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The mechanisms by which professional development may contribute to critical care nurses' intent to stay Goldsworthy, Sandra June 2015

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      THE MECHANISMS BY WHICH PROFESSIONAL DEVELOPMENT MAY CONTRIBUTE TO CRITICAL CARE NURSES’ INTENT TO STAY  by   SANDRA JUNE GOLDSWORTHY  H.B.Sc.N (Lakehead University), 1984  M.Sc. (Queen’s University), 2004     A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF   DOCTOR OF PHILOSOPHY  in   THE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES  (Nursing)    THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver)      April, 2015 © Sandra June Goldsworthy, 2015    ii  Abstract The current international nursing shortage is worsening and is particularly acute in critical care settings. In Canada, there is a rapidly aging nursing workforce and at the same time a significant shortfall in the number of new graduates to replace the large numbers of retiring nurses. Intensive Care Units have been shown to have the highest turnover rates and there is currently limited scientific evidence on how to retain critical care nurses. Studies have shown that one of the most commonly listed incentives for this group of nurses is organizational support in the form of access to educational opportunities and career development. This study tested a theoretical Critical Care Nurse Retention model that consisted of a professional development intervention, two mediator variables (perceived organizational support and critical care self-efficacy) and three moderator variables (work environment, general self-efficacy and transfer of learning) as mechanisms that may influence intent to stay in the organization, unit and nursing profession. A quasi-experimental longitudinal design was used in a random sample of 363 critical care nurses from multiple hospital sites in Ontario. The 374-hour intervention included an online component, high fidelity simulation, and a preceptored clinical component. ANCOVA and hierarchical regression were used to analyze the hypothesized model. Findings showed the professional development intervention had a direct effect on intent to stay in the unit and intent to stay in the profession. In addition, the model demonstrated the influence of perceived organizational support as a mediator between the relationship of professional development and intent to stay in the profession.  Final analysis revealed that the model explained 23% of the variance in intent to stay in the profession. This research provides new evidence supporting the relevance and importance of investing in professional development opportunities and its subsequent impact on intent to stay.  iii  Preface This dissertation is original, unpublished, independent work by the author, Sandra June Goldsworthy. The research was conducted under the supervision of committee members: Dr. Maura MacPhee, (co-supervisor, UBC School of Nursing), Dr. Susan Dahinten (co-supervisor, UBC School of Nursing) and Dr. Daniel Skarlicki (Professor, UBC Sauder School of Business). Ethics approval was received from the University of British Columbia Research Ethics Board (ethics approval number H12-02032) and the Durham College research Ethics Board (ethics approval number 019-1213).     iv  Table of Contents  Abstract ........................................................................................................................................... ii Preface............................................................................................................................................ iii Table of Contents ........................................................................................................................... iv List of Tables ................................................................................................................................. ix List of Figures ................................................................................................................................. x Acknowledgements ........................................................................................................................ xi Dedication ..................................................................................................................................... xii Chapter 1. Introduction ................................................................................................................... 1 The Nursing Shortage.................................................................................................................. 2 Nurse Retention Factors .............................................................................................................. 3 Critical Care Nursing .................................................................................................................. 5 The disengagement process. .................................................................................................... 6 Problem Statement ...................................................................................................................... 7 Chapter 2. Literature Review ........................................................................................................ 10 Theoretical Perspectives on Intent to Stay ................................................................................ 12 Price and Mueller Model ........................................................................................................... 13 Boyle et al. Model ..................................................................................................................... 15 Cowden Model .......................................................................................................................... 17 Professional Development......................................................................................................... 21 Professional Development: Simulation Research ..................................................................... 25 Summary: Professional Development ....................................................................................... 26 Work Environment .................................................................................................................... 27 Summary: Work Environment .................................................................................................. 32 Perceived Organizational Support ............................................................................................. 33 Summary: Perceived Organizational Support ........................................................................... 36 Transfer of Learning.................................................................................................................. 37 v  Transfer of Learning: Summary ................................................................................................ 42 Self-Efficacy.............................................................................................................................. 43 Summary: Self-Efficacy ............................................................................................................ 48 Summary of Literature .............................................................................................................. 49 Chapter 3. Conceptual Framework ............................................................................................... 53 Critical Care Nurse Retention Model ........................................................................................ 53 Hypothesis 1. ......................................................................................................................... 53 Hypothesis 2. ......................................................................................................................... 54 Hypothesis 3. ......................................................................................................................... 54 Hypothesis 4. ......................................................................................................................... 55 Hypothesis 5. ......................................................................................................................... 55 Hypothesis 6. ......................................................................................................................... 56 Outcome: Intent to Stay............................................................................................................. 57 Chapter 4. Methods ....................................................................................................................... 58 Design........................................................................................................................................ 58 Research Hypotheses................................................................................................................. 59 Study Setting and Sample ......................................................................................................... 60 Target population, sample and setting. .................................................................................. 60 Sampling strategy and recruitment feasibility. ...................................................................... 61 Recruitment procedures. ........................................................................................................ 63 Ethical Considerations............................................................................................................... 64 Measures.................................................................................................................................... 64 Professional Development Intervention .................................................................................... 67 Work Environment .................................................................................................................... 68 Perceived Organizational Support ............................................................................................. 70 Transfer of Learning.................................................................................................................. 71 Self-Efficacy.............................................................................................................................. 71 Domain specific self-efficacy. ............................................................................................... 71 General self-efficacy.............................................................................................................. 72 Intent to Stay ............................................................................................................................. 72 vi  Demographic Variables ............................................................................................................. 73 Data Collection Procedures ....................................................................................................... 73 Data Analysis Strategy .............................................................................................................. 74 Inferential statistics. ............................................................................................................... 76 Sub-analyses: mediation. ....................................................................................................... 77 Mediator Testing ....................................................................................................................... 77 Sub-Analyses: Moderation Testing ........................................................................................... 78 Chapter 5. Results ......................................................................................................................... 82 Sample ....................................................................................................................................... 83 Descriptive Statistics ................................................................................................................. 84 Research Hypotheses: Results ................................................................................................... 88 Research Hypothesis 1 .............................................................................................................. 91 Intent to stay in the organization. .......................................................................................... 91 Intent to stay in the unit. ........................................................................................................ 92 Intent to stay in the profession. .............................................................................................. 92 Predicting Intent to Stay in the Organization ............................................................................ 94 Predicting Intent to Stay in the Unit .......................................................................................... 96 Predicting Intent to Stay in the Profession ................................................................................ 98 Mediation ................................................................................................................................ 100 Research hypothesis 2. ........................................................................................................ 100 Research hypothesis 3. ........................................................................................................ 101 Moderation .............................................................................................................................. 103 Research hypothesis 4. ........................................................................................................ 103 Predicting Critical Care Self-Efficacy..................................................................................... 105 Research hypothesis 5. ........................................................................................................ 105 Subgroup Analyses .................................................................................................................. 107 Research hypothesis 6. ........................................................................................................ 107 Results: Summary ................................................................................................................... 108 Research hypothesis 1. ........................................................................................................ 108 Research hypothesis 2. ........................................................................................................ 109 vii  Research hypothesis 3. ........................................................................................................ 109 Research hypothesis 4. ........................................................................................................ 109 Research hypothesis 5. ........................................................................................................ 110 Research hypothesis 6. ........................................................................................................ 110 Chapter 6. Discussion ................................................................................................................. 111 Overview of Theoretical Model .............................................................................................. 112 Discussion of the Research Hypotheses .................................................................................. 113 Research hypothesis 1. ........................................................................................................ 113 Research hypothesis 2. ........................................................................................................ 116 Research hypothesis 3. ........................................................................................................ 118 Research hypothesis 4. ........................................................................................................ 119 Research hypothesis 5. ........................................................................................................ 120 Research hypothesis 6. ........................................................................................................ 120 Implications for Nursing Practice and Management ............................................................... 121 Implications for Nursing Education ........................................................................................ 122 Implications for Nursing Research .......................................................................................... 124 Implications for Policy ............................................................................................................ 125 Strengths and Limitations........................................................................................................ 126 Limitations. .......................................................................................................................... 126 Strengths. ............................................................................................................................. 128 Final Conclusions .................................................................................................................... 128 REFERENCES ........................................................................................................................... 130 APPENDICES ............................................................................................................................ 150 Appendix A: Intent to Stay Model Comparisons .................................................................... 150 Appendix B: College of Nurses of Ontario Request for Home Mailing Addresses ............... 152 Appendix C: Letter with Mailing of Second Questionnaire ................................................... 156 Appendix D: Questionnaire ..................................................................................................... 157 Appendix E: Follow up Post Card Reminder .......................................................................... 165 Appendix F: Letter of Information .......................................................................................... 166 Appendix G: Letter of Consent ............................................................................................... 168 viii  Appendix H: Demographic Information ................................................................................. 169 Appendix I: The Practice Environment Scale of the Nurse Work Index ................................ 172 Appendix J: General Self-Efficacy ......................................................................................... 173 Appendix K: Transfer of Learning .......................................................................................... 174 Appendix L: Critical Care Nursing Self Efficacy ................................................................... 176 Appendix M: Intent to Stay ..................................................................................................... 178 Appendix N: POS Scale (short version) .................................................................................. 179 Appendix O:  Additional Description of Sample at Time 1 .................................................... 180 Appendix P: Group Differences Time 1 and Time 4 .............................................................. 181 Appendix Q: Differences within Comparison and Treatment Group ..................................... 182     ix  List of Tables Table 1. Sample Size at Data Collection Time Points .................................................................. 59 Table 2. Conceptual and Operational Definitions of Study Variables.......................................... 66 Table 3. Data Collected at Each Time Point ................................................................................. 74 Table 4. Description of Sample at Time 1 .................................................................................... 84 Table 5. Main Study Variables Means and Standard Deviations ................................................. 86 Table 6. Correlation between Major Study Variables: Comparison Group .................................. 89 Table 7. Correlations between Major Study Variables: Treatment Group ................................... 90 Table 8. Intent to Stay in the Organization: Differences between Groups ................................... 91 Table 9. Intent to Stay in the Unit: Differences between Groups ................................................. 92 Table 10. Intent to Stay in the Profession: Differences between Groups ..................................... 93 Table 11. Hierarchical Regression Analysis Results for Variables Predicting Intent to Stay in the Organization at Time 4 (N=138) ......................................................................................... 95 Table 12. Hierarchical Regression Analysis Results for Variables Predicting Intent to Stay in the Unit at Time 4 (N=138) ....................................................................................................... 97 Table 13. Hierarchical Regression Analysis Results for Variables Predicting Intent to Stay in the Profession at Time 4 (N=138) ............................................................................................. 99 Table 14. Perceived Organizational Support: Mediation at Time 4 (N=141)............................. 101 Table 15. Critical Care Self-efficacy: Mediation at Time 4 (N=141)......................................... 103 Table 16. Moderation Regression Analysis Results for Variables Predicting POS at Time 4 ... 105 Table 17. Moderation Regression Analysis Results for Variables Predicting Critical Care Self-efficacy (CCSE) at Time 4 ................................................................................................ 107   x   List of Figures Figure 1. Causal Model of Turnover (Price & Mueller, 2001). .................................................... 14 Figure 2. Critical Care Nurse Intent to Stay Framework (Boyle et al., 1999). ............................. 16 Figure 3. Cowden Theoretical Model of Clinical Nurses’ Intent to Stay. .................................... 19 Figure 4. The Critical Care Nurse Retention Model ..................................................................... 57 Figure 5. Mediation: POS ............................................................................................................. 78 Figure 6. Mediation: Critical Care Self-efficacy .......................................................................... 78 Figure 7. Moderation: Work Environment Factors....................................................................... 80 Figure 8. Moderation: General Self-Efficacy ............................................................................... 81 Figure 9. Critical Care Nurse Retention Model ............................................................................ 94 Figure 10. Mediation: POS ......................................................................................................... 100 Figure 11. Mediation: Critical Care Self-efficacy ...................................................................... 102 Figure 12. Work Environment as a Moderator ........................................................................... 104 Figure 13. Predicting Critical Care Self-efficacy ....................................................................... 106      xi  Acknowledgements  I have many special people to thank and acknowledge as I traversed this doctoral journey. First, I would like to extend my sincere gratitude to my dissertation supervisors Dr. Maura MacPhee and Dr. Susan Dahinten for their guidance and willingness to share their experience and mentor me during my time at UBC. It has been an incredible learning experience and I will be proud to call myself a graduate of the University of British Columbia. I would also like to extend my sincere gratitude to Dr. Daniel Skarlicki, my committee member, from the UBC Sauder School of Business. Your insight and experience were extremely valuable during this process, thank you.  I would also like to acknowledge my loyal friends and family who have stood by me through ‘thick and thin’ and have been tireless in their support and encouragement along the way. A special mention to Thom, Lisa and Kim you are the best friends anyone could ask for and I feel you have earned this degree along with me!  Finally, I could not have done this without the support of my husband and three sons. There are no words that can describe the love, support and sacrifice they have unconditionally provided through this journey. They believed in me when I did not believe in myself and were my biggest cheering section always urging me on with “you can do it!” and lots of hugs. In particular, my husband’s sense of humour and practical advice have saved me and uplifted me on many occasions. I think they have all learned a lot about research along the way and were even willing participants in stuffing envelopes and putting on stamps on the many hundreds of mail out surveys.   The PhD journey is one of great learning but also a test of one’s resilience, perseverance and courage. It opens doors to a whole new world and many exciting opportunities. My deepest thanks again to all of you for your support, friendship, and willingness to share your experience.          xii  Dedication I dedicate this work to my son Ryan and my mother Joan, both cancer survivors. I began this journey as our son was completing treatment and subsequent cure of his cancer. There is not a day that goes by that I am not inspired by their courage, bravery and determination.   1  Chapter 1. Introduction Retention of nurses is an important issue given the current aging nursing workforce and the difficulty of recruiting sufficient numbers of nursing students to meet the demand for supply of nurses. The retention of nurses in critical care units is particularly urgent since it has been shown that this area has the highest turnover rates among all units. In fact, Canadian critical care turnover rates were as high as 77.9% per year in some units with a national turnover average of 26.7% (O’Brien-Pallas, Tomblin-Murphy, Shamian, Li & Hayes, 2010; O’Brien-Pallas, Tomblin-Murphy, Shamian, 2008). In an era in which the retention of nurses is critical, organizational support, healthy work environments and professional development opportunities have been shown to be some of the most crucial ways to improve employee’s retention. In an attempt to retain employees, research has been conducted in nursing and other sectors such as business, to examine human resource strategies that promote organizational effectiveness and productivity. Nursing management science studies, have shown that educational opportunities, such as professional development, are a type of organizational support associated with increased employee intent to stay (Abualrub & Al-Zaru, 2008; Kovner, Brewer, Cheng & Djukic, 2007; Ulrich, Lavandero, Hart,Woods, Leggett, Friedman, D’Aurizio & Edwards, 2009). This chapter outlines the mechanisms by which professional development may influence nurses’ intent to stay. The terms retention and intent to stay are used interchangeably and refer to the nurses’ decisional process to stay in their current job position. Given the complexity of the critical care setting and the high turnover rates in this area, there is an urgent need to examine factors that would increase the likelihood of nurse retention in the ICU in order to stabilize the existing workforce. 2  The Nursing Shortage Currently we are facing a worldwide nursing shortage particularly in specialty units such as critical care (O’Brien-Pallas et al., 2010; Stone, Larson, Mooney-Kane & Smolowitz, 2006; Tomblin Murphy, Birch, Alder, MacKenzie, Lethbridge, Little & Cook, 2009). In a Canadian study that examined turnover among over 8,000 nurses in acute care settings, it was found that critical care units reported the highest turnover of all acute settings that were measured (O’Brien-Pallas et al., 2010). There are many contributing factors to the nursing shortage including the following: the rapidly aging nursing workforce, the increased demand for health services due to increased aging of the population, and difficulties in recruiting and retaining sufficient nurses in the profession (Aiken, Sloane, Bruyneel, Vandenheede & Sermeus, 2013; Borkowski, Amann, Song & Weiss, 2007; O’Brien-Pallas, Duffield & Hayes 2006) and factors such as manager and peer support in the nurse work environment (Ulrich et al., 2006).  The average age of a Canadian nurse is increasing and is currently 45 years (CIHI, 2012). In Canada, in 2007 there was already a shortage of 11,000 full time equivalent (FTE) registered nurses and it is projected that if no policy interventions are implemented; there will be a shortfall of 60,000 FTE registered nurses by 2022 if this trend continues (Tomblin Murphy et al., 2009). Historically, more attention has been given to recruitment than to retention of the existing workforce (O’Brien-Pallas et al., 2006). The risk of investing more resources in recruitment of nurses is that focus is lost on the current existing experienced workforce. It has also been shown that it takes years to see the impact of increasing the supply: therefore it may be better to focus on the existing nursing workforce since these nurses already exist in the workplace and are experienced in their specialties (O’Brien-Pallas & Tomblin-Murphy, Birch, Kephart & Meyer, 2006).  3  Nurse retention is of great concern to organizations because of the costs associated with nurse turnover. Turnover costs include employee replacement, lost productivity and potential negative effects related to the provision of safe, quality care (Hayes, O’Brien-Pallas, Duffield, Shamian, Buchan, Hughes, Laschinger & North, 2012). When experienced nurses retire or leave the organization the cost to replace them can be as much as $82,000-$88,000 US per nurse (Jones, 2005). Indirect costs of turnover also include a decrease in staff morale and group productivity (Hayes, O’Brien-Pallas, Duffield, Shamian, Buchan, Hughes, Laschinger, North & Stone, 2006). Nurse Retention Factors There is empirical evidence to demonstrate that professional development and ongoing educational activities are highly valued by nurses and serve as a key motivator in relation to intent to stay and Perceived Organizational Support (Bjork et al., 2007; Bournes & Ferguson-Pare, 2007; Hayes et al., 2006). In addition, professional development opportunities have been linked to healthy work environments and are a standard guiding principle in the US magnet hospital criteria (Kramer, Schmalenberg, Maguire, Brewer, Burke, Chmielewski, Waldo, 2008) and in the American Association of Critical Care Nurses (AACN) Healthy Work Environment Model (AACN, 2005).The term ‘magnet’ was developed in 1982 by the American Academy of Nurses to describe hospitals that “attract and retain” nurses because of the quality of the nurse work environment. The five core elements of the healthy work environment as outlined by AACN include: skilled communication, true collaboration, appropriate staffing, meaningful recognition and authentic leadership. Meaningful recognition refers to: “Recognition of the value and meaningfulness of one’s contribution to an organization’s work is a fundamental human need and an essential requisite to personal and professional development (p.33, AACN, 2005).” 4  Professional development and ongoing educational activities are highly valued by nurses and serve as a key motivator in relation to intent to stay and a signal that the organization values and recognizes them. In addition to the provision of professional development opportunities and the presence of a healthy work environment, the following section will describe other key factors that have been shown to influence retention of employees within an organization. The factors include the levels of perceived organizational support, how well learning from professional development opportunities is transferred into the practice environment and finally individual levels of self-efficacy. Minimal research has been conducted in nurse populations to examine the impact of these factors. An individual’s perceived organizational support (POS) refers to: “the employee’s perception concerning the extent to which the organization values their contribution and cares about their well-being” (Eisenberger, Huntington, Hutchison & Sowa, 1986). POS is based on Social Exchange Theory (Blau, 1964) and will be discussed further in Chapter 2. In 2009, Riggle, Edmondson and Hansen conducted a meta-analysis of POS and job outcomes including: organizational commitment, job satisfaction, performance and intent to leave. The findings demonstrated that POS has a strong negative relationship with turnover or intent to leave. Specifically, POS accounted for nearly 25% of the variance in intent to leave across the studies analyzed. Although there has not been an in depth study of POS in the nursing population, POS has been examined for more than twenty years widely in numerous other employment settings. Organizations make large financial investments in order to prepare nurses for safe, quality healthcare delivery. They also expect a return on investment with respect to competency attainment-or transfer of learning to practice. In order for this to occur, it has been established 5  that there are three major predictors of transfer of learning; trainee characteristics (i.e., self-efficacy), a healthy work environment (i.e., that includes manager and peer support), and training design (i.e., the training environment needs to closely replicate the practice environment such as the simulation laboratory; Baldwin & Ford, 1988; Facteau, Dobbins, Russell, Ladd & Kudisch, 1995). Transfer of learning was previously used to measure primarily training design and delivery methods but is now emerging as an important factor in measuring organizational outcomes such as behaviour change, performance and turnover (Kirkpatrick & Kirkpatrick, 2004). Self-efficacy plays an important role in moderating transfer of learning (Gist, Stevens & Bavetta, 1991). It has been shown to moderate the relationship between training and newcomer adjustment (Saks, 1995). When new employees do not adjust well in the initial phase of a job, it can lead to disengagement and turnover outcomes. Self-efficacy has also been shown to be strongly related to work performance and can be developed through mastery experiences which largely involve ‘hands-on’ learning (Bandura, 1986). The opportunity to repeat tasks, such as simulated learning experiences, is related to increased levels of self-efficacy or the belief that one can perform the task (Bandura, 1986). Critical Care Nursing The critical care practice setting requires nurses to have specialized skills and knowledge and to be able to critically think rapidly in life and death situations (Canadian Association of Critical Care Nurses, 2009). High level cognitive and emotional competencies are associated with the technical and relational dilemmas encountered daily in these settings. This environment can be very stressful and nurses can be susceptible to high levels of job dissatisfaction. In a large study conducted in the US with 55,516 acute care nurses, it was found that job satisfaction levels 6  in critical care were one of the lowest (Boyle, Miller, Gajewski, Hart & Dunton, 2006). Historically, intensive care units have attracted younger nurses; therefore, the large decline in the number of RNs under the age of 30 in the workforce worsens the shortage of nurses in critical care areas (Ulrich et al. 2006). Given the complexity of the critical care setting and the high turnover rates in this area, there is an urgent need to examine factors associated with nurse retention.  