Individual Role Engagement Alignment Profile (ireap) Psychometric Review of the Instrument 2012

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2 ireap Technical Psychometric Report October 2012 Individual Role Engagement Alignment Profile (ireap) Psychometric Review of the Instrument 2012 Contents Executive Summary... 3 Purpose... 4 Development... 5 Description of instrument... 6 Use and interpretation... 7 Description of validation population... 9 Reliability Internal consistency reliability Test- Retest Reliability Validity Face Validity Convergent Validity Construct Validity - Confirmatory Factor Analysis Engagement Relationships Simple Linear Regressions Engagement and Work Productivity Engagement and Cynicism Engagement and Exhaustion Engagement and Professional Efficacy Engagement and Emotional Instability Engagement Relationships Simple Linear Regressions Engagement and Satisfaction + Importance Role Alignment and Maslach s Burnout Measures Engagement Relationships ANOVA s Role Alignment and Engagement Length of Time in Current Role and Engagement Length of Time with Current Organisation and Engagement Future Developments for ireap Because Pty Ltd 2012 Page 2

3 ireap Technical Psychometric Report October 2012 Executive Summary The individual Role Engagement Alignment Profile (ireap) is a diagnostic tool which measures an individual s levels of engagement towards their organisation and how aligned their motivations are in their current role. It is a tool designed to support organisational engagement initiatives, career enrichment, manager engagement coaching and encourage individual responsibility for decision- making whether to stay and grow in roles, move internally or to exit the organisation. The instrument is built on research from motivational theorists such as Maslow, McClelland, Adams and Hertzberg. There are a series of seven scales, each with seven items totalling 49 aspects of work which address the motivational blades (importance and fulfilment / satisfaction) of Security, Belonging, Expertise, Self- Actualisation, Work- Life, Community and World Altruist. The engagement and commitment measures and enabling factors are derived from more contemporary research from consulting firms such as Gallup and the Corporate Leadership Council as well as the coaching and consulting practice of Because Pty Ltd. A psychometric review of this tool was conducted in 2012 to evaluate the validity and reliability of the instrument. A total of 756 respondents were involved in the data collection and analysis. The demographic profile of the respondents revealed that 62% were female and the most highly concentrated respondent age group was years of age followed closely by the age- group The sample was highly educated with 76% having a degree or higher level qualifications and 73% were employed full- time whereas 15% were self- employed. A high proportion, 38% of respondents was professionals whereas 23% were senior managers and 9% junior managers. Furthermore 29% of respondents had been in their current role for 2-5 years with a similar 27% working with their current organisation for the same period of time. The research findings confirm that the ireap is a sound instrument with strong internal reliability (Cronbach s alpha) scores ranging from.74 through to.91 for the motivational blades and the engagement enablers scale. The engagement measure sub- scales showed a similar result with Advocacy (.844), Contribution (.707) and Intention to Stay (.791) all showing strong internal reliability. The ireap has excellent face validity with 87.5% of respondents indicating that the engagement profile in the engagement risk and opportunity matrix is correct for them. It has good convergent validity as significant correlations were found with similar instruments (e.g., Maslach Burnout Inventory, Utrecht Work Engagement and the Work Extrinsic and Intrinsic Motivation Scale). A confirmatory factor analysis of engagement (Importance + Satisfaction) indicated the seven- factor model for the ireap has acceptable fit. A multiple regression analysis revealed that satisfaction with the individual motivational factors accounts for 52.3% of the variance on the level of engagement. Furthermore engagement was found to be a significant predictor of cynicism, exhaustion, professional efficacy and work productivity. This highlights the importance of understanding employee engagement to further increase professional efficacy and productivity, whilst lowering cynicism and exhaustion. Because Pty Ltd 2012 Page 3

