CANADIAN NURSING LABOUR FORCE: EXAMINING THE RELATIONSHIP BETWEEN JOB DISSATISFACTION, NURSE DISSATISFACTION AND INTENT TO QUIT

by

Anshoo Kamal

A thesis submitted in conformity with the requirements for the degree of Master of Science Department of Health Policy, Management and Evaluation University of Toronto

© Copyright by Anshoo Kamal 2011

Final

Canadian Nursing Labour Force: Examining the Relationship between Job Dissatisfaction, Nurse Dissatisfaction and Intent to Quit Anshoo Kamal Master of Science Department of Health Policy, Management and Evaluation University of Toronto 2011

Abstract Canada is challenged with a perceived nursing shortage. Better understanding of the factors that influence satisfaction and turnover may help to formulate improved strategies for retention of the nursing workforce. Our analysis revealed that satisfaction levels in both the job and the nursing profession are high in the Canadian nursing workforce corresponding to relatively high retention rates in the workforce. We found that dissatisfaction with the job and nursing are distinct concepts that are intrinsically associated. Dissatisfaction in the job significantly increased the likelihood of dissatisfaction with being a nurse and vice versa for RNs. Also, nurses were more likely to express intentions to switch jobs than intentions to leave nursing. Job dissatisfaction was the strongest predictor for both the intentions to leave nursing and switch jobs. The findings suggest that targeting both the job structures and the profession‟s role would help to maintain and improve retention rates for nurses.

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Acknowledgments I extend my sincere gratitude and appreciation to my supervisors, Dr. Audrey Laporte and Dr. Raisa Deber, for providing me with their guidance and support, along with the benefit of their knowledge and expertise in their respective fields. They have provided me with an extremely valuable learning experience that I will carry with me into the future. I would also like to thank my committee member, Dr. Andrea Bauman, for sharing her knowledge in health human resources and nursing. I also extend a thank you to Dr. Frieda Daniels for her collaboration in managing the National Survey Work and Health of Nurses (NSWHN). I would like to acknowledge the Toronto Region Statistics Canada Research Data Centre (Toronto RDC) at the University of Toronto for facilitating access to the NSWHN survey. Finally, I would like to thank my family for their patience, encouragement and support throughout, especially my mother, Shakti Kamal.

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Contents Acknowledgments ................................................................................................ iii Chapter 1 Introduction ........................................................................................... 1 Chapter 2 Theoretical Framework .......................................................................... 4 2.1

Income-Leisure Model Applied to Nursing ...................................................................4

2.2

Job Search Theory Applied to Nursing ..........................................................................6

2.3

Individual and Work Factors Influencing Income-Leisure Trade-Off.............................7

2.4

Outcome Measures ...................................................................................................... 12

2.5

Theoretical Frameworks for Job Satisfaction, Nurse Satisfaction and Intent-to-Quit .... 13

Chapter 3 Literature Findings ...............................................................................15 3.1

Overview .................................................................................................................... 15

3.2

Outcome Variables ...................................................................................................... 16

3.3

Explanatory Variables ................................................................................................. 18

3.4

Significance of this Project .......................................................................................... 28

Chapter 4 Data Source, Variables and Methods ....................................................30 4.1

Data Source ................................................................................................................ 30

4.2

Survey Sample Population, Timelines and Weighting ................................................. 30

4.3

Creating the Regulated and Employed Nurses Sample for the Project.......................... 31

4.4

Missing/Non-Responses .............................................................................................. 31

4.5

Limitations .................................................................................................................. 33

4.6

Coding Outcome Variables ......................................................................................... 35

4.7

Coding Explanatory Variables ..................................................................................... 38

4.8

Descriptive Results ..................................................................................................... 50

4.9

Model Methodology.................................................................................................... 50

4.10

Marginal Effects ......................................................................................................... 51

4.11

Two Step Simultaneous Equation Probit Model: Job and Nurse Dissatisfaction:.......... 51

4.12

Binary Probit Model for LPNs Job Dissatisfaction ...................................................... 57

4.13

Multinomial Probit Model - Intent-to Quit Model........................................................ 58

4.14

Sensitivity Analysis..................................................................................................... 60

Chapter 5 Descriptive Results ...............................................................................64 5.1

Descriptive Results for Explanatory Variables by RNs and LPNs ................................ 64

5.2

Descriptive Results for Outcome Variables by RNs and LPNs .................................... 70

5.3

Descriptive Results for Outcome Variables by Key Explanatory Variables.................. 72

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5.4 Descriptive Results for Relationship between Job/Nurse Dissatisfaction and Intent to Quit for RNs and LPNs .......................................................................................................... 78

Chapter 6 Job and Nurse Dissatisfaction Model Results for RNs ..........................81 6.1

Results from Threshold Analysis ................................................................................. 81

6.2

Job Dissatisfaction Results .......................................................................................... 82

6.3

Nurse Dissatisfaction Results ...................................................................................... 87

Chapter 7 Job Dissatisfaction Model Results for LPNs .........................................91 7.1

Job Dissatisfaction Results for LPNs ........................................................................... 91

Chapter 8 Intent to Quit Model Results for RNs and LPNs ...................................97 8.1

Intent-to-Leave Nursing .............................................................................................. 98

8.2

Intent-to-Switch Jobs ................................................................................................ 105

8.3

At Risk...................................................................................................................... 113

Chapter 9 Discussion and Conclusion .................................................................119 9.1

Job and Nurse Dissatisfaction.................................................................................... 119

9.2

Determinants of Job and Nurse Dissatisfaction .......................................................... 120

9.3

Factors that Influence Nurse Dissatisfaction .............................................................. 120

9.4

Factors that Influence Job Dissatisfaction .................................................................. 121

9.5

Intent to Quit ............................................................................................................. 122

9.6

Factors that Influence Intentions to Quit .................................................................... 123

9.7

Conclusion ................................................................................................................ 125

Appendices .........................................................................................................128 References ..........................................................................................................167

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Table List Table 1: Correlation between Variables for RNs and LPNs ....................................................... 39 Table 2: Age and Sex ................................................................................................................ 40 Table 3: Marital Status, Children, Health Status and Household Income.................................... 41 Table 4: Number of Jobs and Held a Non-Nursing Job .............................................................. 42 Table 5: Education Variables..................................................................................................... 43 Table 6: Work Characteristics ................................................................................................... 43 Table 7: Work Sector Variable .................................................................................................. 45 Table 8: Shift Type, Number of Shift Changes and Usual Shift Hours ....................................... 46 Table 9: Area of Responsibility ................................................................................................. 47 Table 10: Full-Time/Part-Time/Casual Status ............................................................................ 48 Table 11: Job Dissatisfaction Structural Equation Model ........................................................... 54 Table 12: Nurse Dissatisfaction Structural Equation Model ....................................................... 56 Table 13: Categorical Variable Imputations for RNs and LPNs ................................................. 61 Table 14: Continuous Variable Imputations for RNs and LPNs ................................................. 61 Table 15: Average Values for the Score Variables for RNs and LPNs ....................................... 70 Table 16: Job and Nurse Dissatisfaction for Registered Nurses.................................................. 78 Table 17: Predicted Dissatisfaction Values at the 50th and 90th Percentiles for RNs ................... 81 Table 18: Actual vs. Predicted Job Dissatisfaction at the 0.20 Threshold ................................... 82 Table 19: Actual vs. Predicted Nurse Dissatisfaction at the 0.20 Threshold ............................... 82 Table 20: Significant Explanatory Variables Influencing Job Dissatisfaction for RNs ............... 83 Table 21: Significant Explanatory Variables that Influence Nurse Dissatisfaction for RNs ........ 88 Table 22: Explanatory Variables Significant in Predicting Job Dissatisfaction for LPNs............ 92 Table 23: Explanatory Variables Significantly Influencing Intent-to-Leave Nursing for RNs .... 99 Table 24: Explanatory Variables Significantly Influencing Intent-to-Leave Nursing for LPNs... 99 Table 25: Explanatory Variables Significant in Influencing Intent to Switch Jobs for RNs ...... 105 Table 26: Explanatory Variables Significant in Influencing Intent to Switch Jobs for LPNs .... 106 Table 27: Explanatory Variable Significantly Influencing at Risk of Leaving the Job and/or Nursing for RNs ...................................................................................................................... 113 Table 28: Explanatory Variable Significantly Influencing at Risk of Leaving the Job and/or Nursing for LPNs .................................................................................................................... 114

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Figure List Figure 1: Labour Supply Curve ...................................................................................................5 Figure 2: Job and Nurse Dissatisfaction ..................................................................................... 13 Figure 3: Intent to Quit .............................................................................................................. 14 Figure 4: Deriving the Intent-to-Quit Variable ........................................................................... 37 Figure 5: Age Distribution for RNs and LPNs ........................................................................... 64 Figure 6: Marital Status by RNs and LPNs ................................................................................ 65 Figure 7: Health Status by RNs and LPNs ................................................................................. 66 Figure 8: Household Income by RNs and LPNs......................................................................... 66 Figure 9: Work Sector by RNs and LPNs .................................................................................. 67 Figure 10: Full-Time, Part-Time, Casual Distribution for RNs and LPNs .................................. 68 Figure 11: Shift Type by RNs and LPNs ................................................................................... 69 Figure 12: Job Satisfaction by RNs and LPNs ........................................................................... 70 Figure 13: Nurse Satisfaction by RNs and LPNs ....................................................................... 71 Figure 14: Intent to Quit by RNs and LPNs ............................................................................... 71 Figure 15: Job Dissatisfaction by Age Cohorts for LPNs ........................................................... 72 Figure 16: Job Dissatisfaction by Age Cohorts for RNs ............................................................. 73 Figure 17: Intent to Quit by Age Cohorts for LPNs ................................................................... 74 Figure 18: Intent to Quit by Age Cohorts for RNs ..................................................................... 74 Figure 19: Job Dissatisfaction by Work Sector for LPNs ........................................................... 75 Figure 20: Job Dissatisfaction by Work Sector for RNs ............................................................. 75 Figure 21: Intent to Quit by Full-Time, Part-Time, Casual Status for LPNs ............................... 77 Figure 22: Intent to Quit by Full-Time, Part-Time, Casual Status for RNs ................................. 77 Figure 23: Intentions to Quit by Job Dissatisfaction for RNs ..................................................... 79 Figure 24: Intentions to Quit by Job Dissatisfaction for LPNs ................................................... 79

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Appendices Appendix 1: Descriptive Differences between RNs and LPNs by Explanatory Variables ........ 128 Appendix 2: Descriptive Differences between RNs and LPNs by Outcome Variables ............ 129 Appendix 3: Descriptive Differences in Key Variables by Job Dissatisfaction for LPNs ......... 129 Appendix 4: Descriptive Differences in Key Variables by Nurse Dissatisfaction for LPNs ..... 130 Appendix 5: Descriptive Differences in Key Variables by Intent to Quit for LPNs ................. 130 Appendix 6: Descriptive Differences in Key Explanatory Variables by Job Dissatisfaction for RNs......................................................................................................................................... 131 Appendix 7: Descriptive Differences in Key Explanatory Variables by Nurse Dissatisfaction for RNs......................................................................................................................................... 131 Appendix 8: Descriptive Differences in Key Explanatory Variables by Intent to Quit for RNs132 Appendix 9: Intent to Quit Model – Registered Nurse Coefficient Estimates .......................... 133 Appendix 10: Intent to Quit Model – Registered Nurses Average Marginal Effect ................. 138 Appendix 11: Intent to Quit Model – Licensed Practical Nurses Coefficient Estimates ........... 143 Appendix 12: Intent to Quit Model – Licensed Practical Nurses Average Marginal Effects .... 148 Appendix 13: Intent to Quit Model for RNs with Limited Variables ....................................... 154 Appendix 14: Job Dissatisfaction RN Results at 0.20 Threshold ............................................. 157 Appendix 15: Job Dissatisfaction for RNs Average Marginal Effects at the 0.20 Threshold .... 158 Appendix 16: Nurse Dissatisfaction Results for RNs 0.20 Threshold ...................................... 159 Appendix 17: Nurse Dissatisfaction Average Marginal Effects for RNs 0.20 Threshold ......... 160 Appendix 18: Nurse Dissatisfaction Results for RNs at the 0.50 Threshold ............................ 162 Appendix 19: Job Dissatisfaction Model for RNs at the 0.50 Threshold ................................. 163 Appendix 20: Job Dissatisfaction Results for LPNs ................................................................ 164 Appendix 21: Job Dissatisfaction for LPNs Average Marginal Effects ................................... 165

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Chapter 1 Introduction Health care is a labour-intensive industry and the single-largest health care professional group within it is nurses (inclusive of all nursing classes). There were 332,794 nurses in Canada in 2007 (Canadian Institute for Health Information, 2008). In Canada, nursing is a self-regulated profession with controlled acts set by each province and territory (Canadian Nursing Association, 2007). In each province and territory, the self-regulating nursing profession sets entry-to-practice requirements, determines who achieves licensure and assures public safety (Canadian Nursing Association, 2007). There are two primary groups of regulated nurses in Canada called registered nurses (RNs) and licensed practical nurses (registered practical nurses in Ontario) (LPNs). Each class of nurses has its own entry to practice requirements and scope of practice, as set by the regulatory body. Further, registered nurses can also specialize to develop specific competencies ranging from community nursing to emergency nursing (Canadian Nursing Association, 2007). Nursing is a female-dominated workforce (more than 90% are female in Canada), who are also getting older with an average age of 45 in 2007 (Canadian Institute for Health Information, 2008). Nurses, generally, work at the front lines of patient care and research indicates that they have a significant positive impact on patients, including improved patient outcomes and satisfaction (Shannon & French, 2005) (A. Tourangeau, Doran, Pringle, & et al, 2006). Therefore, as factors such as advances in medical technology and population aging lead to increased health care utilization, the demand for the nursing workforce will also increase at a time when experts state that retirement rates among nurses will also grow (Pyper, Winter 2004; Pyper, Winter 2004; Simoens, Villeneuve, & Hurst, 2005; Zigmond, 2008; Zigmond, 2008) These trends have contributed to a perceived nursing shortage in Canada and globally. The Canadian Nurse Advisory Committee (2002) indicated a possible shortage of 16,000 nurses in the early 2000s (Canadian Nursing Advisory Committee, 2002). Similarly, the Organization for the Economic Co-operation and Development (OECD) (2005) indicated that there were nurse shortages in almost all OECD countries (Simoens et al., 2005) and the World Health

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Organization in 2006 estimated that 57 countries across the world have a critical shortage of nurses (World Health Organization, 2006). Therefore, a perceived nursing shortage is not only a Canadian issue but also potentially a global issue with multiple countries considering how to recruit more nurses and retain their existing workforce. The perceived nursing shortage can be attributed to multiple factors, including human resources management issues such as heavy workloads and limited full-time opportunities (Canadian Nursing Advisory Committee, 2002; Simoens et al., 2005). Further, Canadian researchers found that the restructuring of hospitals in the 90s to control costs negatively affected the nursing workforce, which resulted in lower nurse autonomy, patient focus, patient satisfaction, higher costs, more hours per patient day, lower morale and job satisfaction (Canadian Nursing Advisory Committee, 2002; Shannon & French, 2005; Simoens et al., 2005). Policy levers to address the perceived shortage include reducing exits from the workforce; thereby, improving rates of retention (Canadian Nursing Advisory Committee, 2002; Simoens et al., 2005). This project will examine the nursing workforce, with a focus on RNs and LPNs employed in Canada, to determine the factors that would be associated with turnover intentions within the nursing workforce at the job (intentions to leave a particular job within nursing without leaving the profession) and at the market level (intentions to leave the profession). By investigating and identifying the factors that could influence a nurse‟s decision to change jobs or leave the workforce, this project could help to inform policy decisions that would help to address the perceived nursing shortage through improved retention at the job and market level. To examine turnover intentions in the nursing workforce, we will investigate three concepts as outcomes: Job Dissatisfaction: A nurse‟s stated level of dissatisfaction, inverse of satisfaction, with the specific job. Nurse Dissatisfaction: A nurse‟s stated level of dissatisfaction, inverse of satisfaction, with the profession (i.e. being a nurse) independent of the job. Intent to Quit: A nurse‟s intentions toward a future labour force decision based on the following alternative sub-options: stay in nursing, leave nursing, switch jobs and being at risk of leaving.

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The project will address the following questions: 1) What is the nature of the relationship, if any, between a nurse‟s satisfaction in the main job (referred to as job dissatisfaction) and independently in the profession (referred to as nurse dissatisfaction)? 2) Are there specific individual and work factors that influence satisfaction with the job and the profession? Are there differences between the two concepts? 3) Which individual and work factors, including satisfaction with the job and the profession, influence intentions to quit for nurses? a. Is there a difference between intentions to quit the nursing workforce and intentions to switch jobs?

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Chapter 2 Theoretical Framework This chapter outlines the theoretical framework, derived from the income-leisure model and differential wage theory from labour economics, supporting the foundation of this project. There has been a substantial amount of nursing research, qualitative and quantitative, examining the role of job satisfaction in nursing. This framework will provide a useful context to understand the factors that have been identified in both the nursing and economics literature. Specifically, we will outline and define the different concepts in the framework and apply them to the nursing profession and the three outcome variables: job dissatisfaction, nurse dissatisfaction and intent to quit.