The disengagement process. Most of the previous intent to stay research has been based on the Price and Mueller (1981) intent to stay model that is now over thirty years old. Nursing work contexts, skill mixes and patient care delivery models have changed greatly in the last thirty years with newer variables such as work environment context and perceived organizational support emerging as important variables. The decision to leave a workplace does not happen suddenly but rather occurs by disengagement over a period of time. Studies have shown that when nurses consider leaving, the progression of disengagement happens in stages and usually includes intending to first leave the unit, then the organization and finally the nursing profession (Morrell, 2005). Some earlier literature suggested that there is a gradual disengagement process from thinking about leaving to actually leaving. A US qualitative study with former nurses (N=26) showed that 85% of the participants thought about leaving six to twelve months before actually quitting their positions (Landstrom, Biordi & Gillies, 1989). In a longitudinal survey study conducted over twelve months among Israeli registered nurses (RNs, N=250), practical nurses (PNs, N= 140), it was found that RNs disengaged from the unit first, then the organization and finally the profession (Krausz, 1995).  7  Another study conducted among former RNs from three regions in England reinforced the notion of a gradual disengagement process (Morell, 2005). In this study, a convenience sample of nurses was surveyed to determine reasons for leaving the profession. Results showed that 14% of the nurses left due to a personal expected positive event (i.e., a partner’s work transfer), 30% left because of a single event or ‘shock’ that occurred at work, and the majority (56%) left the profession by way of a gradual decision to leave. O’Brien-Pallas and colleagues (2010) conducted a large pan-Canadian turnover study and found that the majority of nurses leaving their positions did so within six months of making that decision. Primary reasons for leaving were poor working relationships with managers, lack of autonomy, workload and lack of support for professional development activities.  Problem Statement The current international nursing shortage is worsening and is particularly acute in critical care settings. In Canada, there is a rapidly aging nursing workforce and at the same time a significant shortfall in the number of new graduates to replace the large numbers of retiring nurses (Tomblin Murphy et al., 2009). Intensive Care Units have been shown to have the highest turnover rates and there is currently limited scientific evidence on how to retain critical care nurses (O’Brien-Pallas et al., 2010; Stone et al., 2006). Studies have shown that one of the most commonly listed incentives and retention strategies for this group of nurses is organizational support in the form of access to educational opportunities and career development (O’Brien- Pallas et al., 2006; Shields et al., 2001; Ulrich et al., 2006). Nurses report that there is little organizational support for continuing education in the workplace and that resources for professional development have been cut with hospital restructuring and cutbacks (O’Brien-Pallas et al., 2006). Studies have shown that when employees feel supported and valued by their 8  organizations and work within healthy work environments that include ongoing professional development opportunities that they will be more likely to stay within the unit and the organization. Given the limited knowledge about retention of critical care nurses and the effect of organizational support, investment in professional development opportunities, healthy work environments, transfer of learning and self-efficacy, this study examined intent to stay and its relationship to these factors. It is also known that nurses disengage from their jobs gradually versus suddenly and typically leave the unit first, then the organization and finally the nursing profession. Effective retention strategies utilized earlier may halt the rapid turnover in Canadian ICUs and results of this study may provide some insight into urgently needed strategies that may assist in stabilizing the critical care nurse workforce. Design challenges with earlier research on intent to stay among nurses have included: the preponderance of cross-sectional designs, small sample sizes, single site studies and lack of standardized measures. A limited number of studies were found that utilized an interventional design. In order to address design issue encountered in previous nurse retention studies, this study is longitudinal in nature measuring variables at different time points and explores a professional development intervention not previously tested among critical care nurses.  This study adds to the science by exploring relationships among nurses where little or no empirical evidence has been demonstrated. During my review of the critical care nursing literature, I was unable to locate any studies that examined many of the concepts related to critical care nurse retention, such as transfer of learning and self-efficacy among critical care nurses. A limited number of studies were located on the influence of perceived organizational support (POS) and work environment among critical care nurses. No studies were found that 9  examined a professional development intervention for nurses that included online, simulation and practicum setting learning components. Little is known about the relationship of self-efficacy and transfer of learning among the nursing population and its relationship to intent to stay. Although transfer of learning and organizational outcomes such as performance and turnover has been studied in the business sector, there are few studies in the nursing population.  This research examined the relationship between POS, work environment and intent to stay since there was limited information on how these variables may together influence intent to stay.     10  Chapter 2. Literature Review The purpose of this literature review was to examine previous empirical determinants of intent to stay among nurses. The key concepts examined in this chapter included the mechanisms by which professional development may influence intent to stay among nurses. This review includes the concepts of: perceived organizational support, work environment, transfer of learning and self-efficacy in relation to nurses’ intent to stay in their unit, hospital and profession. Each section of the literature review begins with a description of pertinent conceptual models that have been tested with nurses in international and Canadian contexts. The philosophical traditions of the models were considered with respect to the concepts and relationships proposed in key models. Each section addressed knowledge limitations that exist and need to be addressed through model refinement and testing. In conducting this literature review, key words and combinations of key words were used for searching in books, journals, dissertations and government publications from 1964 to present. The computer databases used to identify the related literature included Web of Science, ABI inform, and ERIC. The indexes were searched using the following key words: intent to stay, intent to remain, retention, and nurses. Also used were combinations of key words: critical care nurses, nurse turnover, work environment, transfer of learning, transfer of training, self-efficacy, training self-efficacy, perceived organizational support, professional development, and job satisfaction. The search produced studies from Canada, the United States, Australia, the United Kingdom, Jordan, Taiwan, Ireland, China, Italy, Belgium, Norway, and Singapore. References were searched based on titles and then after key scholars in the area were identified, and their names were searched for related publications. 11  Studies selected for this literature review were related closely to the focus of this doctoral dissertation and included combinations of the variables of intent to stay, turnover, work environment, transfer of learning, transfer of training, self-efficacy, pre-training self-efficacy, professional development, high fidelity simulation, and perceived organizational support. For each of the studies chosen, a critical appraisal was conducted to determine whether or not the research addressed a related question to the current research, and whether or not the study had been conducted in a similar population, setting, and circumstances as the proposed research. The research selected was also examined to identify from whom the data were collected (i.e., managers, staff nurses, allied health professions) and where the study was conducted (i.e., acute care, hospitals, single site versus multi-site). The methods of the research were reviewed and results were analyzed in each study to determine whether or not the results were consistent with the reported data and if the results were compared with previous research findings. Each study was then explored to determine whether or not a model had been used, and if so, its completeness. Measures were reviewed in each research paper to determine their relevance to the question and to evaluate the psychometric properties. Furthermore, the statistical methods of each study were examined for their appropriateness for the design and data. The goal of this literature review was to illuminate what is known in the area and to outline the gaps. A summary of the related empirical literature is also presented. Several terms are used interchangeably in the literature related to nurse retention. Other terms, such as turnover, are also used in the literature with regards to nurse retention. Turnover may be voluntary or involuntary and is a measurement of actual turnover, whereas ‘intent’ refers to an individual’s desire or thought process about staying or leaving (Gregory et al., 2007). The concepts of intent to stay and intent to leave can be described as ‘different sides of the same 12  coin’ and as a result appear in the empirical literature as common dependent variables in retention models. A systematic review of nurse retention literature found that intent to stay is the strongest predictor of turnover and is often used as a proxy for turnover when actual turnover data cannot be collected (Hayes, et al., 2006, 2012). In the following section, the development of intent to stay theory was examined followed by an exploration of the key intent to stay studies in international and Canadian nursing contexts. Theoretical Perspectives on Intent to Stay Three models of intent to stay have informed the development of the model being tested in the current research. The dependent variable, intent to stay, was the focus of all three frameworks. These three different conceptual models were used to illustrate the hypothesized relationship between organizational characteristics, individual characteristics, and the work environment. The historical context has been important in developing the intent to stay models and reflects cycles of nursing shortages including the current context and the sustained shortage. The first model is Price and Mueller’s (1986, 2001) ‘Causal Model of Turnover’; the second is Boyle et al.’s (1999) ‘Critical Care Nurse Intent to Stay Framework’; and the third is Cowden’s (2012) ‘Theoretical Framework of Clinical Nurses’ Intent to Stay’ model. Until the Cowden model emerged, intent to stay models explained 12-52% of the variance in intent to stay. The Cowden (2012) model explained 63% of the variance of intent to stay. The following section describes each conceptual model and identifies their strengths and weaknesses. Conceptual gaps are highlighted; the gaps will be addressed with the proposed Critical Care Nurse Retention Model (Chapter 3). 13  Price and Mueller Model The most well-known intent to stay model in the nursing literature is by Price and Mueller (1986, 2001), the ‘Causal Model of Turnover’. The Price and Mueller model has evolved over two decades of research using nurse populations, and has its origins in sociology. The sociological tradition from a symbolic interactionist perspective examines how people interact with each other in specific situations and how they derive meaning from these interactions. This perspective examines interaction at the micro level, as in work settings, and is the basis of the social exchange theory that describes the process of social exchange between staff and managers (Blau, 1964). Furthermore, from the interactionist perspective, social exchanges are based on society norms of fairness and reciprocity. When inequalities exist in the exchange, such as between a manager and a nurse, a power differential is created that can lead to conflict and negative feelings about the exchange. This sociological perspective provides a lens for examining and appreciating the complexity within the nurse work environment. The notions of reciprocity and social exchange are expanded in the section on perceived organizational support. In the Price and Mueller model, the three major constructs related to intent to stay include: the environment, the organization, and the individual (Figure 1). The environment can refer to the external environment (outside work) or the work environment. In the Price and Mueller model, the organizational variables refer to the internal work environment factors. The environmental variables in this model are: kinship responsibilities and opportunity (external work environment), while the individual variables are: general training, job motivation, met expectations, and affectivity (positive or negative). Affectivity refers to an individual’s emotional response to their work. The structural or organizational variables (internal work 14  environment) are: autonomy, distributive justice, job hazards, job stress, pay, professional growth, promotional chances, routinization, and social support. Professional growth was operationalized as an opportunity to increase job-related knowledge and skills. Predictor variables may influence an outcome directly or indirectly through a third variable (i.e., a mediator). Finally, the mediating variables in this model are: job satisfaction, organizational commitment, and search behavior. Mediation analysis answers the question of ‘whether’ and ‘how’ a predictor variable influences the outcome variable through a third variable (Hayes, 2013). Price (2001) argued that propositions without mediating variables are often incomplete. Figure 1. Causal Model of Turnover (Price & Mueller, 2001).   15  When this model was proposed almost 30 years ago it was developed as a framework to understand turnover of hospital nurses and it was the most comprehensive causal model of nurse turnover at the time. The model has since been criticized for not being parsimonious by having too many variables and for having a large number of insignificant variables (Griffeth & Hom, 2004). Despite the number of variables, this model explained only 17% of the variance in intent to stay of nurses with the 1981 model and 12% of the variance with the 1986 model. Although the model has been used as a foundation in numerous nursing studies, it does not include internal work environment characteristics such as manager support or adequate resources and workload (Brewer et al., 2012). Furthermore, the model is limited by the lack of testing using longitudinal designs, using non-diverse samples, and for the difficulty in developing reliable, valid tools (i.e., for measurement of kinship responsibility), according to Price (2001). The strength of the model is that it provided a foundation for future models by identifying the importance of intent to stay in predicting turnover, and was a beginning for understanding some elements of the work environment that predicted intent to stay by mediating the variables of job satisfaction and organizational commitment. Boyle et al. Model In the late-1990s, a causal model of intent to stay was developed specifically to predict critical care nurses’ intent to stay (Boyle, Bott, Hansen, Taunton, & Woods, 1999) (Figure 2).  16  Figure 2. Critical Care Nurse Intent to Stay Framework (Boyle et al., 1999).  The Boyle et al. (1999) model again reflects the sociological perspective by focusing on the nurse work environment and the social interactions within that environment. Boyle and colleagues modified the Price and Mueller model by expanding the internal work environment variables to include manager characteristics and to conceptualize job stress (situational and personal) as a mediating variable to assist in explaining the relationship between manager and organizational characteristics and intent to stay. In this model, four sets of predictor variables were proposed to influence intent to stay either directly or indirectly through the mediating variables of job stress, job satisfaction, and organizational commitment. The four sets of predictor variables included: 1) manager characteristics (power: the manager’s ability to control others, influence: the amount of control managers have over aspects of the work environment, leadership style: the ability to set out clear expectations and the regard for comfort and well-being of staff), 2) organizational characteristics (distributive justice: how rewards and punishments are related to performance, promotional opportunity, control over nursing practice), 3) work characteristics (autonomy, instrumental communication: how the organization 17  communicates with staff about the job, work group cohesion, and routinization: the repetitiveness of the job), and 4) nurse characteristics (opportunity elsewhere).The strength of the Boyle framework was the conceptualization of the nurses’ internal work environment versus the external environment (i.e., kinship responsibilities). The immediate nurse work environment includes the importance of manager characteristics and the proposed relationships to predict intent to stay among critical care nurses. This model was initially tested by Boyle and colleagues among ICU nurses (N=255) from four large acute care hospitals in the US using a cross-sectional descriptive study. The measures used in the study were primarily from those developed by Price and Mueller. The Boyle et al. (1999) model explained 52% of the variance in intent to stay of critical care nurses. Five variables were found to have direct effects on intent to stay of critical care nurses: manager’s position power and manager’s influence over work coordination (manager characteristics), opportunity elsewhere and promotional opportunity (organizational characteristics), and job satisfaction/enjoyment (the mediating variable). Manager characteristics that were found to have significant indirect effects on predicting intent to stay were leadership styles in which managers clearly defined their own role, identified expectations for staff, and had regard for the well-being and comfort of staff. None of the internal work environment characteristics (i.e., autonomy, instrumental communication and work group cohesion) were found to have a significant direct or indirect effect on intent to stay in this model. Cowden Model The Cowden (2012) model built on previous intent to stay models by expanding manager characteristics to include praise and recognition, shared decision making, and supervisor support. Predictors and mediators of intent to stay were grouped into six categories. The first four categories of predictors included: work characteristics, manager characteristics, organizational 18  characteristics, and nurse characteristics. The last two categories of mediators were cognitive and affective responses to one’s work. In this model, cognitive response to work refers to concepts such as organizational commitment, empowerment, and opportunities. Cognitive responses are derived from perceptions of structural attributes of the job (Cowden & Cummings, 2014). Affective responses to work refer to the emotional aspects such as: job satisfaction, desire to stay, and moral distress. Cowden (2012) argued that affective responses emerge from positive feelings about one’s job position. Cowden was not clear on how these two dimensions (affective and cognitive) are delineated in the model but introduces these aspects broadly. Moral distress was added as a response to work, and abuse was added to work characteristics in the model. Cowden modified workload by adding the variable ‘time to nurse’ in organizational characteristics (Figure 3). In addition, Cowden added the mediating variables of cognitive and affective responses to explain the relationship between manager, organization, work, and nurse characteristics with intent to stay. Furthermore, the concepts of empowerment (cognitive response to work), adequate staffing (organizational characteristics) and position preference (nurse characteristics) were added to the model as predictors to gain a better understanding of the nurse’s perception of the work environment.   19  Figure 3. Cowden Theoretical Model of Clinical Nurses’ Intent to Stay.              Variables common to both Boyle et al. and Cowden’s models include: manager characteristics (i.e., leadership/management practices), work characteristics (i.e., work group cohesion, autonomy), nurse characteristics (i.e., age, education and work status), and organizational characteristics (i.e., career opportunities). In addition, both the Boyle and Cowden models included the mediator variables: organizational commitment, job stress, and job satisfaction (Appendix A). Limitations of the Cowden model include the level of complexity and large sample size required to adequately test the model. It could also be argued that the variables Cowden grouped Intent to stay Manager characteristics:  Leadership  Praise & recognition  Shared decision making  Supervisor support Cognitive response to work:  Empowerment  Organizational commitment  Quality of care  Opportunity elsewhere Organization characteristics:  Career development  Staffing  Time to nurse Affective response to work:  Desire to stay  Job satisfaction  Joy at work  Moral distress Work characteristics:  Abuse  Autonomy  Work group cohesion Nurse characteristics:  Age  Education level  Position preference  Tenure  Work status 20  among the cognitive responses to work could also have an affective component to them. For instance, organizational commitment has been tested as a three-dimensional construct and has demonstrated a clear affective dimension (Meyer & Allen, 1993). Furthermore, empowerment has been extensively studied by Laschinger and colleagues and has also been found to have an affective dimension (Laschinger et al., 2009). It is unclear how Cowden determined the affective and the cognitive division of variables in this model. The Cowden model was tested among 415 RNs and RPNs from acute care hospitals and it explained 63% of the variance in intent to stay (Cowden & Cummings, 2014). The model was built on established theory and literature and when the model was tested, the results showed that the relationship between managerial characteristics (i.e., perceived leadership) and intent to stay was mediated by empowerment. Direct relationships were found with intent to stay that included organizational commitment, desire to stay, and autonomy. In the next section, studies that support the predictor variables, third variables (i.e., mediating variables), and outcome variables in Price and Mueller’s (1986), Boyle et al.’s (1999), and Cowden’s (2012) models are explored as well as what is known about the process in which nurses make the decision to leave their positions. Many of these studies were descriptive cross-sectional survey studies of nurses’ work environments where intent to stay was one outcome variable. A systematic review by Hayes et al. (2012) examined factors that were most predictive of nurse turnover. As mentioned before, turnover is the behaviour associated with the decisional process of intent to stay (O’Brien-Pallas et al., 2010). The review critiqued the research between 2006 and 2012 with respect to the relationships between nurse turnover and nurse, patient, and organizational outcomes. Although most of the studies selected for the systematic review did not specify the theoretical intent to stay model that informed their study, 48 studies were related to 21  the predictors specified in Boyle et al.’s (1999) model and Cowden’s (2012) Intent to Stay model for nurses. The new model being tested, the Critical Care Nurse Retention Model focuses on similar elements found in Boyle’s (1999) and Cowden’s (2012) intent to stay models. New concepts were added to the current model that have not yet been explored in the nursing literature. These include: professional development, perceived organizational support, transfer of learning, general self-efficacy, and critical care self-efficacy. The elements that were similar to previous models, included: work environment characteristics (i.e., manager leadership style and support, staffing resources, and workload) and individual nurse characteristics (i.e., age, tenure, and education level). Key international and Canadian studies pertaining to intent to stay will be explored and justification will be made for the new Critical Care Nurse Retention Model. Professional Development A number of studies examined the availability of professional development opportunities for nurses and their perceived value and importance as an incentive. Professional development opportunities can be defined as: “Planned educational and experiential bases of the professional nurse for the enhancement of practice, education, administration, and research or theory development to the end of improving health for the public” (American Nurses Association, 1984). Examples of professional development opportunities for nurses include: conferences, unit in-services, certificate programs (i.e., critical care), and workshops. Rewards such as pay, recognition, respect from managers and colleagues, as well as benefits such as ongoing educational opportunities and professional development have been frequently cited in the retention literature as motivators for intent to stay (Abualrub & Al-Zaru, 2008; Kovner, Brewer, Cheng & Djukic, 2007; Lynn, Redman & Zomordi, 2006; Khowaja, 22  Merchant & Hirani, 2005; O’Brien-Pallas et al., 2010). In identifying specific rewards that would increase job satisfaction and intent to stay, nurses have identified that professional development opportunities are positive incentives (Abualrub & Al-Zaru, 2008; Cortese, 2007; Bjork et al., 2007; O’Brien-Pallas et al., 2006; Mion et al., 2006; Andrews, Manthorpe & Watson, 2005; Yin & Yang, 2002; Shields & Ward, 2001; Aiken et al., 2001; McNeese-Smith et al., 2000; Kosmoski & Calkin, 1986; McCloskey, 1974). Nurses highly value professional development opportunities and see them as a signal of organizational support. In a study of Swedish hospital registered nurses (N=15) six years after graduation, Hallin and Danielson (2008) used in-depth semi-structured RN interviews. The authors found that the nurses participating in the study did not feel that their organization was supporting their professional development and growth. Furthermore, the nurses in the study reported limited financial compensation for the educational activities. The authors concluded that continuing education is important to experienced nurses since it provides motivation and intellectual stimulation, and may influence their intent to stay in the organization. Nurses have been shown to value professional development opportunities more than other factors (e.g., pay). Morgan and colleagues (2009) conducted semi-structured interviews with 20 acute care nurses from two academic health care centers in the southern US to determine factors contributing to job satisfaction in the context of a nursing shortage. They found that pay was not a predominant satisfier and that a system was needed to foster personal growth in practice, with the recognition of the nurses’ achievements. The authors recommended that organizational support, such as investment in professional development and recognition programs for nurses, should be strongly emphasized. The findings concur with an earlier study of nurses (N=14,400) in the UK by Shields and Ward (2001). The authors showed that 23  dissatisfaction with promotion and training opportunities were more important motivators than workload or pay for nurses. In a qualitative Canadian study with semi-structured interviews of nurses (N=16) who had greater than 10 years of experience, Leurer, Donnelly and Domm (2007) reported the value that nurses attribute to professional development opportunities. The nurses were asked what retention strategies they would recommend to policy makers (Leurer, Donnelly & Domm, 2007). Seven themes emerged as retention strategies including: recognition (being recognized by their organization for their efforts), supportive management, and being provided with professional development opportunities. The participants in this study put a high value on professional development activities and suggested that far more investment should be made in the area of continuing education for nurses. One nurse said, “...That’s something that would make nurses get excited about their practice again” (Leurer, et al., 2007, p. 314). Professional development such as attending conferences, training workshops, and formally upgrading the staff’s education were considered as areas that organizations should invest in as retention strategies. Nurses value professional development at all career stages. A study from Taiwan examined the career needs of 177 nurses from 30 acute care hospitals at different stages and career development programs (Chang et al., 2007). Through cross-sectional surveys and interviews, the nurses’ career stages were assessed and turnover intention was measured. From the interviews, nurses were found to highly value and want on the job training, seminars, advanced professional curricula, and certificates and degrees. The authors also reported that if appropriate career development programs were offered, the nurses’ intent to stay increased. In a US study, similar results were found (Stone et al., 2006). In a sample of ICU nurses (N=202) 24  who participated in a cross-sectional survey, the researchers found that organizations that supported professional practice and clinical competence had decreased turnover. A Canadian study demonstrated the importance of allocating a portion of hours worked as professional development time. In the initial descriptive study, conducted at an Ontario teaching hospital (N= 912 RNs), nurses were asked what would motivate them to stay in their position and what would drive them away (Ferguson-Pare, 2002). The top motivators to stay included: manager support, providing learning opportunities and support for professional development, and camaraderie among staff (Ferguson-Pare, 2002). As a follow-up to the initial research, a longitudinal descriptive study was conducted at the same Ontario hospital site of 33 acute care registered nurses and 55 patients. In this study, a professional development model was implemented and evaluated (Bournes & Pare, 2007). In the model, nurses spent 80% of their salaried time in direct patient care and 20% of their salaried time in professional development activities; this is known as the 80/20 Model. The findings of the study showed that overtime was decreased significantly, sick time did not increase, turnover was lower than in the control units, and patient and nurse satisfaction increased significantly. Nurses who were working in the study unit reported that they felt respected, satisfied, and listened to. Also, no significant increase in the labour cost occurred when the 80/20 Model was implemented. This study confirmed, once again, that nurses highly value ongoing professional development opportunities. “A successful retention strategy is one that makes it possible for nurses to rekindle their passion for their work and fosters ongoing professional development” (Bournes & Ferguson-Pare, 2007, p. 237). Furthermore, the results of the study showed that not only were the nurses more satisfied, but the patients and families were more satisfied in environments where ongoing professional development opportunities were available for nurses. Interestingly, this intervention proved cost 25  efficient, in terms of better retention rates and less sick time costs, and costs were not significantly different from the control units. Because the study was conducted at a single hospital site, the generalizability of findings is limited. Professional Development: Simulation Research Although nurses have indicated they value professional development opportunities at all career stages, no research has examined which method of educational delivery is the most effective in retaining nurses. An educational strategy that has been gaining traction within nursing over the last five to ten years is the use of high fidelity human simulators (Goldsworthy & Graham, 2013). High fidelity simulation mimics the practice setting and allows students to practice in a safe setting where the repetition of skills can occur along with reflective debriefing to deepen and possibly extend the learning that occurs during the simulation. A recent systematic review evaluated the use of simulation in undergraduate education. In the 101 research papers that were examined, seven themes emerged from the synthesis of the research (Forunda, Liu & Bauman, 2013). The themes included: confidence/self-efficacy, satisfaction, skills/knowledge and anxiety/stress. The researchers concluded that more robust simulation research is needed in nursing. In another recent systematic review that examined simulation-based learning in nursing education, a total of 12 studies were included in the final review (Cant & Cooper, 2010). The authors found that simulation improved knowledge/skill, critical thinking, and confidence among nurses. The research also showed that simulation may be advantageous over other teaching methods, depending on the context, method, and whether or not simulation best practices were followed. Examples of best practices in simulation include: curriculum-based scenarios, use of a three-step simulation process (briefing, simulation, and debriefing), and preparation of the 26  physical environment that closely mimics the practice setting (International Association for Clinical Simulation and Learning, 2013). A few studies have explored the impact of skills learned in simulation and how this transfers to the practice setting. In a US study of critical care nurses (N=24, over 880 medication doses) that compared a simulation intervention versus traditional lecture, and the influence on medication error rates in critically ill patients, significantly fewer medication errors occurred in the group that received the simulation intervention (Ford et al., 2010). Another US study compared lecture with simulation among senior-level nursing students (N=54) and found that neither teaching strategy was effective in isolation (White et al., 2013). A small number of research studies on simulation have demonstrated an increased clinical performance and self-efficacy in specific situations, such as among nursing students (N=54) in caring for patients with distributive shock (White et al., 2013), registered nurses (N=47) handling obstetrical emergencies such as eclampsia and pre-eclampsia (Christian et al., 2012), preparing nursing students (N=120) for paediatric practice settings (Meyer, Connors, Hou and Gajewski, 2011), and decreasing medication administration errors among nursing students (N=54) in acute medical surgical practice settings (Sears, Goldsworthy & Goodman, 2010). Summary: Professional Development From a number of key studies, the empirical evidence establishes that professional development and ongoing educational activities are highly valued by nurses in Canada, and globally, and serve as a key motivator for intent to stay. Professional development activities have been shown to be important across all career stages (Chang et al., 2007). Strategies that include the allotment of professional development time within the scheduled working hours such as with the 80/20 Model have been shown to reduce turnover rates (Bournes et al., 2007). 