4 ireap Technical Psychometric Report October 2012 Purpose The individual Role Engagement Alignment Profile is a unique on- line diagnostic tool designed to: Help individuals become more self- aware about what their engagement and motivational needs are and how well they are being fulfilled at work Support people to take individual responsibility for their engagement and to make choices to either stay and grow in their role, move internally or explore opportunities externally Improve the robustness and quality of career and engagement related conversations between managers, coaches and staff Facilitate people and organisations to reap the rewards of engagement though identification of specific strategic and tactical interventions that will increase: o o o performance and profitability, career mobility and retention the effectiveness of career development conversations between a manager and their staff, the likelihood of behavioural change at the individual level Plug gaps left by engagement surveys which focus on the we instead of the me and do not account for the satisfaction of individual motivation factors which drive 52% of engagement within an organisation. Because Pty Ltd 2012 Page 4

5 Development The ireap instrument was developed from a mixture of practitioner experience and research into motivational theories and models of engagement. The research was developed by Pamela Frost over a period of 6 years. The motivational model that the ireap is based upon is shown in Figure 1. Figure 1. Motivational blades... The motivational blades of security, belonging, expertise and self- actualisation have been derived and adapted from Maslow s Hierarchy of Needs which was pioneering research into motivation at the time. The motivational blades of work- life, community and world altruist were influenced by the research and consulting work of Wilf Jarvis (Four Quadrant Leadership) and Richard Barratt (Liberating the Corporate Soul). The development of work aspects underpinning the model also has been heavily influenced by the previous psychometric analyses as well as the coaching and consulting work of the developer Pamela Frost who has been an organisational development practitioner in the fields of talent identification and management, capability development, outplacement and career enrichment for 20 years. There are 49 aspects of work where each are measured in terms of: 1. Importance to the person in general 2. Fulfilment in their current role The theoretical basis of measuring the gap between these variables (referred to as dissonance or alignment) comes from research related to Adam s Equity Theory and the psychological contract meaning the larger the gap (or greater the dissonance) the more the creative tension, or discomfort that exists within the individual. As this tension will be uncomfortable for them, they will be motivated to close the gap(s) and create some kind of movement. In a career context that movement typically relates to changes such as a changing perspectives and expectations, job redesign, promotion, taking on additional responsibilities, reducing responsibilities, internal transfer, make a career change or exiting the organisation. The variables related to level of engagement with the organisation have been influenced by the work of consulting companies such as Gallup, Corporate Leadership Council and Hewitt. Engagement is defined by the extent to which the individual is committed to the organisation, how Because Pty Ltd 2012 P a g e 5

6 much they are prepared to contribute to the organisation and how hard they are working to drive the organisation forward. The variables within the engagement measures scale therefore relate to advocacy, contribution and intention to stay. With the engagement enablers scale the variables relate to items which will encourage / support or conversely a person s capacity to be fully engaged in their work. The include factors such as the state of health of the individual, their workload, resources available and degree of support of their line manager. Description of instrument The ireap instrument is an online instrument measuring 49 aspects of work (importance and fulfilment) and takes between minutes to complete. The engagement factors are separated into engagement measures and engagement enablers. There are 10 different items which measure engagement and are categorised by intention to stay, contribution and advocacy. An additional item (job satisfaction) is included within the instrument but not taken as a direct measure of the engagement level. There are a further 13 items which have been included in the instrument as engagement enablers to indicate the variables which can support or impede a person s capacity to fully engage in their work. There are four different reports available each derived from the same questionnaire construction (summary, full, engagement development worksheets and a group / team report). The key output of the ireap reports is a profile of the individual or team in an engagement risk and opportunity matrix see Figure 2. For each cell of the matrix the report will reveal: Risks to the individual and to the organisation of that person s current level of engagement and current level of alignment (or conversely dissonance) Opportunities for the individual and the organisation for increased engagement Specific engagement and career development strategies Figure 2. Engagement Risk and Opportunity Matrix... Because Pty Ltd 2012 P a g e 6

