403 N/n Demographics % Female Age N/n N/n N/n 92.9% 𝑥𝑥 35 (21>50) 97.6% 𝑥𝑥 47 (2472) 91.5% 𝑥𝑥 49 (26-76) 86.5% 13.5% 𝑥𝑥 11.5 (1-28) <3 35.1% >3 64.9% 79.7% 5.1% <1 <3 100% 90.1% 9.9% 𝑥𝑥 8.1 (1-35) 𝑥𝑥 6.3 (0-35) 98% 3% 𝑥𝑥 9.3 (1-44) Job Satisfaction Turnover Intent Organizational Commitment ↑ Nsig Nsig Desire for Mentorship Role Definition Work-life balance Program Type + + + + + + + B Bachelors Masters & Post Certif >Doctorate Years Exp Years Current Job Outcomes Themes 𝑥𝑥 48 (27-67) B Kim 2016 Pathak 2017 325/288 200/200 N/n N/n 100% 79% 20-40 (20-61) 43% 5% 43% NS <3 52% >3 48% 0-5 34% 5-10 46% >10 20% NS ↑ ↑ ↑ DeAngelis 2013 N/n Pogodzinski 2015 N/n Farnese 2016 N/n 2221/1159 380/184 79% 𝑥𝑥 27 >80% NS NS NS 4.6% <2 <2 100% <3 <3 <1 <1 ↓ Manzi 2017 N/n NS 396/117 33% 𝑥𝑥 26 NS NS NS ↓ ↑ ↑ + + + F F F + + + F + F + + B Key: ↑or ↓ Effect of mentorship; B-Both Formal & Informal; F-Formal Mentorship Program; I-Informal Mentorship; N-number of sample size; n-number of final participants NS-Not stated; Nsig-Not statistically significant APP MENTORSHIP Appendix I Theoretical Framework and Evidence-Based Practice Model Diagrams Figure 1I. The Theory of Organizational Socialization (Tuttle, 2002, p. 80) 53 APP MENTORSHIP Figure 2I. Application of Organizational Socialization and Mentorship Themes (Adapted from Saks, Uggerslev, & Fassina, 2007, p. 417) Figure 3I. Meyer and Allen’s Three Component Model of Employee Commitment (Kreitner & Kinicki, 2013, p.164) 54 APP MENTORSHIP Figure 4I. The Stevens Star Model of Knowledge Transfer (©Stevens, 2015. Used with Permission) 55 APP MENTORSHIP Appendix J Instrument Permission Letters Figure 1J. MATCMEC Academic Subscription Notification 56 APP MENTORSHIP Figure 2J. MFQ9 Permission Letter 57 APP MENTORSHIP Figure 3J. PBM Permission Letter 58 APP MENTORSHIP Appendix K Complete Survey 59 APP MENTORSHIP 60 APP MENTORSHIP 61 APP MENTORSHIP 62 APP MENTORSHIP 63 APP MENTORSHIP 64 APP MENTORSHIP 65 APP MENTORSHIP 66 APP MENTORSHIP 67 APP MENTORSHIP 68 APP MENTORSHIP 69 APP MENTORSHIP 70 APP MENTORSHIP 71 APP MENTORSHIP 72 APP MENTORSHIP 73 APP MENTORSHIP 74 APP MENTORSHIP 75 APP MENTORSHIP 76 APP MENTORSHIP 77 APP MENTORSHIP Appendix L IRB and Consent Documents Figure 1L. ASU IRB Exemption Letter 78 APP MENTORSHIP 79 APP MENTORSHIP Figure 2L. Consent with survey 80 APP MENTORSHIP 81 Appendix M Results Tables and Charts Table 1M. Demographic Descriptives Gender Question Frequency Percent Female 21 87.5 Male 3 12.5 Other 0 0 Total 24 100.0 0 21 3 24 0 87.5 12.5 100.0 17 7 24 70.8 29.2 100.0 1 1 2 1 1 3 1 2 1 1 1 1 1 7 24 4.2 4.2 8.3 4.2 4.2 12.5 4.2 8.3 4.2 4.2 4.2 4.2 4.2 29.2 100.0 1 9 5 4.2 37.5 20.8 Highest Degree Earned Bachelors degree Masters degree Doctorate Total Type of License Held Nurse Practitioner Physician Assistant Total Years RN Experience 3 4 5 6 7 10 11 13 16 