27  A variety of study designs have been used to conduct research in this area, though most studies are descriptive and cross-sectional. Interventional or longitudinal studies demonstrating the influence that professional development can have on a nurse’s intent to stay are lacking, and no studies have been conducted in the critical care nursing population describing specific professional development activities related to intent to stay. Although professional development opportunities have been established in the literature as a motivator or ‘pull’ factor for nurses to stay in their current position, specific effective strategies for delivering such opportunities have not been explored in the nursing population. Simulation is an emerging strategy in nursing education that has been shown to be more effective than other educational strategies (i.e., lecture or videos) for preparing nurses for practice. More robust research is needed in this area, beyond the simulation laboratory and into practice settings, to examine nurse outcomes such as intent to stay in the organization, unit, and profession. Work Environment Canadian nurse mean turnover rates have been shown to be 19.9%, with supportive work environments playing a key role in curtailing turnover (O’Brien-Pallas et al., 2010). Nurse work environments have been rapidly changing in the last 15 years as hospitals make efforts to reduce costs, streamline services, and cope with a worsening nursing shortage. Many of the definitions of a healthy work environment for nurses refer to practice environments that offer opportunities for autonomy, professional development, accountability, and control over the work environment (Estabrooks et al., 2002; Lake, 2002). The Registered Nursing Association of Ontario (RNAO) defines a healthy nurse work environment as: “…a practice setting that maximizes health and well-being of nurses, quality of patient outcomes and organizational system performance” (RNAO, 2013). The characteristics of a healthy nurse work environment include: strong 28  leadership, autonomy, manageable workloads, praise and recognition, participation in decision making, and collegial nurse physician relationships (Cowden & Cummings, 2014). Deteriorating work environments have been shown to negatively affect nurse and patient outcomes (McGillis-Hall, 2005). Unhealthy work environments can also lead to decreased work satisfaction and increased turnover among nurses, especially in the ICU, where high levels of stress occur daily as nurses are challenged to meet the complex needs of critically ill patients and their families (Scmalenberg & Kramer, 2007). In 2003, the Institute of Medicine (IOM) was so concerned about the influence of nurse work environments on the quality of patient care and the nursing shortage that they published an entire volume focusing on transforming nurse work environments to improve patient safety. Manager characteristics are key constructs of a supportive work environment in Boyle et al.’s (1999) and Cowden’s (2012) intent to stay models. In terms of manager characteristics, research findings support transformational or relational versus task or transaction-driven management styles. Transformational nurse leaders are inspirational, use shared decision making, mentor nurses, and provide praise and recognition (McGuire & Kennerly, 2006). Cowden and colleagues (2011) conducted a systematic review that examined the relationship between leadership practices and intent to stay among nurses. Twenty-three studies were included in the review, and overall, the authors found that relational leadership styles can influence the work environment and intent to stay among nurses. Cummings and colleagues (2010) also conducted a systematic review that examined the relationships between styles of leadership, nurse outcomes, and work environments. Fifty-three studies were included in the review and the authors found that the relational style, compared to a task-driven leadership style, was viewed more positively by nurses. Six of the studies showed associations between 29  management style and work environment factors, like collaboration between physicians and nurses, empowerment, and role clarity. In an Australian study of 1559 RNs working in 21 different hospitals, a secondary analysis examined the influence of manager leadership style on job satisfaction and intent to leave (Duffield et al., 2011). The results showed that when managers, who were perceived as good leaders (i.e., used relational approaches like shared decision making, being visible, providing praise and recognition), the nursing staff reported increased levels of job satisfaction and decreased levels of intent to leave. These results supported an earlier study on a large sample of Canadian nurses (N=717) from seven acute care hospitals (Doran et al., 2004). In this descriptive cross-sectional study, the results showed that if nurses perceived their manager to have a positive relational leadership style (i.e., transformational), the nurses reported a higher level of job satisfaction and intent to stay in their current position. In a descriptive cross-sectional study of Jordanian nurses (N=275) from three acute care hospitals, the influence of manager support and individual nurse characteristics on intent to stay at work were examined (AbuAlRub, 2010). The results showed that the greatest effect on the level of intent to stay (17%) was due to support from managers. Specifically related to the critical care nursing context is the American Association of Critical Care Nurses (AACN) Healthy Work Environment framework, which includes six elements required to establish and sustain a healthy work environment: skilled communication, true collaboration, effective decision making, appropriate staffing, meaningful recognition, and authentic leadership (AACN, 2005). An important aspect of supportive work environments and the intent to stay reported by nurses is the need to be valued and recognized within the 30  workplace. In fact, 75% of the American Association of Critical Care (AACN) members cited recognition of their contributions as a core element of a healthy work environment (AACN, 2005). In the AACN (2005) standards for establishing and sustaining healthy work environments document, meaningful recognition is among the priority standards of their model. Nurses are reporting a deterioration of their work environments in Canada and globally. In a large multi-country study (RN4cast study), examining the working conditions for nurses in the European nurse workforce (N=33,659 nurses), the results showed that nurses in all 12 countries had concerns about their work environment, which they reported to be fair or poor (Aiken et al., 2013). Another large cross-sectional observational 12 country European study (N= 23,159 acute care nurses) that examined nurses’ intention to leave the profession used work environment factors as independent variables (Heinen et al., 2013). The results showed that the work environment characteristics, such as nurse leadership, nurse-physician relationships, and career development opportunities, were related to intention to leave the profession at a cross-national level. Similar results were found in a Belgian study (N=3,186 acute care staff nurses) of 272 randomly selected hospital sites (Van den Heede et al., 2013). In this study, a single global work environment measure was found to be significantly associated with retention of nurses. A large US study was one of the first to specifically examine the work environments of critical care nurses (Ulrich, Lavendero, Hart, Woods, Leggett, & Taylor, 2006) The convenience sample included 4,034 American Association of Critical Care Nurses (AACN) members who were recruited through an online survey. The survey items were developed by the researchers based on a previous survey of AACN members in 2004. In this study, 48.6% of the respondents indicated they planned on leaving their current positions within the next three years. The top-31  ranked factors for intent to stay included: lack of recognition from managers, administrators, executives, and physicians. A cross-sectional descriptive study was conducted among critical care nurses (N= 698 staff nurses from 34 ICUs), with the aim of identifying differences in nurses’ perceptions of work environment, by type of ICU (Schmalenberg & Kramer, 2007). The authors found that neonatal and paediatric ICUs scored significantly higher than other types of ICUs in reporting the highest percentage of positive attributes of the work environment, with specific relation to such factors as: autonomy and control over practice, nurse/physician relationships, and adequacy of staffing. The study provides some evidence that nurses’ perceptions vary with regards to the work environments of different types of ICUs, and not only can organizational differences exist in the work environments but differences may also exist within ICU specialty areas. In the Canadian context, Leiter and Laschinger (2006) tested a work-life model with a large nursing sample (N=8597). The aim of the study was to examine the relationship of the work and practice environment to professional burnout. The work-life model included the professional practice environment qualities (i.e., supportive management, policy involvement, staffing, and physician-nurse relationships). The authors found that when nurses have access to work structures that allow them to accomplish their job, like strong leadership, the nurses experience increased levels of a perceived supportive work environment. Canadian researchers have also studied the work environment for nurses and its importance in retaining nurses from a generational viewpoint. In two studies in Quebec, Lavoie-Tremblay and colleagues (2011) studied nurse turnover in relation to their age category. In the first study, 309 nurses participated in a cross-sectional survey that measured characteristics of the work environment that included latitude in decision making, psychosocial demands, and social 32  support (i.e., colleagues and managers). The results showed that 61.5% of the nurses intended to leave their current position, and of those planning to leave their position, the reason was cited as being due to an imbalance between effort and rewards (i.e., career opportunities) and a lack of support from colleagues and managers. In a subsequent correlational descriptive study (N=145 – 59 Generation X and 86 Generation Y) by Lavoie-Tremblay and colleagues (2011), elements of the nurse work environment were explored for their potential influence on the Generation Y nurses’ intent to leave. No difference was found between the age groups (Generation X and Generation Y), in terms of their work environment scores. Intention to leave the unit was found to be significant in relation to three of the work environment subscales: nurse participation in hospital affairs, nursing foundations of quality care, and collegial nurse-physician relations. Summary: Work Environment Research in the area of healthy nurse work environments began over 20 years ago, with more studies being conducted in the last 5 to 10 years, likely motivated by the nursing shortage. The nurse work environment studies have primarily been descriptive cross-sectional surveys with very few reported interventional studies. Most of the research has been conducted in the US with a few studies in Canada, Europe, and Australia. No studies have examined the ICU nurse work environment. The urgency of examining nurse work environment factors has accelerated in recent years due to the nursing shortage and concerns with retaining and stabilizing the nursing workforce. With cutbacks, nursing shortages, and changing patient care delivery models, healthy workplaces have gained traction as a variable that influences whether a nurse stays or leaves the unit, the organization, or even the nursing profession. More interventional research is needed to determine 33  strategies that will facilitate healthy work environments for nurses. The empirical literature has established the risks for nurse outcomes, such as in turnover. In addition, key elements of the nurse work environment, such as nurse/physician communication, control over practice, and manager leadership, have been shown to influence nurse outcomes such as intent to stay (Cummings et al., 2010; Shalk et al., 2010; Scmalenberg & Kramer, 2007). The research is beginning to establish the relationship between healthy work environments, nurses, and organization and patient outcomes, though more research is needed to confirm the important factors for strengthening the nurses’ work environment. Perceived Organizational Support Perceived organizational support (POS) refers to “the employee’s perception concerning the extent to which the organization values their contribution and cares about their well-being” (Eisenberger, et al., 1986). Perceived organizational support is rooted in  social exchange theory (Homans, 1958; Blau, 1964) and is demonstrated when an employee feels obligated to reciprocate when the organization does something for them. Nevertheless, the employee must believe in the sincerity of the organizational support (i.e., praise and approval) for it to have value. In fact, higher levels of POS are related to job conditions, pay, and job enrichment if the employee believes the employer voluntarily contributed the rewards, instead of being contingent on a union or safety or other reason (Eisenberger, Cummings, Armeli & Lynch, 1997; Shore & Shore, 1995). Social exchange theory, (Blau, 1964), provides the theoretical underpinning of the POS theory (Eisenberger et al., 1986), finding its roots in both the economic and social psychological perspective in describing the process of negotiated exchanges between parties. The social psychology perspective refers to individual behavior within a social context, such as the nurse’s 34  behavior with the employer. In the case of the nurse, the effort or productivity is exchanged for the perceived reward or benefit. Perceived rewards or benefits in the acute care hospital setting can take many forms; for example: being valued or recognized by the manager and organization, being provided with tangible rewards such as educational opportunities, having time off to attend professional development opportunities, or simply being listened to and being included in the decision making. Eisenberger and colleagues (1986) found that POS was related to commitment, affective attachment to the organization, and decreased absenteeism. In their US study, the survey of POS (developed by Eisenberger et al., 1986) was used to examine how employees perceive they are being valued by the organization. In a follow-up to the study, Eisenberger and his colleagues (1990) studied business employees (N=361) and found that POS was positively related to job attendance and performance. Professional development opportunities have been found to positively influence the development of POS, and subsequently, levels of intent to stay. In a large US study of 20,000 employees from a variety of organizations, the antecedents and consequences of POS were explored. Employees who participated in professional development opportunities within an organization were found to have higher levels of POS, which was directly related to higher levels of intent to stay (Wayne, Shore & Liden, 1997). Similar results were found in another US study, where favorable work conditions were found to increase POS, which in turn decreased turnover (Rhoades et al., 2001). In the study, favorable work conditions were defined as perceived manager support and organizational rewards. A subsequent longitudinal US study also found that supportive human resource (HR) practices contributed to increased levels of POS (Allen, Shore & Griffeth, 2003). The authors defined supportive HR practices as: participation in decision 35  making, fairness of rewards, and the availability of growth opportunities. Furthermore, POS was shown to mediate relationships related to voluntary turnover. In a meta-analysis on the antecedents and consequences of POS, organizations show that they value their employee’s contributions and well-being in three main ways (Rhoades & Eisenberger, 2002). The major POS antecedent categories of beneficial treatment to employees were: supervisor support, organizational rewards and favorable job conditions (i.e., training, recognition, and autonomy), and fairness (i.e., the way in which rewards and resources are distributed). In the meta-analysis, the consequences of increased levels of POS were shown to be related to positive employee outcomes (i.e., positive mood and job satisfaction) and positive organizational outcomes (i.e., increased commitment, increased performance, and decreased turnover). The meta-analysis also showed that recent studies used POS in a mediating role between favorable treatment of employees and positive outcomes for the employee and the organization, like in decreased turnover. Riggle, Edmondson, and Hansen (2009) conducted a meta-analysis of POS examining the effects of four employee outcomes: organizational commitment, job satisfaction, performance, and intent to leave. The inclusion criteria for the meta-analysis were correlation to one or more of the four employee outcomes. From the 167 studies included in the meta-analysis, the authors found that POS had a strong negative relationship with intent to leave. Also, the effects of POS were more pronounced in non-frontline employees. Specifically, POS accounted for nearly 25% of the variance in intent to leave across the studies analyzed. In a study of POS in the front-line nursing population, professional development and job engagement were explored (Trinchero, Brunetto & Borgonovi, 2013). Job engagement was defined as satisfying and positive feelings related to one’s job position. In the cross-sectional 36  study of acute care nurses in Italy (N=827), the results demonstrated that investment in professional development opportunities for nurses enhances their work environment by improving affective responses (engagement) to their current position. Furthermore, POS was shown to predict engagement of nurses, and training and development accounted for 25% of the variance in engagement. The researchers suggested that more research would be needed to identify which professional development opportunities are most likely to enhance engagement among nurses. In the only Canadian study of nurses that explored POS, Laschinger and colleagues (2006) examined antecedents and consequences of POS. The study was a descriptive secondary analysis from a larger study, where 126 middle-level nurse managers were surveyed. The authors found that the organizational characteristics most related to POS were: rewards for effort, respect, job security, autonomy, and monetary gratification. Work conditions and levels of POS were found to have a strong impact on empowerment and individual job performance levels. Summary: Perceived Organizational Support A small number of international studies of nursing populations have specifically examined POS, and even fewer have focused on the Canadian context, though the subject is well studied in other employee groups. The research has established that an employee’s perception of organizational support is increased with favorable treatment, such as open communication and investment in professional development opportunities. Increased levels of POS are related to positive organizational outcomes such as increased intent to stay and decreased turnover. Trinchero et al. (2013) showed that POS was related to job engagement in nurses, though little is known about the influence of POS among nurses on their intent to stay in the organization, unit, or profession. Perceived organizational support is a complex subject and the overall employee 37  perception is shaped by organizational support that includes communication, feedback, and mechanisms for reward and recognition within the organization. In the next section of the literature review, the focus is on factors that influence training, transfer of learning, and intent to stay. Transfer of Learning Organizations are not only interested in retaining nurses but in retaining employees who are high performers and able to successfully transfer learning into the practice environment. Every year, hospitals invest a significant amount of funding into educational programs to provide the necessary training for nurses who are new to critical care, so that they can transition effectively into the critical care environment (Ministry of Health and Long Term Care Ontario, 2014). The programs are designed to enhance knowledge, competency, and judgement for providing safe patient care to critically ill patients (Registered Nurses Association of Ontario, 2009). Many of the competencies learned in these programs are related to high risk skills that must be performed often in rapidly changing patient conditions. Ideally, organizations would like to have maximal return on their investment for the programs to ensure that the training is effective for the transfer of skills and competencies into practice. Transfer of learning refers to a change in behaviour on the job once training has been received (Noe, 2006). Positive transfer of learning is used interchangeably in the literature with transfer of training, which is defined as: the degree to which trainees effectively apply knowledge, skills, and attitudes gained in the training context to the job (Newstrom, 1986) and the extent to which the learning that results from the training experience transfers to the job and leads to meaningful changes in work performance (Goldstein & Ford, 2002). Transfer of learning has been conceptualized in the literature as both a mediator and a moderator. Key studies in 38  transfer of learning are presented in the next section, along with major findings, measures, and the relationship to the current proposed study variables, including self-efficacy. The most frequently cited transfer of learning model is the Baldwin and Ford (1988) model. This framework includes three main components: training inputs (trainee characteristics, training design, and work environment factors), training outputs (acquisition of knowledge and skills during training), and conditions of transfer (generalization of knowledge and skills and the maintenance of skills learned over time). Trainee characteristics include self-efficacy and motivation, while the training design includes method of training and use of training objectives. In addition, specific work environment characteristics include: transfer climate, peer and supervisor support, and opportunities or barriers to applying the learned behaviors in the work setting. Later, Facteau and colleagues (1995) developed a transfer of learning model that incorporated peer support, manager support, pre-training motivation, and task constraints, which were similar to the Baldwin and Ford (1988) model, except that input variables were also included, such as training reputation, incentives, compliance, organizational commitment, career exploration, and career planning based on predicting perceived transfer of training. Facteau and colleagues found that, of the four support constructs (peer, subordinate, top management, and supervisor), only supervisory support was related to pre-training motivation. Learners that are motivated are more likely to engage in learning (Clayton, Blume, & Auld, 2010). Examples of factors that promote transfer include: supervisor and peer encouragement to use new skills, task cues that remind employee to use new skills, and rewards for using new skills in a work setting. Organizations that encourage and promote continuous learning have systems in place for sharing knowledge and learning is rewarded and supported by managers. In contrast, some obstacles in 39  the work environment have been shown to inhibit transfer (Noe, 2006); for example: work conditions (time pressures, few opportunities to use skills, and inadequate equipment), lack of peer support, and lack of management support. A small number of studies have explored the influence of transfer of learning on turnover intention among employees, though no studies have been conducted in the nursing population. One study examined the relationship of organizational learning culture, job satisfaction, and organizational outcomes among informational technology (IT) employees in the US (Egan, Yang, & Bartlett, 2004). The authors found that organizational learning culture and job satisfaction influence motivation to transfer learning and turnover intention. In another US study, linking transfer of learning to turnover intention, 598 child care service workers from 14 child welfare agencies were evaluated, in terms of work environment factors and organizational outcomes, such as retention of employees (Curry & McCarragher, 2005). The seven-year, longitudinal study was aimed at identifying transfer of learning factors that predicted staff retention. The results showed that co-worker support was important for retention in workers with less experience, and supervisor support was a key retention factor in highly experienced workers. Trainee characteristics, such as self-efficacy, also play an important role in transfer of learning. Chiaburu and Marinova (2005) examined goal orientation, training self-efficacy, and organizational supports (peer and supervisor) and their influence on skill transfer. They studied 186 corporate employees who attended a one-day leadership and customer service training course. The results showed that peer support and self-efficacy predicted skill transfer. Two of the major meta-analyses in the area of transfer of learning were conducted by Arthur et al. (2003) and by Blume et al. (2010). The focus of Arthur’s meta-analysis was measurement of effectiveness of training in organizations specifically related to design and 40  evaluation features. The features included: type of evaluation criteria, implementation of a training needs assessment, the skill or task characteristics, and the match between skill characteristic and training method. The overall results from 165 studies revealed a medium to large effect size for organizational training. Most studies with effective training were found to use multiple training methods (i.e., lecture and psychomotor skill application). The results showed that, for maximal training effectiveness, the skills required in the workplace must be matched with the training and evaluation method. For example, in the nursing training context, high-fidelity human simulators must be used to create a realistic clinical environment in the lab so that nurses can learn specific skills and competencies. The second major meta-analysis, by Blume and colleagues (2010), included 89 studies and explored the predictive factors of transfer of training. The primary predictors that were highlighted in the meta-analysis were: trainee characteristics, work environment characteristics, and the training intervention. For the three categories, the research was mainly focused on the training design and delivery methods. Pre-training self-efficacy was found to have a small to moderate relationship with transfer of learning. Transfer climate was found to have the strongest relationship with transfer of learning. Pre-training self-efficacy was also found to have a higher moderating effect on transfer of learning, for open versus closed skills. Open skills are training objectives tied to learning principles, whereas, closed skills are training objectives tied to specific skills that must be produced identically in the work environment. In the literature, some studies have examined the effect of high-fidelity simulation interventions on the transfer of learning and performance in the practice area. Gunberg Ross (2012) completed a review of the literature on simulation and psychomotor skill acquisition and found a few studies that examined simulation and skill acquisition among nurses. Much of the 41  research in this area is descriptive and no quantitative studies focus on psychomotor or cognitive skill attainment. In a US systematic review of the literature that examined the use of simulation for nursing staff education and development, few rigorous research studies were found to support its use. The author of this review also concluded that more research is required on the transfer of skills and knowledge from the simulation laboratory to the practice setting (Hallenbeck, 2012).  A large systematic review and meta-analysis was conducted to examine technology-enhanced simulation used in health professions education (Cook, Hatala, Brydges, Zendejas, Szostek, Wang et al., 2011). In the meta-analysis, 609 eligible studies were found, and of these, 137 were randomized studies and 405 used a single group pre-test post-test design. The results showed a small to moderate effect that favored simulation in comparison to other instructional strategies (i.e., video, lecture, and small group). Nurses and nursing students accounted for 79 of the studies that were reviewed. This analysis extracted studies that involved a broad spectrum of simulation, across all fidelity levels of simulators and other simulation strategies including the use of cadavers. In one of the few studies on performance improvement in the clinical setting, the effect of a simulation activity was examined on the performance of established interprofessional critical care unit teams. The sample included 40 teams comprised of one doctor and three nurses from nine different critical care units in eight hospitals in New Zealand (Frengley, Weller, Torrie, Dzendrowskyj, Yee, Paul et al., 2011). Teams participated in cardiac and airway scenarios and the results of the ten-hour intervention showed an improvement in team work and evidence for changes to patient management. In another simulation intervention study of 38 medical-surgical registered nurses in Australia, simulation was shown to have positive effects on performance. The intervention consisted of 14 hours of theory related to clinical emergencies that could lead to 42  cardiac arrest. The lecture was followed by three hours of practice in the simulation lab with high-fidelity simulators. The results showed that nurses’ confidence and perceived technical and non-technical skills in responding to patient emergencies were enhanced after simulation (Gordon & Buckley, 2011). Nevertheless, the study was limited by its small sample, self-report researcher-developed measure, and the relatively short simulation intervention. Transfer of Learning: Summary No Canadian studies of transfer of learning have been conducted with nurses. Most of the research on transfer of learning has been conducted in the US, with workplace context studies primarily beginning in the 1970s. Most of the studies measured transfer of learning at one point in time, rather than over several data points; at least one short-term and one long-term measure should be used to evaluate the maintenance of transfer of learning over time (Gaudine & Saks, 2004). No rigorous studies were found that reported the measurement of transfer of learning in the nursing workplace context. Limitations of the research included: small sample sizes, data collected at single workplace sites, predominately self-report measures, short training periods (i.e., median length of the reported training was six hours), and a wide range of post measurement timeframes (i.e., from immediately after training to 163 weeks post-training) (Arthur, Bennett, Edens, & Bell, 2003; Blume, Ford, Baldwin, & Huang, 2010). For organizations to benefit from their investments in employee training, the predictors of transfer of learning must be carefully considered. Initially most transfer of learning research focused on the design of the training programs. More recently, transfer of learning has emerged as a contributor to organizational outcomes with the emphasis on how skills are transferred from the training context to the work environment. The major predictors of transfer of learning have been established as: trainee characteristics (motivation, ability), work environment 43  characteristics (climate for transfer, management and peer support, opportunity to perform, and technological support) and the training design (Noe, 2006). To promote transfer of learning, employees require specific conditions in the immediate work environment that promote transfer of learning such as: manager support, adequacy of resources, and opportunity to practice skills.  