7 Use and interpretation The ireap instrument should be used in a development context for executive coaching, leadership and team development, talent retention and career development. The instrument should not be used as an assessment input into performance reviews, recruitment and selection or decisions relevant to promotion or termination. The ireap instrument will profile people on the engagement risk and opportunity matrix outlined above. Each of the cells has a risk, an opportunity and recommended development actions. The engagement factors on the y- axis are scored on a 7- point Likert scale. The breakdown of scores is as follows; low engagement = up to 3.99, moderate = and high = For alignment on the x- axis of the matrix, the scores again are calculated as the difference between satisfaction and importance for all of the 49 aspects of work. These scores are averaged across the matrix. The breakdown of scores is as follows; high alignment= or greater, moderate = between and and low = less than Table 1: Distribution of ireap Data in Engagement Risk and Opportunity Matrix Level of Engagement Scale Current Scale High: 5.7 or greater Moderate: between 4.0 and 5.69 Low: less or equal to 3.99 Total sample: Level of Alignment Scale Current Scale High: or greater Moderate (between and ) Low: less than RED ALERT TURBULENCE FLYING HIGH % 10.58% 18.92% TAXIING SEAT BELTS ON ALTITUDE CHANGE % 21.04% 16.93% STORMY WEATHER TRANSIT LOUNGE DEPARTURE GATE % 4.76% 2.25% ENGAGEMENT High % Moderate % Low % TOTAL 756 ALIGNMENT % Low Moderate High TOTAL % 36.38% 38.10% % Because Pty Ltd 2012 P a g e 7

8 ireap Technical Psychometric Report October 2012 The ireap instrument indicated that: 32% of respondents have high levels of engagement 51% of respondents have moderate levels of engagement 17% of respondents have low levels of engagement These statistics can be benchmarked against research published by consulting companies such as Blessing White, Hewitt and the Corporate Leadership Council. It is important to note however that different organisations will use different models of engagement and therefore definitions and classifications of how engagement is ultimately measured. Also different time- frames for analysis, population groupings, industry sectors and occupational groups are included in other analyses so therefore it is expected there will be slight variations in engagement profile results for the ireap when compared against the benchmark data. Some of the more notable and recent engagement benchmarks include: Blessing White published in February 2011 that in Australia and New Zealand, 36% of their respondents are highly engaged and 17% of respondents were disengaged 1. Right Management Consultants conducted research in with over 28, 810 employees representing 10 major industry sectors in 15 countries. They found significant differences in engagement by country but in Australia, engagement levels (high engagement) were 36% 2. Gallup has tracked the engagement levels of the U.S. working population for the past decade. Its most recent employee engagement research shows that 28% of American workers are engaged, 54% are not engaged, and 18% are actively disengaged. Throughout the decade, the percentage of engaged employees ranged from 26% to 30%, while the percentage of actively disengaged employees ranged from 15% to 20% 3. Finally, the Corporate Leadership Council indicated in 2005 that in the U.S. 11% of employees are true believers or highly engaged, compared to 13% which are the disaffected or very disengaged 4. 1 Blessing White Employee Engagement 2011 Report: Beyond the numbers a practical approach for individuals, managers and executives. Page33. This research is based on interviews with HR consultants and line managers and online survey responses for about 11,000 people across the world. 2 Right Management Consultants: Organisational Effectiveness and Employee Engagement: Discovering how to make them happen. Page5. 3 Gallup Organisation. Despite the Downturn, Employees remain engaged. January downturn- employees- remain- engaged.aspx 4 Corporate Leadership Council: Driving Employee Performance and Retention through Engagement: A quantitative analysis of the effectiveness of employee engagement strategies This analysis was based on a study of more than 50,000 employees at 59 member organizations in 27 countries and 10 industries. Because Pty Ltd 2012 Page 8

9 These statistics support the construct validity of the ireap instrument in that there is plausible consistency in the construction of the survey elements that measure overall levels of engagement and commitment towards the organisation. Description of validation population The psychometric review of this instrument was based on the following demographic data of respondents: N=756 62% female Median age is years 76% have a degree or higher level qualifications 73% employed full- time, 15% self- employed / contractors and 10% part- time 38% were professionals whereas 23% were senior managers, with 12% junior managers Median time in current role is 2-5 years 22% time in current role for 1-2 years and 29% in current role for 2-5 years Median length of time with the organisation is 2-5 years 27% working with current organisation for 2-5 years and 25% in current organisation for > 10 years Graphical representations of this data are available below: Gender 38% Male 62% Female Figure 3. Distribution of respondents according to gender Because Pty Ltd 2012 P a g e 9