2.1 Income-Leisure Model Applied to Nursing The income-leisure model from labour economics provides the theoretical framework for the study of the relationship between job dissatisfaction, nurse dissatisfaction and the nurse‟s decision to work or not to work in a given job or the profession. As noted in Chapter 1 (Introduction), job dissatisfaction is the nurse‟s level of dissatisfaction with the main job and nurse dissatisfaction is the level of dissatisfaction with the profession independent of the job. Theoretically, when choosing to provide labour, individuals face a trade-off between earning income and having leisure time given their market opportunities (i.e. the value of any foregone opportunities such as other jobs) and the opportunity cost of non-labour time (e.g. the value of child care) . Income represents the compensation individuals receive for providing their labour in lieu of leisure time (Benjamin et al., 1998; Killingsworth, 1983). In contemporary economics, income includes pecuniary benefits (i.e. pay) and non-pecuniary benefits, including health benefits, childcare support, flexible work hours, autonomy, job safety, etc. (Benjamin et al., 1998; Buhr, 2009; Killingsworth, 1983; Le'vy-Garboua, Montmarquette, & Simonnet, 2007). The term leisure encompasses all production activities that are not in the formal labour market (paid-for) sense, such as household chores, caring for dependants, including children or other family members, obtaining education, participating in charitable activities and leisure (Benjamin et al., 1998; Killingsworth, 1983). Within this framework, individuals must choose to work or

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not to work, as well as choose where to work based on their specific preferences and tastes (Benjamin et al., 1998; Killingsworth, 1983; Le'vy-Garboua et al., 2007). The optimal combination of income and leisure for individuals will differ based on their own preferences, the valuation of the opportunities for compensation and leisure available to them and their budget constraints (Benjamin et al., 1998; Killingsworth, 1983). The budget constraint represents the income available to an individual that can be allocated across a variety of goods and services (Killingsworth, 1983). Under these conditions, individuals will choose whether to work, and if they choose to work, where to work to maximize their utility given their budget constraint. The model postulates that rational utility-maximizing individuals will aim to achieve their optimal point (i.e. combination between time in income-earning and leisure activities) on their highest achievable indifference curve where they would be indifferent to more income or more leisure (Benjamin et al., 1998; Killingsworth, 1983). Figure 1: Labour Supply Curve

This would be the individual‟s “reservation wage” or if expanded further the “reservation compensatory bundle of pay and non-pecuniary benefits” (Benjamin et al., 1998) at which the individual would choose to work. These preferences and valuation may be influenced by the individual‟s sex (e.g. women tend to have more household and childcare responsibilities) and age

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(e.g. older individuals near retirement) (Benjamin et al., 1998; Killingsworth, 1983), required level of education (Becker, 1975), among other characteristics. For example, Killingsworth (1983) expands on the above basic labour-supply economic model to consider the impact of family budget constraints on an individual‟s utility. Although individuals have their own preferences for benefits, they are usually part of a family unit that pools their consumption and earnings (Killingsworth, 1983). Therefore, household income will have an indirect influence on the individual‟s preference for income and leisure and their maximum utility point (Killingsworth, 1983). Further, some professions have entry to practice requirements (e.g. a required level of education to enter and practice in the profession) for individuals that are imposed by markets via legislation (Becker, 1975). This creates a minimum standard required by an individual before entering a profession thereby, increasing the individual‟s required investment into human capital (Becker, 1975). The minimum required investment may then influence an individual to have a greater “reservation bundle” to recoup that investment. However, it may also increase the opportunity cost of leaving the profession. The basic utility framework assumes that individual utility is a function of previous, current and future work-related income, other income, leisure and tastes and preferences, which the individual will seek to maximize given the budget constraint (Benjamin et al., 1998; Killingsworth, 1983; Le'vy-Garboua et al., 2007). Numerous factors can influence individuals‟ optimal points at which they maximize their utility from the working and not-working trade-off and where they work at any point in time. These factors include:  their expected compensatory bundle (i.e. pecuniary and non-pecuniary benefits) to work,  their opportunity cost of other market opportunities and/or not-working activities,  disutility-inducing job or profession characteristics (e.g. risk of injury, stress), and/or  latent tastes and preferences unique to individuals.

2.2 Job Search Theory Applied to Nursing As noted above, the decision to work or not also includes the decision of where to work or not to work. Job search theory explains that an individual will decide to switch jobs if the expected

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utility from the alternative job is greater than the utility from the current job, minus the cost of moving to a new job (Buhr, 2009) (Le'vy-Garboua et al., 2007). This is referred to as the opportunity cost of other market opportunities. The cost of moving to a new job will be influenced by individual characteristics such as age, number of children, education level, marital status and spousal earnings because these influence the individual‟s mobility, preferences and tastes and the market opportunities available to the individual (Buhr, 2009). In the valuation of the alternative job, the individual would rationally expect that the pecuniary and non-pecuniary compensation is greater than the current job both in the current and future state (Buhr, 2009; Le'vy-Garboua et al., 2007).

2.3 Individual and Work Factors Influencing Income-Leisure Trade-Off The following section will briefly address the theoretical concepts that illustrate the basis by which some of the primary characteristics would be expected to influence labour force decisions. The influencing characteristics can be categorized into two groups: individual-based or workbased.

2.3.1

Individual Characteristics

There are multiple factors, some observable and some not, that can influence an individual‟s valuation of the “reservation compensatory bundle” and the opportunity cost of non-work related activities. A few of the key individual characteristics include demographics, education and observable or unobservable preferences (e.g. work hours) that may influence utility derived from the job and/or the profession and therefore, the intent to quit decision.

2.3.1.1

Demographics

Males and females may have different preferences based on their trade-off between income and leisure (Benjamin et al., 1998; Killingsworth, 1983; Le'vy-Garboua et al., 2007). For females, having and caring for children is an activity that the leisure equation must account for, perhaps to a different degree than for males. The cost of delaying childbirth or purchasing childcare increases the opportunity cost of choosing to participate in the labour force (Benjamin et al., 1998; Killingsworth, 1983). Age is another factor that may change an individual‟s preferences

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when choosing between income and leisure (Benjamin et al., 1998; Frijters, Shields, & Price, 2007; Killingsworth, 1983; M. A. Shields & Ward, 2001a). For instance, labour force participation for females appears to peak at 35-44 and declines steeply after age 55 (Benjamin et al., 1998; Killingsworth, 1983). Furthermore, older individuals may have acquired extensive specialized human capital in their job and/or profession; they may perceive a greater cost to seeking other market opportunities (Benjamin et al., 1998; Killingsworth, 1983). In addition, the rise of two-earner families would suggest that the presence of another earner in the household lowers the opportunity cost to the individual of forgoing income (Benjamin et al., 1998; Killingsworth, 1983) or switching jobs. For example, an individual with a high earning spouse may be less likely to participate in the labour force or more likely to work reduced hours or be more willing to take a chance on another job (Benjamin et al., 1998; Killingsworth, 1983; M. A. Shields & Ward, 2001a).

2.3.1.2

Level of Education and Investment into Profession – Human Capital Theory

The concept of human capital refers to the investment on the part of individuals in their stock of knowledge and education to increase their own level of skill, and by extension their productivity (Benjamin et al., 1998) (Becker, 1975; Killingsworth, 1983) (Nowak & Preston, 2001). Individuals may invest and acquire human capital through completion of institutional programs (e.g. university degrees, college diplomas, etc.), specific job-related training, general training and/or informal learning by doing (Becker, 1975; Killingsworth, 1983). Individuals generally invest in their human capital at younger ages or earlier in their careers to maximize their rate of return over their work-life (Becker, 1975; Benjamin et al., 1998; Killingsworth, 1983). Formal education investments and returns are usually borne by individuals; however, individuals and employers generally share the cost and returns of on-the-job training (Becker, 1975; Killingsworth, 1983). Acquiring human capital through investing in formal education represents costs to the individual in the form of time, tuition and books, and the opportunity cost of forgone labour-related income and leisure time (Becker, 1975; Benjamin et al., 1998; Nowak & Preston, 2001). Therefore, individuals will expect to recoup human capital investments in the form of higher earnings and better opportunities in the labour force (Becker, 1975; Benjamin et al., 1998; Nowak & Preston,

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2001). Investment in education also increases the value of that individual to the industry specifically, when it leads to specialized skills that are not in abundance of supply (Becker, 1975; Benjamin et al., 1998). Thereby, individuals with higher levels of human capital (through investment in education and training) tend to have better and more market opportunities. Human capital may also be developed through on-the-job training, that is, investing one‟s time into a specific job, profession and/or industry by developing specialized skills or experience (Benjamin et al., 1998)(Becker, 1975)(Nowak & Preston, 2001). Firms may choose to provide new employees with job specific skills, knowledge and experience to enhance their productivity and knowledge in that specialized area (Becker, 1975; Benjamin et al., 1998). Firms recoup their cost of offering such training through higher productivity gains while individuals obtain a return through not only accessing training that they otherwise would not have, but also earning greater compensation over time (Becker, 1975). Firms may also offer lower pay but provide greater training to workers, thereby compensating individuals for the lower pay and recouping their costs (Killingsworth, 1983). This type of training is often measured empirically through an individual‟s age or years in the labour force (Benjamin et al., 1998; Killingsworth, 1983; Nowak & Preston, 2001). Higher levels of job or occupation-specific training increase the cost of turnover for both firms and individuals (Becker, 1975). New workers in a firm or industry may not be as productive relative to experienced workers. Therefore, employers will want to avoid turnover to avoid high costs associated with training and lower productivity in the early stages of employment. For individuals, specialized skills (and the absence of more general skills) may limit their ability to move to other employment because their skills are not easily transferable (Becker, 1975) leading them to face higher costs of switching jobs or occupations. As such, human capital through education, training and experience may influence both the expected compensation level and the opportunity cost of other opportunities.

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2.3.1.3

Preference in work hours

At the market wage (plus benefits) rate, an individual may prefer to work more or fewer hours based on their individual indifference curve (Benjamin et al., 1998; Killingsworth, 1983; M. A. Shields & Ward, 2001a). The individual may prefer to work more hours at the current compensation level but may face a limit on the work hours set by the firm therefore, would be under-employed (Benjamin et al., 1998; Killingsworth, 1983). For example, nurses working part-time who prefer full-time work at the current job at the current level of compensation would be under-employed. These individuals may choose to switch to another job to maximize their utility due to less constrained work hours offered by another job or to work for more than one employer simultaneously (Benjamin et al., 1998; Killingsworth, 1983). Holding all things equal, individuals may also prefer to work fewer hours due to the higher opportunity cost of forgone leisure activities or other production activities (Benjamin et al., 1998; Killingsworth, 1983; M. A. Shields & Ward, 2001a). Therefore, for some individuals flexible work hours or opportunities to work part-time will achieve utility maximization given their trade-off choice between income and leisure (Benjamin et al., 1998; Killingsworth, 1983).

2.3.2

Work Factors: Compensating Wages Differentials and Sector Differences Theory

Jobs, within and across industries, have different characteristics (e.g. work hours, organizational cultures) and compensatory bundles (e.g. higher pay combined with lower benefits) and these may influence the derived utility for employees, based on their own preferences. A misalignment between a job‟s characteristics and an individual‟s preferences may influence the individual‟s intent to quit decision at the job level; whereas, misalignment at the industry or profession level may (e.g. what a nurse could expect to earn more generally in across industries) influence intent to quit at the market level.

2.3.2.1

Theory of Compensating Wage Differentials

In an industry with multiple firms, firms may structure different compensation bundles based upon their own desirable or undesirable work conditions (Benjamin et al., 1998; Killingsworth, 1983). The theory of compensating wage differentials postulates that different sectors or firms will have varying work characteristics due to the nature of the work or culture (Benjamin et al.,

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1998; Killingsworth, 1983). A firm that requires individuals to work shifts (e.g. night shifts) may need to compensate individuals with higher pay, as that is considered to be an undesirable working condition (Benjamin et al., 1998; Holmas, 2002; Killingsworth, 1983). Likewise, firms that require individuals to work in high-risk conditions may offer higher pay to compensate employees for facing that risk (Benjamin et al., 1998; Killingsworth, 1983). Alternatively, a firm may offer flexible work schedules and health benefits but offer lower pay to the individual. To achieve equilibrium, individuals and firms will sort themselves according to their tastes and preferences, budget constraints and available compensating bundles (Benjamin et al., 1998; Buhr, 2009; Killingsworth, 1983; Le'vy-Garboua et al., 2007). For example, a risk-averse individual may choose to work in a job that offers safe working conditions but lower compensation. Within health care, hospital, long-term care and community health care settings are significantly different in their structure, ranging from private and publicly financed to a mix of not-for-profit, for-profit and public providers. Furthermore, the nature of work that nurses perform varies greatly among these sectors and within settings in the same organization (e.g. intensive care unit vs. paediatrics unit in a hospital), as does the level of compensation they receive (A. Baumann et al, 2001; A. Baumann et al, 2006; Cameron, Armstrong-Stassen, Bergeron, & Out, 2004). For example, nurses in homecare settings have to adapt to a greater degree of autonomy due to isolation compared to their counterparts working in hospitals (Cameron et al., 2004; Ellenbecker, 2004; Ellenbecker, 2004; Shaver & Lacey, 2003). On the other hand, nurses who work in hospital settings may be required to do more shift work but may be provided greater compensation (Cameron et al., 2004; Ellenbecker, 2004; Ellenbecker, 2004; Shaver & Lacey, 2003). Further, Tourangeau (2006) finds that within acute hospitals medical nurses reported lower job satisfaction than surgical nurses (A. Tourangeau et al., 2006), indicating that differences can occur within organizations. Thus, each sector or setting will have compensating differentials in response to their work structures and requirements, and individuals will evaluate the compensating differentials in relation to their individual tastes and preferences and budget constraints. Further, working in health care requires the nurse to take on a certain degree of risk (e.g. back injuries) and therefore, would require a level of compensation in return for facing this risk.

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2.3.2.2

Unionization

Unions may influence the compensation bundles and work structures of a firm or industry. Unions are organized labour groups with a mandate to improve the economic well-being of their members (Benjamin et al., 1998; Killingsworth, 1983). Unions may be organized by profession (e.g. a union for all nurses) or by industry/sector (e.g. hospital unions) (Benjamin et al., 1998; Killingsworth, 1983). Unionization influences the employment benefits of their members but also can influence the compensation of non-members. For example, for those within the same profession but working in a different industry, or for those within the same industry but working in a different sector (Benjamin et al., 1998; Killingsworth, 1983). Unions may also help to set industry standards such as basic safety conditions. Thus, unions may influence the utility the nurse derives from working in a particular job and in the profession because they affect the working conditions and compensation by impacting standards and compensation rates for industries.

2.4 Outcome Measures 2.4.1

Dissatisfaction and Intent-to-Quit Measures

The stated satisfaction in the job and the profession should represent that individual‟s assessment of: the current and prospective compensation from the same job and profession, the other market opportunities via other jobs (within the same profession) or another profession, and the opportunity costs of leaving current job and/or profession and continuing to choose to work (Benjamin et al., 1998; Killingsworth, 1983; Le'vy-Garboua et al., 2007; M. Shields & Wilkins, 2006)(M. A. Shields & Ward, 2001b). Satisfaction in both the job and the profession may be mutually dependent. The assessment of the job may influence the assessment of the profession and vice versa. Further, individual characteristics and latent tastes and preferences may influence this assessment along with the firm‟s working conditions and compensation structure (Benjamin et al., 1998; Killingsworth, 1983; Le'vy-Garboua et al., 2007). Satisfaction in the job and/or the profession may theoretically influence an individual‟s stated intentions to either stay or leave a particular job or the profession (Benjamin et al., 1998; Frijters et al., 2007; Killingsworth, 1983; M. Shields & Wilkins, 2006; M. A. Shields & Ward, 2001b).

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Intentions to quit should represent the individual‟s choice based on the subjective assessment about whether or not leaving the job or profession would increase their utility (Benjamin et al., 1998; Frijters et al., 2007; Killingsworth, 1983; Le'vy-Garboua et al., 2007; M. A. Shields & Ward, 2001b).

2.5 Theoretical Frameworks for Job Satisfaction, Nurse Satisfaction and Intent-to-Quit The frameworks outlined below were derived from the concept that differences in individual characteristics and specific work characteristics may influence an individual‟s utility from the job and the profession and the individual‟s intentions to quit. The explanatory variables were selected based on their theoretical and empirical importance, as described in this chapter and Chapter 3 (Literature Review). Figure 2: Job and Nurse Dissatisfaction

Individual Characteristics (age, sex, marital status, level of education, household income)

Work Characteristics (provinces/territories, union status, shift type, hours and burden, FT/PT/Casual, choice in schedules, area of responsibility, role overload, job strain, job insecurity, skill discretion)

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Job Dissatisfaction

Nurse Dissatisfaction

Individual Characteristics (age, sex, marital status, have children by age, health status, level of education, non-nursing education, have a nonnursing job)

Work Characteristics (sector, provinces/territories, social support, decision authority)

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Figure 3: Intent to Quit Individual Characteristics (age, sex, have children by age, marital status, household income, health status, level of education in nursing, non nursing education)

Stay

Work Characteristics (sector, province/territory, union status, shift type, hours and burden, FT/PT/Casual, choice in schedules, area of responsibility, role overload, job strain, job insecurity, skill discretion, decision authority, social support)

Switch Jobs

Intent to Quit Leave

At Risk

Job Dissatisfaction Nurse Dissatisfaction

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Chapter 3 Literature Findings This chapter outlines the findings in the reviewed literature to date on the outcomes: job satisfaction, nurse satisfaction and intent to quit. The findings highlight the key explanatory variables that influence one or more of the outcomes. Further, the literature tends to support the importance of job satisfaction on intentions to quit and suggests that intentions to quit are significant in influencing actual quitting behavior.