Self-Efficacy An individual’s self-efficacy can influence how they approach tasks and new challenges, such as learning situations. Self-efficacy is conceptualized as being general or domain specific. General self-efficacy is a trait-like generality dimension defined as: “…an individual’s perception of their ability to perform across a variety of situations” (Judge, Erez, & Bono, 1998, p. 170). Domain-specific self-efficacy refers to how an individual feels capable of approaching and performing specific tasks, such as competencies in critical care (Bandura, 1986). Self-efficacy is differentiated conceptually from similar constructs, like self-esteem, which is considered to be a relatively stable ‘trait’. Situational self-efficacy, on the other hand, is considered to be a ‘state’ that is dynamic in time and in different contexts (Gist & Mitchell, 1992). The concept of self-efficacy arises from social cognitive theory, in which an individual’s reactions and actions are based on what the individual has observed in others (Bandura, 1986). Self-efficacy is broadly defined as: “…people’s judgements about their capabilities to organize and execute courses of action required to attain designated types of performance; it is concerned not with the skills one has but with judgments of what one can do with whatever skills one possesses” (Bandura, 1986, p. 391). At the beginning of self-efficacy theory development, Bandura published Social Learning and Personality Development (1963) and introduced the concepts of observational learning and vicarious reinforcement. Later, he published a new iteration of the theory in which self-beliefs 44  emerged as an important component of the theory (Bandura, 1977). As the theory evolved, Social Foundations of Thought and Action: A Social Cognitive Theory was published (1986). In this publication, Bandura describes the important role of cognitive, self-regulatory and self-reflective processes in how people adapt to situations and change, to demonstrate the dynamic nature of self-efficacy in different domains. Within self-efficacy theory, individual and environmental factors are at play to inform or change an individual’s behavior within a specific context. Bandura relabelled his theory “social cognitive versus social learning theory” to signal the essential role played by cognition in an individual’s views of reality and subsequent behaviors. Domain-specific self-efficacy is typically developed through mastery experiences and through vicarious learning and modeling by observing others perform the task (Bandura, 1986). Mastery experiences are largely gained through hands-on experience, as through practice in the clinical setting with patients or through practice in the simulation laboratory with simulated patients. Bandura (1986) also argued that self-efficacy develops with opportunity to repeat tasks. Individuals that have increased levels of self-efficacy feel they can have an impact on their environment, whereas, individuals with low levels of self-efficacy view problems as unmanageable and insurmountable. Individuals with low self-efficacy may avoid a situation, instead of facing a task, if they may not be able to do it. The development of self-efficacy occurs in four categories: enactive mastery (personal attainments), vicarious experience (modeling) by observing others succeed through their efforts, verbal persuasion that one possesses the capabilities to cope successfully, and physiological arousal (i.e., anxiety) in that individuals judge their level of anxiety and vulnerability to stress (Bandura, 1982). Enactive mastery is the most important factor in determining individual levels of self-efficacy and when an individual 45  successfully performs a task, their self-efficacy level increases, compared to when they are unsuccessful and their level of self-efficacy decreases. The following review of the literature will explore relationships between self-efficacy and its influence on transfer of learning and intent to stay among employees. Research on self-efficacy in relation to training interventions is important in the understanding of effective training. An individual with higher self-efficacy is more likely to make an effort and persist longer at a task, compared to those with lower self-efficacy. Self-efficacy has been shown to significantly influence academic success, persistence, and career competency (Bandura, 1993). Task-specific self-efficacy has also been shown to influence a novice’s adjustment to the workplace (Saks, 1995; Stajkovic & Louthans, 1998). Furthermore, domain-specific self-efficacy has been operationalized in the literature as a moderator of training methods for post-training self-efficacy and performance (Gist, Stevens, & Bavetta, 1991). Training has been shown to increase task/domain-specific self-efficacy (Tannenbaum, Mathieu, Salas, & Cannon-Bowers, 1991), and several studies have established the relationship between training and self-efficacy (Gist, 1991; Mathieu et al., 1993), revealing that levels of self-efficacy predict trainee learning and performance (Salas & Cannon-Bowers, 2001). Self-efficacy can be enhanced through formal training programs, especially, when the individual perceives the training to be similar to the work environment where they will be applying their skills (Luthans & Youssef, 2007). Tannenbaum and colleagues (1991) had similar findings: when training meets the participant’s expectations, their organizational commitment, self-efficacy, and training motivation are positively influenced. Self-efficacy has also been found to moderate training methods for such outcomes as transfer of learning (Gist, 1992; Pham, Mien, & Gijselaers, 2010; 46  Saks, 1995) and has been found to be a key variable in transfer of learning research (Machin & Fogarty, 1997). In addition to the influence of self-efficacy on training outcomes, in a limited number of studies, self-efficacy was found to influence employee turnover outcomes (McNatt & Judge, 2008; Saks, 1995). Meta-analyses have also demonstrated that self-efficacy is strongly associated with work-related performance (Bandura & Locke, 2003; Stajkovic & Luthans, 1998). Colquitt and colleagues (2000) demonstrated that self-efficacy predicts motivation to learn. Individuals with increased levels of self-efficacy will have a greater likelihood of persevering and performing on the job. In summary, self-efficacy is a motivational construct that influences whether or not an individual believes they can complete the task, which influences their effort, coping, and persistence. Tannenbaum and colleagues (1991) conducted research where pre- and post-training attitudes were compared among 1037 US naval recruits during an eight-week orientation training intervention. When the training met the participants’ expectations, they had an improvement in their post-training attitudes, in terms of organizational commitment and self-efficacy. The authors found that levels of pre-training motivation and self-efficacy may ‘prime’ individuals so that they will be able to extract the most out of training. Earlier work by Mathieu, Martineau, and Tannenbaum (1993) tested a model that contained individual and situational antecedents of self-efficacy development as a result of training. The authors found that the initial self-efficacy levels had a strong positive relationship with mid-course self-efficacy. McNatt and Judge (2008) tested a self-efficacy enhancing intervention and its relationship in accounting auditors and found that levels of post-training self-efficacy were significantly related to decreased levels of employee intention to quit and actual turnover, 47  measured five months post-intervention. The authors reported that self-efficacy can play an important role in influencing job attitudes (i.e., intention to quit) and during employee role transitions into a new job position. Studies in the nursing population have explored the influence of self-efficacy and performance for specific tasks. In one study exploring self-efficacy in the nursing population, a simulation intervention was delivered to 112 undergraduate nursing students (Bambini, Washburn & Perkins, 2009). In the intervention, the training included maternal/child scenarios that mimicked the real practice settings, which were delivered via high-fidelity patient simulators. The results showed a significant increase in the levels of self-efficacy when pre-tests were compared to the post-test measures (Bambini, Washburn & Perkins, 2009). Similar results were found in a US study (N=49 registered nurses) where high-fidelity simulation training was conducted for pre-eclampsia and eclampsia management. Nurse levels of self-efficacy were significantly increased when the pre- and post-tests were compared (Christian & Krumweide, 2012). In addition, the levels of self-efficacy were found to be sustained over time when the post-tests were re-administered at eight-weeks post-intervention. In this single group design, the nurses also reported being highly satisfied with simulation as an effective teaching strategy. In the Canadian context, Gaudine and Saks (2004) conducted a longitudinal quasi-experimental study to test a relapse prevention strategy and the transfer of learning enhancement on self-efficacy, performance, and the transfer of learning behaviour in a sample of acute care nurses from eleven different units in one Canadian hospital. A relapse prevention strategy refers to a specific transfer component that takes place after the initial training and provides participants with strategies on how to transfer newly acquired knowledge and skills to the 48  practice setting. Transfer enhancement interventions are focused on coaching participants to identify opportunities where new knowledge can be applied. Results were measured at three time intervals: immediately after the two-day training for complex interpersonal skills; and at two months and six months. The results of the initial training program showed increased levels of self-efficacy and self-efficacy also predicted the transfer of learning up to six months after the initial intervention. Nevertheless, the results did not show increased levels of transfer of learning related to the relapse prevention and post-training transfer enhancement intervention. The transfer of learning and self-efficacy measures were developed by the researchers according to the specific context of the training, and both scales demonstrated Cronbach’s alpha of > .90. Self-efficacy has also been studied in relation to how newcomers adjust to the workplace. In a longitudinal Canadian study with newly hired entry level accountants (N=154), the moderating and mediating effects of self-efficacy were studied with regards to training and newcomer adjustment during their first year of employment (Saks, 1995). An individual’s initial level of domain/task-specific self-efficacy was found to moderate the relationship between training and adjustment. Employees who had higher levels of task-specific self-efficacy, or believed that they could succeed in specific tasks, had higher rates of transfer of learning. A hierarchical regression analysis showed that the initial domain-specific self-efficacy explained a significant amount of the variance in post-training self-efficacy. In addition, levels of post-training domain-specific self-efficacy were found to mediate the relationships between training, professional commitment, and intention to quit the organization and the profession. Summary: Self-Efficacy Self-efficacy has been examined as a ‘trait-like’ generality dimension and a domain/task-specific ‘state-like’ construct. General self-efficacy best predicts general performance across a 49  broad spectrum of contexts and situations, while domain-specific self-efficacy best predicts motivation in a domain-or task-specific context. Most researchers have focused on domain-specific self-efficacy; however, Chen and colleagues (2008) found that “ … high general self-efficacy can maintain employees’ work motivation throughout rapidly changing stressful job demands and circumstances and buffer them from the potentially demotivating impact of failure”. Eden et al. (1988) found that general self-efficacy influences domain-specific self-efficacy across tasks and situations. In the literature, self-efficacy has been operationalized as a mediator and a moderator and causal links have been made between self-efficacy and transfer of learning, as well as self-efficacy, newcomer adjustment in the workplace, and intent to stay. General self-efficacy has also been shown to moderate external influences such as training on performance (Eden et al., 1988). In the nursing literature, few studies have examined self-efficacy. Much of the previous self-efficacy research was conducted in classroom settings versus organizational settings, and few of these studies were longitudinal in nature. Most of the studies on self-efficacy focus on specific domains versus a general context. In the few studies dealing with simulation and self-efficacy, high-fidelity simulation has been shown to be positively related to both general self-efficacy and situation-specific self-efficacy among nurses. Summary of Literature In a worldwide nursing shortage that continues to worsen, critical care units have been significantly affected (O’Brien-Pallas et al., 2010). In Canada, ICUs have some of the highest rates of turnover, highlighting the urgent need to examine the factors influencing the RNs’ intent to stay in this area. The disengagement process tends to be a gradual process, beginning with the 50  nurse’s decision to leave the unit, and then the organization, and finally, the nursing profession altogether (Morell et al., 2005). International and Canadian research has demonstrated the top factors that influence intent to stay, including: aspects of the nurse work environment related to manager characteristics (i.e., relational leadership style and manager support, and shared decision making) and internal work characteristics (i.e., professional development opportunities, staffing, and workload). Nurse work environments have changed significantly over the last few years, with hospital cutbacks, changing skill mixes, and patterns of health care delivery. Unhealthy work environments can lead to decreased levels of intent to stay among nurses. A healthy work environment is also emerging as an important variable in retaining nurses in the ICU, though little research has addressed this issue. Critical care nurses have a unique workplace environment that requires high levels of specialized competency and the ability to critically and rapidly perform in life and death situations. Nurses have identified that part of a healthy work environment includes ongoing professional development opportunities. Research has shown that nurses value professional development at all stages of their career. To date, research is lacking on which educational strategies might be best for motivating nurses to stay in their position (or in their organization and profession). Simulation education is emerging as a strategy for effectively increasing self-efficacy and clinical competency among nurses, though simulation has not been examined in relation to intent to stay among nurses. Investment by organizations in professional development is seen as a form of organizational support that signals to nurses that the organization values their contributions and cares about their well-being. Healthy work environments that include manager support and 51  organizational rewards (i.e., professional development opportunities) have been found to increase levels of perceived organizational support; however, little research has been done in this regard, with front-line nurses and their intent to stay. Hospitals make large financial investments to provide orientation programs to assist nurses in transitioning into the critical care setting. To determine whether or not the organization is receiving a good return on its investment, the idea of transfer of learning is being used to measure organizational and workplace outcomes, like performance and turnover. Hospitals are also interested in whether or not employees can apply the skills they learn in training to the practice setting, to provide safe, high quality care. Unhealthy work environments that lack manager support and have inadequate resources are seen as having obstacles in the transfer of learning to employees. Transfer of learning increases when the training environment is similar to the practice setting and when employees have opportunities to practice their skills immediately after training. The major predictors of transfer of learning are: trainee characteristics (i.e., levels of self-efficacy), work environment, and training design. A few studies have examined the influence of transfer of learning on intent to stay, but none of these were with the nursing population. Self-efficacy, which is closely related to transfer of learning, has been studied in two dimensions: ‘trait’ (general self-efficacy) and ‘state’ (domain-specific self-efficacy) (Chen, 2008). Bandura (1986) identified important factors in the development of domain/task-specific self-efficacy, such as: mastery of tasks, observation of others succeeding through their efforts, and verbal persuasion that one possesses the capabilities to cope successfully when approaching specific tasks. General self-efficacy has been found to influence domain-specific self-efficacy 52  (Judge, Bono, & Locke, 2000). Training also increases levels of self-efficacy and self-efficacy moderates the relationship between training and newcomer adjustment and intent to stay. Simulation has emerged in recent years as an educational strategy for nurses and has been shown to increase levels of self-efficacy, competence, and performance. Further research is needed in this area to establish the influences of simulation and the transfer of learning to the practice setting. Much of the simulation research has been conducted in simulation labs without considering the transfers of learning behaviours over time. No research has explored the relationship between transfer of learning, self-efficacy, and turnover intentions of nurses in critical care. In summary, complex factors influence intent to stay, including a number of interrelated variables such as: professional development opportunities, perceived organizational support, healthy work environments, self-efficacy, and transfer of learning. In this study the effects of a specific training program on critical care nurse intent to stay were explored. The theoretical model developed in this study was informed by the models of Price and Mueller (1981, 2001), Boyle et al. (1999), and Cowden (2012), which includes concepts related to the work environment. Additional new concepts have also been included; namely: perceived organizational support, self-efficacy, transfer of learning, and professional development opportunities. Testing the new predictors of intent to stay with previously tested predictors may provide more insight into the affective and cognitive aspects of the nurses’ intent to stay, which have been shown to be the most important predictor of actual turnover.    53  Chapter 3. Conceptual Framework The aim of this study was to examine the influence of a professional development intervention on critical care nurses’ intent to stay, the mechanisms of effect, and the influence of other organizational factors on these relationships. This study was informed by several theories: the Social Exchange Theory (Blau, 1964), Organizational Support Theory (Eisenberger et al., 1986), Transfer of Learning Theory (Baldwin & Ford, 1988; Holton, Bates & Ruona, 2000; Noe & Schmitt, 1986) and Social Cognitive Theory (Bandura, 1986). These theories have been described in the preceding literature review chapter. A conceptual model representing this study, the Critical Care Nurse Retention Model, is outlined below (see Figure 4). Critical Care Nurse Retention Model Hypothesis 1. First, the professional development intervention is likely to relate positively to intent to stay since nurses view the investment in professional development opportunities for staff as a signal of organizational support. The theoretical underpinning to this hypothesis is perceived organizational support theory, which has its roots in social exchange theory and posits that employees that feel supported by their organizations will, in exchange, reciprocate by having increased levels of performance and a higher likelihood of staying with the organization (Eisenberger et al., 1986). An employee has a higher level of perceived organizational support when they feel the organization values them, invests in them (i.e., providing rewards or such as professional development or educational opportunities). The Critical Care Nurse Retention Model hypothesizes a positive relationship between professional development intervention and intent to stay among critical care nurses. 54  Hypothesis 2. Second, it is predicted that professional development opportunities relate to intent to stay via its effect on perceived organizational support. Nurses who feel supported by their organizations through investments such as educational opportunities are more likely to stay on the job, in the organization and in the profession. It is therefore hypothesized that perceived organizational support will mediate the relationship between the professional development intervention and intent to stay among critical care nurses. This hypothesis is informed by perceived organizational support theory (Eisenberger et al., 1986). Mediating variables are a third variable that influences the relationship between predictor and outcome variables and specifies the ‘how’ and ‘why’ the intervention or predictor is effective (Hayes, 2013). Perceived organizational support has been clearly established in the literature as an important predictor of intent to stay (Riggle & Edmondson, 2009).  Hypothesis 3. Third, it is predicted that professional development positively relates to intent to stay through its effect on critical care self-efficacy. Nurses who feel better prepared and to approach tasks in the critical care setting will have a higher level of self-efficacy that will enable them to approach the competencies required to practice safely in ICU, which will in turn reduce the likelihood the nurse will feel the need to quit (i.e., a higher intent to stay). This hypothesis was informed by Bandura’s (1986) social cognitive theory which describes how individuals and environmental factors influence an individual’s behaviour in a specific context. Bandura’s (1986) theory posits that domain specific self-efficacy is developed through mastery experiences which are largely gained through hands-on practice. Professional development has been shown to be related task specific self-efficacy has been shown to influence a novice’s adjustment to the 55  workplace (Saks, 1995). An example of hands-on experience in the critical care nurse context is being able to achieve mastery in the management of a cardiac arrest. It is therefore hypothesized that critical care self-efficacy will mediate the relationship between the professional development intervention and intent to stay among critical care nurses. Hypothesis 4. Fourth, the relationship between the professional development intervention and perceived organizational support is moderated by the work environment, such that the association is stronger when key elements of the work environment (i.e., manager support, adequate workload and resources, involvement in hospital affairs and collegial nurse physician relations) are higher versus lower. This hypothesis was informed by the intent to stay models of Boyle et al. (1999) and Cowden (2012). In these models work environment factors (i.e., manager support) were shown to influence intent to stay. In the current study, work environment was tested as a moderator variable. A moderator variable affects the direction or strength between two variables, and moderating effects account for additional variance in the outcome variables beyond what is explained by the predictor variable (Baron & Kenny, 1986; Bennett, 2000). Magnet hospital research in the US has shown that “magnet-like” work environments are associated with better nurse outcomes, such as increased intent to stay (Schmalenberg & Kramer, 2007). In Canada, magnet-like work environments are also referred to as healthy work environments or quality practice environments (Cummings et al., 2010; Estabrooks, Tourangeau, Humphrey, Hesketh, & Giovanetti, 2002). Hypothesis 5. Fifth, the relationship between the professional development intervention and critical care self-efficacy will be moderated by general self-efficacy, such that the association is stronger 56  when nurses have higher levels of general self-efficacy. This hypothesis is underpinned by Bandura’s (1986) social cognitive theory and explored general versus domain specific self-efficacy. General self-efficacy refers to how an individual perceives their capability of approaching and performing tasks across a wide variety of contexts and is a product of an aggregation of previous experiences (Chen, 2008). Although this relationship has not been studied in the nursing population, general self-efficacy has been shown to moderate the relationship between training and performance outcomes among business professionals (Eden et al., 1988).  Hypothesis 6. Sixth, the relationship between critical care self-efficacy and intent to stay will be moderated by transfer of learning, such that the association is stronger when nurses have higher levels of transfer of learning. This hypothesis was informed by the Facteau et al. (1995) transfer of learning model.  Transfer of learning incorporates elements of the work environment such as transfer climate (i.e., manager support, peer support, the opportunity to practice new skills). When a positive transfer climate is in place, the employee will have a higher likelihood of transferring skills learned (i.e., in the simulation lab) to the practice setting.  It was hypothesized that nurses who feel more comfortable in approaching critical care competencies (i.e., management of a cardiac arrest, prioritization of care for a critically ill patient) would have a smoother adjustment to the workplace and therefore a higher likelihood of staying in the ICU, the organization and the profession. This relationship is hypothesized to be stronger when there are higher levels of transfer of learning, or the opportunity to apply learned skills in the practice area.  57  Figure 4. The Critical Care Nurse Retention Model  Outcome: Intent to Stay Major meta-analyses of turnover have shown that the crucial component in retention models is the ‘intention’ of the employee since intention to stay or leave is the most powerful predictor of actual turnover (Griffeth, Horn & Gaertner, 2000; Hayes et al., 2006; Steel & Ovalle, 1984; Steel & Lounsbury, 2009; Tett & Meyer, 1993). In the nursing population, studies have shown that one of the key motivators of intent to stay is organizational support in the form of access to professional development/educational opportunities (O’Brien- Pallas et al., 2006; Shields et al., 2001; Ulrich et al., 2006). Therefore, the general outcome of interest in this study is intent to stay. Intent to stay has been measured on three dimensions: intent to stay in current position, intent to stay in the organization, and intent to stay in the nursing profession. However, most studies have only examined the nurse’s intent to stay in his or her current position. The Critical Care Nurse Retention Model extends the conceptualization of intent to stay to include staying within the organization and the profession. Clearly, intent to stay within the profession of nursing has serious implications in terms of the current nursing shortage.   58  Chapter 4. Methods The purpose of this study was to examine the influence of a professional development intervention on critical care nurses’ intent to stay, the mechanisms of effect, and the influence of other organizational factors on these relationships. A secondary objective of the study was to explore the influence of transfer of learning on intent to stay among critical care nurses. Design This study used a quasi-experimental design to test the effects of a professional development intervention on critical care nurses’ intent to stay. It also tested the Critical Care Nurse Retention Model. Participants included a convenience sample of critical care nurses who had attended a professional development program that consisted of simulation and practicum components, and a comparison group that consisted of a random sample of critical nurses obtained from the professional licensure registry in the same province. Data were collected at four time points in the treatment group and two time points in the comparison group. In the treatment group data collection time points included: Time 1 (prior to the simulation portion of the intervention), Time 2 (two weeks after Time 1- post-simulation), Time 3 (three months after Time 2- at the end of the practicum portion of the intervention) and Time 4 (6-8 months after Time 3 dependent on practicum completion time). In the comparison group, data collection for Time 1 aligned with Time 1 data collection in the treatment group and Time 4 aligned with Time 4 data collection in the treatment group.  The sample size at each data collection point is reported in Table 1. Data collection was completed with the comparison group through two mailed surveys and was also collected via mail for Time 3 and 4 in the treatment group yielding an expected but smaller return rate of 59  between 29-44%. In contrast, the Time 1 and 2 data collection from the treatment group were in person and yielded a 98% return rate. Time 1 and Time 4 data are used for comparing outcomes across groups and Time 2 and 3 data are used for comparing outcomes in the treatment group.  Table 1. Sample Size at Data Collection Time Points Cohort Time 1 n Time 2 n Time 3 n Time 4 n Treatment: Group 1  65 65 28 --- Treatment: Group 2  27 27 5 --- Treatment: Group 3  90 78 13 --- Group 1,2,3 (total) 182 170 46 65 Comparison (total) 181 --- --- 73 Note. Group 1, 2 and 3= treatment group, Time 1= post online and pre-simulation component, Time 2= post simulation component, Time 3= post practicum component, Time 1 to Time 2= 3 weeks duration, Time 2 to Time 3= 3 months duration. Time 4= 6-8 months post practicum (or post Time 3).  Research Hypotheses 1. There will be a significant difference in critical care nurses intent to stay (unit, organization, and profession) for nurses who receive the professional development intervention compared with a comparison group of critical care nurses, while controlling for their baseline levels of intent to stay. 2. Perceived organizational support will mediate the relationship between the professional development intervention and intent to stay among critical care nurses. 3.  Critical care self-efficacy will mediate the relationship between the professional development intervention and intent to stay among critical care nurses. 60  4. Positive work environments will moderate the effect of professional development on perceived organizational support, such that the effect will be stronger when work environment scores are higher versus lower. 5. General self-efficacy will moderate the influence of professional development on critical care self-efficacy, such that the effect will be stronger when general self-efficacy levels are higher versus lower. 6. Transfer of learning will moderate the relationship between critical care self-efficacy and intent to stay among critical care nurses, such that the effect will be stronger when transfer of learning scores are higher versus lower. Study Setting and Sample Target population, sample and setting. The target population consisted of critical care nurses from Ontario. For this study, critical care units included: intensive care units (ICU), coronary care units (CCU), cardiovascular intensive care units (CVICU), and neurological intensive care units (Neuro ICU). Part-time and full-time RNs were included in this study. Treatment group participants were a convenience sample of RNs enrolled in a critical care graduate certificate e-learning program at Durham College located in southern Ontario, Canada. Comparison group participants were RNs who were registered with the College of Nurses of Ontario (CNO), the nurse licensing body in Ontario, and who work in critical care units within Ontario. Participants were excluded from the comparison group if they were working on a casual or agency basis or are currently attending or had previously attended the Durham College Critical Care e-Learning program.  61  Sampling strategy and recruitment feasibility. Two sampling strategies were used. A convenience sample of potential intervention group participants was recruited from the Durham College critical care e-learning program prior to the start of the intervention. This program served as the professional development intervention for this study. There are three program intakes per year (January, May and September), and typical intake is 100 critical care RNs. The intervention group was recruited from two intakes, thus having access to approximately 200 students. The return rate in the treatment group was 100% (182) Time 1, 98% (170) Time 2 for the in-person surveys and 36% (46) Time 3 and 32% (65) Time 4 for the mailed surveys. Comparison group participants were randomly recruited through mail lists of critical care RNs obtained from the College of Nurses (CNO) registry in Ontario. Mailing lists are available to graduate nursing students conducting research through an application process and nominal fee once ethics approval for the research had been obtained (Appendix B). RNs indicate on their annual renewal form whether they may be contacted for research purposes. According to the CNO, in 2009, the response rate of RNs in indicating their willingness to be sent research surveys was 65%. Even though nurses indicate willingness to participate in surveys, it is expected that a lower number would actually complete the survey. According to anecdotal notes of a well-known Canadian nurse researcher, reported survey rates among registered nurses in Ontario are 38 % (H. Laschinger, personal communication, 2011). The return rates of mailed surveys in this study were 29% (181) for Time 1 and 44% (73) for Time 4 in the comparison group. The power of a statistical test refers to the ability to detect a significant effect within the confines of a specific research model. As power increases, the risk of a Type II error (failing to 62  find a relationship that exists in the population) is reduced (Burns & Grove, 2011). Conventionally, 0.80 has been established as an adequate statistical power (Cohen, 1977; Cohen, Cohen, West & Aiken, 2003). For this study, sample size for multiple regression was calculated with 0.80 power at an alpha level of .01 with nine independent variables in the model. The risk of making a Type I error is reduced with a .01 significance level versus a greater significance level such as .05. A Type 1 error occurs when the null hypothesis is rejected when in fact, it is true, in other words, a relationship is found in the population when, in fact it does not exist (Burns & Grove, 2011). For a small effect (R2= .02), a sample size of 1079 would be required. In order to detect a medium effect (R2= .15), a minimum sample of 154 would be sufficient and finally to detect a large effect (R2= .25) a minimum sample of 97 would be required. This sample size was calculated using the a-priori sample size online calculator for multiple regression (Cohen, 1988; Soper, 2011). A practically achievable minimum sample size of 154 would be sufficient, for the combined sample (treatment + comparison groups), for a medium effect (or large) size to address hypothesis 1. In order to address the hypotheses relating to mediation and moderation effects within the treatment group, a total sample size of 308 would be required (154 in the treatment group and 154 in the comparison group). Since mail and email surveys typically yield a low response rate (Vangeest & Johnson, 2011), oversampling of each group was done to ensure that the sample was large enough to meet the minimum sample requirements as determined by a power analysis. The goal was to achieve a minimum sample size of 154 in each group (treatment and comparison). A total of 363 participants were recruited (comparison group n= 181, treatment group n= 182) therefore achieving adequate power for this study. 