10 Age 1% 3% 12% % % % Figure 4. Distribution of respondents according to age Educa^on 3% 24% 36% Other Degree Postgraduate Masters 37% PhD or Equivalent Figure 5. Distribution of respondents according to highest level of education Employment Status 2% 15% 10% Employee- Full Time Employee- Part Time 73% Self- Employed/Contracter Other Figure 6. Distribution of respondents according to employment status Because Pty Ltd 2012 P a g e 10

11 Occupa^onal Level 23% 30% Other 9% Professional Junior Manager 38% Senior Manager Figure 7. Distribution of respondents according to occupational level Length of Time in Current Role 12% 16% 21% Less than 12 months 1-2 years 22% 29% 2-5 years 5-10 years More than 10 years Figure 8. Distribution of respondents according to length of time in current role Length of Time in Current Organisa^on 25% 22% 11% 15% 28% Less than 12 months 1-2 years 2-5 years 5-10 years More than 10 years Figure 9. Distribution of respondents according to length of time in current organisation Because Pty Ltd 2012 P a g e 11

12 Reliability Internal consistency reliability The internal consistency reliability has been measured by Cronbach s alpha for both importance and satisfaction items as well as for the engagement measures. It is used to provide a mean coefficient for all of the split half pairings of items in the scale and regarded as a stringent test of reliability for instruments such as this. Alpha coefficients should ideally be in the range of to be neither too low nor too high. As can be seen from Table 2, the alpha coefficients obtained for the ireap instrument are all strong, indicating strong internal reliability. Table 2 Cronbach s alpha for ireap blades (importance and satisfaction) and Engagement (n=756). Engagement Measures (aggregate).906 Advocacy.844 Contribution.707 Intention to Stay Engagement Enablers ireap Blades Importance Satisfaction Security Belonging Expertise Self- Actualisation Work- Life Community World Altruist Test- Retest Reliability Test- retest reliability was not assessed as the ireap is a state based instrument rather than a trait based instrument. This means the ireap measures how a respondent feels at the specific time of completing the ireap, known as a state in time, rather than a measure of a characteristic that remains relatively constant over time, known as a trait. In the context of the ireap, responses can be dependent on environmental and organisational context and the very communication of their results can lead them to change their behaviour, possibly resulting in an increase of self- awareness, initiating a conversation with their manager or an undertaking of an internal shift in perspective or expectation, which can affect their responses. Because Pty Ltd 2012 P a g e 12

13 Validity Face Validity Face validity refers to whether on the surface the report seems to fit the purpose and be true for the person. The outcomes of the report and the profile on the engagement risk and opportunity matrix do seem to have high face validity for the 1000 s of respondents who have now completed the instrument. Consistent feedback is provided that people feel very comfortable about how they have been profiled in the engagement risk and opportunity matrix. To evaluate face validity of the instrument the following process steps were adopted. 1. Respondents were sent an invite to complete the instrument online 2. Prior to receiving their report they were asked to predict where they would be profiled on the engagement risk and opportunity matrix. They were sent an which asked them to make a rating as to whether they thought that they experienced high, moderate or low engagement. They were also asked to indicate whether they felt they are experiencing high, moderate or low levels of alignment in their current role. A short description was provided to define each of these states and guide their selection. 3. Once they made their selection they were sent their report to peruse. 4. Finally they were asked to validate whether they agreed with how the ireap instrument had profiled their result. They were also invited to make relevant comments. The face validity results are shown below in Table 3: Table 3 Face Validity Results for ireap 2012 Predictions Number Percentage (%) Number of respondents who predicted correctly % Number of respondents who predicted incorrectly % Number of respondents who did not provide prediction 0 0.0% 40 Sample size Validations Number of respondents validating Engagement matrix correct % Number of respondents validating Engagement matrix incorrect 1 2.5% Number of respondents who did not provide validation feedback 4 10% 40 Sample size This indicates that the ireap instrument has very high face validity with 87.5% of respondents confirming the final placement in the engagement matrix as being true and correct for them. Because Pty Ltd 2012 P a g e 13