3.1 Overview A number of empirical studies from various disciplines (e.g. nursing, economics, and health administration) analyze key predictors of and relationships between job satisfaction, nurse satisfaction and intentions to quit the job or the profession for nurses. The studies could be categorized into four groups: job and/or nurse satisfaction, intentions to quit the organization or the labour force, predicting actual exit behaviour and identifying reasons for leaving. The studies on satisfaction with the job and/or the profession were primarily based on cross-sectional survey data from the USA and Ontario and used linear regression analysis (Ingersoll & et al, 2002; H. Laschinger, 2001; Leveck, 1996; Leveck, 1996; Nogueras, 2006; M. A. Shields & Ward, 2001b; I. Zeytinoglu, Denton, & Davies, 2007). We identified five major studies that examined intentions to quit or remain employed. Of them, two were from the UK and the USA and used a probit regression analysis on cross-sectional data to examine predictors of intentions to quit (C. S. Brewer et al., 2006; M. A. Shields & Ward, 2001b). The remaining four were from Canada (including two which were Ontario-based) utilizing cross-sectional survey data and linear regression approaches (H. K. S. Laschinger, Leiter, Day, & Gilin, 2009; A. E. Tourangeau & Cranley, 2006; I. Zeytinoglu et al., 2007; I. Zeytinoglu, 2006a). One study examined both intentions to quit the job and nursing (I. Zeytinoglu, 2006a). The third category contains studies from the UK, US, Australia and Norway that used either panel or longitudinal data and the probit regression method to predict actual quits from the labour force or the specific market (e.g. National Health Service) for nurses (Holmas, 2002)(C. S. Brewer et al., 2006; A. E. Clark, 2001; Doiron & Jones, 2006; Frijters et al., 2007; C. Parker, 1995). Finally, there were a

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few key studies from Canada and Sweden that used survey data to examine reasons why nurses left the profession (Duffield, Pallas, & Aitken, 2004; L. O'Brien-Pallas, Duffield, & Hayes, 2006; Sjo¨gren & et al, 2005).

Shields (2001) examines both predictors of job satisfaction and its effect on intentions to quit for nurses and represents a key reference for this project (M. A. Shields & Ward, 2001b).

3.2 Outcome Variables From our review, studies to date have not examined job satisfaction, nurse satisfaction and intentions to quit together when considering the working decisions of nurses. The below section will highlight the findings for the aforementioned variables.

3.2.1

Nurse Satisfaction

The research on predictors of nurse satisfaction and its influence on turnover intentions examined reasons nurses enter the profession and reasons they left the profession. Professional commitment is both the attachment to the profession and the satisfaction derived from the work that defines the profession (Nogueras, 2006; Parry, 2008). Shields (2001) found that nurses enter the profession for rewarding work, job security, helping others, promotion, pay and flexibility (M. A. Shields & Ward, 2001b). Studies addressing the question of why nurses leave the profession highlight that factors such as decision-making, relationship with management, stability in the job, and availability of other opportunities are significant reasons for leaving nursing (Duffield et al., 2004; L. O'Brien-Pallas et al., 2006; Sjo¨gren & et al, 2005), and could be associated with nurse satisfaction. Other studies found that both experience in the profession and higher levels of education positively correlate with occupational commitment because both increase investment into the profession (Nogueras, 2006). Leveck (1996) examined both organizational job satisfaction (feelings toward the organization) and professional job satisfaction (feelings toward the profession) and did not find a direct relationship between the two types of satisfaction but rather an indirect relationship through other variables (e.g. job stress) (Leveck, 1996). However, Parry (2008), using a repeated measures design, found that occupational commitment and job satisfaction were positively associated (Parry, 2008). When accounted for, nurse satisfaction as independent of the job, does appear to have a positive

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influence on intentions to remain employed (Hayes, 2006; A. E. Tourangeau & Cranley, 2006; I. Zeytinoglu, 2006a) and not change professions (Parry, 2008).

3.2.2

Job Satisfaction

Job satisfaction is the individual‟s assessment of the wage and non-pecuniary benefits of the job in the past, the expected future benefits from that job compared to any available outside opportunities (Killingsworth, 1983; Le'vy-Garboua et al., 2007). There is extensive research on job satisfaction and its relationship with intentions to quit and actual exits. There is consensus in the literature that a critical predictor of intention to quit, usually defined as leaving the employer or the organization, is a nurse‟s level of job satisfaction (C. S. Brewer et al., 2006; A. Clark, 2001; Doiron & Jones, 2006; Ellenbecker, 2004; Ellenbecker, October 2001; Frijters et al., 2007; Hayes, 2006; Holmas, 2002; Ingersoll & et al, 2002; Le'vy-Garboua et al., 2007; T. Lee, 1999; Leveck, 1996; L. O'Brien-Pallas, 2010; Parry, 2008; M. A. Shields & Ward, 2001a; M. A. Shields & Ward, 2001b; Simmons, Nelson, & Neal, 2001; I. Zeytinoglu et al., 2007; I. U. Zeytinoglu et al., 2006; I. Zeytinoglu, 2006b). Shields (2001) in the study on the National Health Service in the UK, found that nurses dissatisfied with the job had a 65% likelihood of quitting (M. A. Shields & Ward, 2001a; M. A. Shields & Ward, 2001b). Thus, job satisfaction is the proxy measure of whether the individual is maximizing utility within the current job from the pecuniary and non-pecuniary benefits and specific working conditions (Benjamin et al., 1998; Killingsworth, 1983; Le'vy-Garboua et al., 2007; M. A. Shields & Ward, 2001b).

3.2.3

Intentions to Quit

Studies to date have extensively examined predictors of intentions to quit the job or the profession and its relationship to actual quitting behaviour. Turnover or quitting, in itself, can range from leaving the job, the profession or the workforce entirely (A. Baumann, 2010) (Mercer, 1979) (Hayes, 2006). Empirically, intent has been measured as intent to leave or quit (Nogueras, 2006; M. A. Shields & Ward, 2001b)(Borkowski & Amann, 2007), intention to work or remain employed (C. S. Brewer & et al., 2008; A. E. Tourangeau & Cranley, 2006) or turnover intention (I. Zeytinoglu et al., 2007), all reaching similar conclusions with respect to its predictors. The aforementioned definitions generally focus on external turnover, whereas turnover can also be categorized as internal, which would refer to individuals leaving one job for

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another within the same organization (A. Baumann, 2010). Regardless, the consensus is that intentions to quit appear to be a good proxy of quitting behaviour (Frijters et al., 2007; T. Lee, 1999; Mercer, 1979; M. A. Shields & Ward, 2001b). Mercer (1979) found that 80% of the nurses that had expressed intentions to leave the UK National Health Service actually left, while 90% of those that had intentions to stay remained in the NHS (Mercer, 1979). Moreover, Shield (2001) notes that in the absence of panel data, intent to quit is a latent turnover measure of quitting. Further, Mercer (1979), Frijter (2007) and Holmas (2002) found that the predictors of intentions to quit and actual quitting behaviour were the same (Frijters et al., 2007; Holmas, 2002; Mercer, 1979). A limitation with the reviewed literature has been that few studies have examined the difference between intentions to leave the job compared to the profession. The studies have either examined intentions to leave the job or a sector (M. A. Shields & Ward, 2001b) (L. O'Brien-Pallas, 2010; I. Zeytinoglu et al., 2007), intentions to leave nursing (Borkowski & Amann, 2007; C. S. Brewer & et al., 2008; C. S. Brewer et al., 2006; A. E. Tourangeau & Cranley, 2006), or intentions to leave the hospital or the profession as separate models (I. U. Zeytinoglu et al., 2006).

3.3 Explanatory Variables The following section will address the key explanatory factors that the literature to date has found to be significantly associated with satisfaction in the job or the profession and intentions to quit.

3.3.1

Individual Characteristics

As noted in the theory chapter, individual characteristics may influence the utility individuals derive from their job by affecting their expectations for compensatory bundles, their opportunity cost of not working and their own underlying tastes and preferences. Age: Numerous studies, whether using panel or cross-sectional data, have found that age had a significant influence on satisfaction in the job and nursing, along with intentions to quit (Frijters et al., 2007; Nogueras, 2006; C. Parker, 1995; M. A. Shields & Ward, 2001b) (Holmas, 2002)(Wieck, Dols, & Northam, 2009; Wilson, 2008). With respect to both satisfaction in the job and the profession, studies found that older nurses tended to be satisfied and younger nurses were less likely to be satisfied (Ingersoll & et al, 2002; Nogueras, 2006; M. A. Shields & Ward, Anshoo Kamal

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2001b; Wilson, 2008). For older nurses, this may be attributed to their investment into the job and profession, along with their seniority level leading to potentially better benefits (Ingersoll & et al, 2002; Nogueras, 2006; Wilson, 2008). In addition, those that were very dissatisfied may have already exited the profession. In contrast, younger nurses may not yet have established themselves in the job or profession and may not enjoy the same level of benefits. LavoieTremblay (2008) found a high proportion (61%) of new nurses had intentions to quit their jobs for another (Lavoie-Tremblay, O'Brien-Pallas, Glinas, Desforges, & Marchionni, 2008). While, Baumann (2010) indicates that the first five years are highest for turnover (A. Baumann, 2010). The evidence supports using age groups in the models to identify generational cohorts that are more or less likely to be dissatisfied with either aspect or have intentions to quit. Marital Status: The nursing workforce is female dominated and thus, their labour-life cycle will likely be discontinuous due to family-care responsibilities (Benjamin et al., 1998). Their labour decisions and preferences may be highly influenced by their marital status, the presence of children and their household income due to each factor‟s influence on non-work responsibilities and non-work income (Benjamin et al., 1998; Killingsworth, 1983; Nowak & Preston, 2001; C. Parker, 1995). For instance, several studies have found that there are differences in the factors that influence intentions to work for married versus single nurses, such as the presence of spousal income (C. S. Brewer et al., 2006; C. Parker, 1995). In contrast, the findings are mixed with regard to the influence of marital status on the intentions to quit for nurses. They range from being less likely to quit (Holmas, 2002; C. Parker, 1995), to more likely to quit or search for other jobs (Buhr, 2009; A. Clark, 2001) or not having an effect (Frijters et al., 2007; M. A. Shields & Ward, 2001b). These differences may arise from the other factors (e.g. spousal income, children) that the study may have included to predict intentions to quit or quitting behaviour. Marital status does not appear to influence job or nurse satisfaction directly. Children: The presence of children may influence intentions to quit because they influence nonwork responsibilities (C. S. Brewer & et al., 2008; C. S. Brewer et al., 2006; Ellenbecker, 2004; Holmas, 2002; C. Parker, 1995; M. A. Shields & Ward, 2001b). Shields (2001) identified a ushaped curve related to the number of children and intentions to quit with the bottom of the curve being at four children (M. A. Shields & Ward, 2001b). The age distribution of children may also be critical because it changes the child-care responsibilities required from the individual. For

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instance, nurses with older children were found to have lower exit rates from their job and the profession relative to not having children, suggesting older children may act as a stabilizer on exit rates (C. S. Brewer & et al., 2008; Holmas, 2002). However, having younger children did not necessarily increase the intent to quit (Frijters et al., 2007; Holmas, 2002) and in one study, having younger children actually increased the desire to work (C. S. Brewer & et al., 2008). This may reflect that nurses may desire or be able to reduce their labour supply temporarily (i.e. temporary leave or work part-time) in response to their other responsibilities without quitting the job or the workforce (Blythe, 2005; C. S. Brewer et al., 2006; Holmas, 2002). Household Income: Research has examined the income available to an individual, including salary, spousal income and other income combinations or total household income, as theoretically households generally pool their earnings and costs (Benjamin et al., 1998; Killingsworth, 1983; Le'vy-Garboua et al., 2007). The empirical literature suggests that a nurse‟s pay does not exert a strong influence on intentions to quit when compared to other nonpecuniary factors (Ahlburg & Mahoney, 1996; Askildsen, Baltagi, & Holmas, 2003; EstrynBehar, van der Heijden, Fry, & Hasselhorn, 2010; Holmas, 2002; M. A. Shields & Ward, 2001b). In contrast, Lum (1998) found that satisfaction with pay had a direct influence on intention to quit along with an indirect effect through job satisfaction for nurses (Lum, 1998). Other studies on intentions to quit found that the presence of higher levels of other or spousal income increased the likelihood of quitting, especially for married nurses (C. S. Brewer et al., 2006; Holmas, 2002; C. Parker, 1995). Brewer (2008) also found that nurses that were working were more likely to have lower spousal income relative to those not working in nursing (C. S. Brewer & et al., 2008), suggesting self-selection. Some studies also found that the importance of the nurse‟s income to the family significantly reduced intentions to quit (I. U. Zeytinoglu et al., 2006). The level of household income can also influence why nurses leave, as Rajapaksa (2009) found that nurses that left the workforce and had higher household income (greater than $75,000) were more likely to state that they left to find jobs with better hours, more satisfaction and higher incomes (Rajapaksa & Rothstein, 2009). Studies on job satisfaction have found that pay is one of the factors that influence job satisfaction (Ingersoll & et al, 2002; Lum, 1998; M. A. Shields & Ward, 2001b; Wilson, 2008). Therefore, both pecuniary benefits to the individual and household income appear to be important factors for both satisfaction and intentions to quit.

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Education: A nurse‟s level of education reflects her investment into the profession and may influence her utility derived from the job and the profession along with the opportunity costs for leaving (Becker, 1975; Benjamin et al., 1998). Nurses also generally partake in continuing education requiring ongoing investment in human capital over several time-periods, which could change their expectations over time (Becker, 1975). In some provinces, entry-to-practice standards for registered nurses have recently changed education requirements from a diploma earned at college to a baccalaureate earned at a university (Pringle, Green, & Johnson, 2004). For LPNs, education requirements have moved from certificate to college diploma requirements (Pringle et al., 2004). These changes increase the costs of entering the profession and therefore, may increase the earnings expectation (including non-pecuniary benefits) for nurses (Becker, 1975; Benjamin et al., 1998; Killingsworth, 1983; H. Lee, 2008; Nowak & Preston, 2001). An empirical study of RN earnings in Canada when comparing the differentials between diploma and baccalaureate earnings found that RNs with higher levels of education had higher earnings (H. Lee, 2008). Nurses with higher levels of education in nursing were found to have greater probabilities of having intentions to quit and actually quitting their jobs (C. S. Brewer & et al., 2008; C. S. Brewer et al., 2006; A. Clark, 2001; Doiron & Jones, 2006; Frijters et al., 2007; Lum, 1998; M. A. Shields & Ward, 2001b; A. E. Tourangeau & Cranley, 2006; I. U. Zeytinoglu et al., 2006). In addition, higher levels of education were strongly associated with lower job satisfaction (M. A. Shields & Ward, 2001a; M. A. Shields & Ward, 2001b). Alternatively, two USA studies on registered nurses found that higher levels of education increased commitment to the profession and lowered intent to leave the profession (Borkowski & Amann, 2007; Nogueras, 2006). However, these two studies specified the profession while the others primarily examined intentions to quit the job. This suggests that education may influence job satisfaction and intentions to quit the job differently than nurse satisfaction and intentions to leave nursing.