63  Recruitment procedures. The treatment and comparison groups were recruited by mail contact and mailed information and consent forms during the first two weeks of the program for each cohort. All participants were provided with a letter of information, a consent form and a Time 1 survey describing the study (see Appendix C and D) where they were asked to mail back using the provided pre-addressed pre-stamped envelope. Recruitment took place from two of the program intakes (January, May, and September) in order to yield the sample size required for this study.  The principal investigator mailed all surveys on UBC letterhead and used UBC identified envelopes. Since the principal investigator was the coordinator of the program for the first two of three cohorts recruited, a research assistant de-identified survey data for the principal investigator to maintain participant confidentiality. During recruitment, the researcher was only present during the explanation of the letter of information in the face-to-face recruitment stages (pre-simulation and post-simulation). In addition, the researcher participated in the delivery of the simulation module. Response rates can be enhanced by increasing the frequency of contact, mail versus email or fax distribution and by including the official university letterhead endorsement (Hill, Fahrney, Wheeless & Carson, 2006; Vangeest & Johnson, 2011). To encourage participation, incentives were offered to both groups. A draw for a coffee card and book store gift certificate were held at the completion of the study.   Nurse survey response rates are typically less than 60% (Cook, Dickinson & Eccles, 2009). A modified Dillman (2000) method was used for initial recruitment of participants in order to maximize survey response rates. In this method, the initial survey was mailed out to the treatment group and mailed out to the comparison group out followed by a mailed reminder post 64  card two weeks later (see Appendix E). In addition, since further recruitment was needed, a second, mailed survey was sent to all potential recruits three weeks after the reminder post card (see Appendix K). There were 8,477 critical care RNs registered with the Ontario (College of Nurses of Ontario, 2010). The mail-outs to the comparison sample occurred within two weeks of the recruitment of the treatment group at Time 1 and Time 4 in order to ensure the maturation effects were similar for both groups. A total of 600 surveys (200 per treatment cohort) were mailed to the comparison group and yielded a response of 181 (30%) at Time 1. At Time 4, 181 surveys were mailed to the initial comparison group participants and yielded a return rate of 73 (40%). All data were collected between September 2012 and April 2014. Ethical Considerations Study approval was obtained from the University of British Columbia Behavioural Research Ethics Board and the Durham College Research Ethics Board. All study participants received a letter of information describing the study (see Appendix F) and a copy of the consent form (see Appendix G). Participants were informed of their right to privacy, informed consent, option for voluntary withdrawal at any point during the study and protection from harm. All study data were stored in locked, metal cabinets and on password protected computers. In compliance with UBC ethics requirements, data files will be kept for five years past the end of the study period and after this five-year period, all electronic copies will be erased and all hard copies of study data will be shredded.  Measures Three established scales, two adapted scales and one researcher-developed scale were used in this study in addition to researcher generated questions. The researcher created questions 65  that addressed demographic characteristics and levels of financial support for professional development opportunities (See Appendix H). The established instruments that were utilized in this study included the Survey of POS (SPOS; Eisenberger, Huntington, Hutchison, Sowa, 1986), the Practice Environment Scale of the Nurse Work Index (PES-NWI; Lake, 2002) and the General Self-efficacy Scale (GSE, Jerusalem and Schwarzer, 1995). Three adapted measures were used in this study: the Kim, Price, Mueller & Watson (1996) intent to stay scale, the PES-NWI scale (Lake, 2002) and the Facteau (1995) transfer of learning measure. In addition, there was a researcher-developed measure, the Critical Care Nursing Self-efficacy Scale based on Bandura’s guide to developing domain specific self-efficacy measures. See Table 2 for conceptual and operational definitions of all study variables.               66  Table 2. Conceptual and Operational Definitions of Study Variables  Construct Conceptual Definition Operational Definition Predictor Variable Professional Development Intervention Professional development educational program Participation in a 8 month-long (324 hour) Critical Care e-learning certificate program offered by Durham College in southern Ontario. (1 = treatment group, 0 = comparison group) Moderating Variables Work Environment Factors Respondents’ perceptions of their work environment which includes subscales used in this study: 1. Nurse participation in hospital affairs.  2. Nurse manager, ability, leadership and support of nurses. 3. Staffing and resource adequacy  4. Collegial nurse-physician relations. The Practice Environment Scale of the Nurse Work Index (PES-NWI) (see Appendix I) General Self-efficacy    Transfer of Learning The degree to which an individual believes they are capable of approaching a new situation or tasks in general.  The extent to which the learning that results from a training experience transfers to the job and leads to meaningful changes in work performance. The General Self Efficacy Scale (see Appendix J)    Transfer of learning was measured through self-report based on the adapted Facteau et al.,1995 Transfer of Learning Measure (see Appendix K) Mediating Variables Critical Care Self-efficacy The degree to which an individual believes they are capable of performing a specific critical care nursing task. The Critical Care Nursing Self-efficacy Scale (see Appendix F)   Outcome variable   Intent to Stay   Organization  Unit  Profession Respondents’ reports of their intention to stay in the unit that they currently work within the organization they work with, and the nursing profession.  The 12 intent to stay questions were adapted from the Kim, Price, Mueller & Watson (1996) instrument. There are 4 items for each of the outcome variables: intent to stay in current position, the organization and the nursing profession (see Appendix E)   67  Professional Development Intervention  The professional development intervention was a 324-hour self-paced critical care certificate program offered over a maximum of a one-year period. The program included the following three components: a) six instructor-facilitated online learning modules offered in an asynchronous format; b) an onsite instructor-facilitated 39-hour high fidelity simulation course held over two weekends; and c) a preceptored practicum over ten 12-hour shifts in an adult critical care unit. This professional development intervention is intended to prepare registered nurses for the critical care practice setting. The program curriculum is standardized and has been delivered for five years with a consistent faculty team. Traditional models of critical care training for nurses entering critical care include a condensed classroom format to deliver theory followed by a practicum course. The Durham College program is unique compared to traditional critical care training models since it is comprised of three discrete training modalities, with a distinct sequencing model of interactive online learning followed by an intensive simulation laboratory course and finally a practicum component.  The Simulation Intervention Component  The simulation component of the intervention was comprised of 39 hours of simulated critical care cases conducted within the simulation lab at Durham College. Participation in the cases included three ‘preparation stations that included arrhythmia/12 lead ECG interpretation, management of mechanical ventilation and hemodynamic monitoring management (i.e., arterial lines and pulmonary artery catheters). Following the preparation stations, each student participated in nine critical care cases which consisted of patients experiencing: respiratory distress/acute respiratory failure, septic shock, hypovolemic shock, myocardial infarction, 68  abdominal aortic aneurysm repair (AAA), hemodynamic instability, end of life (mock family conference), acute renal failure and head injury/trauma.  Each case was delivered via a pre-determined template that included learning objectives, pre-test questions, an initial patient phase, an evolving patient phase and a conclusion phase, The case was followed by guided debriefing and post-test questions. The duration of each case was 60 minutes and included ten minutes for pre-brief and review of the learning objectives, a 20- minute case and 30 minutes for debriefing and a post quiz.  All eight instructors were registered nurses with greater than 25 years each of critical care practice experience. Each of the instructors had mentored with the Durham College critical care simulation team prior to independently running simulation cases. The evaluation and testing of the students was completed by instructors via competency-based checklists that were created by a team of critical care experts and had been trialed over a five-year period prior to being used in the study. Work Environment The PES-NWI is the most widely reported measure that has been used to examine various aspects of a nurse’s work environment (Lake, 2002; Warshawsky & Havens, 2011). The PES-NWI has evolved from the Nurse Work Index (NWI; Kramer & Hafner, 1989) and the NWI- Revised (NWI-R; Aiken & Patrician, 2000). The PES-NWI has been used extensively in the US, to study the difference between magnet and non-magnet hospitals with respect to nurse and patient outcomes. The PES-NWI has also been used to study Canadian nurse’s work environments, and one study focused on Canadian critical care nurses’ work environments with respect to staffing and nurse-physician relationships (Laschinger, 2008; Leiter & Laschinger, 2006). 69  The PES-NWI consists of five subscales with a total of 31 items measured on a 4-point response scale ranging from 1 (strongly disagree) to 5 (strongly agree) that assess different elements of the nurse work environment. The five subscales include: nurse participation in hospital affairs, nursing foundations for quality of care, nurse manager ability, leadership and support of nurses, staffing and resource adequacy subscale and collegial nurse-physician relations. The PES-NWI is scored by calculating a mean composite score of each subscale and then an overall composite of mean scores. New scoring additions to this instrument categorize favourable practice environments as those that had 4 or 5 subscale mean scores greater than 2.5, mixed if 2 or 3 subscale means were greater than 2.5, and unfavourable if none or one of the 5 subscales achieved a mean score of 2.5 with all means being equally weighted (Aiken, Clarke, Sloane, Lake, & Cheney, 2008; Lake & Friese, 2006). Internal consistency for the subscales of this instrument have been reported in nursing populations ranging between 0.70-0.89 (Parker, Tuckett & Hegney, 2010).The PES-NWI takes approximately ten minutes to complete. In the current study, four of the five subscales were used (20 items). The subscale nursing foundations for quality of care was not used in this study since a number of the items overlapped with other measures being utilized. Specifically, any aspects related to professional development were not included among the PES-NWI items in order to emphasize professional development as a unique aspect of the model used in the current research. In addition, one item, career development/clinical ladder opportunity, was not used from the nurse participation in hospital affairs subscale since it was not appropriate in the Canadian practice setting context. Clinical ladders are career advancement paths where compensation is provided at each level. Health care organizations in Canada do not use clinical ladders or subsequent additional compensation levels. 70  The 20 items of the PES-NWI scale were subjected to principal components analysis (PCA) using SPSS version 22. Prior to performing the PCA, the suitability of data for factor analysis was assessed. Inspection of the correlation matrix revealed many coefficients of .3 or above. The Kaiser-Meyer Olkin value was .88 exceeding the recommended value of .6 (Kaiser, 1970, 1974) and Bartlett’s Test of Sphericity (Bartlett, 1954) reached statistical significance, supporting the factorability of the correlation matrix. Principal components analysis revealed the presence of four components with eigenvalues exceeding 1, explaining 37.61, 13.08, 7.02 and 6.83 percentage of the variance. The screeplot explained a clear break after the fourth component; therefore it was decided to retain four components. Perceived Organizational Support The Survey of POS (SPOS) measures the individual’s perception of the extent to which the employer values their contributions and also their well-being (Eisenberger, Huntington, Hutchison, & Sowa, 1986). The SPOS is an eight-item survey which is a short form of the longer, 36-item POS survey. (Appendix N). In this measure, the items are measured on a 7-point Likert scale that ranges from 0 (strongly disagree) to 6 (strongly agree). Shore and Tetrick (1991) established the unidimensionality of the SPOS and established construct validity of this measure. The SPOS takes approximately five minutes to complete. The instrument is scored by summing the scores for a possible range of scores from 0-56. Higher scores indicate higher levels of POS. This short version eight-item scale has reported high internal reliabilities in a wide variety of sample populations including nurse samples with an average reliability of 0.90 (Laschinger, Purdy, Cho & Almost, 2006; Rhoades & Eisenberger, 2002). The SPOS has demonstrated discriminant validity from related constructs such as affective commitment and work satisfaction 71  (Stinglhamber & Vandenberghe, 2004). Examples of questions include: “The organization really cares about my well-being” and “The organization cares about my general satisfaction.”  Transfer of Learning The Transfer of Learning Scale was adapted to the critical care nursing context from the Facteau and colleagues’ (1995) 9-item measure (see Appendix K). The adapted measure contains six items and is measured on a 5-point response scale ranging from 1 (strongly disagree) to 5 (strongly agree) that assesses how well the individual perceives that they have transferred the learning from the intervention into the critical care practice setting. After receiving ethics approval from University of British Columbia and Durham College ethics review boards, the measure was piloted with 25 critical care nursing students enrolled in the critical care e-learning program at Durham College in January 2012 to establish internal consistency which was determined to be 0.75 in this sample. The instrument is scored by summing the scores for a possible range of scores from 5-30. Higher scores indicate higher levels of self-reported transfer of learning.   Self-Efficacy Domain specific self-efficacy. Domain specific self-efficacy was measured by the Critical Care Nursing Self-efficacy Scale that was researcher-developed using Bandura’s guide for developing domain specific self-efficacy scales, with reference to the ten core competencies of the Durham College critical care program which include: hemodynamic monitoring, arrhythmia interpretation, 12-lead ECG interpretation, vasoactive drip calculation, mechanical ventilation, recognition of hemodynamic instability and ability to prioritize in rapidly changing situations (see Appendix L). This ten-item 72  scale is measured on a 0-100-point scale that yields a final composite score of 0-1000. After receiving ethics approval from the University of British Columbia and Durham College, the scale was piloted with 25 critical care nursing students enrolled in the critical care e-learning program at Durham College in January 2012 to assess its internal consistency. The Cronbach’s alpha for the Critical Care Self-efficacy Scale was found to be 0.83.  General self-efficacy. In addition to the measurement of domain specific critical care self-efficacy, a general self-efficacy measure (GSE) was used as a baseline in the initial survey to all participants (see Appendix J). The GSE measure used was the 10-item Jerusalem and Schwartzer (1995) scale. The measure is unidimensional and is scored on a 1-4 Likert scale (1- hardly true to 4-exactly true) when the sum is calculated a final composite score ranging from 10-40 is produced. Intent to Stay Intent to stay was measured by 12 items adapted to the critical care nursing context from the Kim, Price, Mueller and Watson (1996) intent to stay measure (see Appendix M). The questions measured the nurse’s intent to stay in his or her current job, in the organization and in the nursing profession. Higher scores in each category indicated a higher level of intent of staying in the current job, within the organization and in the nursing profession. The 12-item scale contains three subscales (intent to leave the unit, organization or profession) with four questions each. Responses were measured along a four-point scale with a response range of 1 (highly unlikely) to 4 (highly likely). The total composite score will yields a possible score of 4-16 on each subscale (unit, organization and profession). The higher the score, the more likely the individual intends to stay in the unit, the organization or the nursing profession. The Cronbach’s alpha of this instrument has been reported as 0.86 in samples with medical personnel (Kim, 73  Price, Mueller, & Watson, 1996). It was anticipated that the entire survey would take 15-20 minutes to complete. The 12 items of the Intent to Stay (organization, unit and profession) scale were subjected to principal components analysis (PCA) using SPSS version 22. Prior to performing the PCA, the suitability of data for factor analysis was assessed. Inspection of the correlation matrix revealed many coefficients of .3 or above. The Kaiser-Meyer Olkin value was .83 exceeding the recommended value of .6 (Kaiser, 1970, 1974) and Bartlett’s Test of Sphericity (Bartlett, 1954) reached statistical significance, supporting the factorability of the correlation matrix. Principal components analysis revealed the presence of three components with eigenvalues exceeding 1, explaining 37.9%, 13.82% and 11.93% of the variance. The screeplot explained a clear break after the third component; therefore it was decided to retain three components (intent to stay in the organization, the unit and the profession). Demographic Variables Participants were asked researcher-designed questions regarding the following items: age, gender, tenure as an RN and tenure in the critical care work setting, education level, and type of ICU the individual was employed within (see Appendix H). In addition, participants were surveyed on the frequency of educational opportunities supported by their organization and any associated financial or time support for these activities. Data Collection Procedures The measures used at each time point are displayed in Table 3. Repeated measures in both groups included work environment, POS, critical care self-efficacy and intent to stay. In addition, transfer of learning was used as a repeated measure in the treatment group. 74   Table 3. Data Collected at Each Time Point                                                0                        2 weeks                12 months            18 months Cohort Time 1 (Intervention) Time 2 Time 3 Time 4 Treatment Group   Demographics POS WE GSE CCSE TOL ITS --- POS WE --- CCSE TOL ITS --- POS WE --- CCSE TOL ITS --- POS WE --- CCSE --- ITS Comparison Group    Demographics POS WE GSE CCSE* ITS --- --- --- --- --- --- --- --- --- --- --- --- --- POS WE --- CCSE ITS Note. Treatment group= Groups 1, 2 and 3, POS=POS, WE=work environment, GSE= General Self-efficacy, CCSE= Critical Care Self-efficacy, TOL= Transfer of Learning., ITS= intent to stay in the organization, unit and profession,*CCSE (n=88) in comparison group.  Data Analysis Strategy The data analysis strategy for this research is described in the following section as it relates to the study hypotheses. After cleaning the data, descriptive statistics were analyzed to determine whether data were normally distributed. Data were assessed for the extent and pattern of missingness as these factors can impact the validity of the findings. The three patterns of missing data are: systematic, missing completely at random (MCAR) and missing at random (MAR). The preferred method of determining whether data is MCAR is to run a predictive regression model in which a dummy code is created (i.e., missing value= 0, non-missing value=1) and treated as a dependent variable. If the dummy variable is predicted by any of the 75  variables the data cannot be MCAR (Fox-Wasylyshyn & El-Masri, 2005). Missing data can be handled by either deletion or imputation techniques. Deletion refers to excluding subjects with missing data and imputation technique refers to replacing the missing value with an estimate (Fox-Wasylyshyn & El-Masri, 2005). In this study, regression imputation was used. This technique involves using available data from complete cases to predict values of missing data for incomplete cases. Further data cleaning removed substantial outliers by examining standardized residuals potentially reducing the probability of Type I and Type II errors (Osborne & Waters, 2002). Outliers (i.e., extreme cases) can seriously bias the results by "pulling" or "pushing" the regression line in a particular direction thereby leading to biased regression coefficients which can lead to a completely different set of results. Outliers were evaluated by performing the regression both with and without these outliers, to examine their specific influence on the results. Since the model remained stable (i.e., the adjusted predicted value is the same as the predicted value) the outliers were retained. As there was a normal distribution, a correlation matrix was generated to determine where relationships between variables existed. Multicollinearity occurs when there is a multiple correlation between one variable and a set of others in the range of .90 or higher, (Norman & Streiner, 2000). Multicollinearity among the independent variables was examined and was not detected since no correlations between variables were higher than .90; therefore no variables were removed.  The main analytic strategies used were one-way analysis of covariance (ANCOVA) and hierarchical multiple regression. In hierarchical regression, known predictors that have been identified in previous research are entered into the equation first followed by predictors where 76  less is known about relationships (Field, 2009). In order to ensure the results of the test were not under-estimated or over-estimated, the assumptions of multiple regression were tested and no violations of the assumptions were found. Inferential statistics. Research Hypothesis 1: There will be a significant difference in critical care nurses intent to stay (unit, organization, and profession) for nurses who receive the professional development intervention compared with a comparison group of critical care nurses, while controlling for their baseline levels of intent to stay. One-way ANCOVA analyses were used to compare the effectiveness of the professional development intervention in relation to intent to stay in the organization, the unit and the profession. Hierarchical multiple regression analyses were used to assess the direct effects of the professional development intervention on intent to stay, controlling for intent to stay at Time 1, participants' demographic characteristics (i.e., age, education and employment status), and other key variables in the Critical Care Nurse Retention Model. The beta coefficients indicate how many standard deviations a dependent variable changed, per standard deviation increase in the predictor variable and the R2 statistic indicates the percentage of variance (R2) in the outcome variable intent to stay that is explained by the full model. Even though demographic characteristics have not been shown to have a strong effect on intent to stay, they were controlled for in the analysis (Griffeth, Hom & Gaertner, 2000). The purpose of controlling or isolating these variables is to improve the internal validity of this study and to eliminate any ‘interference’ or confounding variables that could compromise the findings. Threats to validity of this quasi-experimental study were controlled by the presence of a comparison group, adequate sample size, the use of reliable measures, administration of a 77  standardized treatment and, most importantly for a quasi-experimental study, by controlling for baseline levels of intent to stay. Sub-analyses: Mediation. Research Hypothesis 2: Perceived organizational support will mediate the relationship between the professional development intervention and intent to stay among critical care nurses. Research Hypothesis 3: Critical care self-efficacy will mediate the relationship between the professional development intervention and intent to stay among critical care nurses. Mediator Testing In this study, it was determined whether POS mediates the effect of the professional development intervention on intent to stay and whether critical care self-efficacy mediates the effect of the professional development intervention on intent to stay among critical care nurses (see Figures 5 and 6 below). In a mediating model X exerts influence on Y through an intervening or mediating variable. The PROCESS analysis was performed to test for mediating effects of POS on the relationship between the professional development intervention and intent to stay. In addition, the test was repeated to evaluate the mediating effects of critical care self-efficacy on the relationship between the professional development intervention and intent to stay. In the PROCESS analysis test for mediation, the joint significance test is used to test mediation. The joint significance test is a procedure that ignores the total effect of X on Y (i.e., Step 1 in the model above) and uses the significance of the effect of X on M and the effect of M on Y coefficients to analyze mediation. If the effect of X on Y and the effect of M on Y controlled for X is found to be significant then mediation is present. Preacher & Hayes (2004, 2008) argue that the significance of indirect effects should be tested through SPSS macros which use a bootstrap approach to obtaining confidence intervals in testing mediators. In this approach 78  intent to stay at Time 1 was entered as the covariate when POS was analyzed for mediation and also when CCSE was analyzed as a mediator.  Figure 5. Mediation: POS        Figure 6. Mediation: Critical Care Self-efficacy          Sub-Analyses: Moderation Testing Research Hypothesis 4: Positive work environments will moderate the effect of professional development on perceived organizational support, such that the effect will be stronger when work environment scores are higher versus lower.       Critical Care Self-efficacy      Professional Development Intervention Intent to Stay Professional Development Intervention POS Intent to Stay 79  Research Hypothesis 5: General self-efficacy will moderate the influence of professional development on critical care self-efficacy, such that the effect will be stronger when general self-efficacy levels are higher versus lower. Research Hypothesis 6: Transfer of learning will moderate the relationship between critical care self-efficacy and intent to stay among critical care nurses, such that the effect will be stronger when transfer of learning scores are higher versus lower. Hierarchical multiple regression was used to test the moderating effects identified in Hypotheses 4, 5 and 6. To test Hypothesis 5, the extent that work environment factors moderate the relationship between the professional development intervention and POS, a moderated hierarchical regression was performed in which the professional development intervention work was entered first into the regression, followed by work environment, POS and then the interaction term between work environment factors and the professional development intervention as predictors of POS (Bennett, 2000). The interaction term represents a joint relationship between two predictor variables and this relationship accounts for additional variance beyond a single variable alone. If the interaction term explains a statistically significant amount of the variance in POS then a moderator effect is present (see Figure 7). In the event there is a moderating effect, this indicates that the moderating variable has the ability to enhance or reduce the effects of the professional development intervention on POS. For instance, higher levels of a healthy work environment may enhance the effect of the professional development intervention on levels of POS. This process was repeated with general self-efficacy being entered and tested for an interaction with critical care self-efficacy by using hierarchical multiple regression. In the first step the independent variable (professional development intervention) and the moderator 80  (general self-efficacy) were entered into the model as predictors of critical care self-efficacy. The interaction term (the product of the two independent variables, professional development intervention and general self-efficacy) was entered next since this represents the moderation effect (Bennett, 2000). If the interaction term explains a statistically significant amount of the variance in critical care self-efficacy, we can conclude that moderator effect is present (see Figures 7 and 8).  Figure 7. Moderation: Work Environment Factors   81  Figure 8. Moderation: General Self-Efficacy                      __________________________        Critical Care Self-efficacy Professional Development Intervention x General Self-efficacy General Self-efficacy Professional Development Intervention Step 2 Step 1 82  Chapter 5. Results This study was designed to extend knowledge of the factors that influence intent to stay among critical care nurses. This chapter presents the results from this study in relation to the six research hypotheses: 1. There will be a significant difference in critical care nurses intent to stay (unit, organization, and profession) for nurses who receive the professional development intervention compared with a comparison group of critical care nurses, while controlling for their baseline levels of intent to stay. 2. Perceived organizational support will mediate the relationship between the professional development intervention and intent to stay among critical care nurses. 3.  Critical care self-efficacy will mediate the relationship between the professional development intervention and intent to stay among critical care nurses. 4. Positive work environments will moderate the effect of professional development on perceived organizational support, such that the effect will be stronger when work environment scores are higher versus lower. 5. General self-efficacy will moderate the influence of professional development on critical care self-efficacy, such that the effect will be stronger when general self-efficacy levels are higher versus lower. 6. Transfer of learning will moderate the relationship between critical care self-efficacy and intent to stay among critical care nurses, such that the effect will be stronger when transfer of learning scores are higher versus lower. First, the description of the sample is presented followed by descriptive statistics of the study variables, lastly each hypothesis and the associated analyses will be presented.  83  Sample A total of 363 participants were recruited for the study (comparison group n= 181, treatment group n= 182). The comparison group was composed of critical care registered nurses recruited from the Ontario College of Nurses registry while the treatment group was recruited from a college critical care certificate program in Ontario. The average age of the comparison group was 45 while the average age in the treatment group was 29 (see Table 4). Most participants were employed full time (comparison= 59 %, treatment= 70%). In the treatment group, 51% worked in large teaching hospitals compared to 31% of the comparison group. In the treatment group 91% were baccalaureate prepared whereas only 42% of the comparison group were baccalaureate prepared. Nurses that indicated that they worked casually in the critical care unit were not included in the sample since this group typically has a wide variation in number of shifts worked combined with a smaller number of hours worked in the setting than full time or part time positions therefore limiting exposure to the environment. In addition, casually employed nurses do not have a regular set of shifts in the ICU. Additional demographics are found in Appendix O.   84  Table 4. Description of Sample at Time 1 Characteristic Treatment Group (n=182) Comparison Group (n=181)  f (%) f (%) Age (years) M(SD)   29(SD=8)                    45(SD=10)  Gender      Male    23(13%)                      11(6%)    Female  159(87%)                  166(94%) Highest Nursing Education      Diploma     13(7%)                    95(54%)    Baccalaureate                      165(91%)                    75(42%)    Masters        4(2%)                        7(4%) Certificates/Certifications      CNCC         0                      20(9%)    Critical Care Certificate         0                  107(59%) Employment Status      Full Time 128(70%)                  105(59%)    Part Time   50(28%)                    65(37%) Type of Hospital      Teaching                         93(51%)                    57(31%)    Community     84(46%)                  101(56%)    Small         4(2%)                    24(13%) Note. CNCC= Certified Nurse Critical Care (national certification)  Descriptive Statistics The means and standard deviations for each of the study variables at each data collection point are presented in Table 5. Nurses in the treatment group reported higher average levels of POS at all data collection point than was reported by nurses in the comparison group. In addition, nurses in the treatment group reported higher levels of working in a healthy work environment 85  than did the comparison group. Initial levels of general self-efficacy and critical care self-efficacy were lower on average in the treatment group than in the comparison group (see appendices P and Q for additional mean differences results). All study measures showed good internal consistency with alpha coefficients greater than .79 with the exception of intent to stay in the organization (treatment group, α = .66), intent to stay in the profession (treatment group, α = .78 and comparison group, α = .68). The highest Cronbach’s alphas were demonstrated with the work environment measure (PES-NWI, α = .90, treatment group and α = .92 comparison group), POS (α = .85, treatment group and α = .91, comparison group) and CCSE  (α =.85 treatment group and α = .91, comparison group). Cronbach’s alphas for all measures (at Time 1) are displayed in Table 5. 