14 Convergent Validity The models underpinning the ireap instrument do not come from a single theoretical model; they are derived from a number of different models. All participants completed the ireap tool (N=756) however those participants were randomly selected to complete one of two tests that were constructed for testing convergent validity. Endicott Work Productivity Scale (1977) (N=271) Maslach Burnout Inventory developed by Maslach and Jackson (1981) (N=295) Utrecht Engagement Scale developed by Schaufeli, Salanova, González- Romá and Bakker (2002) (N=286) Work Demands scale developed by Bolino and Turnlet (2005) (N=286) Work Extrinsic and Intrinsic Motivation Scale (WEIMS) developed by Deci and Ryan (2000) (N=295) As can be seen from Table 4, the engagement measures aspect of the ireap has good convergent validity with expected correlations with similar assessment tools. Table 4 Engagement Correlations with Existing Scales Pearson Correlation Sig. (2- tailed) p< p<0.01 p<.001 p<.001 p< p<.001 p<.001 p< p<.001 p<.001 p<.001 p<.001 p<.001 p<.001 Endicott Work Productivity Maslach Burnout Inventory Cynicism Emotional Stability Exhaustion Professional Efficacy Utrecht Work Engagement Absorption Dedication Vigor Work Demands Workplace Extrinsic & Intrinsic Motivation (WEIM) Amotivation Identification Integration Intrinsic Motivation Introjection Based on the results presented in Table 4, the ireap has convergent validity as strong associations were found with other assessments that measure similar constructs. Because Pty Ltd 2012 P a g e 14

15 Construct Validity - Confirmatory Factor Analysis Three confirmatory factor analyses (CFA s) were conducted to determine how well a seven- factor model fits the ireap. CFA s were conducted on importance + satisfaction, satisfaction only and engagement. A separate CFA was conducted on the satisfaction aspect of the ireap due to the fact that satisfaction with current work aspects was found to have the greatest impact on engagement. This was expected as regardless of how important an employee thinks a particular work aspect is to them, it is the fulfilment or satisfaction of that work aspect in their current role which effects their engagement levels the most. Chi- Square The overall chi- square goodness of fit was significant for all three CFA s, which is normally expected with a large sample size (Kenny, 20115). Therefore, the root mean square error of approximation (RMSEA), the comparative fit index (CFI), and the standardised root mean square residual (SRMR), which are more reliable fit indices, were investigated. These are shown in Tables 5, 6 and Table 7. The following guide provides an indication of how to interpret the results for each of these tests. RMSEA The root mean square error of approximation (RMSEA) is probably the most popular measure of fit used in psychometric analysis. Values of.01,.05, and.08 indicate excellent, average, and poor fit respectively. CFI The comparative fit index (CFI) is another measure of fit. Essentially it is a measure of item correlations, comparing the predicted model to an independent model where it is assumed that the variables are not correlated. The closer this value is to 1, the better the fit. SRMR The standardised root mean square residual (SRMR) is another measure of fit that compares correlations between the target model and another model. It is thought to be acceptable if below.08. Importance + Satisfaction CFA Table 5 ireap (Importance + Satisfaction) Confirmatory Factor Analysis Results Fit Indices Value RMSEA.060 CFI.701 SRMR Because Pty Ltd 2012 P a g e 15

16 The confidence intervals of the ireap Importance + Satisfaction RMSEA are As the RMSEA value is acceptable, and the upper confidence interval does not exceed.08, it indicates the seven- factor model for the ireap has acceptable fit. The actual factor loadings for the Importance + Satisfaction and confirmatory factor analysis are shown in Table 6. It should be noted that a factor loading of.45 or greater is generally seen as fair. Table 6 Factor Loadings for ireap Importance + Satisfaction Instrument Security Q01 Q02 Q03 Q04 Q05 Q06 Q07 Expertise Importance Importance Satisfaction Satisfaction Q15 Q16 Q17 Q18 Q19 Q20 Q21 Work/Life Q29 Q30 Q31 Q32 Q33 Q34 Q35 World Altruist Q43 Q44 Q45 Q46 Q47 Q48 Q Importance Importance Satisfaction Satisfaction Belonging Q08 Q09 Q10 Q11 Q12 Q13 Q14 Self- Actualisation Q22 Q23 Q24 Q25 Q26 Q27 Q28 Community Q36 Q37 Q38 Q39 Q40 Q41 Q42 Importance Importance Satisfaction Satisfaction Importance Satisfaction The items that did not load well on this CFA (scoring below.45) are being subsequently revised. For a detailed explanation please see the Further Developments section at the end of this report. Because Pty Ltd 2012 P a g e 16