17 20 21 28 N/A Years of APP Experience Less than 1 year 1 -3 years 4 - 8 years APP MENTORSHIP 8 - 12 years 13 - 17 years 17 - 20 years More than 20 years Total Years at BMDACC <6 months 6 months to 2 years 2 to 5 years 5+ years Total 2 3 2 2 24 8.3 12.5 8.3 8.3 100.0 7 6 8 3 24 29.2 25.0 33.3 12.5 100.0 82 Table 2M. Mentorship Perceptions and Experience Question Are a mentor & preceptor the same thing Have you ever had an APP mentor Have you ever been an APP mentor Have you had a formal or arranged mentorship Have you had an informal mentorship Frequency Percent No 19 Yes 5 Total 24 79.2 20.8 100.0 No 8 Yes 16 Total 24 33.3 66.7 100.0 No 15 Yes 9 Total 24 62.5 37.5 100.0 No 17 Yes 7 Total 24 70.8 29.2 100.0 No Yes Total Have you had a mentor within the same organization No Yes Total Have you had a mentor outside the organization No Yes Total I have NO experience with mentorship No 11 13 24 45.8 54.2 100.0 14 10 24 58.3 41.7 100.0 18 6 24 75.0 25.0 100.0 17 70.8 APP MENTORSHIP Was a mentor provided on hire Do you have any teaching experience Do you have any education certifications Yes 7 Total 24 29.2 100.0 No 17 Yes 7 Total 24 70.8 29.2 100.0 No 11 Yes 13 Total 24 45.8 54.2 100.0 No 21 Yes 3 Total 24 87.5 12.5 100.0 Figure1M. Ranking of Mentor Functions by Domain Role Modeling Domain Teaching Skills 8 F r e q Clinical Skills 6 4 Organizational Knowledge 2 Time Management 0 1 2 3 4 5 Bedside Manner Most to Least Valued Psychosocial Domain 15 F r e q Motivational Support Emotional Support 10 After Work Availability 5 Friendship 0 1 2 3 Most to Least Valued 4 5 Same Gender 83 APP MENTORSHIP 84 Career Development Domain 16 Professional Knowledge 14 F r e q 12 Goal Setting 10 8 Networking 6 Providing Challenges 4 2 0 Similar Education 1 2 3 4 5 Most to Least Valued Table 3M. Perceived barriers correlation tables Correlations Mentor Preceptor NP or PA Spearman's rho Other Emp the Same Had APP Mentor Been APP Mentor Teaching Exp Education Cert OCA Total Score MFQ9 Total Score PBM Total Score 1.000 -.122 .348 .259 -.118 -.514* -.243 .186 .067 -.007 . .569 .096 .221 .582 .010 .253 .384 .756 .975 -.122 1.000 .011 -.145 -.026 .558** .194 -.067 -.128 .075 Sig. (2-tailed) .569 . .961 .499 .902 .005 .364 .756 .552 .729 Mentor Preceptor the Correlation Coefficient .348 .011 1.000 .363 .238 -.146 .116 -.052 .090 -.164 Same Sig. (2-tailed) .096 .961 . .081 .262 .496 .588 .809 .676 .443 Had APP Mentor Correlation Coefficient .259 -.145 .363 1.000 .365 -.296 .267 -.333 -.052 -.129 Sig. (2-tailed) .221 .499 .081 . .079 .161 .207 .112 .810 .549 -.118 -.026 .238 .365 1.000 .367 .228 -.006 .151 -.163 .582 .902 .262 .079 . .078 .285 .977 .481 .447 -.514* .558** -.146 -.296 .367 1.000 .095 .115 .141 -.097 .010 .005 .496 .161 .078 . .659 .592 .512 .650 -.243 .194 .116 .267 .228 .095 1.000 -.164 .009 -.092 Sig. (2-tailed) .253 .364 .588 .207 .285 .659 . .443 .966 .670 Correlation Coefficient .186 -.067 -.052 -.333 -.006 .115 -.164 1.000 .416* -.357 Sig. (2-tailed) .384 .756 .809 .112 .977 .592 .443 . .043 .087 Correlation Coefficient .067 -.128 .090 -.052 .151 .141 .009 .416* 1.000 -.352 Sig. (2-tailed) .756 .552 .676 .810 .481 .512 .966 .043 . .092 -.007 .075 -.164 -.129 -.163 -.097 -.092 -.357 -.352 1.000 .975 .729 .443 .549 .447 .650 .670 .087 .092 . NP or PA Correlation Coefficient Sig. (2-tailed) Other Emp Been APP Mentor Correlation Coefficient Correlation Coefficient Sig. (2-tailed) Teaching Exp Correlation Coefficient Sig. (2-tailed) Education Cert OCA Total Score MfQ9 Total Score PBM Total Score Correlation Coefficient Correlation Coefficient Sig. (2-tailed) **. Correlation is significant at the 0.01 level (2-tailed). *. Correlation is significant at the 0.05 level (2-tailed). APP MENTORSHIP 85 Correlations MFQ9 Total Age Age Pearson Correlation Years RN 1 Years APP Pearson Correlation .345 Sig. (2-tailed) .176 OCA Total Score -.288 -.151 .176 .176 .000 .156 .172 .481 .410 1 .081 .184 -.462 -.598* .058 .758 .479 .062 .011 .825 1 * .491 -.101 .043 .021 .015 .640 .842 .921 1 .181 .363 -.417* .399 .081 .043 1 .380 -.469* .067 .021 1 -.351 .000 .758 Pearson Correlation .299 .184 .491* Sig. (2-tailed) .156 .479 .015 -.288 -.462 -.101 .181 .172 .062 .640 .399 -.151 -.598* .043 .363 .380 .481 .011 .842 .081 .067 * * Pearson Correlation Pearson Correlation .681 PBM Total Score .299 .681 Sig. (2-tailed) Sig. (2-tailed) PBM Total Score Score .081 Sig. (2-tailed) MFQ9 Total Score OCA Total Score ** Pearson Correlation Yrs at IHDS Yrs at IHDS ** .345 Sig. (2-tailed) Years RN Years APP .093 Pearson Correlation .176 .058 .021 -.417 -.469 -.351 Sig. (2-tailed) .410 .825 .921 .043 .021 .093 1 **. Correlation is significant at the 0.01 level (2-tailed). *. Correlation is significant at the 0.05 level (2-tailed). Table 4M. Organizational commitment correlation tables. Correlations Mentor Preceptor OCA Total Score Spearman's rho OCA Total Score OCN Total Score Mentor Preceptor the Same Other Emp on Hire Teaching Exp -.333 -.006 -.067 -.133 .115 . .007 .022 .809 .112 .977 .756 .536 .592 .538** 1.000 .479* .193 .083 .006 -.216 .086 -.030 Sig. (2-tailed) .007 . .018 .365 .699 .977 .311 .688 .888 Correlation Coefficient .464* .479* 1.000 .067 -.250 .087 .007 .047 .352 Sig. (2-tailed) .022 .018 . .756 .239 .685 .972 .829 .092 -.052 .193 .067 1.000 .363 .238 .011 -.103 -.146 .809 .365 .756 . .081 .262 .961 .630 .496 -.333 .083 -.250 .363 1.000 .365 -.145 .259 -.296 .112 .699 .239 .081 . .079 .499 .221 .161 -.006 .006 .087 .238 .365 1.000 -.026 -.308 .367 .977 .977 .685 .262 .079 . .902 .144 .078 -.067 -.216 .007 .011 -.145 -.026 1.000 -.122 .558** .756 .311 .972 .961 .499 .902 . .569 .005 -.133 .086 .047 -.103 .259 -.308 -.122 1.000 -.146 .536 .688 .829 .630 .221 .144 .569 . .497 Correlation Coefficient Correlation Coefficient Correlation Coefficient Correlation Coefficient Correlation Coefficient Sig. (2-tailed) Mentor Provided on Hire Been APP Mentor -.052 Sig. (2-tailed) Other Emp Had APP Mentor .464* Sig. (2-tailed) Been APP Mentor the Same .538** Sig. (2-tailed) Had APP Mentor OCN Total Score 1.000 Correlation Coefficient Sig. (2-tailed) OCC Total Score OCC Total Score Mentor Provided Correlation Coefficient Sig. (2-tailed) APP MENTORSHIP Teaching Exp 86 Correlation Coefficient .115 -.030 .352 -.146 -.296 .367 .558** -.146 1.000 Sig. (2-tailed) .592 .888 .092 .496 .161 .078 .005 .497 . **. Correlation is significant at the 0.01 level (2-tailed). *. Correlation is significant at the 0.05 level (2-tailed). Correlations Age Age Years RN Pearson Correlation 1 Sig. (2-tailed) Years RN Years APP Yrs at IHDS OCA Total Score Pearson Correlation .345 Sig. (2-tailed) .176 Pearson Correlation Program to develop skills Program to build relationship MFQ9 Total Program to Program to build Score Score Score Score develop skills relationship .345 .681** .299 -.288 -.445* -.291 -.151 .095 .191 .176 .000 .156 .172 .029 .168 .481 .660 .371 1 .081 .184 -.462 -.335 -.206 -.598* -.073 -.306 .758 .479 .062 .189 .427 .011 .781 .233 1 .491* -.101 -.568** -.206 .043 .048 .131 .015 .640 .004 .334 .842 .824 .542 1 .181 -.375 -.096 .363 -.044 -.101 .399 .071 .656 .081 .837 .638 1 .561** .631** .380 .247 .359 .004 .001 .067 .245 .085 1 .540** -.047 -.031 .062 .006 .828 .887 .772 1 .352 .073 .064 .092 .736 .767 1 -.063 .049 .769 .819 1 .879** Sig. (2-tailed) .000 .758 Pearson Correlation .299 .184 .491* Sig. (2-tailed) .156 .479 .015 -.288 -.462 -.101 .181 .172 .062 .640 .399 -.445* -.335 -.568** -.375 .561** .029 .189 .004 .071 .004 -.291 -.206 -.206 -.096 .631** .540** .168 .427 .334 .656 .001 .006 -.151 -.598* .043 .363 .380 -.047 .352 Sig. (2-tailed) .481 .011 .842 .081 .067 .828 .092 Pearson Correlation .095 -.073 .048 -.044 .247 -.031 .073 -.063 Sig. (2-tailed) .660 .781 .824 .837 .245 .887 .736 .769 Pearson Correlation .191 -.306 .131 -.101 .359 .062 .064 .049 .879** Sig. (2-tailed) .371 .233 .542 .638 .085 .772 .767 .819 .000 Pearson Correlation Pearson Correlation Pearson Correlation Sig. (2-tailed) MFQ9 Total Score OCN Total .081 Sig. (2-tailed) OCN Total Score Yrs at IHDS OCC Total .681** Sig. (2-tailed) OCC Total Score Years APP OCA Total Pearson Correlation **. Correlation is significant at the 0.01 level (2-tailed). *. Correlation is significant at the 0.05 level (2-tailed). Table 5M. Likert Means Scores for Custom Perceived Barriers Min Max M SD Productivity requirements 1.00 6.00 3.28 1.35 Role expectations 1.00 6.00 3.06 1.23 No exp teaching 1.00 5.00 2.61 .89 No training to teach 1.00 5.00 2.67 .93 No mentoring skills 1.00 6.00 3.00 1.22 .000 1