86   Table 5. Main Study Variables Means and Standard Deviations   Treatment Group Comparison Group   Time 1 (n=182) Time 2 (n=170) Time 3 (n=46) Time 4 (n=65)  Time 1 (n=181) Time 4 (n=73)  α M(SD) M(SD) M(SD) M(SD) α M(SD) M(SD)  POS  .85  33.1(8.2)   34.5(8.1)     34.7(8.5)  32.7(4.9)  .91   29.5(11.1)  27.7(7.9)  WE  .90     2.7(.5)   ---  ---      2.7(.5)  .92   2.6(.6)           2.5(.6)  WESS1  .85    2.6(.6)  ---  ---  2.6(.5)  .86  2.3(.7)  2.2(.6)  WESS2  .80    2.9(.6)  ---  ---  2.9(.6)  .89  2.7(.8)  2.6(.7)  WESS3  .86    2.2(.7)  ---  ---  2.3(.7)  .83  2.3(.8)  2.2(.9)  WESS4  .92     3.1(.7)  ---  ---  3.1(.6)  .90  3.0(.8)  3.0(.8)  GSE  .79    30.2(3.2)  ---  ---  ---  .88    32.4(4.2)  ---  CCSE   .85  681.9(199.4)  857.3(87.5)  854.6(83.7)   800.2(116.5)  .91   907.4(103.7)        869.4(113.3)  ITS-org   .66       11.0(2.9)      12.0(3.4)     12.2(2.9)  10.8(3.9)  .80    12.1(3.3)  10.3(4.5)  ITS-unit   .81      10.6(3.5)     11.7(3.6)    11.8(3.1)  11.2(3.9)  .75    12.0(3.1)  9.7(3.6)    87  Table 5. Main Study Variables Means and Standard Deviations (cont’d)  Treatment Group Comparison Group   Time 1 (n=182) Time 2 (n=170) Time 3 (n=46) Time 4 (n=65)  Time 1 (n=181) Time 4 (n=73)  α M(SD) M(SD) M(SD) M(SD) α M(SD) M(SD)  ITS-prof   .78      13.2(2.1)     13.9(2.3)    13.5(2.4)  12.2(3.5)  .68   13.5(2.4)  9.4(2.7)  TOL   .84      21.9(3.9)    23.6(3.5)    23.8(3.5)  ---  ---   ---  --- Note. POS= POS, WE= work environment, WESS1= work environment subscale 1: Nurse Participation in Hospital Affairs, WESS2=work environment subscale 2: Nurse Manager Ability, Leadership and Support of Nurses, WESS3=work environment subscale 3: Staffing and Resource Adequacy, WESS4=work environment subscale 4: Collegial Nurse-Physician Relations, GSE=General Self-Efficacy, *Critical Care Self-efficacy control group (n=89), TOL=Transfer of Learning ITS=Intent to Stay.   88  Research Hypotheses: Results In the following section correlations will be presented initially to demonstrate the strength of relationships between major study variables (see Tables 6 and 7). Following this, the results relating to each research hypothesis will be presented.  89   Table 6. Correlation between Major Study Variables: Comparison Group Variable 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 1.Age ---                 2.Gender .03 ---                3.Education -.22 -.01 ---               4.Yrs RN .88 .13 -.22 ---              5.Yrs CC .47 .13 -.23 .59 ---             6.POS T1 .03 -.03 -.02 .02 -.01 ---            7.POS T4 .06 .06 .05 .06 -.03 .49 ---           8.WE T1 -.12 .01 .08 -.11 -.04 .63 .15 ---          9.WE T4 .01 -.11 .01 .03 -.05 .09 .15 -.01 ---         10.GSE T1 .04 -.10 -.05 .07 .05 -.04 .01 -.03 .01 ---        11.CCSE T1 .39 -.03 -.42 .35 .22 .04 .13 .07 -.10 .09 ---       12.CCSE T4 .24 .11 -.15 .26 .27 .13 .27 .13 -.06 .06 .76 ---      13.ITSorg T1 .11 .11 .08 .12 .11 .27 .07 .31 .02 -.02 .08 .13 ---     14.ITSorg T4 .10 -.14 -.07 .05 -.02 .14 .12 .02 .04 -.11 -.22 -.01 .36 ---    15.ITSunit T1 .18 .07 -.05 .14 -.01 .22 .05 .28 .11 .04 .10 .07 .81 .35 ---   16.ITSunit T4 .02 -.11 .08 .00 .14 .15 .14 .18 -.02 .13 -.06 -.01 .23 .56 .20 ---  17.ITSprof T1 -.05 .09 -.02 .00 -.11 .05 -.12 .06 -.01 .14 -.01 -.06 .25 .06 .34 -.01 --- 18.ITSprof T4 .02 -.07 .25 -.09 -.01 .09 .27 .15 -.06 -.11 -.23 .16 .20 .40 .25 .47 -.13 Note. 1=Time 1, 4= Time 4, Yrs RN= years as a Registered Nurse, Yrs CC= Years in Critical care, Gender (0=female, 1=male), POS= POS, WE=work environment, GSE= General Self-efficacy, CCSE=Critical Care Self-efficacy, ITS-org= Intent to Stay in the organization, ITS- unit= Intent to Stay in the unit, ITS-prof= Intent to Stay in the Profession. Time 1 n=181, Time 4 n=73. Bold face font= p<.05 or p<.01.   90  Table 7. Correlations between Major Study Variables: Treatment Group Variable 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 1.Age ---                    2.Gender -.10 ---                   3.Education -.28 -.01 ---                  4.Yrs RN .69 .01 -.47 ---                 5.Yrs CC .43 .01 -.25 .52                 6.POS T1 -.03 -.16 -.03 -.04 -.07 ---               7.POS T4 .12 -.05 -.11 .02 -.06 -.15 ---              8.WE T1 -.05 -.10 .15 -.08 -.15 .54 .08 ---             9.WE T4 .07 -.25 -.04 .01 -.07 .28 .27 .80 ---            10.GSE T1 .18 -.03 -.06 .11 .02 .18 -.04 .25 .07 ---           11.CCSE T1 .18 -.17 -.02 .15 .19 .11 .10 .16 .12 .24 ---          12.CCSE T4 -.08 -.10 -.19 .05 .03 .07 -.15 .04 .04 -.01 .08 ---         13. TOL T1 .12 -.21 .03 .07 .04 .20 .02 .15 .29 .12 .26 .03 ---        14. TOL T2 .05 -.15 -.02 .00 .04 .22 -.15 .07 .13 .09 .05 .25 .22 ---       15.TOL T3 -.08 -.04 .14 -.13 -.25 .16 .28 .19 .15 .36 -.17 .13 .24 .25 ---      16.ITSorg T1 .10 -.20 -.16 .17 .12 .34 -.12 .19 .36 .12 .08 .15 .17 .13 -.08 ---     17.ITSorg T4 .14 .03 -.01 .05 .20 .02 .09 -.26 -.36 .03 -.04 .01 -.07 -.06 .01 -.13 ---    18.ITSunit T1 .04 -.17 -.11 .08 .13 .26 -.08 .17 .17 .08 .06 .10 .13 .22 .04 .76 .03 ---   19.ITSunit T4 -.02 .25 .07 -.09 .15 -.05 .01 -.24 -.29 -.10 -.25 -.08 -.19 -.06 .12 -.27 .72 -.16 ---  20.ITSprof T1 .06 .07 -.02 .04 .15 .01 .01 .10 .10 .10 .01 -.13 .04 .02 .21 .18 .06 .15 .04 --- 21.ITSprof T4 -.08 .08 .12 -.04 -.11 -.01 .13 -.07 .01 -.11 .09 -.14 -.06 -.20 .19 -.04 .40 -.07 .42 .07 Note. 1=Time 1, 4= Time 4, Yrs RN= years as a Registered Nurse, Yrs CC= Years in Critical Care,  Gender (0=female, 1=male), POS= POS, WE=work environment, GSE= General Self-efficacy, CCSE= Critical Care Self-efficacy, TOL= transfer of learning, ITS-org= Intent to Stay in the organization, ITS- unit= Intent to Stay in the unit, ITS-prof= Intent to Stay in the Profession. Time 1 n=182, Time 4 n=65. Bold face font=p<.05 or p<.01.91  Research Hypothesis 1 There will be a significant difference in critical care nurses intent to stay (unit, organization, and profession) for nurses who receive the professional development intervention compared with a comparison group of critical care nurses, while controlling for their baseline levels of intent to stay. A one-way between-groups ANCOVA was conducted to compare the effectiveness of a professional development intervention designed to increase critical care nurses’ intent to stay in the unit, the organization and in the profession. The independent variable was the critical care program intervention and the dependent variable consisted of scores on the intent to stay in the organization, unit and profession scales eight months after the intervention was completed. Intent to stay in the organization. After controlling for intent to stay at Time 1 (pre-simulation and pre-practicum), there was no significant difference between the intervention group and the control group on post-intervention scores on the intent to stay in the organization scale F (1,138)=.91, p= .34, partial eta squared= .01 (see Table 8). Table 8. Intent to Stay in the Organization: Differences between Groups Source SS df MS F p Partial eta squared ITSorgT1  61.19    1 61.19 3.48 .06 .03 Group       15.99    1 15.99   .91 .34 .01 Error  2424.50 138 17.57    Note. ITSorg=intent to stay in the organization, T1= Time 1, R2= .03 *p < .05, ** p < .01, ***p < .001.  92  Intent to stay in the unit. After controlling for intent to stay in the unit at Time 1 (pre-simulation and pre-practicum), there was a significant difference found between groups with  the intervention group having higher scores than the comparison group on post-intervention scores on the intent to stay in the unit scale F (1,138) =. 5.76, p= .02, partial eta squared= .04 (see Table 9).  Table 9. Intent to Stay in the Unit: Differences between Groups Source SS df MS F p Partial eta squared ITSunitT1         .14    1   .14 .01 .92 .00 Group      81.02    1 81.02 5.76 .02* .04 Error 1941.78 138 14.07    Note. ITSunit=intent to stay in the unit, T1= Time 1, R2= .04 *p < .05  Intent to stay in the profession. After controlling for intent to stay in the profession at Time 1 (pre-simulation and pre-practicum), there was a significant difference found between groups with the intervention group having higher scores than the comparison group on post-intervention scores on the intent to stay in the profession scale F (1,137) =28.04, p= .00, partial eta squared= .17 (see Table 10).  93  Table 10. Intent to Stay in the Profession: Differences between Groups Source SS df MS F p Partial eta squared ITSprofT1    1.09 1     1.09 .11 .74 .00 Group 268.63 1 268.63     28.04 .00 .17 Error    1312.69      137     9.58    Note. ITSprof=intent to stay in the profession, T1= Time 1, R2= .17 *p < .05, ** p < .01, ***p < .001.  The Critical Care Nurse Retention Model being tested is presented in Figure 9 below. Preliminary analyses were conducted to ensure no violation of the assumptions of normality, linearity, multicollinearity and homeoscedascity occurred. Hierarchical regression was used to assess the ability of the intervention, POS, work environment, general self-efficacy, and critical care self-efficacy to predict intent to stay (in the organization, unit and profession) at Time 4 after controlling for intent to stay in the organization, unit and profession (Time 1), age, highest education level and employment status. Age and employment status were eventually removed from the regression in order to create a more parsimonious model since they were not found to be significant in any of the models.  94  Figure 9. Critical Care Nurse Retention Model  Predicting Intent to Stay in the Organization  Hierarchical regression was used to assess the ability of the intervention, POS, work environment, general self-efficacy and critical care self-efficacy to predict intent to stay in the organization at Time 4 after initially controlling for intent to stay in the organization at Time 1, age, highest education level and employment status (see Table 11). In the final model 7% of the variance was explained for intent to stay in the organization.         95   Table 11. Hierarchical Regression Analysis Results for Variables Predicting Intent to Stay in the Organization at Time 4 (N=138)  B SE B Β CI (95%) R2 Change in R2 Model 1:     ITSorgT1   .20  .11  .15  -.03, .42  .02  .02 Model 2:    ITSorgT1    Education   .20       -.03  .11 .71  .15       -.00  -.03, .42 -1.44, 1.38  .02  .00 Model 3:    ITSorg T1    Education    Intervention   .21     -.40      .92   .12 .78 .80  .16*     -.05      .11  .02, .44 -1.94, 1.14 -.65, 2.5  .03  .01 Model 4:      ITSorg T1     Education    Intervention    WE T4   .24 -.44 1.29 -.06  .12 .77 .82 .03         .18*      -.05      .15     -.14  .01, .47 -1.97, 1.09 -.34, 2.92 -.12, .01  .05  .02 Model 5:     ITSorg T1    Education    Intervention    WE T4    POS T4  .24     -.41 .92     -.07 .08  .12 .77 .86 .04 .06   .18*       -.05       .11*      -.17       .14  .01, .47 -1.93, 1.12 .78, 2.61 -.13, .00 -.03, .19  .07  .02 Model 6:     ITSorg T1    Education    Intervention    WE T4    POS T4    GSE T1   .24 -.43 .77 -.07 .08 -.07  .12 .77 .88 .04 .06 .10    .18* -.05  .09 -.17  .14  .06  .02, .47 -1.96, 1.10 -.97, 2.52 -.13, .00 -.03, .19 -.26, .12  .07  .00 Model 7:     ITSorg T1    Education    Intervention    WE T4    POS T4    GSE T1    CCSE T4  .25 -.48 .66 -.07 .09 -.07 -.00  .12 .78 .90 .04 .06 .10 .00     .19* -.06  .08 -.17  .15 -.06 -.05  .02, .48 -2.02, 1.06 -1.12, 2.45 -.13, .00 -.02, .20 -.26, .12 -.01, .00  .07  .00 Note. WE= work environment, POS= POS, GSE= General Self-efficacy, CCSE= Critical Care Self-efficacy, ITSprof= intent to stay in the profession,  = standardized beta coefficient; R2 = .07, Model 7: F (1, 130) = .32, CI (95%) = 95% confidence intervals. p < .001. *p < .05, ** p < .01, ***p < .001. 96  Predicting Intent to Stay in the Unit Hierarchical regression was used to assess the ability of the intervention, POS, work environment, general self-efficacy and critical care self-efficacy to predict intent to stay in the unit at Time 4 after controlling for intent to stay in the unit at Time 1, age, highest education level and employment status (see Table 12). In the final Model 8% of the variance was explained for intent to stay in the unit. Model 6 and 7 did not contribute to additional R squared change. The only variable that was statistically significant was the intervention in Model 3 ( = .19, p<.05), Model 4 ( = .23, p<.05) and Model 6 ( = .20, p<.05). The intervention became statistically significant only after controlling for work environment and then later ceased to be significant when other controls were entered.             97  Table 12. Hierarchical Regression Analysis Results for Variables Predicting Intent to Stay in the Unit at Time 4 (N=138)  B SE B Β CI (95%) R2 Change in R2 Model 1:     ITSunit T1   -.05  .10       -.04  -.24, .15  .00  .00 Model 2:    ITSunitT1    Education   -.02 .92  .10 .64       -.02 .12*  -.22, .17 .35, 2.19   .02   .02 Model 3:    ITSunit T1    Education    Intervention   .01 .37 1.40  .10 .70 .72  .01 .05  .19*  -.18, .21 -1.0, 1.75 -.02, 2.83  .04  .02 Model 4:      ITSunit T1     Education    Intervention    WE T4   .03 .33 1.71      -.05  .10 .69 .75 .03  .03 .05  .23*     -.14  -.16, .23 -1.04, 1.70 .24, 3.19 -.11, .01  .06  .02 Model 5:     ITSunit T1    Education    Intervention    WE T4    POS T4   .04 .36 1.42      -.06 .07  .10 .69 .77 .03 .05  .03 .05 .19     -.16 .13  -.16, .23 -1.01, 1.73 -.11, 2.95 -.12, .01 -.03, .17  .07  .01 Model 6:     ITSunit T1    Education    Intervention    WE T4    POS T4    GSE T1   .03 .38 1.55 -.06  .07 .06  .10 .69 .80 .03 .05 .09   .03 .05  .20*    -.16      .13      .06  -.16, .23 -.99, 1.75 .03,3.2 -.12, .01 -.03, .17 -.11, .23  .08  .00 Model 7:     ITSunit T1    Education    Intervention    WE T4    POS T4    GSE T1    CCSE T4  .04 .34 1.45 -.06 .07 .06       -.00  .10 .70 .82 .03 .05 .09 .00  .03 .05 .19 -.16 .13 .06     -.06  -.16, .23 -1.05, 1.72 -.17, 3.06 -.12, .01 -.03, .17 -.11, .23 -.01, .00  .08  .00 Note. WE= work environment, POS= POS, GSE= General Self-efficacy, CCSE= Critical Care Self-efficacy, ITSunit=intent to stay in the unit,  = standardized beta coefficient; R2= .08, Model 8: F (1, 130) = .37, CI (95%) = 95% confidence intervals, *p < .05, ** p < .01, ***p < .001. 98   Predicting Intent to Stay in the Profession Hierarchical regression was used to assess the ability of the intervention, POS, work environment, general self-efficacy and critical care self-efficacy to predict intent to stay in the profession at Time 4 after controlling for intent to stay in the profession (Time 1), age, highest education level and employment status. In the final Model 23% of the variance was explained for intent to stay in the profession (see Table 13). Model 4 and 7 did not contribute to additional R squared change. Education was found to be statistically significant in Model 2 ( = .28, p<.001). Once the intervention was entered at Model 3, it was found to be statistically significant in models Model 3 and 4 ( = .36, p<.001), Model 5( = .30, p<.001), Model 6 and 7 ( = .28, p<.001). In addition POS was found to be significant in all models once entered (Model 5, 6 and 7  = .21, p<.001).            99  Table 13. Hierarchical Regression Analysis Results for Variables Predicting Intent to Stay in the Profession at Time 4 (N=138)  B SE B β CI (95%) R2 Change in R2 Model 1:     ITSprofT1   -.06  .13  -.04  -.31, .19  .00  .00 Model 2:    ITSprofT1    Education   -.04 1.85  .12 .55     -.03     .28***  -.28, .21 .77, 2.93  .08  .08 Model 3:    ITSprof T1    Education    Intervention  -.02 .85 2.41  .12 .57 .58     -.01     .13     .36***  -.25, .21 -.28, 1.98 1.25, 3.57   .18  .10  Model 4:      ITSprof T1     Education    Intervention    WE T4   -.02  .84 2.45 -.00  .12 .57 .61 .03     -.01     .13  .36***    -.01  .25, .21 -.29, 1.98 1.24, 3.64 -.05, .05   .18   .00 Model 5:     ITSprof T1    Education    Intervention    WE T4    POS T4    .00  .88 1.99 -.02  .10  .11 .56 .62 .03 .04  .00       .13     .30***      -.05   .21**  -.22, .23 -.23, 2.00 .76, 3.22 -.07, .03 .02, .18   .22   .04 Model 6:     ITSprof T1    Education    Intervention    WE T4    POS T4    GSE T1   .02 .86 1.85 -.02 .10       -.06  .12 .56 .64 .03 .04 .07       .11      .13   .28***     -.05      .21**     -.07  -.21, .24 -.26, 1.98 .59, 3.12 -.07, .04 .02, .18 -.20, .08   .23   .01 Model 7:     ITSprof T1    Education    Intervention    WE T4    POS T4    GSE T1    CCSE T4  .02 .86 1.85 -.02  .10 -.06 -1.77  .12 .57 .66 .03 .04 .07 .00   .01  .13      .28** -.05      .21** -.07  .00  -.21, .25 -.27, 1.99 .55, 3.16 -.07, .04 .02, .18 -.20, .08 -.01, .01   .23   .00 Note. WE= work environment, POS= POS, GSE= General Self-efficacy, CCSE= Critical Care Self-efficacy, ITSprof= intent to stay in the profession,  = standardized beta coefficient; R2 = .23, Model 3: F (1, 133) = 16.98, CI (95%) = 95% confidence intervals. , *p < .05, ** p < .01, ***p < .001. 100   Mediation Research hypothesis 2. Perceived organizational support will mediate the relationship between the professional development intervention and intent to stay among critical care nurses. Figure 10. Mediation: POS      Mediation analyses were completed to determine whether POS had a mediating effect on the relationship between the professional development intervention and intent to stay at Time 4 (see Figure 10). The analysis was completed using the PROCESS mediation tool in SPSS (Hayes, 2013). This tool allows for a bootstrapping method that does not violate the assumption of normality and works well for small sample sizes. The Hayes (2013) PROCESS macro calculates bootstrapping directly within the SPSS program. Point estimates and confidence intervals are provided and allow for the interpretation of significance in a mediation analysis. Only intent to stay in the profession at Time 4 was run as an outcome variable in the mediation analysis since intent to stay in the organization and intent to stay in the unit were not found to be significant when the full model was analyzed. The professional development intervention was entered as the independent variable, POS was entered as the mediator variable and intent to stay in the profession at Time 1 was entered in each analysis as the covariate. The Professional Development Intervention Intent to Stay T4 POS T4 101  total effect and the direct effect were significant in predicting the relationship between the professional development intervention and intent to stay in the profession (see Table 14). The indirect effect, or effect of POS in mediating the relationship between the professional development intervention and intent to stay in the profession was significant (indirect effect = .46, 95% CI .09, .97), therefore the hypothesis that POS will mediate the relationship between the professional development intervention and intent to stay in the profession among critical care nurses was supported.  Table 14. Perceived Organizational Support: Mediation at Time 4 (N=141)  Effect SE p C.I. Total Effect       ITSorgT4 .68 .71 .34 -.73, 2.09   ITSunitT4 1.56 .65 .02 .27, 2.85   ITSprofT4 2.78 .52 .00 1.74, 3.82      Direct Effect       ITSorgT4 .35 .76 .65 -1.16, 1.85   ITSunitT4 1.31 .69 .06 -.06, 2.68   ITSprofT4 2.32 .55 .00 1.23, 3.41      Indirect Effect  Boot SE  Boot C.I.   ITSorgT4 .33 .29  -.16, .99   ITSunitT4 .25 .27  -.19, .85   ITSprofT4 .46 .22  .09, .97 Note. ITSorg= intent to stay in the organization, ITSunit=Intent to stay in the unit, ITSprof=Intent to stay in the profession, T4= Time 4, Model Summaries: ITSorg R2=.03, F(2, 138)=2.01, ITSunit R2= .05, F(3, 137) =2.37, ITSprof R2= .13, F(2, 137)=10.01.  Research hypothesis 3. Critical care nursing self-efficacy will mediate the relationship between the professional development intervention and intent to stay among critical care nurses. 102  Figure 11. Mediation: Critical Care Self-efficacy       Mediation analyses were also completed to determine whether critical care self-efficacy had a mediating effect on the relationship between the professional development intervention and intent to stay at Time 4 (see Figure 11). Analyses were completed using the PROCESS mediation tool in SPSS (Hayes, 2013). Only intent to stay in the profession at Time 4 was run as an outcome variable in the mediation analysis since intent to stay in the organization and intent to stay in the unit were not found to be significant when the full model was analyzed. The professional development intervention was entered as the independent variable, critical care self-efficacy was entered as the mediator variable and intent to stay in the profession at Time 1 was entered in each analysis as the covariate. The total effect and the direct effect were significant in predicting the relationship between the professional development intervention and intent to stay in the profession (see Table 15). The indirect effect, or effect of CCSE in mediating the relationship between the professional development intervention and intent to stay in the profession was not significant (indirect effect = .02, 95% C.I. -.26, .33), therefore the hypothesis that critical care self-efficacy will mediate the relationship between the professional development intervention and intent to stay among critical care nurses was not supported.     Professional Development Intervention Intent to Stay T4 Critical Care Self-efficacy T4 103  Table 15. Critical Care Self-efficacy: Mediation at Time 4 (N=141)  Effect SE p C.I. Total Effect       ITSorgT4 .68 .71 .34 -.73, 2.09   ITSunitT4 1.56 .65 .03 .27, 2.85   ITSprofT4 2.78 .52 .00 1.74, 3.82      Direct Effect       ITSorgT4 .62 .74 .40 -.85, 2.09   ITSunitT4 1.48 .68 .03 .14, 2.82   ITSprofT4 2.78 .55 .00 1.69, 3.87      Indirect Effect  Boot SE  Boot C.I.   ITSorgT4 .06 .21  -.36, .48   ITSunitT4 .08 .19  -.24, .54   ITSprofT4 .02 .15  -.26, .33 Note. ITSorg= intent to stay in the organization, ITSunit=Intent to stay in the unit, ITSprof=Intent to stay in the profession, T4= Time 4, Model Summaries: ITSorg R2=.03, F(2, 138)=2.01, ITSunit R2= .05, F(3, 137) =2.37, ITSprof R2= .13, F(2, 137)=10.01.  Moderation Research hypothesis 4. Positive work environments will moderate the effect of professional development on perceived organizational support, such that the effect will be stronger when work environment scores are higher versus lower. A hierarchical multiple regression model was tested to investigate whether the association between the professional development intervention and POS depends on a positive work environment (see Figure 12). After computing the professional development by work environment interaction term (PD x WE) and controlling for perceived organizational support (POS) at Time 1, the predictors and the interaction were entered into a hierarchical regression model. Results indicated that POS at Time 1 predicted POS at Time 4.  104  The intervention was statistically significant after POS Time 1 was controlled for in Models 2( = .30, p<.001) and after work environment was controlled for in Model 3 ( = .27, p<.001). Results did not support the hypothesis that work environment moderated the effect of the intervention on the relationship between the professional development intervention and POS. The intervention was both found to have independent effects on POS at Time 4 after controlling for POS at Time 1, but the interaction term of PD x WE was not found to be statistically significant in this regression model (see Table 16). Figure 12. Work Environment as a Moderator                     Intervention POS T4 Work Environment T4 105  Table 16. Moderation Regression Analysis Results for Variables Predicting POS at Time 4 Variable B SE B β t Model 1    POS T1   .23  .06  .33  4.03*** Model 2    POS T1    Intervention   .19 4.27  .06 1.11  .27 .30  3.47** 3.87*** Model 3     POS T1     Intervention     WE T4  .18 3.80 .09   .06 1.13 .05  .25 .27 .14  3.22** 3.37*** 1.79 Model 4   POS T1   Intervention    WE T4    Intervention x WE T4   .18 1.19 .07 .06  .06 7.47 .07 .16  .26 .09 .11 .20  3.23** .16 1.00 .35 Note. WE= work environment, POS= Perceived organizational support, T4= Time 4 R2= .22 (N=140 , p<.001), Model 2,F(1, 135)=14.94 *p<.05, **p<.01, ***p<.001  Predicting Critical Care Self-Efficacy Research hypothesis 5. General self-efficacy will moderate the influence of professional development on critical care self-efficacy, such that the effect will be stronger when general self-efficacy levels are higher versus lower. 106  Figure 13. Predicting Critical Care Self-efficacy     A multiple regression model was tested to investigate whether the association between the professional development intervention and critical care self-efficacy (CCSE) depends on a higher level of general self-efficacy (see Figure 13). After computing the professional development by general self-efficacy interaction term (PD x GSE) and controlling for CCSE at Time 1, the predictors and the interaction were entered into a hierarchical regression model. CCSE at Time 1 was significant in predicting CCSE at Time 4 ( = .27, p<.01) but became non-significant once the other variables were added. Results did not support the hypothesis that GSE moderated the effect of the intervention on the relationship between the professional development intervention and CCSE (see Table 17). In addition, the interaction term of PD x GSE was not found to be statistically significant in this regression model.  Intervention CCSE T4 GSE T1 107   Table 17. Moderation Regression Analysis Results for Variables Predicting Critical Care Self-efficacy (CCSE) at Time 4 Variable B SE B β t Model 1    CCSE T1  .16  114.42  .27    2.70** Model 2    CCSE T1    Intervention  .10 -49.1  .07 27.9  .17 -.20  1.42 -1.74 Model 3    CCSE T1      Intervention    GSE T1  .10 -49.10 -3.1  .07 28.50 3.27  .17 -.21 -.01  1.41 -1.72 -.10 Model 3    CCSE T1    Intervention    GSE T1    Intervention x GSE T1  .11 76.89 1.10 -4.00  .07     222.01 4.11 7.00  .19 .32 .04 -.51  1.50 .35 .27 -.57 Note. GSE= General Self-efficacy, CCSE=Critical Care Self-efficacy, T1= Time 1, T4= Time 4 R2=. 11 (N=138 ), Model 2 F(1. 90)=3.03 *p<.05, **p<.01, ***p<.001  Subgroup Analyses Research hypothesis 6. Transfer of learning will moderate the relationship between critical care self-efficacy and intent to stay among critical care nurses, such that the effect will be stronger when transfer of learning scores are higher versus lower. A subgroup analysis was completed among the treatment group, where hierarchical multiple regression was used to test the effects of critical care self-efficacy (Time 3, post-simulation) and transfer of learning (Time 3) on the three intent to stay variables (Time 3). The regression models were tested to investigate whether the association between the critical care self-efficacy and intent to stay in the organization, unit or profession was influenced by the level 108  of transfer of learning. After computing a professional development and transfer of learning interaction term (PD x TOL) and controlling for intent to stay (organization, unit or profession) at Time 1, the predictors and the interaction were entered into a hierarchical regression model. Results did not support the hypothesis that transfer of learning moderates the effect on the relationship between the critical care self-efficacy and intent to stay in the organization. No moderation effect was present for intent to stay in the organization, the unit or the profession. Additional findings showed that there was a significant increase in transfer of learning levels at the completion of the simulation component (Time 3). Results: Summary Research hypothesis 1. There will be a significant difference in critical care nurses intent to stay (unit, organization, and profession) for nurses who receive the professional development intervention compared with a comparison group of critical care nurses, while controlling for their baseline levels of intent to stay. Through the use of ANCOVA, after adjusting for intent to stay Time 1 scores, significant differences were found between groups on the intent to stay in the unit and intent to stay in the profession scores. No significant difference was found between groups for intent to stay in the organization. Furthermore, it was found through the use of hierarchical regression, that the total model was responsible for 8% of the variance in intent to stay in the unit and 23% of the variance in intent to stay in the profession. The hierarchical regression analyses did not show statistically significant results for the intervention on intent to stay in the organization in this study sample. Therefore, the hypothesis was supported for two of the intent to stay outcomes (unit and profession). 109  Research hypothesis 2. Perceived organizational support will mediate the relationship between the professional development intervention and intent to stay among critical care nurses.  POS was not found to be statistically significant in mediating the relationship between the professional development intervention and intent to stay in the organization or unit. A statistically significant mediation effect was found for intent to stay in the profession and at Time 4. Research hypothesis 3.  Critical care self-efficacy will mediate the relationship between the professional development intervention and intent to stay among critical care nurses.  Critical care self-efficacy was not found to be statistically significant in mediating the relationship between the professional development intervention and intent to stay in the organization, unit and profession at Time 4. Research hypothesis 4. Positive work environments will moderate the effect of professional development on perceived organizational support, such that the effect will be stronger when work environment scores are higher versus lower. Work environment was statistically significant at Time 1 in Models 2 (= .18, p<.05) and Model 3 (= .20, p<.05). The total variance explained by the model was 16% (see table 12). Work environment did not show statistically significant results for moderation effect between the intervention and POS at Time 4. 110  Research hypothesis 5. General self-efficacy will moderate the influence of professional development on critical care self-efficacy, such that the effect will be stronger when general self-efficacy levels are higher versus lower. GSE was not shown to moderate the effect of the professional development intervention on critical care self-efficacy in this study. Research hypothesis 6. Transfer of learning will moderate the relationship between critical care self-efficacy and intent to stay among critical care nurses, such that the effect will be stronger when transfer of learning scores are higher versus lower. Transfer of learning Time 3 was not shown to moderate the relationship between critical care self-efficacy Time 4 and intent to stay in the organization, the unit or the profession at Time 4 among critical care nurses. However, the treatment group had a significant difference in transfer of learning scores from pre-simulation to post-simulation reflecting their transfer of learning from theory to practice. In summary, two of the six research hypotheses were supported in this study. In addition, significant relationships were noted between major study variables. The implications of these findings are discussed in the following chapter.   111  Chapter 6. Discussion The purpose of this study was to examine the influence of a professional development intervention on critical care nurses’ intent to stay. In this study a theoretical Critical Care Nurse Retention model was tested. The theoretical model consisted of the professional development intervention, two mediator variables (POS and critical care self-efficacy) and three moderator variables (work environment, general self-efficacy and transfer of learning) as mechanisms that may influence intent to stay in the organization, unit and nursing profession (see Figure 4). The intention was to assess whether professional development, part of a healthy work environment, relates to intent to stay as a means to retain critical care nurses and assist in stabilizing the critical care nursing workforce. A secondary intention was to examine general self-efficacy, critical care self-efficacy and transfer of learning as potential mechanisms to assist in the adjustment of registered nurses to critical care and the subsequent impact of these variables on intent to stay in the organization, unit and nursing profession. A quasi-experimental longitudinal design was used to test the hypotheses in this study. Data were collected from 363 critical care nurses from multiple hospital sites in Ontario, Canada over an 18-month period and reflect specific time points of the phased intervention. Overall, two of the six research hypotheses were supported. Findings showed the professional development intervention had a direct effect on intent to stay in the profession (see Table 14, p. 100). Furthermore, it was found that POS mediated the relationship between the professional development intervention and intent to stay in the organization, the unit and the profession. In this chapter, an overview of the findings specific to factors that influence intent to stay among critical care nurses will be discussed. Next, an overview of the theoretical model will be provided followed by a detailed discussion of each research hypothesis and the findings related 112  to key study variables. In addition, implications for nursing practice and management, nursing education, nursing research and policy followed by strengths and limitations of the study, final conclusions and directions for future research are discussed. Overview of Theoretical Model The overall model demonstrated that intent to stay is a multi-faceted process that is affected by work, organizational and individual characteristics. Each dimension of intent to stay (organization, unit and profession) was tested as an outcome variable. Similarities with the current model in comparison with previous intent to stay models (Boyle et al., 1999; Cowden, 2012) were that intent to stay conceptualized as the outcome variable. In addition, previous models hypothesized a relationship between predictor internal work environment characteristics such as manager support, workload and resource adequacy and individual nurse characteristics (i.e., age, education and tenure) and intent to stay. The current model hypothesized work environment as a moderator to explain the relationship between professional development and intent to stay in that favourable work environments would enhance the relationship between professional development and the nurses’ intention to stay. The current model added POS as a mediator to explore its impact in influencing the relationship between professional development and intent to stay. Another addition to the current intent to stay model was the hypothesized relationship between professional development and intent to stay through mediation of critical care self-efficacy. General self-efficacy and transfer of learning as moderators were also new to this model versus previous models. The hypothesized current model was partially supported demonstrating direct effects of the professional development intervention on intent to stay in the unit and in the profession. Furthermore, POS was found to have an indirect effect on the 113  relationship between professional development and intent to stay in the profession. The specific findings are discussed below. A one-way between-groups ANCOVA was conducted to compare the effectiveness of a professional development intervention designed to increase critical care nurses’ intent to stay in the unit, the organization and in the profession. Significant differences were found between groups for intent to stay in the unit (ICU) and in the profession. In addition, hierarchical regression results demonstrated a significant direct effect between the professional development intervention and intent to stay in the profession and intent to stay in the unit. The professional development intervention and perceived organizational support were found to contribute the most compared with other variables in relation to intent to stay in the profession. The whole model explained 23% of the variance in intent to stay in the profession. Discussion of the Research Hypotheses Research hypothesis 1. It was hypothesized that there would be a significant difference in critical care nurses’ intent to stay (unit, organization, and profession) for nurses who receive the professional development intervention compared with a comparison group of critical care nurses, while controlling for their baseline levels of intent to stay. The professional development intervention was a 12-month critical care certificate program that included a 215-hour online theoretical component, followed by a 39-hour simulation component and finishing with a 120-hour critical care practicum. Findings of the current study demonstrated that professional development is linked to intent to stay in the unit and profession one year after the intervention. Results showed that the phased intervention that was implemented in this study, comprised of online, simulation and 114  practicum components, predicted intent to stay in the ICU and in the nursing profession one year after the intervention. The results however, were not significant in predicting intent to stay in the organization in this sample. Although there is no supporting literature, it could be speculated that these results indicate that nurses identify more with their unit (the ICU) since this is their immediate work environment and less with the organization since the immediate environment may have more impact on the nurses’ perceptions. In addition, the nurses in the treatment group could have viewed their immediate manager (versus the organization) as responsible for the allocation and investment of funding for them to attend the critical care certificate. This factor could have had a greater impact on how their intention to stay developed in relation to the ICU and the profession versus intent to stay in the organization.  