17 Satisfaction CFA Table 7 ireap (Satisfaction only) Confirmatory Factor Analysis Results Fit Indices Value RMSEA.065 CFI.821 SRMR.080 The confidence intervals of the ireap (Satisfaction only) are As the RMSEA vale is acceptable, and the upper confidence interval does not exceed.8, it indicates the seven- factor model for the ireap has acceptable fit. The actual factor loadings for the Satisfaction and confirmatory factor analysis are shown in Table 8. It should be noted that a factor loading of.45 or greater is generally seen as fair. Table 8 Factor Loadings for ireap Satisfaction only Security Q01 Satisfaction.36 Belonging Q08 Satisfaction.58 Q02.65 Q09.71 Q03.67 Q10.75 Q04.61 Q11.78 Q05.69 Q12.75 Q06.44 Q13.70 Q07.49 Q14.73 Expertise Q15 Satisfaction.65 Self- Actualisation Q22 Satisfaction.79 Q16.78 Q23.80 Q17.75 Q24.84 Q18.76 Q25.84 Q19.79 Q26.80 Q20.50 Q27.64 Q21.79 Q28.61 Because Pty Ltd 2012 P a g e 17

18 ireap Technical Psychometric Report October 2012 Work/Life Satisfaction Community Satisfaction Q29.73 Q36.52 Q30.66 Q37.75 Q31.37 Q38.81 Q32.79 Q39.80 Q33.72 Q40.77 Q34.85 Q41.81 Q35.78 Q42.57 World Altruist Satisfaction Q43.75 Q44.81 Q45.76 Q46.77 Q47.76 Q48.44 Q49.56 Engagement CFA Table 9 ireap Engagement Confirmatory Factor Analysis Results Fit Indices Value RMSEA.092 CFI.923 SRMR.055 Model fit statistics are acceptable (RMSEA =.092, CFI =.923, SRMR =.055). After conducting the exploratory factor analysis on SPSS for the engagement measure, we then conducted the confirmatory factor analysis (see Table 10 below). It should be noted that a factor loading of.45 or greater is generally seen as fair. Because Pty Ltd 2012 Page 18

19 Table 10 Factor Loadings for ireap Engagement Engagement Dimension Factor Advocacy CHOQ15EF ENDQ04EF AUTQ05EF Contribution IDEQ16EF OWNQ17EF DISQ13EF RISQ03EF INVQ07EF OBLQ01EF EMOQ10EF Intention to Stay Because Pty Ltd 2012 Loading P a g e 19