3.3.2

Work Characteristics

Studies, such as Shields (2001) and Frijters (2007) that focused on nurses‟ intentions to quit the specific market (e.g. National Health Service) or actual quitting behaviour included work specific characteristics to examine their influence on the quitting decision and behaviour (M. A. Shields & Ward, 2001b) (Frijters et al., 2007). Studies that examined exits from the workforce, such as Brewer (2008) and Parker (1995) did not include a comprehensive set of work specific

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characteristics (C. S. Brewer & et al., 2008; C. Parker, 1995). However, research based on surveys of nurses that had left the workforce identified work specific characteristics as reasons for leaving (Duffield et al., 2004; L. O'Brien-Pallas et al., 2006). The specific work characteristics, conditions and compensation presented to the nurse will influence the perceived level of utility from the job and profession. Therefore, these characteristics are important to consider when examining predictors of satisfaction and intentions to quit. Union Status: Across Canada, 80% of nurses, both RNs and LPNs, are union members compared to the general employed population (30%) (M. Shields & Wilkins, 2006). However, these union rates varied by province and sector. A Canada-wide study found that nine out of ten nurses employed in hospitals were unionized compared to the community sector where seven out of ten were unionized (M. Shields & Wilkins, 2006). Ontario had the lowest rate of unionization of all provinces (73%) for both groups of nurses (RNs may have lower unionization rates than LPNs) (M. Shields & Wilkins, 2006). Union rates may have an impact on employment variables such as pay rates, opportunities for advancement and the amount of shift work (Holmas, 2002; M. A. Shields & Ward, 2001b)(Benjamin et al., 1998)(Killingsworth, 1983). For example, nurses of a particular type (RN or LPN) with a given number of years of experience may earn a particular hourly wage. Rates for overtime and part-time work, level of shift work and scheduling can also be specified in the contracts or collective agreements. Shields (2001) notes that including union status without the specific work characteristics can bias unionization‟s effect on satisfaction upwards, since unions influence the specific working conditions (M. A. Shields & Ward, 2001b). Unionization also appears to have a positive impact on job satisfaction and intentions to leave such that both union members and workers in a unionized environment were less likely to quit (A. E. Clark, 2001). Empirically, unionization has been found to influence job satisfaction and intentions to quit the job or the workforce and will therefore, be included in our models. Region: The province or territory that nurses work in may cause their work characteristics to differ as the market structure and union environments vary by province and territory in Canada. The other market opportunities available to the nurse may also differ due to the economic

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environment of that region (C. S. Brewer & et al., 2008). Our models will include the province/territory where the nurse works to determine if there are any differences with respect to satisfaction and intentions to quit. Sector: Studies suggest that the roles and skills that nurses develop differ depending on their sector and clinical unit (Cameron et al., 2004; Ellenbecker, 2004; L. O'Brien-Pallas, 2010). Therefore, working in a specific sector or clinical area may increase the nurse‟s investment in that job and sector and may increase the cost of leaving that sector or clinical area for another. However, studies have also found different rates of nurse retention and job satisfaction across the sectors (hospital, long-term care, community and other), suggesting that there may be compensating differentials (Cameron et al., 2004)(Alameddine et al., 2006)(Shaver & Lacey, 2003). Alameddine et al. (2006) define the term stickiness as the propensity of the nurse to remain in the same sector in year 2 as in year 1; it is a proxy measure for the attractiveness of the specific sector (Alameddine et al., 2006). Hospitals were found to have the highest stickiness rates while home care and mental health settings, within the community sector, had the lowest rates (Alameddine et al., 2006). Therefore, nurses may choose not to work in a sector if they perceive that the compensation (pecuniary and non-pecuniary) offered is insufficient to compensate for the disutility of the job. Variation also occurs by sector for work characteristics. For example, long-term care institutions tended to have the lowest proportion (54%) of full-time jobs (M. Shields & Wilkins, 2006). Other research suggests that nurses working in the community setting had greater autonomy and control over schedules but also lower wages (A. Baumann et al, 2001; Cameron et al., 2004; Ellenbecker, October 2001). Several studies have examined the effect of settings on retention (e.g. the size of the workplace or clinical unit) and found significant differences in quitting rates or intentions to quit (Doiron & Jones, 2006; Frijters et al., 2007; Leveck, 1996; L. O'Brien-Pallas, 2010) (A. Tourangeau et al., 2006). Further, both Ingersoll (2002) and Shaver (2003) found that the nurses‟ job setting had a significant influence on job satisfaction but not nurse satisfaction (Ingersoll & et al, 2002; Shaver & Lacey, 2003). This suggests that the sector or setting (i.e. different units same organization) that nurse works within could be an important factor for both job satisfaction and intentions to quit. Full-Time/Part-Time/Casual: Theoretically, greater amounts of work hours reduce utility because the individual has less available leisure time (Benjamin et al., 1998; Killingsworth,

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1983). However, nurses may also prefer to work a certain number of hours to achieve their desired income or to address their non-work responsibilities. Different studies have examined the number of hours worked, full-time, part-time and casual status and their influence on satisfaction in the job and intentions to quit. For example, Shields (2001) finds that working more hours negatively influences job satisfaction; however, controlling for shift type, the total number of hours is no longer significant (M. A. Shields & Ward, 2001b). Several studies that examined intentions to quit, desire to work or reasons for leaving found that nurses that were not satisfied or were not working their preferred hours had lower retention in the job and nursing (Borkowski & Amann, 2007; C. S. Brewer & et al., 2008; Doiron & Jones, 2006; Frijters et al., 2007; Rajapaksa & Rothstein, 2009). Other studies examined the impact of working full-time or part-time on satisfaction and intentions to quit. They found that for registered nurses working full-time significantly reduced the likelihood of intentions to leave the job (Frijters et al., 2007; Holmas, 2002; L. O'Brien-Pallas, 2010; C. Parker, 1995; A. E. Tourangeau & Cranley, 2006), suggesting that full-time nurses were more invested in their jobs. Further, Zeytinoglu (2006) found that nurses that preferred a different status from what they were working were more likely to have intentions to leave their job (I. U. Zeytinoglu et al., 2006). Blythe et al (2005) examined the trade-off between working different statuses and found that nurses that were older or had younger children preferred part-time jobs; however, the majority of nurses were satisfied with their full-time jobs (Blythe, 2005). There also appear to be specific benefits and security tied to full-time jobs that are not available in a part-time or casual position (Blythe, 2005). Finally, Daniels (2010) found a strong association between job dissatisfaction and working in a casual position for nurses in Ontario (Daniels, 2010). The evidence on the influence of, specifically, working in a casual position on satisfaction or intent to quit is limited. The findings suggest that it is important to consider nurse‟s work status when examining their job satisfaction and intentions to quit. Shift Work: Shift work is a prominent feature of nursing, especially in the hospital sector and it has been found to be linked to stress and poorer health status (Costa, 1996; Simmons et al., 2001). Shift work includes type of shift (day, evening, night and weekend shifts), shift rotations (the number of shift changes) and the usual shift hours (eight to twelve hours). Shields (2001) and Zeytinoglu (2006) found that nurses that were not working their preferred shift were more likely to be dissatisfied and to have intentions to leave the job (M. A. Shields & Ward, 2001b; I. Anshoo Kamal

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U. Zeytinoglu et al., 2006). Most studies found that higher levels of shift work is related to higher exits from the sector/industry and dissatisfaction with the job (Duffield et al., 2004; Frijters et al., 2007; Holmas, 2002). Therefore, our project includes all three characteristics of shift work (i.e. type, rotation and hours) to determine their association with satisfaction and intentions to quit. Area of Responsibility: The role that nurses‟ play in their job may affect the utility they derive from their job because it will influence their work conditions. Nurses that generally move into roles with more responsibilities (e.g. managerial) may be more invested but also may develop skills that are easily transferable to other opportunities (M. A. Shields & Ward, 2001b). Studies examining intentions to quit have found that nurses working in a non-direct care role are more likely to have intentions to quit and actually more likely to quit nursing or the organization (C. S. Brewer & et al., 2008; Frijters et al., 2007; M. A. Shields & Ward, 2001b). Choice in Schedules: Flexibility in and control over schedules is a prominent theme in the nursing literature. Nurses value flexibility in their schedules allowing them to address their own preferences and non-work responsibilities (Blythe, 2005; Bookey-Bassett, Laporte, & et al, July 2008; Duffield et al., 2004; Sjo¨gren & et al, 2005) and experts believe flexibility is related to greater job satisfaction (Robb, 2003). Studies suggest that a lack of flexibility in schedules is a common reason for nurses to have intentions to leave and to have left the profession (BookeyBassett et al., July 2008; Duffield et al., 2004; Sjo¨gren & et al, 2005). Wilson et al (2008) also found that younger nurses were less likely to be satisfied with flexibility over schedules and it was a more important issue for them than older nurses (Wilson, 2008). This may also be an artefact of a union environment, as nurses with more seniority will likely have more choice in their schedules (Wilson, 2008). Childcare support: As noted in various studies, work-life balance is an important factor for nurses in influencing satisfaction and intentions to quit (Duffield et al., 2004; Wilson, 2008). Theoretically, child-care responsibilities may be significant in the nursing profession due to its female workforce (Benjamin et al., 1998; Killingsworth, 1983). Although studies have not specifically addressed the non-pecuniary benefit of employer sponsored child-care support, many studies found that nurses that perceived an imbalance in their work-life responsibilities were less

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likely to be satisfied and more likely to have intentions to leave nursing (A. Baumann et al, 2001; Duffield et al., 2004; Sjo¨gren & et al, 2005). Employers that provide support for child-care, leading to better work-life balance may positively influence a nurse‟s intention to remain employed. Workload and Stress: Workload includes items such as not having enough time to complete tasks, having too much to do and working overtime to complete work (I. Zeytinoglu et al., 2007). Researchers have found that heavy workloads are associated with poor health and burnout (A. Baumann et al, 2001) and that it is a significant component of job dissatisfaction (Hayes, 2006; M. A. Shields & Ward, 2001b; Wilson, 2008; I. Zeytinoglu et al., 2007). Research has also found that heavy workloads were significantly linked to leaving nursing and having intentions to quit the sector (Cline, 2004; Doiron & Jones, 2006; Holmas, 2002; Sjo¨gren & et al, 2005). For instance, Holmas (2002) found that higher occupancy rates and bed to nurse ratios were significantly associated with higher exit rates from hospitals (Holmas, 2002). Further, heavy workloads combined with a lack of support resources were found to influence burnout, stress and reduced personal accomplishment, which are elements of job strain (Simmons et al., 2001; A. Tourangeau, 2010; A. E. Tourangeau & Cranley, 2006). High levels of job strain were found to be negatively associated with job satisfaction and intentions to quit the job (Lavoie-Tremblay et al., 2008) (I. U. Zeytinoglu et al., 2006)(Wieck et al., 2009) (H. K. S. Laschinger et al., 2009; H. Laschinger, 2001)(Leveck, 1996). Both workload and job strain were included in our job satisfaction and intentions to quit models. Control over Practice and Decision Autonomy: Significant non-pecuniary benefits include skill utilization and involvement in decision-making or autonomy in work or professional practice. Nurses invest significantly in their education and development as a professional, and as such would value the use of their knowledge and skills as nurses. Researchers have found that nurses who left the nursing profession cited dissatisfaction with the use of their skills at work and their decision-making ability (L. O'Brien-Pallas et al., 2006) (Sjo¨gren & et al, 2005) (Duffield et al., 2004) (Estryn-Behar et al., 2010). Studies on factors associated with job satisfaction found a strong negative association with the lack of skill usage, task variety and decision-making ability (M. A. Shields & Ward, 2001b) (Cameron et al., 2004; Ellenbecker, October 2001) (A. Baumann et al, 2001; Bookey-Bassett et al., July 2008). Ellenbecker (2001) found that decision-making

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influence in the job also influenced job satisfaction for nurses in home care (Ellenbecker, October 2001). Further, Laschinger (2001) found that psychological empowerment, defined as competence and decision autonomy, was directly related to job satisfaction (H. Laschinger, 2001). Research suggests that the use of nurses‟ skills and competence in their job along with decision-making autonomy are both significantly associated with both job and professional satisfaction and intentions to quit. Work Relationships: The support and relationship with peers and managers fostered at the job acts as a non-pecuniary benefit for nurses and the utility they derive from working. Laschinger (2001) describes structural empowerment to include support from peers and managers, which was found to have a strong negative association with job strain and positive association with job satisfaction (H. Laschinger, 2001). Nurses that foster supportive relationships with their peers and perceive their supervisors and managers to be supportive may feel less stressed in their jobs and may develop positive attitudes towards their job and organization. Nurses often cite dissatisfaction with social support, relationships with peers and managers, as reasons for leaving the position and/or the profession, suggesting that it would be an important factor for professional satisfaction and intentions to leave the profession (Duffield et al., 2004; EstrynBehar et al., 2010; I. U. Zeytinoglu et al., 2006) (Cline, 2004) (Lavoie-Tremblay et al., 2008). Leveck (1996) also found group cohesion to be a contributor to professional satisfaction (Leveck, 1996). Zeytingolu (2006) estimated propensity to leave the hospital and nursing and found that support from peers was a significant predictor especially for full-time nurses for both outcomes (I. U. Zeytinoglu et al., 2006). Full-time nurses would spend the most time in their job and therefore, may have a higher sensitivity toward the relationships. Studies in Canada and the U.K. have also cited that social support is positively associated with job satisfaction (A. Baumann et al, 2001; Cameron et al., 2004; M. A. Shields & Ward, 2001b). Further, O‟BrienPallas (2010) found that hospital units with better leadership had improved job satisfaction (L. O'Brien-Pallas, 2010). The literature supports the hypothesis that social support and good working relationships were significant contributors to both satisfaction in the job and the profession along with intentions to leave nursing. Job Insecurity: High levels of insecurity may decrease the perceived future benefits of staying in the current job. Shields (2001) found that security was a key factor identified by nurses to

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enter the profession, a component of job satisfaction and a factor that contributed to intentions to quit (M. A. Shields & Ward, 2001b). Another British study also found a strong correlation between security and satisfaction and found that temporary nurses were less likely to stay in the job (A. Clark, 2001). However, this may have resulted from involuntary turnover once the temporary contract ended. In Canada, Bauman (2001) observed that job security heightens both satisfaction and organizational commitment (A. Baumann et al, 2001), while Blythe et al (2005) illustrated that nurses were concerned about security in their jobs when determining whether to work full-time or part-time (Blythe, 2005). These findings indicate that job security is a factor that should be studied for nurses and how it may influence their satisfaction levels and intentions to quit. Relationship between Non-Pecuniary Benefits: Laschinger (2001) and other studies found that decision autonomy, social support, workload and job strain can also influence each other (A. Baumann et al, 2001; H. K. S. Laschinger et al., 2009; H. Laschinger, 2001). For example, higher levels of decision autonomy (e.g. empowerment) and social support can mitigate the negative influence of higher levels of workload on burnout and job strain (H. K. S. Laschinger et al., 2009; H. K. S. Laschinger, Finegan, & Shamian, 2001). This in turn can influence job satisfaction and turnover intentions (H. K. S. Laschinger et al., 2009). Therefore, it would be important to consider any correlation between these aspects and their individual influence on the outcomes.

3.4 Significance of this Project The literature has not extensively examined the impact of key explanatory variables on satisfaction with the job or the profession, and/or intentions to quit such as the influence of having education in a different field, holding multiple jobs, holding a job outside of the profession and self-reported health status. Theoretically, the benefit and cost of other market opportunities would affect a nurse‟s valuation of utility from the current job and the profession. In addition, health status may influence the cost of working for a nurse due to diminished ability. For instance, Brewer (2008) identified that nurses in the USA that perceived more opportunities to find another job were more likely to quit nursing (C. S. Brewer & et al., 2008). Explanatory variables that can address whether a nurse holds other education, holds more than one job and/or holds a non-nursing job may act as proxy measures for the availability of other market Anshoo Kamal

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opportunities, which may increase the benefit and lower the cost. Further, Shields (2001) notes that nurses with poorer health status could theoretically, perceive lower levels of satisfaction and higher intentions to quit (M. A. Shields & Ward, 2001b). Our project will include these variables in the models for satisfaction and intentions to quit to determine their influence, if any, on satisfaction with the job and the profession and intent to quit. Based on our review, studies have not sufficiently addressed the influence and inter-relationship between satisfaction with the job and the profession through a simultaneous model approach. They also have not examined the differences between intent to quit the current job or the profession as alternative options within one model. This project will add to the literature on satisfaction and intentions to quit by examining the relationship between job and nurse satisfaction and their influence on a nurse‟s decision to either switch jobs or leave the profession entirely. We will also examine intentions to leave the job or to leave the profession as simultaneous alternatives available to the nurse to determine differences in the predictors and to distinguish them as separate but related alternatives available to the nurse.

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Chapter 4 Data Source, Variables and Methods This chapter will describe the data source and the variables used in the models. It will also describe the empirical strategy employed to address each of the study questions.

4.1 Data Source The project utilized survey data from the 2005 National Survey of Work and Health of Nurses in Canada (NSWHN), conducted by the Canadian Institute for Health Information, Statistics Canada and Health Canada. The NSWHN is a cross-sectional survey of nurses who were registered and employed in nursing in Canada. It includes information about demographic characteristics, education, work factors for the main job and other jobs the nurses may have held as well as self-reported health status.

4.2 Survey Sample Population, Timelines and Weighting The NSWHN included in the sampling frame nurses sub-divided into registered nurses (RNs), licensed practical nurses (LPNs) and psychiatric nurses who were registered with the provincial regulatory body and employed in nursing in the fall of 2005; nurses that were retired, unemployed or under the age of 21 were excluded (Statistics Canada, 2005b). Statistics Canada surveyors telephoned nurses to ask them the questions and record their responses between October 2005 and January 2006. The NSWHN sampling frame is based on a stratified random sampling technique. The primary stratification was on the province of registration and type of nurse (registered nurses, registered/licensed practical nurses and psychiatric nurses) (Statistics Canada, 2005b). The second stratification was to ensure reliable estimates for the following categories: age group, place of work and full-time/part-time/casual status (Statistics Canada, 2005b). Statistics Canada anticipated a total sample of 24,443 nurses to be included in the survey based on the inclusion/exclusion criteria (Statistics Canada, 2005b). Of the 24,443 nurses, contact was made with 21,307 and 18,676 nurses responded resulting in a response rate of 80% (Statistics Canada, 2005b).

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Statistics Canada employed a probability sampling technique such that each individual nurse in the sample represents a proportion of nurses like him/herself in the total nurse population (Statistics Canada, 2005b). Statistics Canada provided a sampling weight (WTPM) in its survey data to use to ensure that the survey is representative of the population (Statistics Canada, 2005b). The unweighted survey data is not adjusted for the over/under sampling of specific groups of nurses; therefore, all of our descriptive results and models were estimated using the survey weights provided.