Previous research has demonstrated that professional development opportunities are highly valued by nurses at all career stages (AbualRub, 2008; Aiken et al., 2013; Bournes & Pare, 2007; Hayes et al., 2006; Kovner et al., 2007; O’Brien-Pallas et al., 2010; Stone et al., 2006; Ulrich et al., 2009).  Kovner and colleagues (2007) found that although 81% of nurses reported receiving a preceptor or mentor during orientation, less than 33% of the respondents in their study (N=1,933) reported extended learning opportunities beyond their initial orientation. This finding highlights the need for ongoing availability of learning opportunities in order to address the needs of nurses at all stages of their career. The availability of professional development, or educational opportunities, has also been linked to characteristics of a healthy work environment that both attracts and retains nurses (AACN, 2005; Kramer et al, 2008).  The literature is relatively silent in providing evidence on which strategy of delivery for professional development is the most effective in retaining nurses and promoting transfer of this learning into the practice setting. This was the first time an intent to stay model had been tested 115  with the addition of a specific professional development strategy. The strategy employed in the current research focused on an intensive 39-hour simulation intervention followed by a 120-hour preceptored clinical component conducted in the ICU. The simulation component of the intervention in the current study utilized best practices in simulation including skilled facilitators, validated scenarios, and standardized pre-briefing and guided debriefing formats. In Cant and Cooper’s (2009) and Cook and colleagues (2012) meta-analyses that evaluated the effectiveness of simulation across health professions with the use of mannequins versus other teaching methods (i.e., lecture, small group discussion, video training), simulation education was found to be superior and was associated with improved learning outcomes. In a recent nursing quasi-experimental pre-post design study, the effectiveness of simulation manikin training versus web-based simulation education was evaluated among acute care nurse practitioners and certified nurse anesthetists (N=32). The results showed that performance scores and self-assessment scores of practice ability after training was higher in the simulation manikin group (White, Brannan, Long & Kruszka, 2013). Existing simulation literature comparing educational methods is unclear on whether simulation best practices were followed (INACSL, 2013). Best practices such as: the duration and nature of the simulation intervention was not always fully described, whether a hybrid approach was used (i.e., classroom and simulation, high fidelity and virtual simulation cases) and whether simulation performance was evaluated in teams or individually. The current study provides new evidence about the relationship between professional development and intent to stay not previously studied in the nursing population. Specifically, this study adds to the existing literature by providing a specific professional development strategy that positively impacts whether a nurse will decide to stay in the intensive care unit and in the 116  nursing profession. Furthermore, this study demonstrates that these findings are sustained up to one year after the intervention. Although this professional development intervention did not test simulation as a singular strategy, the results of this study highlight the need for research to further examine the specific impact of simulation as a potential strategy to increase levels of intent to stay among nurses. Research hypothesis 2. It was hypothesized that perceived organizational support (POS) would mediate the relationship between the professional development intervention and intent to stay among critical care nurses in the unit, organization and profession. The findings showed that POS did mediate the relationship between the professional development intervention and intent to stay in the profession at twelve months post intervention. This finding suggests that a nurses’ perception of whether the organization values them and cares about their well being does have significant influence on whether a nurse intends to stay in the nursing profession but not whether they intend to stay in the organization or the unit.   Previous research has shown that employees that have higher levels of POS believe that their contributions and well being are valued by the organization and as a result will be more likely to stay in their current position and have higher levels of performance (Eisenberger et al., 1986). The current study did not conform with the literature related to POS. In the previous literature POS levels have been studied in relationship to intent to stay in the current position and the organization. Eisenberger and colleagues work has not explored POS and its relationship to intent to stay in the profession. Earlier POS research has found that POS is related to commitment and emotional attachment to the organization (Eisenberger et al., 1986). Furthermore, it is known that the employee must believe in the sincerity of the organizational 117  support (i.e. the professional development opportunity) for it to have value (Eisenberger et al., 1997; Shore et al., 1995).  The findings of the current research have implications about organizational loyalty and attachment and the role this may play in intent to stay among nurses in critical care. In the Canadian health care system context, retaining nurses in the profession and the system for the good of all needs further exploration versus the focus on retaining the nurse in the organization alone. The POS measure was developed and primarily tested in the US within a very different health care system context and one might speculate that there may be international differences in nurses’ perceptions of organizational support. The findings in this research did not demonstrate significant findings related to intent to stay in the organization, which may signal that there is a different mechanism in place for nurses within the Canadian context relating to the development of intention to stay behaviours. Given the sociological traditions of intent to stay theoretical frameworks in the literature (Price & Mueller, 2001; Boyle et al., 1999; Cowden, 2012), it has been established that nurses’ intentions are influenced by interactions within groups in their immediate work settings. Nurses may identify more with their immediate work environment and profession versus being influenced by their organizational attachment. In addition, one may speculate on whether the nurses in this study felt the professional development was offered sincerely and whether it was perceived that the organization voluntarily contributed the professional development versus simply providing the critical care program to be competitive in the current hiring landscape.  The relationship between professional development, POS and intent to stay in the unit, organization and profession has not been previously studied in the nursing population. This study has added new knowledge about the mediation effect of POS on the relationship between a professional development intervention and intent to stay in the profession. Further research is 118  needed to explore how intent to stay develops in Canadian nurses and whether the organizational impact is as influential as the nurses’ connection with the unit and the profession. Research hypothesis 3. It was hypothesized that critical care self-efficacy would mediate the effect of the professional development intervention on intent to stay among critical care nurses. This finding was not supported. Critical Care self-efficacy refers to the degree to which a nurse feels she/he is capable of performing a specific critical care competency. Self-efficacy has been shown to have a significant influence on persistence and career competency (Bandura, 1993) and is enhanced by training (Akhu-Zaheya et al., 2012; Christina et al., 2012; Gaudine & Saks, 2004). In addition, self-efficacy has been linked to newcomer’s adjustment in the workplace (Saks, 1995) and to employee turnover intentions (McNatt & Judge, 2008).  The relationship between professional development, critical care self-efficacy and intent to stay has not been studied in the nursing population. It was hypothesized that if a nurse develops increased self-efficacy as a result of training opportunities, this may have a positive influence on intent to stay.  If a nurse feels comfortable and confident in her/his ability to perform the essential skills that are required to practice routinely and safely in ICU, then they may be more likely to adjust well and stay in the unit, organization and profession.  A critical care self-efficacy tool was developed and tested in this study. There was no previous literature or measures that examined critical care self-efficacy in the nursing population. The competencies chosen for this measure included the foundational skills required of critical care nurses working in the ICU and include the ability to: interpret arrhythmias, analyze 12 lead ECGs, manage a mechanically ventilated patient, interpret arterial blood gases, calculate 119  vasoactive drip rates, perform a cardiac output and a pulmonary artery wedge pressure, prioritize care for a critically ill patient and manage a cardiac arrest.  No significant mediation effect for critical care self-efficacy was found in this sample. A potential explanation for this could be that there may be additional factors that may work together with professional development and critical care self-efficacy to influence intent to stay. In addition, attrition at Time 4 may have impacted the results and this may also be an issue for other non-significant findings in relation to Time 4. More research is needed in this area with a larger ICU sample population and further exploration of the psychometrics of the critical care self-efficacy measure. Although the hypothesized relationship between the professional development intervention and intent to stay mediated by critical care self-efficacy was not supported in this sample, a unique measure for critical care self-efficacy was developed and may provide further insight into a nurses’ development of confidence in approaching core critical care competencies. Research hypothesis 4. It was hypothesized that positive work environments will moderate the effect of professional development on perceived organizational support; such that the effect will be stronger when work environment scores are higher versus lower. No moderation effect was found and the hypothesis was not supported in this sample. A potential explanation for this finding could be that many of the nurses that were enrolled in the critical care certificate were transitioning into the ICU at Time 1 and may have still been employed in other areas of the hospital (i.e., medical surgical floors) therefore they may not have been in the ICU for a long enough duration and therefore had the yet had the full impact of the ICU work environment. At Time 4, a smaller sample was available due to attrition over time therefore limiting the 120  generalizability of these results. More research is needed in this area with larger samples and in particular to follow nurses further into their tenure in the ICU in order to capture the full effect of the ICU work environment. Research hypothesis 5. There are no studies in the literature examining critical care self- efficacy and general self-efficacy together. However, high general self-efficacy has been shown to maintain employees’ work motivation throughout rapidly changing stressful job demands and circumstances and buffer them from the potentially demotivating impact of failure (Chen et al., 2008). Eden et al. (1988) found that general self-efficacy influences domain-specific self-efficacy across tasks and situations.  It was hypothesized that general self-efficacy will moderate the influence of professional development on critical care self-efficacy; such that the effect will be stronger when general self-efficacy levels are higher versus lower. Although no moderation effect was found in this sample and the hypothesis was not supported, other findings emerged from the current study related to general self-efficacy and the major study variables. In the treatment group a significant positive relationship was found between general self-efficacy and critical care self-efficacy after the completion of the online component of the intervention (Time 1). Although, no significant results were seen at Time 4 between general self-efficacy and critical care self-efficacy this could have been a result of low sample size at that data collection point. Research hypothesis 6. It was hypothesized that transfer of learning will moderate the relationship between critical care self-efficacy and intent to stay among critical care nurses, such that the effect will be stronger when transfer of learning scores are higher versus lower. This finding was not 121  supported. Although the hypothesis was not supported in this sample, the transfer of learning literature has shown that to promote transfer of learning, employees require specific conditions in the immediate work environment that promote transfer of learning such as: manager support, adequacy of resources, and opportunity to practice skills.  One possible explanation is that nurses in the treatment group had not worked in ICU for long enough to impact the relationship between these variables at Time 1. At Time 4, through attrition in the sample over time, the sample size may not have been large enough to detect a relationship in this sample. In addition, the work conditions may not have been conducive to transfer in this sample therefore impacting the results. Further study is needed with a larger ICU sample population to further explore the impact of critical care self-efficacy and transfer of learning on intent to stay. Implications for Nursing Practice and Management The findings from this study suggest that investment in professional development opportunities for nurses is a motivator of intent to stay and may be a signal to employees that the organization values them as individuals further enhancing the likelihood that they will stay in the unit and the profession. Careful consideration needs to be given to investing not only in new nurses educational needs as they transition into the unit but also to experienced nurses need for professional development. Opportunity to attend educational opportunities has been shown to be important at all stages of a nurse’s career (Hallin & Danielson, 2008; Lavoie-Tremblay et al., 2008). It is important to note, the employee must believe in the sincerity of the organizational support/rewards (i.e., professional development opportunities) in order for them to have value. In fact, there are higher levels of POS if the employee believes the employer voluntarily contributed these rewards versus being contingent on a union, safety or other reason for implementing them (Eisenberger, Cummings, Armeli & Lynch, 1997, Shore & Shore, 1995). This study has also 122  made linkages between the investment in professional development for nurses that includes high fidelity simulation.   Finally, it has been found in previous studies that the decision to stay or leave is a gradual process often starting six months or longer in advance of actually leaving (Morell et al., 2005; O’Brien-Pallas et al, 2010). Professional development opportunities may also provide an incentive or mechanism to not only retain but also to recruit nurses and further stabilize the workforce in critical care. When professional development opportunities are offered consistently for nurses, this may increase the likelihood that nurses will stay by intervening in advance of the typical six months at which a nurse starts to develop the intention to leave or stay. Implications for Nursing Education Nurses transitioning into a critical care specialty area typically require additional preparation beyond the undergraduate level in order to acquire the competencies required to safely practice in the ICU. Historically, critical care programs to prepare nurses for critical care have been comprised of a classroom theoretical component followed by a preceptored practicum. In this study, the critical care program consisted of three discrete components: online, simulation and a preceptored practicum.  A new Critical Care self-efficacy tool was created for this research and provides an opportunity to evaluate which competencies critical care nurses feel least confident about performing. Simulation training allows nurses to be evaluated prior to proceeding to the practice setting and provides an assessment on where additional training may be required.    The results of this study suggest that professional development that includes simulation may be an effective strategy for increasing confidence and allows the nurse to practice in a ‘safe’ 123  environment where no harm will occur to a patient while the nurse is learning new high risk competencies. These findings have implications for nurse educators in the creation and provision of effective training programs for nurses transitioning to critical care and also for existing staff in ICU. In planning professional development opportunities, nurse educators need to give attention to competencies nurses report they are the least confident in and consider designing orientations and critical care programs that will enhance practice opportunities by providing intensive case based simulation scenarios. Simulation provides opportunity for practice with skills not frequently seen in the ICU (high risk/low frequency skills). The findings suggest that attention needs to be given to the ongoing learning needs of not only nurses new to critical care, but alos to experienced ICU nurse and consideration given to professional development opportunities in this group as well. Other implications for nurse educators include the notion of creating an environment conducive to transfer of learning. Creating a positive transfer climate includes factors such as: opportunity to practice and apply new skills, manager and peer support, encouragement and adequate resources (Noe, 2006). The findings in this study suggest that professional development opportunities should be provided to all ICU nurses on an ongoing basis and that consideration to the most effective educational strategy (i.e., simulation) is made prior to program delivery.   This study provided new knowledge in the area of critical care self-efficacy among ICU nurses and further study is needed in developing additional competencies for testing such as communication based competencies that could include family, patients and other health care team members. In addition, further study is needed to examine the period immediately after the preceptorship period ends since the findings in this study showed that critical care self-efficacy means decreased slightly at the end of the practicum phase of the intervention which coincides 124  approximately with the end of the preceptorship period of the orientation. More exploration of nurses’ self-efficacy is needed further into their tenure in ICU to determine whether critical care self-efficacy levels begin to rise again as the nurse adjusts to the critical care practice setting. Implications for Nursing Research Next steps in understanding the effects of professional development among nurses and intent to stay include validating findings in larger samples with a broader pan-Canadian sample of critical care nurses. The Critical Care Nurse Retention Model could also be replicated in other nursing specialty areas such as Emergency or Oncology and also within the general nursing population. Specifically, future research is needed to determine which educational strategies are the most effective in retaining nurses and facilitating adjustment during initial tenure in the ICU. In particular, research is needed to further examine the impact of high fidelity simulation on nurse outcomes such as critical care self-efficacy and intent to stay. Simulation has been established in the literature as superior to other educational methods in relation to performance and transfer or learning into the practice area. Further research could follow nurses beyond the first 18 months of their tenure in ICU to determine whether the results are sustained over time. In addition, newer emerging simulation technologies such as virtual simulation or a hybrid approach of combining high fidelity simulation and virtual simulation could be explored in relation to which method is the most effective at retaining nurses, increasing self-efficacy and the ability to transfer or apply the learning into the practice setting. Future related research could examine the influence of simulation on the development of perceived organizational support and subsequent intent to stay. Further exploration of the relationships between general self-efficacy, critical care self-efficacy and transfer of learning since this study was the first to begin to examine this relationship.  125   Additional studies are needed to understand how nurses adjust within the practice setting and what role achievement of competency and critical care self-efficacy has on the development of intention to stay. Furthermore, future research could examine which elements of a favourable work environment promote an optimal climate that enhances transfer of learning.  Implications for Policy This study highlights the importance of professional development as a motivator and incentive for nurses to feel valued and continue to stay in the ICU and in the nursing profession. The results of this study further advocates for policies that enable implementation of strategies such as the provision of ongoing professional development opportunities and training for nurses transitioning into critical care. In addition, this study also suggests that an intervention that includes simulation may be a key educational strategy to increase confidence of nurses as they develop competency in critical care and transition into the critical care practice setting. Simulation has been shown to be superior to other educational methods in improving performance and transfer/application of learning in the practice setting (Cant & Cooper, 2009; Cook et al., 2012).  In order to invest in front-line nursing staff in the ICU, sustainable, protected funding must be made available so that effective education programs can be provided utilizing strategies such as simulation to increase confidence and competence and the ability to transfer learning into the practice environment. In Ontario, a critical care training fund is available to hospitals through the Ministry of Health and Long Term Care: Critical Care Secretariat. This funding needs to be protected, consistently administered at regular intervals that coincide with hospital hiring cycles and with advance notice to allow for human resource planning. The provision of professional development opportunities and its relationship to intent to stay is well established in the literature 126  and the findings of this study are consistent with these results (AbualRub, 2008; Aiken et al., 2013; Bournes & Pare, 2007; Hayes et al., 2006; Kovner et al., 2007; O’Brien-Pallas et al., 2010; Stone et al., 2006; Ulrich et al., 2009). It is recommended that consideration for an increase in the critical care training funding be advocated for to meet the high turnover needs in ICUs and to assist in stabilizing the nursing workforce in this area. Funding could be made contingent on nurse outcomes such as retention over time and the development of partnerships between educational institutions that house well-developed simulation education resources and hospitals.  Furthermore, funding could be utilized for increasing the number of nurses in Canada that hold national certifications in critical care versus solely being made available for orientation purposes. This study showed that professional development was related to intent to stay in the profession. If a nurse leaves the profession altogether, this could have serious implications for the worsening nursing shortage. The importance of sustainable funding for ongoing critical care training cannot be understated. If cuts are made to training funding for critical care nurses this could negatively impact intent to stay of nurses in critical care. In the short term, cost cutting may seem efficient; however longer outcomes term must be considered such as organizational costs, productivity costs, patient safety and further destabilization of the critical care workforce where turnover is currently the highest across Canada. Strengths and Limitations Limitations. There were several limitations to this study that must be considered. The first limitation was attrition rates at each subsequent timeframe of data collection. The attrition could have 127  impacted the non-significant findings in this study. There were five data collection time points in the treatment group and two data collection points for the comparison group. Data were collected via mail and in person. Mail response rates were low (29-33%) despite use of the Dillman (2000) method and offered incentives. Nurse survey response rates have been reported to be less than 60% in the literature (Cook et al., 2009). In contrast, in person recruitment yielded 98-100% response rates. More research is needed in this area with larger ICU sample populations. Although critical care nurses in the comparison group were randomly selected from the Ontario College of Nurses registry, these nurses had indicated that they could be contacted for research purposes. This may have introduced potential sample selection bias since all nurses in the registry indicating they worked in critical care did not have equal ability to be included in the study which may have limited the generalizability of the findings.  Another limitation to the study could have been the potential for the introduction of measurement bias or common method variance through the use of self-report survey. Common method variance has the potential to inflate or deflate relationships between constructs and lead to Type I or Type II errors (Podsakoff, MacKenzie and Podsakoff, 2012). Although self-report is an important method in analyzing a nurses’ perceptions of their intention to stay and of specific aspects within their work environment, measurement bias must be considered. Several procedural remedies were implemented in this study to mitigate the potential influence of common method variance and included: balancing positive and negative scale items, avoiding ambiguity of scale items, use of valid and reliable measures, eliminating common scale properties by the use of different scale formats and varying anchor points (Podsakoff et al., 2012). Another strategy that was used to control the possibility of common method variance was maintaining confidentiality of responses and the using aggregate versus individual data to ideally 128  mitigate the chance of the participant choosing socially desirable responses.  Even with precautions being taken to limit the possibility of common method variance, it still must be considered when interpreting the results.  As a result of the limitations discussed above, an element of caution is required in interpreting the results of this study. Future research is needed with larger sample sizes and a wider geographical area to overcome limitations and validate the generalizability of the results from this study.  Strengths. There were several key strengths to this study related to the sample, data collection method and the design of the intervention. This study included a standardized intervention that was delivered to all participants in the treatment group. This improved the rigor of the study since there was little variation in the intervention. All study participants had the same curriculum, instructors, method of delivery and evaluations. Intervention evaluation research that controls for baseline assessments allows examination of causal effect among variables rather than simply analyzing correlations between variables.  An additional strength of this study was the longitudinal nature of data collection. Longitudinal studies are helpful in establishing causal relationships and making reliable inferences since this design allows real trends to be separated from chance occurrence. Previous studies in this area have primarily consisted of cross sectional descriptive studies which only provide a ‘snapshot’ of results at one moment in time.  Final Conclusions The contribution of this research is to provide new evidence supporting the relevance and importance of investing in professional development opportunities for nurses and its impact on 129  intent to stay in the nursing profession. In addition, a new measure was developed and tested to evaluate critical care self-efficacy in this study.  The theoretical model tested in this study has suggested causal links between professional development and intent to stay in the unit and in the nursing profession. 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International Journal of Nursing Studies, 39, 573-581. doi:10.1016/S0020-7489(01)00018-9     150  APPENDICES Appendix A: Intent to Stay Model Comparisons Variables Causal Model of Intent to Stay (Price and Mueller,1986) US Critical Care Nurse Intent to Stay Framework (Boyle et al.,1999) US Theoretical Framework of Clinical Nurses’ Intent to Stay (Cowden,2012) Canada Critical Care Nurse Retention Model (Goldsworthy,2014) Canada Independent Environmental Variables  Kinship responsibilities  opportunity Individual Variables  general training  job motivation  met expectations  affectivity (positive or negative) Structural Variables  autonomy  distributive justice  job hazards  job stress  pay  professional growth  promotional chances  routinization  social support Manager characteristics  power (position and personal)  influence (work coordination and personnel resources)  leadership style   Organizational characteristics  distributive justice  promotional opportunity  control over practice  unit characteristics (workload, staffing, skill mix) Work Characteristics  autonomy  instrumental communication  work group cohesion  routinization Manager characteristics  nurses perception of leadership  shared decision making  praise and recognition  supervisor support  Work characteristics  threat of abuse  autonomy  work group cohesion  Nurse characteristics  age  tenure  education  work status  position preference Organizational characteristics  career development opportunities  staffing adequacy  time to nurse  threat of abuse  autonomy  work group cohesion  151  Variables Causal Model of Intent to Stay (Price and Mueller,1986) US  Critical Care Nurse Intent to Stay Framework(Boyle et al.,1999) US Theoretical Framework of Clinical Nurses’ Intent to Stay (Cowden ,2012) Canada Critical Care Nurse Retention Model (Goldsworthy, 2014) Canada Mediators/Moderators Job satisfaction Organizational commitment Search behaviour Nurse characteristics  age  education  job decision priorities  tenure (in position, hospital and profession)  marital status  opportunity elsewhere Other intervening variables  job stress (personal, situational)  job satisfaction  commitment Affective responses to work  Moral distress  Desire to stay  Joy at work  Job satisfaction  Cognitive responses to work  Organizational commitment  Quality of care  Opportunities elsewhere  Empowerment Work Environment  Nurse participation in hospital affairs  Nurse manager ability, leadership and support of nurses  Staffing and resource adequacy  Collegial nurse-physician relations POS  General Self-efficacy  Critical Care Self-efficacy  Transfer of Learning Dependent Intent to Stay Intent to Stay Intent to Stay Intent to Stay  Unit  Organization  Profession       152  Appendix B: College of Nurses of Ontario Request for Home Mailing Addresses   153     154    155      156  Appendix C: Letter with Mailing of Second Questionnaire Dear nurse colleague,   In xxxx I sent you a questionnaire and requested your participation in a study entitled “THE MECHANISMS BY WHICH PROFESSIONAL DEVELOPMENT MAY CONTRIBUTE TO CRITICAL CARE NURSES’ INTENT TO STAY.”  The purpose of the study is to investigate the influence of the work environment and financial support for professional development opportunities on an individual’s perceived support from the organization, commitment to the organization and ultimate intent to stay in the current position, organization and the nursing profession. Your participation is very important to ensure accurate results of the study. The more people I hear from, the better the results will represent the experiences of critical care nurses from across the province. I am sending you a second questionnaire in the hope that you will consider participating.  I would like to remind you that your responses on the questionnaire are anonymous and confidential. By returning the consent form and request of participation in the sealed envelope inside the outer envelope, you ensure that your responses cannot be linked to your name.  