20 Engagement Relationships Simple Linear Regressions Regressions were run to determine the impact of Endicott s Work Productivity measures and Maslach s Burnout measures on the ireap s engagement measures. As can be seen from the results below engagement has significant effects on workplace productivity, cynicism, emotional instability, professional efficacy and emotional exhaustion. In most situations the reverse relationship also held true meaning people experiencing higher levels of the burnout characteristics will have a negative or impeding impact on engagement levels within an organisation. Engagement and Work Productivity Engagement was found to be a significant predictor of work productivity, β = -.03, t(270) = , p <.001 and explained a significant proportion of the variance in work productivity scores, R2 =.11, F(1, 270) = 33.54, p <.001. This result indicates that employees with higher engagement levels are more likely to have higher work productivity levels than employees with lower levels of engagement. Engagement and Cynicism Engagement and cynicism was found to be highly related. Engagement was found to be a significant predictor of cynicism, β= -.81, t(294) = , p <.001. Engagement explained a significant proportion of the variance in cynicism, R2 =.35, F(1, 294) = , p <.001, indicating that as employee engagement increases, employees are less likely to exhibit cynicism than those with lower levels of engagement. Cynicism was also found to be a significant predictor of engagement scores, β= -.44, t (294) = , p <.001 and explained a significant proportion of the variance in engagement scores, R2 =.35, F(1, 294) = , p <.001. This result indicates that as cynicism increases in an employee, they are more likely to have lower engagement levels than those with lower levels of cynicism. Engagement and Exhaustion Engagement was found to be a significant predictor of exhaustion, β= -.52, t(294) = , p <.001. Engagement explained a significant proportion of the variance in exhaustion, R2 =.16, F(1, 294) = 55.60, p <.001, indicating that as employee engagement increases, employees are less likely to exhibit exhaustion than those with lower levels of engagement. The vice versa relationship was also found with exhaustion a significant predictor of engagement, β = -.31, t(294) = , p <.001 and explained a significant proportion of the variance in engagement scores, R2 =.16, F(1, 294) = 55.60, p <.001. This result indicates that employees with higher exhaustion levels are likely to have lower engagement levels than those with lower levels of exhaustion. Because Pty Ltd 2012 P a g e 20

21 Engagement and Professional Efficacy Engagement was found to be a significant predictor of professional efficacy, β=.35, t(294) = 7.58, p <.001. Engagement explained a significant proportion of the variance in exhaustion, R2 =.16, F(1, 294) = 57.42, p <.001, indicating that as employee engagement increases, employees are more likely to exhibit professional efficacy than those with lower levels of engagement. The reverse relationship was also true with Professional Efficacy found to be a significant predictor of engagement, β = -.46, t(294) = 7.58, p <.001 and explained a significant proportion of the variance in engagement scores, R2 =.16, F(1, 294) = 57.42, p <.001. This result indicates that employees with higher professional efficacy levels are more likely to have higher engagement levels than employees with lower levels of professional efficacy. Engagement and Emotional Instability Through a one- way analysis of variance (ANOVA), emotional instability was not found to be a significant predictor of engagement. However, through a simple linear regression, engagement was found to be a significant predictor of emotional instability, β= -.56, t(294) = , p <.001. Engagement explained a significant proportion of the variance in emotional instability, R2 =.19, F(1, 294) = 66.61, p <.001, indicating that as employee engagement increases, employees are less likely to exhibit emotional instability than those with lower levels of engagement. In other words the more engaged a person is the more emotionally stable they are likely to behave at work. Because Pty Ltd 2012 P a g e 21

22 Engagement Relationships Simple Linear Regressions Engagement and Satisfaction + Importance A set of multiple regression analyses was performed on the data, with engagement as the dependent variable, and importance and satisfaction variables as the predictor variables (see Table 11). Importance variables together accounted for 7.2% of the variance in engagement, while 52.3% was accounted for by the satisfaction variables. When entered into the regression analysis together, importance and satisfaction variables together accounted for 53% of the variance in engagement. Table 11 Engagement Multiple Regression Analysis Unstandardized Coefficients B Standardized Coefficients Beta Std. Error IV:Satisfaction (Constant) SatSecurityMean SatBelongingMean *** SatExpertiseMean * SatSActualMean ** SatWLIntMean *** *** * (Constant) ImpSecurityMean ImpBelongingMean ** ImpExpertiseMean ImpWActualMean ImpCommunityMean ImpWAltruistMean SatCommunityMean SatWAltruistMean IV: Importance ImpWLIntMean -.095** * DV: Engagement * p<.05. ** p<.01. *** p<.001. Because Pty Ltd 2012 P a g e 22