4.3 Creating the Regulated and Employed Nurses Sample for the Project This research project focuses on the RNs and LPNs in the survey. Psychiatric nurses were not included as they were only distinctly identified in four provinces, Alberta, British Columbia, Manitoba and Saskatchewan and had a relatively smaller sample (Statistics Canada, 2005b). The NSWHN sample included 16,969, composed of 9,704 RNs and 7,265 LPNs (Statistics Canada, 2005a). This project analyzed RNs and LPNs (separately) and as the focus of the research project was on determinants of job and professional satisfaction and intent to quit the job and or nursing, nurses that reported „self-employed‟, „other‟, „don‟t know‟ or „refusal‟ to the question related to employment status (Statistics Canada, 2005a) were removed from the sample. This left a sample size of 9,508 RNs and 7,120 LPNs for the project.

4.4 Missing/Non-Responses The missing observations in the sample used in the project were due to non-responses in the survey. Nurses that stated `don`t know` or `refusal` to the questions related to the independent variables were re-coded to „missing‟ in the project sample. The full sample includes missing values for both categorical and continuous variables. Using case-wise deletion, the observations where an explanatory variable had a missing value were removed from the model estimation. This led to the removal of 675 observations for RNs and 419 observations for LPNs. The project examined the missing observations, using the Stata commands: “misstable” and “missnested”, to determine if there was a relationship between the variables with missing responses (e.g. missing responses for “having choice in hours” were nested in “having choice in days”). There was no Anshoo Kamal

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apparent pattern between the missing observations such that a missing response in one variable was not dependent upon a missing response in another variable, with the exception of skill discretion, decision autonomy and job strain. The job strain variable is a ratio variable derived from the scores from questions shared with skill discretion or decision autonomy. Little (2005) defines missing variables into three types: missing completely at random (MCAR), missing at random (MAR) and non-ignorable missing at random (NMAR). The first two may reduce the sample size but do not lead to biased results because the missing values are arbitrary or random (Little & Rubin, 1987; Little & Rubin, 1987; Scheuren, 2005). However, the NMAR can lead to bias results if it leads to an underestimation of that specific variable in the model, which may influence the outcome variables (Little & Rubin, 1987; Scheuren, 2005). However, it is difficult to separate out the different types of missing variables and experts believe that in most studies all three may be present to some degree (Little & Rubin, 1987; Scheuren, 2005). Based on our review, it is believe that the missing data is mostly “missing at random”. The missing observation count is small for each explanatory variable relative to the sample size included in the models. The score variables: Social Support and Job Strain had the greatest counts of missing observations. Below is the list of the explanatory variables that had missing variables:                  

Marital Status Self-Reported Health Status Have Education Level at Baccalaureate or Higher Have Non Nursing Education Have Multiple Jobs Union Membership Total Shift Changes in the Past Two Weeks Full-Time, Part-Time, Casual Non Day Shift Non Direct Care Usual Shift Hours Don‟t Choose Days Don‟t Choose Hours Childcare Support Available Job Insecurity Role Overload Decision Authority Skill Discretion

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 

Social Support Job Strain

4.5 Limitations 4.5.1

Self-Reported and Selection Bias

The NSWHN is a self-reported survey that focused on employed nurses. This project is reliant on the nurse reliably and accurately responding to the questions. We did not conduct any validation tests against observed data. Further, there may be an inherent self-selection bias reflected in the survey. The survey includes all employed nurses and it could be argued that nurses that were highly dissatisfied with the job and/or nursing may have already left the nursing workforce, such that the nurses remaining would generally skew the results to a more positive outlook on satisfaction and intentions to quit. However, our project‟s focus was on the employed workforce and their level of satisfaction and intentions to quit. Identifying determinants of dissatisfaction and intentions to quit for nurses who were still in the workforce is valuable insight to employers and decision-makers to retain that specific workforce. Moreover, the survey reflects the population of nurses, including an appropriate representation (e.g. nurses that are relatively new to the profession).

4.5.2

Data Limitations in the NSWHN

The project was limited by the data that was available in the NSWHN. For instance, the NSWHN did not include questions on the nurse‟s location of education (e.g. international), nurse salaries, perceived external opportunities, clinical unit and geographic location (e.g. rural community). For instance, the theoretical literature identifies compensation (i.e. pecuniary factor) as having a potentially important influence on the utility derived from working (Benjamin et al., 1998; Killingsworth, 1983). The NSWHN did not include a question about nurses‟ individual income and benefits but did ask about household income so, we were obliged to use “total household income” in the estimating equations. Economists also recognize the importance of household income as it may influence the working decision because families generally pool earnings and have common budget constraints (Benjamin et al., 1998; Killingsworth, 1983). Nevertheless, the inclusion of the nurse‟s own salary information would have been desirable to include in the analysis. Another example is that nurses that work in rural communities may face

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different work environments and may not offer extensive other alternative market opportunities, which may influence their satisfaction levels and intentions to quit. Nurses in rural areas may also require higher rates of compensation to make up for disutility associated with working and living in rural communities. The addition of the aforementioned variables would add valuable information and should be included, if possible, in future studies on nurse retention.

4.5.3

Cross-Sectional Survey

The NSWHN is an extensive, large and representative cross-sectional survey of nurses across Canada. Cross-sectional data is not suitable to use to determine causation between the individual and work characteristics and dissatisfaction in the job and/or nursing and intentions to quit. Therefore, although this project is able to identify significant predictors of each of the outcome variables, it cannot speak to causal direction of that relationship. For example, do nurses that work in casual positions do so because they are dissatisfied with their job or are they dissatisfied with their job because they work in a casual position are important questions that panel data studies could help to answer. For example, there have been prominent studies that have used panel data, longitudinal data sets that follow individuals over a number of years, to establish the causal relationship between job satisfaction and various work characteristics and quitting behaviour (A. E. Clark, 2001; Frijters et al., 2007; Holmas, 2002). The NSWHN, as crosssectional data, also represents a point-in-time snapshot of nurses and their perceptions of satisfaction levels and intentions to quit. This study cannot assess whether these perceptions would be permanent in nature and panel data analysis would help to determine whether dissatisfied nurses stay dissatisfied over time. Finally, Shields (2001) notes that although unobservable individual heterogeneity (latent differences in individuals) that may influence the studied outcome is a challenge with cross-sectional data, studies have found that large representative survey samples significantly mitigate this limitation and the job satisfaction parameter results are robust to this issue (A. Clark, 2001; M. A. Shields & Ward, 2001b). Therefore, despite these limitations, the NSWHN is a comprehensive large and representative survey of nurses that is able to produce reliable and robust results for our models.

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4.6 Coding Outcome Variables The outcome variables in this research project are binary and categorical, based on the nurse‟s main job, for those with more than one job: 

Job Dissatisfaction – Binary (0, 1)



Nurse Dissatisfaction – Binary (0, 1)



Intent to Quit – Categorical (Stay = 0, Leave Nursing = 1, Switch Jobs = 2, At Risk of Leaving the Profession = 3)

4.6.1

Job Dissatisfaction

In this study, we use the question in the NSWHN that asks about the nurse‟s satisfaction with the main job as the dependent variable for job dissatisfaction. Surveyors assigned the nurse to a main job, if she held more than one, by where the nurse reported working the most hours. Nurses‟ responses to satisfaction in the job question ranged from very satisfied to very dissatisfied, don‟t know and refusal (Statistics Canada, 2005a). We dichotomized the responses into a binary choice between satisfied (very satisfied and satisfied, defined as 0) and dissatisfied (very dissatisfied, dissatisfied and don‟t know, defined as 1). This was done because a relatively small number of registered nurses (12%) indicated job dissatisfaction. Sensitivity analysis verified that aggregation of the “don‟t know” (0.1%) response with dissatisfied did not significantly change the results, but gave a larger sample size. We called this binary variable “job dissatisfaction” to maintain comparability with the “intent-to-quit” model.

4.6.2

Nurse Dissatisfaction

The literature defines nurse satisfaction, distinct from job satisfaction, as the attachment to the profession and signifies the degree to which a nurse finds the work in the profession satisfying (Nogueras, 2006). Similar to the creation of the job dissatisfaction variable, we used the question from the NSWHN “how satisfied are you with your profession outside of the job” (Statistics Canada, 2005a) to create the second dependent variable. The responses range from very satisfied to very dissatisfied, don‟t know and refusal (Statistics Canada, 2005a). Again, we dichotomized the responses into a binary choice between satisfied (very satisfied and satisfied, defined as 0) and dissatisfied (very dissatisfied, dissatisfied and don‟t know, defined as 1).

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Similarly to the job dissatisfaction sensitivity analysis, retaining the “don‟t know” (0.1% for RNs) in the dissatisfied group did not significantly change the results.

4.6.3

Intent to Quit

The third model investigates the relationship between job and nurse dissatisfaction, a set of explanatory variables, and the nurse‟s “intent to quit.” A nurse can have intentions to leave the current job or leave the profession entirely (which would include the job). Noting that leaving the job may mean switching jobs within the same organization or leaving for another organization. We grouped and recoded responses to the following two questions: 1) “In the next 12 months, do you plan to leave the job” and 2) “In the next 12 months, do you plan to leave the nursing profession” into a unordered categorical response variable (0, 1, 2, 3) (Statistics Canada, 2005a). Only those nurses that stated they had intentions to leave their main job were asked to respond to whether they had intentions to leave the profession (Statistics Canada, 2005a). For the first question, we assigned the “don‟t know” to an „at risk‟ cohort. For the “intent to leave nursing” question, the nurses were placed in the “not stated” category if they reported “don‟t know” to the “intent to leave their job” question. We combined the nurses in the “not stated” category (N=497) with the “don‟t know” category to create the “at risk” category. The “at risk” category represents the nurses that were not sure of their intentions over the next 12 months leading to a possibility that they may leave the job and/or the profession. We recoded the nurses that stated they were leaving the job (whether within the same organization or different organizations) but didn‟t know if they were leaving the profession to “switching job” because the intention to quit the job was articulated.

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Figure 4: Deriving the Intent-to-Quit Variable

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4.7 Coding Explanatory Variables The income-leisure choice theory (Benjamin et al., 1998)(Killingsworth, 1983) suggests a number of explanatory variables that could influence job dissatisfaction, nurse dissatisfaction and intent-to-quit respectively. Chapter 3 (Literature Review) outlines the findings from the empirical models to date and the literature on the importance of these variables. These findings informed the selection of the explanatory variables to be included in each model. Some variables that the literature identified as influencing job dissatisfaction, nurse dissatisfaction and/or the intent-to-quit were not asked through the NSWHN, and therefore could not be included in the models. The explanatory variables were categorized into two main groups: 1) Individual Characteristics and 2) Work Characteristics. The explanatory variables included in each model differed based on their theoretical and empirical importance.

4.7.1

Multicollinearity among Explanatory Variables

Multicollinearity exists when two or more explanatory variables are inter-related, such that it is difficult to ascertain the independent influence of these variables on the outcome (Greene, 1997). Models with multicollinearity will lead to results that are prone to large fluctuations and biases in individual parameter estimates, although not to the overall variance explained on the model (Greene, 1997). We applied the Pearson correlation to test for mutlicollinearity among the variables. The correlation R2 produces results between -1 to +1. Generally, the closer the R2 is to -1 or +1 suggests a strong correlation between the variables; however, researchers apply different thresholds to the R2 to determine the strength. We applied the following criteria, in absolute terms, to determine the strength of the association among the variables: 

R2 > 0.8 is a strong correlation



0.6 < R2 < 0.8 is a moderate correlation



R2 < 0.6 is a weak correlation

We used the results from the correlation analysis to determine which explanatory variables could not be included in the equations based on if they were significant and moderately to highly

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correlated with others. As a result, we excluded the variables Years in Nursing, Employment Status and Usual Weekly Hours from our explanatory variables list. Two highly correlated variables were „age‟ and „years in nursing‟. The literature identifies “age” as a significant influencing factor on the “intent to quit” for nurses. Nurses in different age cohorts may have different individual preferences and opportunity costs for quitting (Benjamin et al., 1998)(Killingsworth, 1983) (Frijters et al., 2007). The project maintained the „age‟ variable, because the „years in nursing‟ variable did not add much more information to the estimating equations. The variables “usual weekly hours” and “employment status” were moderately correlated with the “full-time/part-time/casual” status variable. Based on this, we removed the employment status and usual weekly hours. According to the empirical literature, the fulltime/part-time/casual variable was a strong predictor of job dissatisfaction and intent to quit relative to the other two variables (Frijters et al., 2007; M. A. Shields & Ward, 2001b). Table 1: Correlation between Variables for RNs and LPNs Variables

RNs

LPNs Variable Maintained

0.82 0.73 Age Age Years in Nursing 0.69 0.77 Full-Time/Part-Time/Casual Full-Time/Part-Time/Casual Status Employment Status (Perm./Temp./Casual -0.60 -0.53 Full-Time/Part-Time/Casual Usual Weekly Hours Full-Time/Part-Time/Casual All of the above correlations were significant at the Bonferroni adjusted (p0.05); thus, we could not

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reject the null hypothesis that the parameter estimates for the common explanatory variables were equal. This suggests that the estimates were stable to the use of the various thresholds. The results from the 0.5 threshold are presented in Appendix 18 and Appendix 19.

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Chapter 5 Descriptive Results This chapter describes the nursing population from the National Survey of Work and Health Nurses (NSWHN) 2005 that was used in our project. As noted in the methods (Chapter 4), the NSWHN included all nurses that were registered with their respective regulatory College, allowing them to practice as a nurse, and employed as nurses. As part of the project, we further removed nurses that were self-employed. Therefore, the descriptive results below represent employed nurses in Canada. The first section of this chapter outlines results for cross-tabulations by nurse group (RNs and LPNs) and the explanatory and outcome variables. The second section presents the results for cross-tabulations between the key explanatory variables and the three individual outcome variables for each nurse group. The descriptive results are for the sample population used in the models: 9,508 RNs and 7,120 LPNs.

5.1 Descriptive Results for Explanatory Variables by RNs and LPNs 5.1.1

Individual Characteristics

Age: RNs and LPNs had similar age distributions, with 62% of each group between the ages of 35 and 54. The single largest age cohort was 45-54 at 34% for RNs and 35% for LPNs. Figure 5: Age Distribution for RNs and LPNs

45-54, 35%

45-54, 34%

35-44, 28% 35-44, 27%

z

0.02 0.01 0.01 0.02 0.00 0.00 0.00 0.00 0.00 0.02

-1.13 0.82 0.34 1.28 1.91 1.47 1.45 -0.08 1.68 1.31

0.26 0.41 0.73 0.20 0.06 0.14 0.15 0.94 0.09 0.19

95% Confidence Interval -0.06 0.02 -0.01 0.04 -0.02 0.03 -0.01 0.06 0.00 0.00 0.00 0.01 0.00 0.01 -0.01 0.01 0.00 0.01 -0.01 0.07

Intent-to Quit Equation: Outcome = At Risk; Base Outcome = Stay Explanatory Variable

Reference Variable

Average Marginal Effect 0.03 0.00 0.00 0.01 -0.01 0.00 -0.01 -0.01

Std. Err.

z

P>z

Job Dissatisfied Nurse Dissatisfied Male Age- less than 35 Age - 45-54 Age - greater than 55+ Not Married Have Children - Under 5 Years Have Children - Aged 6-11 Have Children - Aged 1217 Health Status - Poor-Fair

Job Satisfied Nurse Satisfied Female Age - 35-44 Age - 35-44 Age - 35-44 Married No Children

0.01 0.01 0.01 0.01 0.01 0.01 0.00 0.01

2.58 0.54 0.11 0.79 -1.36 -0.12 -1.61 -1.93

0.01 0.59 0.91 0.43 0.17 0.90 0.11 0.05

0.01 -0.01 -0.02 -0.01 -0.02 -0.01 -0.02 -0.02

0.04 0.02 0.02 0.02 0.00 0.01 0.00 0.00

No Children No Children

0.00 0.00

0.01 0.01

0.31 -0.68

0.76 0.50

-0.01 -0.01

0.01 0.01

Health Status - Good

0.00

0.01

-0.59

0.56

-0.02

0.01

Health Status - Very Good

Health Status - Good

-0.01

0.00

-1.73

0.08

-0.02

0.00

Health Status - Excellent Household Income - less than $50,000 Household Income $100,000 or more Have Education Baccalaureate or Higher Have Non-Nursing Education Have More than One Job Have Non-Nursing Job Atlantic Territories Quebec Manitoba

Health Status - Good Household Income $50,000-$99,999 Household Income $50,000-$99,999 Have Education Diploma/Certificate No Non-Nursing Education One Job No Non-Nursing Job Ontario Ontario Ontario Ontario

-0.02 0.01

0.00 0.01

-3.55 0.70

0.00 0.48

-0.03 -0.01

-0.01 0.02

0.00

0.00

-0.39

0.70

-0.01

0.01

-0.01

0.00

-1.49

0.14

-0.02

0.00

0.01

0.01

1.34

0.18

0.00

0.02

0.01 -0.01 0.00 -0.02 0.00 0.04

0.01 0.01 0.01 0.01 0.01 0.01

1.02 -0.70 0.27 -2.37 -0.59 3.28

0.31 0.48 0.79 0.02 0.55 0.00

-0.01 -0.02 -0.01 -0.03 -0.02 0.02

0.02 0.01 0.01 0.00 0.01 0.07

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Explanatory Variable

Reference Variable

Average Marginal Effect 0.02 0.01 0.02 0.00 0.00 0.00 0.01 0.00 0.00 0.01 -0.01 0.00