I am a registered nurse and a doctoral student in the School of Nursing at the University of British Columbia conducting this study in partial fulfillment of the requirements for the Doctor of Philosophy in Nursing degree. My proposal has been approved by my thesis committee, which is led by my supervisors Dr. Maura MacPhee and Dr. Susan Dahinten, School of Nursing, University of British Columbia. I have also received ethical approval from the Office of Research Ethics at the University of British Columbia for the conduct of this research.  If you have already returned your questionnaire, please disregard this letter and accept my thanks. I appreciate your assistance with the study.   Sincerely,  Sandra Goldsworthy, RN BScN MSc CNCC CMSN, Doctoral Student  Phone: Email:  157  Appendix D: Questionnaire Critical Care Nurse Retention Survey Part 1: Demographic Information  Please complete the following.  1. How long have you been employed as a registered nurse? Number of years ___ months ___   2. How long have you been employed in your present position? Number of years ___ months ___   3. What is your age? ______   4. Sex:  a. Male b.   Female  5. What is the highest education you have received in nursing?  a. Diploma  b. Bachelor’s degree  c.  Master’s degree  d. PhD  e. Other (specify)   6. What is the highest education you have received in a field other than nursing?  a. Diploma  b. Bachelor’s degree  c. Master’s degree  d. PhD   What field is this degree in? e. Not applicable  7. Do you hold specialty certification or specialty certificates? a. CNCC b. Critical Care Certificate c. Other (specify)  d. Not applicable  8. Which of the following defines your employment? a. Full-time  b. Part-time  c. Casual  d. Other (specify)  158  9. What type of critical care unit do you work on?  a. Medical or surgical ICU b. CVICU/CCU c. Other critical care unit (e.g. neurological ICU, Burn ICU)   10. What type of institution do you work in? (If you work in more than one institution, at which institution do you work the most hours?)        a. Small hospital  b. Community hospital  c. Teaching hospital   11. What is your job title?  a. Staff Nurse b. Educator c. Manager  d. Other (specify)    12. How long have you worked in critical care? ______________  13. If you have a Critical Care Certificate, which program did you attend?  a. Critical Care Certificate taken at  b. Not applicable  14. In my organization, in-house continuing education (i.e., in-services) is available. a. Daily  b. Weekly  c. Monthly d. Other. Specify.  15. In-house training is available to me a. Yes b. No  16. Certification fees for CNCC exams are provided. a. Yes b. No  17. Nurses in my organization who achieve certification are recognized. a. Yes. Describe type of recognition.  b. No  18. Are you currently attending a Critical Care Certificate program? a. Yes. Which program?  b. No   159  19. If you are currently enrolled in a Critical Care Certificate program, who provides the tuition reimbursement for the course? a. The hospital I am employed at b. Myself c. RNAO d. Union e. New graduate initiative (government) f. Other. Describe.  20. In the past year I have received financial support from my organization for professional development (i.e., conferences, educational opportunities). a. Yes. Indicate amount of support. $ b. None (if requested) c.         I did not request funding  21. In the last year I have received days of release time for professional development/educational opportunities). a. Yes. Indicate the number of days of release time received. b. None (if requested) c.         I did not request release time.    Part 2: Your Work Environment Please respond to the following statements related to your work environment.   In my work environment Strongly Disagree 1 Mildly Disagree 2 Mildly Agree 3 Strongly Agree 4 22. staff nurses are involved in the internal governance of the hospital.     23. opportunity is provided for staff nurses to participate in policy decisions.     24. opportunities exist for advancement.     25. administration listens and responds to employee concerns.     26. there is a chief nursing officer who is highly visible and accessible to staff.     27. opportunities exist for career development/clinical ladder advancement.      28. nursing administrators consult with staff on daily problems and procedures.     29. nurses have the opportunity to serve on hospital and nursing committees.     30. there is a chief nursing officer equal in power     160  and authority to other top level hospital executives. 31. use is made of nursing diagnoses.     32. an active quality assurance program is in place.     33. there is a preceptor program for newly hired nurses.     34. nursing care is based on nursing, rather than on a medical model.     35. patient care assignments foster continuity of care.     36. a clear philosophy of nursing pervades the patient care environment.     37. written up-to-date care plans exist for all patients.     38. high standards of nursing care are expected by the administration.     39. active staff development or continuing education programs are provided for nurses.     40. nurses on staff are clinically competent.     41. there is a nurse who is a good manager and leader.     42. there is a nurse manager who backs up the nursing staff in decision making, even if the conflict is with a physician.     43. supervisors use mistakes as learning opportunities, not criticism.     44. supervisory staff is supportive of the nurses.     45. praise and recognition are given for a job well done.     46. there is enough staff to get the work done.     47. there are enough registered nurses to provide quality care.     48. adequate support services allow me to spend time with the patients.     49. enough time and opportunities are available to discuss patient care problems with other nurses.     50. a lot of teamwork exists among nurses and physicians.     51. physicians and nurses have good working relationships.     52. collaboration (joint practice) exists among     161  nurses and physicians.   Part 3: Your Perception of the Organization’s Relationship with You Please respond to the following statements about your organization’s relationship with you.  This organization StronglyDisagree 1 Moderately Disagree 2 Slightly Disagree 3 Neither Agree nor Disagree 4 Slightly Agree 5 Moderately Agree 6 Strongly Agree 7 53. values my contribution to its well being.         54. fails to appreciate any extra effort from me.         55. would ignore any complaint from me.        56. really cares about my well-being.        57. would fail to notice even if I did the best job possible.         58. cares about my general satisfaction at work.         59. shows very little concern for me.          60. takes pride in my accomplish-       162  ments at work.     Part 4: Transfer of Learning ** Part 4 is only administered after the online component, after the simulation component and after the practicum component (not prior to starting the program)** Please indicate the degree of your agreement or disagreement with each statement by checking the box that best represents your point of view. Please choose from the following answers:    Strongly Disagree 1 Moderately Disagree 2 Neither Agree nor Disagree 3 Moderately Agree 4 Strongly Agree 5 61. Managers and peers have told me that my behaviour has improved following the *online portion of the Durham College critical care e-Learning program.      62. My intent to stay in my current position has increased due to the skills I developed while taking the *online portion of the critical care e-Learning program at Durham College.      63. My morale is higher due to the skills I developed while taking the *online portion of the critical care e-Learning program at Durham College.      64. I am able to transfer the skills learned in the critical care e-learning program back to my actual job.      163  65. I have changed my job behaviour in order to be consistent with the material taught in the critical care e-Learning program.      66. My actual job performance has improved due to the skills I have learned in the critical care e-Learning program.         Part 5:  ** Part 5 is administered initially, then after the online component, after the simulation component and after the practicum component. After completing the ____________ portion of the Critical Care e-Learning Program please rate how certain you are that you can perform the following critical care skills: Rate your degree of confidence by recording a number from 0-100 using the scale below:  0      10    20  30 40 50 60 70 80 90 100 Cannot do at all Moderately can do Highly certain can do  Critical Care Skills Confidence (0-100) 67. Systematically interpret arrhythmias  68. Systematically interpret 12 Lead ECGs  69. Care for a mechanically ventilated patient  70. Interpret arterial blood gas results  71. Accurately calculate vasoactive infusions  72. Perform a cardiac output  73. Wedge a pulmonary artery catheter  74. Draw blood from an arterial line  75. Prioritize care in the critically ill patient  76. Manage a cardiac arrest   164    Part 6: Final Thoughts Under each heading choose the most appropriate response for you.  My employer: Rate questions 77-89 on a scale from 1 (highly unlikely) to 4 (highly likely) 77. I am considering leaving my present employer. 78. I plan to leave my present employer as soon as possible. 79. I plan to stay with my present employer as long as possible. 80. There are few circumstances under which I would leave my present employer.  My current job position: Rate questions 81-84 on a scale from 1 (highly unlikely) to 4 (highly likely) 81. I am considering leaving the unit I work in. 82. I plan to leave the unit I work in as soon as possible. 83. I plan to stay in the unit I work in as long as possible. 84. There are few circumstances under which I would leave the unit I work in.  The nursing profession: Rate questions 85-88 on a scale from 1 (highly unlikely) to 4 (highly likely) 85. I am considering leaving the nursing profession. 86. I plan to leave the nursing profession as soon as possible. 87. I plan to stay in the nursing profession as long as possible. 88. Under no circumstances would I leave the nursing profession.    Thank you for completing this survey.    165  Appendix E: Follow up Post Card Reminder Dear Critical Care Nurse Colleague,  A few weeks ago, you received a letter requesting your participation in a study entitled “THE MECHANISMS BY WHICH PROFESSIONAL DEVELOPMENT MAY CONTRIBUTE TO CRITICAL CARE NURSES’ INTENT TO STAY.”   If you have already returned the questionnaire, I would like to express my genuine thanks. If you have not completed the questionnaire, I would like to use this postcard as a reminder that your participation is important.  I would also like to remind you that I am a registered nurse and a doctoral student in the Faculty of Nursing at the University of British Columbia conducting this study in partial fulfillment of the requirements for the Doctor of Philosophy in Nursing degree. My proposal has been approved by my thesis committee, which is led by my supervisors Dr. Maura MacPhee and Dr. Susan Dahinten, School of Nursing, University of British Columbia. I have also received ethical approval from the Office of Research Ethics at the University of British Columbia for the conduct of this research.  If you did not receive a copy of the questionnaire, or if you no longer have it, please let me know and I will send you another. My contact information can be found below.  Thank you,   Sandra Goldsworthy, RN BScN MSc CNCC CMSN, Doctoral student, School of Nursing, University of British Columbia  Phone:   Email:    166  Appendix F: Letter of Information Dear Critical Care Nurse, I am writing to invite you to participate in a study entitled “THE MECHANISMS BY WHICH PROFESSIONAL DEVELOPMENT MAY CONTRIBUTE TO CRITICAL CARE NURSES’ INTENT TO STAY”  Purpose of the Study The purpose of this study is to investigate the influence of professional development opportunities on the strengthening of an individual’s perceived support from the organization and ultimate intent to stay in the current position, organization and the nursing profession. This study will also investigate the influence of professional development on the transfer of learning in the clinical setting and subsequent intent to stay. Ontario nurses working in critical care are being invited to participate in this study. I am a registered nurse and a doctoral student in the School of Nursing at the University of British Columbia conducting this study in partial fulfillment of the requirements for the Doctor of Philosophy degree. My proposal has been approved by my thesis committee, which is led by my supervisors Dr. Maura MacPhee and Dr. Susan Dahinten, School of Nursing, University of British Columbia. I have also received ethical approval from the Office of Research Ethics at the University of British Columbia to conduct this research. You have been selected to participate because you indicated on your registration with the College of Nurses of Ontario that you currently work in critical care.  Eligibility and Participation You are eligible to participate if you are working either full-time or part-time in an acute hospital in a critical care setting. Your participation in the study is completely voluntary. Your involvement would consist of completing the survey included in this envelope and returning it in the pre-stamped envelope. The initial questionnaire will take approximately 20 minutes to complete and the follow up questionnaire will take approximately 5 minutes to complete. Your answers are confidential and your name will be removed from the questionnaire and coded in order that it can be matched with the follow up survey. Your name will not be used in any publications or presentations of the results of the study. You may refuse to answer any of the questions and you may choose not to participate. The questionnaires will be kept in a locked filing cabinet at the University of British Columbia School Of Nursing and will be destroyed after five years.   Risks and Benefits There are no known risks associated with participating in this study. There are also no direct benefits associated with participating in the study. It is hoped that through this study, I will gain a better understanding of factors that increase nurse retention in critical care. If you agree to participate, complete the attached consent form. Keep one copy of the consent form for yourself and return the other to me. You have been sent two envelopes. Please seal the consent form in the separate inner envelope and return this inside the outer stamped and addressed envelope 167  along with the questionnaire. When I receive the consent form, it will be removed from your completed questionnaire so that your questionnaire will be coded. If you wish, I will send you a certificate of completion. This will state that you have participated in this research study. You may keep this certificate as part of your reflective practice portfolio. To receive this certificate, complete the form included with the questionnaire and put it into the sealed envelope inside the return envelope along with the consent form. If you have any questions or comments about the study, please feel free to contact me at the address or number listed below. I will be happy to provide you with any information I can. If you have questions about your rights as a research participant, please contact xxxxx , Ethics Review Office, University of British Columbia at telephone xxxxx or by email at xxx@ubc.ca    Thank you very much for your assistance with this study.   Sandra Goldsworthy, RN BScN MSc CNCC CMSN, Doctoral Student University of British Columbia School of Nursing     168  Appendix G: Letter of Consent I agree to participate in a study entitled “THE MECHANISMS BY WHICH PROFESSIONAL DEVELOPMENT MAY CONTRIBUTE TO CRITICAL CARE NURSES’ INTENT TO STAY.”  This study is being conducted by Sandra Goldsworthy, RN, a doctoral student in the School of Nursing at the University of British Columbia, in partial fulfillment of the requirements for the Doctor of Philosophy in Nursing degree. The proposal has been approved by her thesis committee, which is led by her supervisors Dr. Maura MacPhee and Dr. Susan Dahinten, School of Nursing, University of British Columbia. The study has also received ethical approval from the Office of Research Ethics at the University of British Columbia.  I understand that the purpose of the study is to investigate the influence of the work environment and financial support for professional development opportunities on an individual’s perceived support from the organization and ultimate intent to stay in the current position, organization and the nursing profession. I agree to complete the initial questionnaire, which may take approximately 20 minutes of my time and the follow up questionnaire which will take approximately 5 minutes.  I understand that my participation is voluntary and that I may choose not to participate. I understand that I may opt out of answering any question at any time. I understand that the questionnaire will not contain any information about my identity and that my name will not be used in any publication or sharing of the results of the study. I understand that no one other than Sandra Goldsworthy and her thesis committee members will have access to the completed questionnaire at any time.  I understand that there are no known risks involved in participating in the study. I also understand that there are no direct benefits associated with my participation, but that the results may help inform researchers about the issues that are important to critical care nurses in retaining them in their current position, their organization and the nursing profession. I know that if I have any questions or concerns regarding the study, I can contact Sandra Goldsworthy, doctoral student at the School of Nursing, University of British Columbia at xxxx or Sandra.goldsworthy@xxxx. If I have questions about my rights as a research participant, I may contact xxxx, Health Sciences Ethics Review Officer, Ethics Review Office, University of British Columbia at telephone (604) xxx-xxxx or by email at xxxxxx@ubc.ca.   ____________________________    ___________________________  Participant Name (please print)                           Date    ____________________________  Participant Signature Contact information email/and or phone ________________________________________________   169  Appendix H: Demographic Information Part 1: Demographic Information Please complete the following.  1. How long have you been employed as a registered nurse? Number of years ___ months ___   2. How long have you been employed in your present position? Number of years ___ months ___   3. What is your age? ______   4. Sex:  a. Male b.   Female  5. What is the highest education you have received in nursing?  a. Diploma  b. Bachelor’s degree  c.  Master’s degree  d. PhD  e. Other (specify)   6. What is the highest education you have received in a field other than nursing?  a. Diploma  b. Bachelor’s degree  c. Master’s degree  d. PhD   What field is this degree in? e. Not applicable  7. Do you hold specialty certification or specialty certificates? a. CNCC b. Critical Care Certificate c. Other (specify)  d. Not applicable  8. Which of the following defines your employment? a. Full-time  b. Part-time  c. Casual  d. Other (specify)  170  9. What type of critical care unit do you work on?  a. Medical or surgical ICU b. CVICU/CCU c. Other critical care unit (e.g. neurological ICU, Burn ICU)   (specify)    10. What type of institution do you work in? (If you work in more than one institution, at which institution do you work the most hours?)   a.  Small hospital  b. Community hospital  c. Teaching hospital   11. What is your job title?  a. Staff Nurse b. Educator c. Manager  d. Other (specify)    12. How long have you worked in critical care? ______________  13. If you have a Critical Care Certificate, which program did you attend?  a. Critical Care Certificate taken at  b. Not applicable  14. In my organization, in-house continuing education (i.e., in-services) is available a. Daily  b. Weekly  c. Monthly d. Other. Specify.   15. In-house training is available to me a. Yes b. No  16. Certification fees for CNCC exams are provided a. Yes  b. No  17. Nurses in my organization who achieve certification are recognized a. Yes. Describe type of recognition. b. No  18. Are you currently attending a Critical Care Certificate program? a. Yes. Which program?  b. No  171  19. If you are currently enrolled in a Critical Care Certificate program, who provides the tuition reimbursement for the course? a. The hospital I am employed at b. Myself c. RNAO d. Union e. New graduate initiative (government) f. Other. Describe.  20. In the past year I have received financial support from my organization for professional development when I requested it (i.e., conferences, educational opportunities). a. Yes. Indicate amount of support. $ b. No financial support received (if requested) c.        I did not request any funding.  21. In the last year I have received days of release time for professional development/educational opportunities). a. Yes. Indicate the number of days of release time received. b. No release time received (if requested) c.         I did not request any funding     172  Appendix I: The Practice Environment Scale of the Nurse Work Index  The Practice Environment Scale of the Nurse Work Index (PES-NWI) Indicate the degree of your agreement or disagreement with each statement by filling in the circle on your answer sheet that best represents your point of view. Please choose from the following answers. Strongly Disagree 1 Mildly Disagree 2 Mildly Agree 3 Strongly Agree 4  PES-NWI Items by Subscale (used in the current study)  Nurse Participation in Hospital Affairs subscale (8 items) Staff nurses are involved in the internal governance of the hospital. Opportunity for staff nurses to participate in policy decisions. Opportunities for advancement. Administration that listens and responds to employee concerns. A chief nursing officer who is highly visible and accessible to staff. Nursing administrators consult with staff on daily problems and procedures. Staff nurses have the opportunity to serve on hospital and nursing committees. A chief nursing officer equal in power and authority to other top level hospital executives.  Nurse Manager Ability, Leadership and Support of Nurses subscale (5 items) A nurse who is a good manager and leader. A nurse manager who backs up the nursing staff in decision making, even if the conflict is with a physician. Supervisors use mistakes as learning opportunities not criticism. A supervisory staff that is supportive of the nurses. Praise and recognition for a job well done.  Staffing and Resource Adequacy subscale (4 items) Enough staff to get the work done. Enough registered nurses to provide quality care. Adequate support services allow me to spend time with the patients. Enough time and opportunity to discuss patient care problems with other nurses.  Collegial Nurse-Physician Relations subscale (3 items) A lot of teamwork between nurses and physicians. Physicians and nurses have good working relationships. Collaboration (joint practice) between nurses and physicians     173  Appendix J: General Self-Efficacy English version by Ralf Schwarzer & Matthias Jerusalem, 1995   1 I can always manage to solve difficult problems if I try hard enough.  2 If someone opposes me, I can find the means and ways to get what I want.  3 It is easy for me to stick to my aims and accomplish my goals.  4 I am confident that I could deal efficiently with unexpected events.  5 Thanks to my resourcefulness, I know how to handle unforeseen situations.  6 I can solve most problems if I invest the necessary effort.  7 I can remain calm when facing difficulties because I can rely on my coping abilities.  8 When I am confronted with a problem, I can usually find several solutions.  9 If I am in trouble, I can usually think of a solution.  10 I can usually handle whatever comes my way.  Response Format 1 = Not at all true   2 = Hardly true 3 = Moderately true   4 = Exactly true    174  Appendix K: Transfer of Learning Please respond to the following statements about your perceptions of how the online courses have prepared you for the Intensive Care Unit. Place a check mark in the box that best describes how you feel about the statement.  Please indicate the degree of your agreement or disagreement with each statement by filling in the circle on your answer sheet that best represents your point of view. Please choose from the following answers:  Strongly disagree Moderately disagree  Neither disagree nor agree Moderately Agree Strongly agree 1 2 3 4 5  Survey administration specific timeframe instruction inclusion: Time 1: In relation to beginning work in the critical care unit or continuing work in this area, please relate the following questions to how you feel about the following: Time 2: After completing the online components of the critical care e-learning program, please complete the following in relation to how you feel about applying the competencies and skills required to work in the critical care area.  Time 3: After completing the simulation component of the critical care e-learning program, please complete the following in relation to how you feel about applying the competencies and skills required to work in the critical care area. Time 4: After completing the practicum component of the critical care e-learning program or by working in the critical care environment, please complete the following in relation to how you feel about applying the competencies and skills required to work in the critical care area. ** online, simulation or practicum portion  1. Managers and peers have told me that my behaviour has improved following the *online portion of the Durham College critical care e-Learning program. 2. My intent to stay in my current position has increased due to the skills I developed while taking the *online portion of the critical care e-Learning program at Durham College. 3. My morale is higher due to the skills I developed while taking the *online portion of the critical care e-Learning program at Durham College. 4. I am able to transfer the skills learned in the critical care e-learning program back to my actual job. 5. I have changed my job behaviour in order to be consistent with the material taught in the critical care e-Learning program. 175  6. My actual job performance has improved due to the skills I have learned in the critical care e-Learning program.     176  Appendix L: Critical Care Nursing Self Efficacy Listed below are statements that represent possible opinions that YOU may have about your abilities to approach tasks and competencies required while working in the critical care setting. Please indicate the degree of your agreement or disagreement with each statement by filling in the circle on your answer sheet that best represents your point of view. Please choose from the following answers: After completing the _________(online, simulation, practicum) portion of the Critical Care  e-Learning Program please rate how certain you are that you can perform the following critical care skills: Rate your degree of confidence by recording a number from 0-100 using the scale below:   0      10    20  30 40 50 60 70 80 90 100 Cannot do at all Moderately can do Highly certain can do   Critical Care Skill Confidence (0-100) 1. Systematically interpret arrhythmias  2. Systematically interpret 12 Lead ECGs  3. Care for a mechanically ventilated patient  4. Interpret arterial blood gas results  5. Accurately calculate vasoactive infusions  6. Perform a cardiac output  7. Wedge a pulmonary artery catheter  8. Draw blood from an arterial line  9. Prioritize care in the critically ill patient  10. Manage a cardiac arrest    Survey administration specific timeframe instruction inclusion: Time 1: In relation to beginning work in the critical care unit or continuing work in this area, please relate the following questions to how you feel about the following: 177  Time 2: After completing the online components of the critical care e-learning program, please complete the following in relation to how you feel about approaching the competencies and skills required to work in the critical care area.  Time 3: After completing the simulation component of the critical care e-learning program, please complete the following in relation to how you feel about approaching the competencies and skills required to work in the critical care area. Time 4: After completing the practicum component of the critical care e-learning program or by working in the critical care environment, please complete the following in relation to how you feel about approaching the competencies and skills required to work in the critical care area.    178  Appendix M: Intent to Stay (Adapted from Kim, Price, Mueller and Watson, 1996)  Listed below are statements that represent possible opinions that YOU may have about your intention to stay in your current position, your hospital or the nursing profession. Please indicate the answer that best represents your viewpoint.  My current job position: 1) I would like to leave the unit I work in. 2) I plan to leave the unit I work in as soon as possible 3) I plan to stay in the unit I work in as long as possible 4) Under no circumstances will I leave the unit I work in.  My employer: 1) I would like to leave my present employer 2) I plan to leave my present employer as soon as possible 3) I plan to stay with my present employer as long as possible 4) Under no circumstances will I leave my present employer  The nursing profession: 1) I would like to leave the nursing profession. 2) I plan to leave the nursing profession as soon as possible. 3) I plan to stay in the nursing profession as long as possible 4) Under no circumstances will I leave the nursing profession.    179  Appendix N: POS Scale (short version) Format for the 8-item Survey of POS © University of Delaware, 1984. Listed below are statements that represent possible opinions that YOU may have about working at _____. Please indicate the degree of your agreement or disagreement with each statement by filling in the circle on your answer sheet that best represents your point of view about ____. (R) Indicates a reverse-keyed item (scoring is reversed). Please choose from the following answers:  Strongly disagree Moderately Disagree Disagree slightly Neither disagree nor agree Slightly Agree Moderately agree Strongly agree 0 1 2 3 4 5 6   1. The organization values my contribution to its well-being. 3. The organization fails to appreciate any extra effort from me. (R) 7. The organization would ignore any complaint from me. (R) 9. The organization really cares about my well-being. 17. Even if I did the best job possible, the organization would fail to notice. (R) 21. The organization cares about my general satisfaction at work. 23. The organization shows very little concern for me. (R) 27. The organization takes pride in my accomplishments at work    180  Appendix O:  Additional Description of Sample at Time 1 Characteristic Treatment Group (n=182) Comparison Group (n=181)  f (%) f (%) Who paid tuition for critical care program?      Hospital  82(45) ---    Self    57(31.3) ---    RNAO 12(6.6) ---    New Graduate Initiative   2(1.1) ---    Other 1(.5)     --- Type of Critical Care Unit  Worked In      Medical/surgical     124(68.1)    147(81.2)    CVICU/CCU 15(8.2)  19(10.5) Job Title    Staff Nurse    Educator    Manager  179     2   1  180     1     0    M (SD) M (SD) How long employed as an RN?(yrs) 3.6(5.4)    20.8(10.1) How long in current position? (yrs)  1.5(2.8) 13.7(9.4) How long in critical care?(yrs)  .8(3.0) 15.7(9.7) Note. RNAO= Registered Nursing Association of Ontario, CVICU= cardiovascular intensive care unit, CCU= coronary care unit.     181  Appendix P: Group Differences Time 1 and Time 4 Group Differences for Major Study Variables at Time 1  Treatment Group n=182 Comparison Group n=181 M differences    Variables M(SD) M(SD)  df t Eta squared  POS     33.1(8.2)    29.6(11.2)  3.5  357     -3.4***  .03  WE    53.1(10.2)    50.3(12.2)  2.8  361   -2.4*  .02  GSE    30.2(3.2)     32.4(4.2)  2.2  357     5.8***  .09  CCSE          681.9(199.4)          907.4(103.7)  225.5  257     9.8***  .21  ITS-org    11.0(2.9)     12.1(3.4)  1.1  357     3.3***  .03  ITS-unit    10.6(3.5)     12.1(3.1)   1.5  357     4.4***  .11  ITS-prof   13.2(2.1)    13.6(2.4)  .4  357  1.3  .00 Note. POS= Perceived Organizational Support, WE= work environment, GSE= General Self-efficacy, ITS-org= Intent to Stay in the organization, ITS-unit= Intent to Stay in the unit, ITS-prof= Intent to Stay in the profession.                                                                                                                                                                          *p<.05, **p<.01, ***p<.001. Group Differences for Major Study Variables at Time 4  Treatment Group n=65 Comparison Group n=73 M differences    Variables M(SD) M(SD)  df t Eta squared  POS       32.7(4.9)      27.7(7.9)  5.0  136     -4.4**  .12  WE       53.8(9.4)     48.1(11.5)  5.7  139  -3.1***  .07  CCSE  800.2(116.5)  869.4(113.3)  69.2  139      3.9***  .10  ITS-org       10.8(3.9)       10.3(4.5)  .5  139       -.7  .00  ITS-unit      11.2(3.9)        9.7(3.6)  1.5  139     -2.5*  .04  ITS-prof      12.1(3.5)       9.4(2.7)  2.7  138   -5.3***  .17 Note. POS= Perceived Organizational Support, WE= work environment, ITS-org= Intent to Stay in the organization, ITS-unit= Intent to Stay in the unit, ITS-prof= Intent to Stay in the profession.                                                                                                                                                                          *p<.05, **p<.01, ***p<.001.  182  Appendix Q: Differences within Comparison and Treatment Group  Descriptive Statistics for Repeated Measures at Time 1 and Time 4 Comparison Group  Time 1 n=181 Time 4 n=73 M differences p value Partial Eta Squared  M(SD) M(SD)    POS   30.7 (1.3) 27.7 (.9)  -3.0 .01 .08 WE 52.2(1.4) 48.2(1.4)   4.0 .04 .06 CCSE* 907.36 (103.7) 891.1 (111.2)  16.26 n.s. .00 ITSorg    11.9(3.1) 10.3(3.1)         -1.6 .01 .13 ITSunit 12.1(3.1) 9.7(3.6)         -2.4 .001 .24 ITSprof 13.6(2.2) 9.4(2.7)         -4.2 .001 .56  Note. POS= Perceived Organizational Support, WE=work environment, CCSE= Critical Care Self-efficacy, ITS-org= Intent to Stay in the organization, ITS- unit= Intent to Stay in the unit, ITS-prof= Intent to Stay in the Profession. Time 1 n=182, Time 4 n=65, n=39 CCSE, n.s.= not significant  Descriptive Statistics for Repeated Measures at Time 1 and Time 4 Treatment Group  Time 1 n=181 Time 4 n=73 M differences p value Eta squared  M(SD) M(SD)    POS 33.1(8.2) 32.7(4.9) -.4 n.s. .01 WE 54.4(10.2) 53.8(9.4) -.6 n.s. .01 CCSE 704.2(216.9) 818.2(105.1)  114.0 .001 .18 ITSorg 11.2(2.9) 10.8(3.9) -.4 n.s. .01 ITSunit 10.4(3.4) 11.2(3.9) .8 ns .02 ITSprof 13.5(2.1) 12.2(3.5)        -.7 .01 .10  Note. POS= Perceived Organizational Support, WE=work environment, CCSE= Critical Care Self-efficacy,      ITS-org= Intent to Stay in the organization, ITS- unit= Intent to Stay in the unit, ITS-prof= Intent to Stay in the Profession. Time 1 n=182, Time 4 n=65, n.s.= not significant     

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