Std. Err.

z

P>z

Saskatchewan Alberta British Columbia Long-Term Care Community Other Non Union Member Part-Time Casual Non Days Non Direct Care Role Shift Changes - One or More Shift Changes - Didn't Work Usual Shift Hours - less than 8 Usual Shift Hours - greater than 8 Usual Shift Hours - various Don't Choose Work Days Don't Choose Work Hours Childcare Support

Ontario Ontario Ontario Hospital Hospital Hospital Union Member Full-Time Full-Time Day Shift Direct Care Shift Changes None Shift Changes None Usual Shift Hours - 8

0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.00 0.01 0.00 0.01 0.01

1.57 1.19 2.36 -0.75 -0.56 -0.81 1.42 -0.10 0.10 1.27 -1.21 -0.05

0.12 0.23 0.02 0.46 0.57 0.42 0.16 0.92 0.92 0.21 0.23 0.96

0.00 -0.01 0.00 -0.02 -0.02 -0.02 0.00 -0.01 -0.01 0.00 -0.02 -0.01

0.03 0.03 0.04 0.01 0.01 0.01 0.03 0.01 0.02 0.02 0.00 0.01

0.03

0.01

2.02

0.04

0.00

0.05

-0.01

0.01

-0.88

0.38

-0.02

0.01

Usual Shift Hours - 8

-0.01

0.01

-1.25

0.21

-0.02

0.00

Usual Shift Hours - 8 Choose Work Days Choose Work Hours No Childcare Support

-0.01 -0.01 0.01 0.00

0.01 0.01 0.00 0.01

-0.84 -1.42 1.61 -0.13

0.40 0.16 0.11 0.89

-0.02 -0.02 0.00 -0.02

0.01 0.00 0.02 0.01

0.00 0.00 0.00 0.00 0.00 -0.02

0.00 0.00 0.00 0.00 0.00 0.01

1.85 0.49 1.24 1.44 0.92 -1.75

0.06 0.63 0.21 0.15 0.36 0.08

0.00 0.00 0.00 0.00 0.00 -0.03

0.00 0.00 0.00 0.01 0.00 0.00

Role Overload Skill Discretion Decision Autonomy Job Insecurity Social Support Job Strain

Anshoo Kamal

142

95% Confidence Interval

Sept. 21, 2011

Final

Appendix 11: Intent to Quit Model – Licensed Practical Nurses Coefficient Estimates Number of obs Wald chi2 (141) Prob > chi2 Log pseudolikelihood

6,699 769.11 0.000 -28,546.954

Outcome = Leave Nursing; Base Outcome = Stay Explanatory Variable

Reference Variable Individual Characteristics Male Female Age - z

0.40 0.23 0.19 1.36 0.26 -0.04

0.19 0.20 0.16 0.18 0.13 0.19

2.11 1.12 1.14 7.76 2.01 -0.23

0.04** 0.26 0.25 0.00** 0.04** 0.82

0.03 -0.17 -0.13 1.02 0.01 -0.41

0.78 0.63 0.51 1.71 0.51 0.33

-0.17

0.19

-0.90

0.37

-0.54

0.20

-0.04

0.16

-0.24

0.81

-0.35

0.28

0.06

0.20

0.30

0.77

-0.34

0.46

0.09

0.13

0.66

0.51

-0.18

0.35

0.05

0.15

0.32

0.75

-0.24

0.33

-0.04

0.13

-0.29

0.77

-0.29

0.22

-0.14

0.18

-0.78

0.43

-0.50

0.21

0.25

0.15

1.69

0.09*

-0.04

0.55

-0.49 0.67

0.19 0.24

-2.60 2.83

0.01** 0.01**

-0.85 0.21

-0.12 1.14

0.76

0.15

5.17

0.00**

0.47

1.05

-0.07

0.19

-0.35

0.73

-0.43

0.30

-0.21 -0.11 0.92 -0.08

0.24 0.15 0.37 0.17

-0.88 -0.71 2.45 -0.45

0.38 0.48 0.01** 0.65

-0.68 -0.41 0.18 -0.41

0.26 0.19 1.65 0.25

143

95% Confidence Interval

Sept. 21, 2011

Final

Explanatory Variable Manitoba Saskatchewan Alberta British Columbia Part-Time Casual Long-Term Care Community Other Non Direct Care Role Don't Choose Work Days Don't Choose Work Hours Non Day Shift Childcare Available Shift Changes over 2 Weeks - one or more Shift Changes over 2 Weeks - did not work Usual Shift Hours - < 8 Usual Shift Hours - > 8 Usual Shift Hours – Various Role Overload Skill Discretion Decision Authority Job Insecurity Social Support Job Strain _cons

Reference Variable Ontario Ontario Ontario Hospital Hospital Hospital Unionized Full-Time Full-Time Direct Care Choose Work Days

Coefficient

Std. Err

z

P>z

95% Confidence Interval -0.33 0.42 -0.27 0.44 -0.45 0.23 -0.09 0.59 -0.02 0.48 -0.14 0.51 -0.47 0.02 -1.06 -0.23 -0.40 0.70 -1.07 0.26 -0.29 0.35

0.05 0.09 -0.11 0.25 0.23 0.19 -0.22 -0.64 0.15 -0.40 0.03

0.19 0.18 0.18 0.17 0.13 0.17 0.13 0.21 0.28 0.34 0.16

0.26 0.48 -0.63 1.46 1.78 1.12 -1.77 -3.06 0.52 -1.20 0.17

0.80 0.63 0.53 0.15 0.08* 0.27 0.08* 0.00** 0.60 0.23 0.86

Choose Work Hours Day Shift No Child Care Shift Change over 2 Weeks - No Change Shift Change over 2 Weeks - No Change Usual Shift Hours = 8 Usual Shift Hours = 8 Usual Shift Hours = 8

0.00

0.15

0.00

1.00

-0.30

0.30

-0.08 0.13 -0.13

0.13 0.23 0.13

-0.63 0.60 -0.99

0.53 0.55 0.32

-0.33 -0.31 -0.39

0.17 0.58 0.13

0.34

0.17

1.95

0.05*

0.00

0.68

-0.08

0.26

-0.29

0.77

-0.58

0.43

-0.13

0.15

-0.84

0.40

-0.42

0.17

0.00

0.22

0.02

0.98

-0.42

0.43

0.04 0.11 0.02 -0.01 0.10 -0.36 -3.99

0.01 0.04 0.04 0.05 0.03 0.22 0.37

3.32 3.18 0.44 -0.12 3.82 -1.65 -10.89

0.00** 0.00** 0.66 0.91 0.00** 0.10 0.00

0.02 0.04 -0.05 -0.11 0.05 -0.79 -4.71

0.07 0.18 0.09 0.10 0.15 0.07 -3.27

Outcome = Switch Jobs; Base Outcome = Stay Explanatory Variable

Reference Variable

Individual Characteristics Male Female Age - z

-0.09 0.43 -0.30 -0.48 0.25

0.16 0.13 0.13 0.16 0.11

-0.54 3.42 -2.41 -2.96 2.31

0.59 0.00** 0.02** 0.00** 0.02**

144

95% Confidence Interval

-0.41 0.18 -0.55 -0.80 0.04

Sept. 21, 2011

0.23 0.68 -0.06 -0.16 0.46

Final

Explanatory Variable

Reference Variable

Have Children - Age 5 and Under Have Children - Age 6-11 Have Children - Age 12-17 Health Status - PoorFair Health Status - Very Good Health Status – Excellent Household Income =$100,000 Have Non-Nursing Education Have Multiple Jobs Have a Non-Nursing Job Work Characteristics Job Dissatisfied (DUMMY) Nurse Dissatisfied (DUMMY) No Union Atlantic Provinces Territories Quebec Manitoba Saskatchewan Alberta British Columbia Part-Time Casual Long-Term Care Community Other Non Direct Care Role Don't Choose Work Days Don't Choose Work Hours Non Day Shift Childcare Available Shift Changes over 2 Weeks - one or more

Anshoo Kamal

Coefficient

Std. Err

Z

P>z

No

-0.23

0.14

-1.69

0.09*

-0.50

0.04

No

-0.11

0.12

-0.94

0.35

-0.35

0.12

No

-0.18

0.11

-1.59

0.11

-0.40

0.04

Health Status – Good Health Status – Good Health Status – Good Household Income - $50,000-$99,999 Household Income - $50,000-$99,999 No

0.25

0.18

1.40

0.16

-0.10

0.61

0.06

0.11

0.53

0.60

-0.15

0.27

0.00

0.12

0.02

0.99

-0.23

0.24

-0.08

0.10

-0.77

0.44

-0.27

0.12

0.10

0.14

0.68

0.50

-0.18

0.37

0.27

0.11

2.42

0.02**

0.05

0.48

One Job No

0.35 -0.17

0.11 0.18

3.08 -0.91

0.00** 0.36

0.13 -0.52

0.57 0.19

Satisfied with Job

0.89

0.11

7.72

0.00**

0.66

1.11

Satisfied with Nursing Unionized Ontario Ontario Ontario Ontario Ontario Ontario Ontario Full-Time Full-Time Hospital Hospital Hospital Direct Care Choose Work Days Choose Work Hours Day Shift No Child Care Shift Change over 2 Weeks - No

-0.28

0.15

-1.86

0.06*

-0.58

0.02

0.30 -0.13 0.46 -0.24 0.42 0.44 0.21 0.40 0.06 -0.05 0.02 0.12 0.05 0.51 0.08

0.14 0.13 0.26 0.14 0.14 0.14 0.13 0.14 0.10 0.14 0.11 0.17 0.19 0.26 0.13

2.08 -1.03 1.73 -1.65 3.05 3.16 1.61 2.87 0.59 -0.39 0.18 0.70 0.29 1.95 0.65

0.04** 0.30 0.08* 0.10 0.00** 0.00** 0.11 0.00** 0.56 0.69 0.86 0.48 0.77 0.05* 0.52

0.02 -0.39 -0.06 -0.52 0.15 0.17 -0.05 0.13 -0.14 -0.32 -0.19 -0.22 -0.31 0.00 -0.17

0.58 0.12 0.98 0.04 0.69 0.72 0.47 0.67 0.25 0.21 0.23 0.46 0.42 1.02 0.34

-0.18

0.13

-1.44

0.15

-0.43

0.07

-0.02 0.21 -0.12

0.11 0.17 0.10

-0.20 1.24 -1.19

0.84 0.21 0.23

-0.23 -0.12 -0.32

0.19 0.55 0.08

145

95% Confidence Interval

Sept. 21, 2011

Final

Explanatory Variable

Shift Changes over 2 Weeks - did not work Usual Shift Hours - < 8 Usual Shift Hours - > 8 Usual Shift Hours – Various Role Overload Skill Discretion Decision Authority Job Insecurity Social Support Job Strain _cons

Reference Variable Change Shift Change over 2 Weeks - No Change Usual Shift Hours =8 Usual Shift Hours =8 Usual Shift Hours =8

Coefficient

Std. Err

Z

P>z

95% Confidence Interval

0.48

0.16

2.93

0.00**

0.16

0.79

0.10

0.19

0.54

0.59

-0.26

0.46

0.12

0.12

1.03

0.30

-0.11

0.35

0.12

0.17

0.66

0.51

-0.23

0.46

0.02 0.07 0.00 0.09 0.04 0.15 -3.11

0.01 0.03 0.03 0.04 0.02 0.18 0.28

2.08 2.42 -0.14 1.99 1.79 0.85 -11.22

0.04** 0.02** 0.89 0.05* 0.07* 0.40 0.00

0.00 0.01 -0.07 0.00 0.00 -0.20 -3.65

0.04 0.12 0.06 0.17 0.09 0.51 -2.57

Outcome = At Risk of Leaving; Base Outcome = Stay Explanatory Variable

Reference Variable

Individual Characteristics Male Female Age - z

0.05 -0.03 -0.11 0.30 0.33 0.02

0.31 0.20 0.19 0.20 0.16 0.19

0.18 -0.15 -0.57 1.50 2.05 0.10

0.86 0.88 0.57 0.13 0.04** 0.92

-0.55 -0.43 -0.47 -0.09 0.01 -0.35

0.66 0.37 0.26 0.70 0.64 0.38

-0.22

0.17

-1.27

0.21

-0.55

0.12

-0.20

0.18

-1.11

0.27

-0.54

0.15

0.07

0.22

0.32

0.75

-0.36

0.50

0.20

0.14

1.39

0.16

-0.08

0.49

-0.07

0.18

-0.37

0.71

-0.42

0.28

-0.04

0.16

-0.28

0.78

-0.35

0.27

-0.17

0.22

-0.80

0.43

-0.60

0.25

146

95% Confidence Interval

Sept. 21, 2011

Final

Explanatory Variable

Reference Variable

Have Non-Nursing Education Have Multiple Jobs Have a Non-Nursing Job Work Characteristics Job Dissatisfied (DUMMY) Nurse Dissatisfied (DUMMY) No Union Atlantic Provinces Territories Quebec Manitoba Saskatchewan Alberta British Columbia Part-Time Casual Long-Term Care Community Other Non Direct Care Role Don't Choose Work Days Don't Choose Work Hours Non Day Shift Childcare Available Shift Changes over 2 Weeks - one or more Shift Changes over 2 Weeks - did not work Usual Shift Hours 8 Usual Shift Hours – Various Role Overload Skill Discretion Decision Authority Job Insecurity

Anshoo Kamal

Coefficient

Std. Err

Z

P>z

No

0.17

0.17

1.04

0.30

-0.15

0.50

One Job No

-0.14 0.46

0.17 0.22

-0.83 2.07

0.41 0.04**

-0.47 0.03

0.19 0.90

Satisfied with Job

0.71

0.15

4.64

0.00**

0.41

1.01

Satisfied with Nursing Unionized Ontario Ontario Ontario Ontario Ontario Ontario Ontario Full-Time Full-Time Hospital Hospital Hospital Direct Care

0.23

0.18

1.29

0.20

-0.12

0.58

0.23 0.11 0.77 0.13 0.50 0.49 0.43 0.61 0.43 0.40 0.18 0.04 0.07 -0.02

0.14 0.19 0.46 0.22 0.22 0.21 0.20 0.21 0.15 0.18 0.14 0.21 0.22 0.29

1.61 0.56 1.69 0.59 2.23 2.36 2.13 2.96 2.85 2.23 1.26 0.21 0.32 -0.07

0.11 0.57 0.09* 0.56 0.03** 0.02** 0.03** 0.00** 0.00** 0.03** 0.21 0.84 0.75 0.94

-0.05 -0.26 -0.12 -0.30 0.06 0.08 0.03 0.20 0.14 0.05 -0.10 -0.36 -0.36 -0.60

0.50 0.47 1.67 0.57 0.93 0.89 0.82 1.01 0.73 0.76 0.46 0.45 0.50 0.55

0.22

0.21

1.07

0.29

-0.19

0.63

-0.19

0.17

-1.07

0.29

-0.53

0.16

-0.41 0.31 0.16

0.14 0.23 0.14

-2.86 1.36 1.15

0.00** 0.17 0.25

-0.68 -0.14 -0.11

-0.13 0.75 0.43

0.68

0.20

3.37

0.00**

0.29

1.08

-0.39

0.27

-1.45

0.15

-0.91

0.14

-0.24

0.15

-1.56

0.12

-0.54

0.06

-0.06

0.22

-0.28

0.78

-0.49

0.37

0.02 0.04 -0.01 0.01

0.02 0.04 0.04 0.06

1.51 1.11 -0.38 0.18

0.13 0.27 0.71 0.86

-0.01 -0.03 -0.09 -0.10

0.05 0.11 0.06 0.12

Choose Work Days Choose Work Hours Day Shift No Child Care Shift Change over 2 Weeks - No Change Shift Change over 2 Weeks - No Change Usual Shift Hours =8 Usual Shift Hours =8 Usual Shift Hours =8

147

95% Confidence Interval

Sept. 21, 2011

Final

Explanatory Variable

Reference Variable

Social Support Job Strain _cons

Coefficient

Std. Err

Z

P>z

0.03 0.18 -4.08

0.03 0.27 0.31

1.20 0.67 -13.14

0.23 0.50 0.00

95% Confidence Interval -0.02 -0.35 -4.68

0.09 0.70 -3.47

Appendix 12: Intent to Quit Model – Licensed Practical Nurses Average Marginal Effects Outcome = Leaving; Base Outcome = Stay Explanatory Variable

Reference Variable

Avg. Marginal Effect

Std. Err.

Z

P>z

95% Confidence Interval

Individual Characteristics Male

Female

0.03

0.02

1.88

0.06*

0.00

0.06

Age -z

95% Confidence Interval

Nursing No Union

Unionized

-0.02

0.01

-1.33

0.18

-0.04

0.01

Atlantic Provinces

Ontario

-0.01

0.01

-0.67

0.50

-0.02

0.01

Territories

Ontario

0.07

0.05

1.54

0.13

-0.02

0.16

Quebec

Ontario

0.00

0.01

-0.31

0.75

-0.02

0.02

Manitoba

Ontario

0.00

0.01

-0.37

0.71

-0.03

0.02

Saskatchewan

Ontario

0.00

0.01

-0.19

0.85

-0.02

0.02

Alberta

Ontario

-0.01

0.01

-1.13

0.26

-0.03

0.01

British Columbia

Ontario

0.01

0.01

0.75

0.45

-0.01

0.03

Part-Time

Full-Time

0.01

0.01

1.44

0.15

0.00

0.03

Casual

Full-Time

0.01

0.01

0.93

0.35

-0.01

0.03

Long-Term Care

Hospital

-0.01

0.01

-1.99

0.05*

-0.03

0.00

Community

Hospital

-0.03

0.01

-4.43

0.00**

-0.04

-0.02

Other

Hospital

0.01

0.02

0.46

0.65

-0.03

0.05

Non Direct Care Role Don't Choose Work Days Don't Choose Work Hours Not Days Shift

Direct Care

-0.02

0.01

-2.03

0.04**

-0.05

0.00

Choose Work Days Choose Work Hours Day Shift

0.00

0.01

0.01

1.00

-0.02

0.02

0.00

0.01

0.29

0.77

-0.01

0.02

0.00

0.01

-0.38

0.71

-0.02

0.01

Childcare Available Shift Changes over 2 Weeks One or More Shift changes over 2 Weeks - did not work Usual Shift Hours - 8 Usual Shift Hours – Various Role Overload

No Child Care

0.00

0.01

0.33

0.74

-0.02

0.03

Shift Change over 2 Weeks - No Change Shift Change over 2 Weeks - No Change Usual Shift Hours =8 Usual Shift Hours =8 Usual Shift Hours =8

-0.01

0.01

-0.98

0.33

-0.02

0.01

0.01

0.01

1.09

0.28

-0.01

0.04

0.00

0.01

-0.29

0.78

-0.03

0.02

-0.01

0.01

-0.93

0.35

-0.02

0.01

0.00

0.01

-0.05

0.96

-0.03

0.02

0.00

0.00

2.95

0.00**

0.00

0.00

Skill Discretion

0.01

0.00

2.91

0.00**

0.00

0.01

Decision Autonomy Job Insecurity

0.00

0.00

0.50

0.62

0.00

0.01

0.00

0.00

-0.40

0.69

-0.01

0.00

Social Support

0.01

0.00

3.51

0.00**

0.00

0.01

Job Strain

-0.02

0.01

-1.86

0.06*

-0.05

0.00

Anshoo Kamal

149

Sept. 21, 2011

Final

Outcome = Switch Jobs; Base Outcome = Stay Explanatory Variable

Reference Variable

Avg. Marginal Effect

Std. Err.

Z

P>z

-0.01

0.02

-0.90

0.37

95% Confidence Interval

Individual Characteristics Male

Female

Age -z

Long-Term Care

95% Confidence Interval

Hospital

0.00

0.01

0.26

0.80

-0.02

0.02

Community

Hospital

0.02

0.02

0.90

0.37

-0.02

0.06

Other

Hospital

0.00

0.02

0.20

0.84

-0.03

0.04

Non Direct Care Role Don't Choose Work Days Don't Choose Work Hours Not Days Shift

Direct Care

0.07

0.04

1.77

0.08*

-0.01

0.15

Choose Work Days Choose Work Hours Day Shift

0.01

0.01

0.56

0.58

-0.02

0.03

-0.02

0.01

-1.32

0.19

-0.05

0.01

0.00

0.01

0.12

0.90

-0.02

0.02

Childcare Available

No Child Care

0.02

0.02

1.01

0.32

-0.02

0.06

Shift Changes over 2 Weeks - One or More Shift changes over 2 Weeks - did not work Usual Shift Hours 8 Usual Shift Hours – Various Role Overload

Shift Change over 2 Weeks - No Change Shift Change over 2 Weeks - No Change Usual Shift Hours =8 Usual Shift Hours =8 Usual Shift Hours =8

-0.01

0.01

-1.24

0.22

-0.03

0.01

0.05

0.02

2.18

0.03**

0.00

0.09

0.01

0.02

0.66

0.51

-0.03

0.06

0.02

0.01

1.23

0.22

-0.01

0.04

0.01

0.02

0.68

0.50

-0.02

0.05

0.00

0.00

1.64

0.10

0.00

0.00

Skill Discretion

0.01

0.00

2.03

0.04**

0.00

0.01

Decision Autonomy Job Insecurity

0.00

0.00

-0.16

0.87

-0.01

0.01

0.01

0.00

2.05

0.04**

0.00

0.02

Social Support

0.00

0.00

1.35

0.18

0.00

0.01

Job Strain

0.02

0.02

1.00

0.32

-0.02

0.05

Outcome = At Risk; Base Outcome = Stay Explanatory Variable

Reference Variable

Avg. Marginal Effect

Std. Err.

Z

P>z

95% Confidence Interval

Individual Characteristics Male

Female

0.00

0.01

0.04

0.97

-0.02

0.02

Age -z

Have Children Age 6 – 11 Have Children Age 12-17 Health Status Poor-Fair Health Status Very Good Health Status – Excellent Household Income - = $100,000 Have Non-Nursing Education Have Multiple Jobs

No

-0.01

0.01

-1.13

0.26

-0.02

0.00

No

-0.01

0.01

-0.98

0.33

-0.02

0.01

Health Status - Good

0.00

0.01

0.06

0.95

-0.01

0.02

Health Status – Good Health Status – Good Household Income $50,000-$99,999 Household Income $50,000-$99,999 No

0.01

0.01

1.22

0.22

0.00

0.02

0.00

0.01

-0.43

0.67

-0.01

0.01

0.00

0.01

-0.17

0.87

-0.01

0.01

-0.01

0.01

-0.91

0.36

-0.02

0.01

0.00

0.01

0.53

0.60

-0.01

0.02

-0.01

0.01

-1.00

0.32

-0.02

0.01

Have a NonNo Nursing Job Work Characteristics

0.02

0.01

1.44

0.15

-0.01

0.04

Job Dissatisfied (DUMMY) Nurse Dissatisfied (DUMMY) No Union

Satisfied with Job

0.02

0.01

2.47

0.01**

0.00

0.03

Satisfied with Nursing Unionized

0.01

0.01

1.44

0.15

0.00

0.03

0.01

0.01

1.31

0.19

0.00

0.02

Atlantic Provinces

Ontario

0.01

0.01

0.74

0.46

-0.01

0.02

Territories

Ontario

0.03

0.03

0.88

0.38

-0.04

0.09

Quebec

Ontario

0.01

0.01

0.80

0.42

-0.01

0.02

Manitoba

Ontario

0.02

0.01

1.56

0.12

0.00

0.04

Saskatchewan

Ontario

0.02

0.01

1.61

0.11

0.00

0.04

Alberta

Ontario

0.02

0.01

1.73

0.08*

0.00

0.04

British Columbia

Ontario

0.02

0.01

2.03

0.04**

0.00

0.05

Part-Time

Full-Time

0.02

0.01

2.32

0.02**

0.00

0.03

Casual

Full-Time

0.02

0.01

1.81

0.07*

0.00

0.04

Long-Term Care

Hospital

0.01

0.01

1.41

0.16

0.00

0.02

Community

Hospital

0.00

0.01

0.38

0.71

-0.01

0.02

Other

Hospital

0.00

0.01

0.19

0.85

-0.01

0.02

Non Direct Care Role Don't Choose Work Days Don't Choose Work Hours Not Days Shift

Direct Care

0.00

0.01

-0.35

0.72

-0.02

0.01

Choose Work Days

0.01

0.01

1.10

0.27

-0.01

0.02

Choose Work Hours

-0.01

0.01

-0.84

0.40

-0.02

0.01

Day Shift

-0.02

0.01

-2.58

0.01*

-0.03

0.00

Childcare Available

No Child Care

0.01

0.01

0.98

0.33

-0.01

0.03

Anshoo Kamal

One Job

152

95% Confidence Interval

Sept. 21, 2011

Final

Explanatory Variable

Reference Variable

Avg. Marginal Effect

Std. Err.

Z

P>z

95% Confidence Interval

Shift Changes over 2 Weeks - One or More Shift changes over 2 Weeks - did not work Usual Shift Hours 8 Usual Shift Hours – Various Role Overload

Shift Change over 2 Weeks - No Change

0.01

0.01

1.39

0.17

0.00

0.02

Shift Change over 2 Weeks - No Change

0.03

0.01

2.10

0.04**

0.00

0.05

Usual Shift Hours = 8

-0.01

0.01

-1.98

0.05*

-0.02

0.00

Usual Shift Hours = 8

-0.01

0.00

-1.84

0.07*

-0.02

0.00

Usual Shift Hours = 8

0.00

0.01

-0.41

0.68

-0.02

0.01

0.00

0.00

0.92

0.36

0.00

0.00

Skill Discretion

0.00

0.00

0.39

0.70

0.00

0.00

Decision Authority

0.00

0.00

-0.42

0.68

0.00

0.00

Job Insecurity

0.00

0.00

-0.10

0.92

0.00

0.00

Social Support

0.00

0.00

0.52

0.60

0.00

0.00

Job Strain

0.01

0.01

0.76

0.45

-0.01

0.03

Anshoo Kamal

153

Sept. 21, 2011

Final

Appendix 13: Intent to Quit Model for RNs with Limited Variables # of Obs Wald chi2(81) Prob>chi2 Log LL

9,353 780.54 0.000 -137929

Outcome = Leave; Base Outcome = Stay Explanatory Variables

Reference Variables

Coefficient

Std. Err

z

P>z

Male Age -z

0.93 -3.40

0.15 0.19

6.20 -17.54

0.00** 0.00

95% Confidence Interval 0.63 1.22 -3.78 3.02

Outcome = Switch Jobs; Base Outcome = Stay Explanatory Variables

Reference Variables

Coefficient

Std. Err

z

P>z

Male Age - chi2 Pseudo R2 Log pseudolikelihood

8832 476.45 0.000 0.1804 -64508.628

Explanatory Variable

Reference Variable

Coef.

Std. Err.

z

P>z

Predicted Binary Nurse Dissatisfaction Male Age - less than 35 Age -45-54 Age - 55 or older Not Married Have Education Baccalaureate or Higher

Predicted Nurse Satisfied Female Age - 35-44 Age - 35-44 Age - 35-44 Married Have Diploma/Certificate Level Education Household Income $50,000-$99,999 Household Income $50,000-$99,999 Ontario Ontario Ontario Ontario Ontario Ontario Ontario Union Member Full-Time Casual Direct Care Chose Work Days Chose Work Hours

0.36

0.09

3.79

0.00

-0.04 -0.15 0.07 0.17 0.11 0.02

0.13 0.09 0.07 0.09 0.07 0.06

-0.30 -1.74 1.02 1.96 1.55 0.39

0.77 0.08 0.31 0.05 0.12 0.70

-0.29 -0.31 -0.07 0.00 -0.03 -0.10

0.21 0.02 0.21 0.34 0.25 0.15

-0.05

0.10

-0.50

0.62

-0.24

0.14

-0.01

0.06

-0.19

0.85

-0.14

0.11

-0.11 -0.10 0.11 -0.12 -0.06 -0.25 -0.05 -0.05 0.11 0.24 -0.21 0.12 0.29

0.08 0.16 0.09 0.10 0.09 0.10 0.09 0.09 0.07 0.10 0.10 0.08 0.09

-1.52 -0.64 1.26 -1.19 -0.64 -2.53 -0.53 -0.55 1.65 2.35 -2.13 1.37 3.21

0.13 0.52 0.21 0.24 0.53 0.01 0.59 0.59 0.10 0.02 0.03 0.17 0.00

-0.26 -0.42 -0.06 -0.31 -0.23 -0.44 -0.21 -0.22 -0.02 0.04 -0.40 -0.05 0.11

0.03 0.21 0.28 0.08 0.12 -0.06 0.12 0.12 0.23 0.43 -0.02 0.28 0.47

0.18 -0.12 -0.16

0.07 0.09 0.07

2.61 -1.31 -2.23

0.01 0.19 0.03

0.05 -0.30 -0.30

0.32 0.06 -0.02

0.27

0.10

2.72

0.01

0.08

0.47

-0.11

0.15

-0.72

0.47

-0.39

0.18

0.16

0.07

2.23

0.03

0.02

0.31

Household Income - less than $50,000 Household Income greater than $100,000 Atlantic Territories Quebec Manitoba Saskatchewan Alberta British Columbia Not a Union Member Part-Time Casual Non Direct Care Didn't Choose Work Days Didn't Choose Work Hours Non Day Shift Offers Childcare Support Past Two Weeks - one or more changes Past Two Week - did not work Usual Shift Hours - less than eight Usual Shift Hours greater than eight

Anshoo Kamal

Day Shift No Childcare Support Past Two Weeks - No Change Past Two Weeks - No Change Usual Shift Hours – eight Usual Shift Hours – eight

157

95% Confidence Interval 0.17 0.54

Sept. 21, 2011

Final

Explanatory Variable

Reference Variable

Coef.

Std. Err.

z

P>z

Usual Shift Hours – various Role Overload Skill Discretion Job Insecurity Job Strain _cons

Usual Shift Hours – eight

0.07

0.12

0.56

0.58

0.06 0.01 0.08 0.93 -3.72

0.01 0.02 0.03 0.12 0.19

8.15 0.71 2.72 8.04 -19.58

0.00 0.48 0.01 0.00 0

95% Confidence Interval -0.17 0.31 0.05 -0.02 0.02 0.71 -4.09

0.07 0.05 0.13 1.16 -3.35

Appendix 15: Job Dissatisfaction for RNs Average Marginal Effects at the 0.20 Threshold Explanatory Variables

Reference Variables

Predicted Nurse Dissatisfaction Male Age - less than 35 Age - age 45-54 Age - 55 or older Not Married Have Education Baccalaureate or Higher Household Income less than $50,000 Household Income greater than $100,000 Atlantic Territories Quebec Manitoba Saskatchewan Alberta British Columbia Not a Union Member Part-Time Casual Non Direct Care Didn't Choose Work Days Didn't Choose Work Hours Non Day Shift Offers Childcare Support Past Two Weeks - one or more changes Past Two Week - did

Predicted Nurse Satisfied Female Age - 35-44 Age - 35-44 Age - 35-44 Married Have Diploma/Certificate Level Education Household Income $50,000-$99,999 Household Income $50,000-$99,999 Ontario Ontario Ontario Ontario Ontario Ontario Ontario Union Member Full-Time Full-Time Direct Care Chose Work Days

Anshoo Kamal

Average Marginal Effect 0.06

Std. Err.

Z

P>z

0.02

3.79

0.001

0.02

0.10

-0.01 -0.02 0.01 0.03 0.02 0.00

0.02 0.01 0.01 0.01 0.01 0.01

-0.30 -1.74 1.02 1.96 1.55 0.39

0.77 0.08 0.31 0.05 0.12 0.70

-0.04 -0.04 -0.01 0.001 0.001 -0.01

0.03 0.00 0.03 0.05 0.04 0.02

-0.01

0.01

-0.50

0.62

-0.03

0.02

0.00

0.01

-0.19

0.85

-0.02

0.02

-0.01 -0.01 0.02 -0.01 -0.01 -0.03 -0.01 -0.01 0.02 0.04 -0.03 0.02

0.01 0.02 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.02 0.01 0.01

-1.52 -0.64 1.26 -1.19 -0.64 -2.53 -0.53 -0.55 1.65 2.35 -2.13 1.37

0.13 0.52 0.21 0.24 0.53 0.01 0.59 0.59 0.10 0.02 0.03 0.17

-0.03 -0.05 -0.01 -0.04 -0.03 -0.05 -0.03 -0.03 0.001 0.001 -0.05 -0.01

0.00 0.02 0.04 0.01 0.02 -0.01 0.02 0.02 0.03 0.07 0.00 0.04

Chose Work Hours

0.04

0.01

3.21

0.00

0.02

0.06

Day Shift No Childcare Support

0.03 -0.02

0.01 0.01

2.61 -1.31

0.01 0.19

0.01 -0.04

0.04 0.01

Past Two Weeks - No Change Past Two Weeks - No

-0.02

0.01

-2.23

0.03

-0.04

0.001

0.04

0.02

2.72

0.01

0.01

0.08

158

95% Confidence Interval

Sept. 21, 2011

Final

Explanatory Variables

Reference Variables

not work Usual Shift Hours less than eight Usual Shift Hours greater than eight Usual Shift Hours various Role Overload Skill Discretion Job Insecurity Job Strain obs. P pred. P

Change Usual Shift Hours – eight Usual Shift Hours – eight Usual Shift Hours – eight

Average Marginal Effect

Std. Err.

Z

P>z

95% Confidence Interval

-0.01

0.02

-0.72

0.47

-0.05

0.02

0.02

0.01

2.23

0.03

0.00

0.05

0.01

0.02

0.56

0.58

-0.03

0.05

0.01 0.00 0.01 0.13

0.00 0.00 0.00 0.02

8.15 0.71 2.72 8.04

0.00 0.48 0.01 0.00

0.01 0.00 0.00 0.10

0.01 0.01 0.02 0.16

0.112 0.073

Appendix 16: Nurse Dissatisfaction Results for RNs 0.20 Threshold Number of obs Wald chi2(27) Prob > chi2 Pseudo R2 Log pseudolikelihood

8833 205.3 0 0.0648 -67460.5

Explanatory Variables

Reference Variable

Coef.

Std. Err.

z

P>z

Predicted Job Dissatisfaction Male Age - less than 35 Age - 45-54 Age - 55 or older Not Married Have Children - Under 5 Years Have Children - 6-11 Have Children 12-17 Health Status - Poor-Fair Health Status - Very Good Health Status - Excellent Have Education Baccalaureate or Higher Have Non-Nursing Education Have Non-Nursing Job Atlantic

Predicted Job Satisfied

0.37

0.08

4.72

0.00

95% Confidence Interval 0.22 0.52

Female Age - 35-44 Age - 35-44 Age - 35-44 Married No Children

0.04 -0.23 -0.03 0.02 0.06 0.00

0.13 0.09 0.08 0.09 0.06 0.08

0.27 -2.65 -0.39 0.20 0.99 -0.03

0.78 0.01 0.70 0.84 0.32 0.97

-0.22 -0.40 -0.18 -0.17 -0.06 -0.17

0.29 -0.06 0.12 0.20 0.19 0.16

No Children No Children Health Status - Good Health Status - Good Health Status - Good Have Education Diploma/Certificate No Non-Nursing Education No Non-Nursing Job Ontario

-0.06 0.01 0.08 -0.19 -0.14 -0.06

0.08 0.07 0.10 0.07 0.07 0.06

-0.80 0.21 0.74 -2.78 -1.85 -0.94

0.43 0.83 0.46 0.01 0.06 0.35

-0.22 -0.12 -0.13 -0.32 -0.28 -0.18

0.09 0.15 0.28 -0.06 0.01 0.06

0.11

0.07

1.54

0.12

-0.03

0.24

0.16 -0.15

0.11 0.07

1.41 -2.20

0.16 0.03

-0.06 -0.29

0.37 -0.02

Anshoo Kamal

159

Sept. 21, 2011

Final

Explanatory Variables

Reference Variable

Coef.

Std. Err.

z

P>z

Territories Quebec Manitoba Saskatchewan Alberta British Columbia Long-Term Care Community Other Decision Authority Social Support _cons

Ontario Ontario Ontario Ontario Ontario Ontario Hospital Hospital Hospital

-0.02 0.10 0.04 -0.01 -0.08 0.07 -0.07 0.07 0.07 0.06 0.04 -1.62

0.15 0.08 0.09 0.08 0.09 0.08 0.08 0.08 0.08 0.02 0.01 0.13

-0.15 1.28 0.51 -0.06 -0.85 0.83 -0.91 0.92 0.84 4.19 2.61 -12.82

0.88 0.20 0.61 0.95 0.39 0.41 0.36 0.36 0.40 0.00 0.01 0.00

95% Confidence Interval -0.31 0.27 -0.05 0.25 -0.13 0.22 -0.17 0.16 -0.25 0.10 -0.09 0.23 -0.22 0.08 -0.08 0.22 -0.09 0.22 0.03 0.10 0.01 0.06 -1.87 -1.37

Appendix 17: Nurse Dissatisfaction Average Marginal Effects for RNs 0.20 Threshold Explanatory Variable

Reference Variable

Std. Err. 0.02

z

P>z

Predicted Job Satisfied

Avg. M.E. 0.07

Predicted Job Dissatisfaction Male Age - less than 35

4.72

0.00

0.04

0.10

Female Age - 35-44

0.01 -0.03

0.02 0.01

0.27 -2.65

0.78 0.01

-0.04 -0.06

Age - 45-54 Age - 55 or older Not Married Have Children - Under 5 Years Have Children - 6-11 Have Children 12-17 Health Status - Poor-Fair Health Status - Very Good

Age - 35-44 Age - 35-44 Married No Children

0.00 0.00 0.01 0.00

0.01 0.02 0.01 0.01

-0.39 0.20 0.99 -0.03

0.70 0.84 0.32 0.97

-0.03 -0.03 -0.01 -0.03

0.05 0.01 0.02 0.03 0.03 0.03

No Children No Children Health Status - Good Health Status - Good

-0.01 0.00 0.01 -0.03

0.01 0.01 0.02 0.01

-0.80 0.21 0.74 -2.78

0.43 0.83 0.46 0.01

-0.03 -0.02 -0.02 -0.05

Health Status - Excellent Have Education Baccalaureate or Higher Have Non-Nursing Education Have Non-Nursing Job Atlantic Territories Quebec Manitoba Saskatchewan Alberta British Columbia Long-Term Care

Health Status - Good Have Education Diploma/Certificate No Non-Nursing Education No Non-Nursing Job Ontario Ontario Ontario Ontario Ontario Ontario Ontario Hospital

-0.02 -0.01

0.01 0.01

-1.85 -0.94

0.06 0.35

-0.04 -0.03

0.01 0.02 0.05 0.01 0.00 0.01

0.02

0.01

1.54

0.12

-0.01

0.04

0.03 -0.02 0.00 0.02 0.01 0.00 -0.01 0.01 -0.01

0.02 0.01 0.02 0.01 0.01 0.01 0.01 0.01 0.01

1.41 -2.20 -0.15 1.28 0.51 -0.06 -0.85 0.83 -0.91

0.16 0.03 0.88 0.20 0.61 0.95 0.39 0.41 0.36

-0.01 -0.04 -0.05 -0.01 -0.02 -0.03 -0.04 -0.02 -0.03

0.07 0.00 0.04 0.04 0.04 0.03 0.01 0.04 0.01

Anshoo Kamal

160

95% C.I.

Sept. 21, 2011

Final

Explanatory Variable

Reference Variable

Community Other Decision Authority Social Support obs. P 0.09812 pred. P .0859325

Hospital Hospital

Anshoo Kamal

161

Avg. M.E. 0.01 0.01 0.01 0.01

Std. Err. 0.01 0.01 0.00 0.00

z

P>z

0.92 0.84 4.19 2.61

0.36 0.40 0.00 0.01

95% C.I. -0.01 -0.02 0.01 0.00

Sept. 21, 2011

0.04 0.04 0.01 0.01

Final

Appendix 18: Nurse Dissatisfaction Results for RNs at the 0.50 Threshold Number of Observations Wald chi2(27) Prob > chi2 Pseudo R2 Log pseudolikelihood

8,833 185.33 0 0.0591 -67871.471

Explanatory Variable

Reference Variable

Coef.

z

P>z

0.04 -0.23

Std. Err 0.13 0.09

Male Age - chi2 Pseudo R2 Log pseudolikelihood

8,832 445.68 0.00 0.1759 -64857.564

Explanatory Variable

Reference Variable

Coef.

Std. Err

Z

P>z

Male Age - 8 Hours Usual Shift Hours - Various Non Direct Care Childcare Available Don't Choose Work Days

Anshoo Kamal

163

95% Confidence Interval -0.26 0.24 -0.36 -0.03 -0.06 0.22 0.02 0.36 -0.01 0.26 -0.11 0.14

Sept. 21, 2011

Final

Explanatory Variable

Reference Variable

Coef.

Std. Err

Z

P>z

Don't Choose Work Hours Role Overload Skill Discretion Job Insecurity Job Strain _cons

Choose Work Hours

0.30 0.06 0.01 0.10 1.10 -3.94

0.09 0.01 0.02 0.03 0.11 0.19

3.32 8.82 0.59 3.56 9.82 -20.89

0.00** 0.00** 0.55 0.00** 0.00** 0.00

95% Confidence Interval 0.12 0.48 0.05 0.08 -0.03 0.05 0.04 0.15 0.88 1.31 -4.31 -3.57

Appendix 20: Job Dissatisfaction Results for LPNs Number of obs Wald chi2(45) Prob > chi2 Pseudo R2 Log pseudolikelihood

6701 496.47 0 0.194 -18670.4

Explanatory Variable

Reference Variable

Coef.

Male Age - less than 35 Age - 45-54 Age - 55 or older Not Married Have Children - Under 5 Years Have Children - 6-11 Have Children - 12- 17 Household Income - less than $50,000 Household Income $100,000 or greater Health Status - poor-fair Health Status - very good Health Status – excellent Non Union Member Have Non Nursing Education Have Non Nursing Job Have More than One Job Atlantic Territories Quebec Manitoba

Female Age - 35-44 Age - 35-44 Age - 35-44 Married No Children No Children No Children Household Income $50,000-$99,999 Household Income $50,000-$99,999 Health Status - good Health Status - good Health Status - good Union Member No Non-Nursing Education No Non-Nursing Job One Job Ontario Ontario Ontario Ontario

Anshoo Kamal

164

z

P>z

0.11 -0.23 -0.01 0.15 0.15 -0.11

Std. Err. 0.12 0.10 0.09 0.10 0.08 0.11

95% C.I.

0.88 -2.25 -0.17 1.47 2.01 -1.02

0.38 0.03 0.87 0.14 0.05 0.31

-0.13 -0.43 -0.19 -0.05 0.00 -0.32

0.35 -0.03 0.16 0.36 0.30 0.10

0.11 -0.20 0.07

0.09 0.08 0.07

1.26 -2.48 1.02

0.21 0.01 0.31

-0.06 -0.36 -0.07

0.28 -0.04 0.21

0.09

0.10

0.97

0.33

-0.10

0.28

0.20 -0.08 -0.06 -0.06 -0.08

0.11 0.07 0.08 0.11 0.09

1.78 -1.17 -0.71 -0.54 -0.97

0.08 0.24 0.48 0.59 0.33

-0.02 -0.23 -0.22 -0.26 -0.25

0.41 0.06 0.10 0.15 0.09

-0.07 0.11 -0.14 -0.07 0.17 -0.15

0.13 0.09 0.09 0.22 0.10 0.10

-0.49 1.15 -1.68 -0.31 1.75 -1.45

0.62 0.25 0.09 0.76 0.08 0.15

-0.33 -0.07 -0.31 -0.50 -0.02 -0.35

0.19 0.29 0.02 0.37 0.35 0.05

Sept. 21, 2011

Final

Explanatory Variable

Reference Variable

Coef.

z

P>z

-0.02 0.24 0.31 -0.08 -0.10 -0.16 0.21 -0.29 -0.01

Std. Err. 0.10 0.09 0.10 0.07 0.14 0.15 0.07 0.22 0.13

Saskatchewan Alberta British Columbia Long Term Care Community Other Non Day Shift Non Direct Care Usual Shift Hours - less than 8 Usual Shift Hours - greater than 8 Usual Shift Hours – various Shift Changes - did not work Shift Changes - one or more shift changes Don't Choose Work Hours Don't Choose Work Days Part Time Casual Have Childcare Support Role Overload Skill Discretion Job Insecurity Job Strain Decision Authority Social Support _cons

Ontario Ontario Ontario Hospital Hospital Hospital Day Shift Direct Care Usual Shift Hours - 8

95% C.I.

-0.15 2.66 3.17 -1.22 -0.72 -1.12 2.83 -1.31 -0.06

0.88 0.01 0.00 0.22 0.47 0.26 0.01 0.19 0.95

-0.21 0.06 0.12 -0.22 -0.37 -0.45 0.06 -0.73 -0.26

0.18 0.42 0.49 0.05 0.17 0.12 0.35 0.14 0.25

Usual Shift Hours - 8

0.17

0.08

2.08

0.04

0.01

0.34

Usual Shift Hours - 8

0.16

0.12

1.28

0.20

-0.08

0.40

Shift Changes - no changes Shift Changes - no changes Chose Work Hours Chose Work Days Full Time Full Time No Childcare Support

0.13

0.11

1.09

0.28

-0.10

0.35

-0.11

0.07

-1.58

0.12

-0.25

0.03

-0.02 0.07 0.05 0.23 -0.05 0.07 0.04 0.06 0.34 0.08 0.10 -3.59

0.09 0.10 0.07 0.09 0.12 0.01 0.02 0.03 0.13 0.02 0.01 0.22

-0.19 0.75 0.65 2.42 -0.44 8.81 2.11 2.07 2.64 4.06 6.97 -16.68

0.85 0.45 0.51 0.02 0.66 0.00 0.04 0.04 0.01 0.00 0.00 0.00

-0.20 -0.12 -0.09 0.04 -0.30 0.05 0.00 0.00 0.09 0.04 0.07 -4.02

0.16 0.26 0.18 0.41 0.19 0.08 0.08 0.11 0.59 0.12 0.13 -3.17

Appendix 21: Job Dissatisfaction for LPNs Average Marginal Effects Explanatory Variable

Reference Variable

Male Age - less than 35 Age - 45-54 Age - 55 or older Not Married Have Children - Under 5 Years Have Children - 6-11 Have Children - 12- 17 Household Income - less

Anshoo Kamal

Std. Err. 0.02 0.01 0.01 0.02 0.01 0.02

z

P>z

Female Age - 35-44 Age - 35-44 Age - 35-44 Married No Children

Avg. M.E. 0.02 -0.03 0.00 0.03 0.03 -0.02

0.88 -2.25 -0.17 1.47 2.01 -1.02

0.38 0.03 0.87 0.14 0.05 0.31

-0.03 -0.06 -0.03 -0.01 0.00 -0.05

0.06 -0.01 0.03 0.07 0.05 0.01

No Children No Children Household Income -

0.02 -0.03 0.01

0.02 0.01 0.01

1.26 -2.48 1.02

0.21 0.01 0.31

-0.01 -0.05 -0.01

0.05 -0.01 0.04

165

95% C. I.

Sept. 21, 2011

Final

Explanatory Variable

Reference Variable

than $50,000 $50,000-$99,999 Household Income Household Income $100,000 or greater $50,000-$99,999 Health Status - poor-fair Health Status - good Health Status - very good Health Status - good Health Status - excellent Health Status - good Non Union Member Union Member Have Non Nursing No Non-Nursing Education Education Have Non Nursing Job No Non-Nursing Job Have More than One Job One Job Atlantic Ontario Territories Ontario Quebec Ontario Manitoba Ontario Saskatchewan Ontario Alberta Ontario British Columbia Ontario Long Term Care Hospital Community Hospital Other Hospital Non Day Shift Day Shift Non Direct Care Direct Care Usual Shift Hours - less Usual Shift Hours - 8 than 8 Usual Shift Hours Usual Shift Hours - 8 greater than 8 Usual Shift Hours Usual Shift Hours - 8 various Shift Changes - did not Shift Changes - no work changes Shift Changes - one or Shift Changes - no more shift changes changes Don't Choose Work Hours Chose Work Hours Don't Choose Work Days Chose Work Days Part Time Full Time Casual Full Time Have Childcare Support No Childcare Support Role Overload Skill Discretion Job Insecurity Job Strain Decision Authority Social Support obs. P 0.140255 pred. P 0.091967

Anshoo Kamal

166

Avg. M.E.

Std. Err.

z

P>z

95% C. I.

0.02

0.02

0.97

0.33

-0.02

0.05

0.04 -0.01 -0.01 -0.01 -0.01

0.02 0.01 0.01 0.02 0.01

1.78 -1.17 -0.71 -0.54 -0.97

0.08 0.24 0.48 0.59 0.33

-0.01 -0.04 -0.04 -0.04 -0.04

0.08 0.01 0.02 0.02 0.01

-0.01 0.02 -0.02 -0.01 0.03 -0.02 0.00 0.05 0.06 -0.01 -0.02 -0.02 0.03 -0.04 0.00

0.02 0.02 0.01 0.03 0.02 0.01 0.02 0.02 0.02 0.01 0.02 0.02 0.01 0.02 0.02

-0.49 1.15 -1.68 -0.31 1.75 -1.45 -0.15 2.66 3.17 -1.22 -0.72 -1.12 2.83 -1.31 -0.06

0.62 0.25 0.09 0.76 0.08 0.15 0.88 0.01 0.00 0.22 0.47 0.26 0.01 0.19 0.95

-0.05 -0.01 -0.05 -0.08 -0.01 -0.05 -0.03 0.01 0.02 -0.04 -0.06 -0.06 0.01 -0.09 -0.04

0.03 0.05 0.00 0.05 0.06 0.01 0.03 0.08 0.10 0.01 0.02 0.01 0.05 0.01 0.04

0.03

0.02

2.08

0.04

0.00

0.06

0.03

0.02

1.28

0.20

-0.02

0.08

0.02

0.02

1.09

0.28

-0.02

0.06

-0.02

0.01

-1.58

0.12

-0.04

0.00

0.00 0.01 0.01 0.04 -0.01 0.01 0.01 0.01 0.06 0.01 0.02

0.02 0.02 0.01 0.02 0.02 0.00 0.00 0.00 0.02 0.00 0.00

-0.19 0.75 0.65 2.42 -0.44 8.81 2.11 2.07 2.64 4.06 6.97

0.85 0.45 0.51 0.02 0.66 0.00 0.04 0.04 0.01 0.00 0.00

-0.03 -0.02 -0.02 0.00 -0.05 0.01 0.00 0.00 0.01 0.01 0.01

0.03 0.04 0.03 0.08 0.03 0.01 0.01 0.02 0.10 0.02 0.02

Sept. 21, 2011

Final

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Final

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