23 Of the importance variables, belonging was the strongest predictor of engagement, followed by work life and self- actualisation. Of the satisfaction variables, the strongest predictors of engagement were work life, self- actualisation and belonging. However, when both importance and satisfaction variables were entered into the regression analysis, none of the importance variables were significant predictors of engagement. Conversely of the satisfaction variables, all except for world altruist, were significant predictors of engagement. Role Alignment and Maslach s Burnout Measures A set of multiple regression analyses was performed on the data, with role alignment as the dependent variable, and Maslach s Burnout measures as the predictor variables (see Table 12). Cynicism accounted for 30.8% of the variance in role alignment, emotional stability accounted for 24.2% of the variance in role alignment, while exhaustion and professional efficacy accounted for 24.3% and 11.7% of the variance in role alignment, respectively. Table 12 Role Alignment Multiple Regression Analysis Unstandardized Coefficients B Standardized Coefficients Beta Std. Error DV: Role Alignment Cynicism (Constant) Cynicism *** Emotional Instability *** Exhaustion (Constant) Exhaustion *** Professional Efficacy (Constant) *** Emotional Instability (Constant) Professional Efficacy * p<.05. ** p<.01. *** p<.001 Because Pty Ltd 2012 P a g e 23

24 Table 13 Role Alignment Multiple Regression Analysis (Alignment constant) Unstandardized Coefficients B Standardized Coefficients Beta Std. Error DV: Burnout Alignment (Constant) Exhaustion (Dependent) Alignment (Constant) Professional Efficacy (dependent Alignment (Constant) Cynicism ( Dependent) Alignment (Constant) Burnout Overall (Dependent) ***.353*** *** *** This table indicates that there is a very strong relationship between role alignment and burnout. As role alignment improves by 1 unit then burnout will decline by 0.70 points. The strongest relationships are with the sub- factors of cynicism and exhaustion. For every 1 unit improvement in alignment, exhaustion will reduce by 0.78 points. Likewise if alignment were to improve by 1 unit then cynicism would reduce by 0.94 points. Role alignment and professional efficacy were positively related but not as strong an influence as the other variables. Similarly the lower an employee s role alignment, the more emotionally unstable and exhausted an employee is likely to be. Conversely the higher an employee s role alignment, the higher an employee s professional efficacy is likely to be. Because Pty Ltd 2012 P a g e 24

25 Engagement Relationships ANOVA s Several one- way analyses of variances (ANOVA s) were conducted to determine the impact of other variables on employee engagement. Role Alignment and Engagement The impact of role alignment on engagement was considered. Role alignment was found to be a statistically significant predictor of engagement (F(2,753) = , p<.001), indicating that as employees are more aligned in their role, they are more likely to report higher levels of engagement than employees with lower levels of role alignment. Of interest, low role alignment was specifically found to be a significant predictor of disengagement, (F(1,754) = , p<.001), highlighting the importance of alignment to engagement. Length of Time in Current Role and Engagement A one- way ANOVA was conducted to examine whether there were statistically significant differences in overall engagement amongst length of time in current role. Levene s Statistic was not significant (p=.331), meaning the homogeneity of variance assumption was not violated. Subsequently length of time in current role was found to be a statistically significant predictor of engagement (F(4,751) = 9.47, p<.001). Post- Hoc Scheffe tests revealed significant differences in overall engagement with respondents who have worked in their current role for more than 10 years (M=5.61, SD=1.20) having significantly higher engagement scores than respondents who have worked in their current role for less than 12 months (M=4.87, SD=1.20), 1-2 years (M=4.80, SD=1.09), 2-5 years (M=5.40, SD=1.03), and 5-10 years (M=5.17, SD=1.06). There were no other significant differences between the other length of time in current role groups for overall engagement scores. Length of Time with Current Organisation and Engagement A one- way ANOVA was conducted to examine whether there were statistically significant differences in overall engagement amongst length of time in current organisation. Levene s Statistic was significant (p=.039), therefore the Welch statistic was looked at. Subsequently length of time in current organisation was found to be a statistically significant predictor of engagement (F(4,307) = 8.661, p<.001). Post- Hoc Games- Howell tests revealed significant differences in overall engagement with respondents who have worked in their current organisation for more than 10 years (M=5.39, SD=1.0) having significantly higher engagement scores than respondents who have worked in their current organisation for less than 12 months (M=4.83, SD=1.32), 1-2 years (M=4.80, SD=1.21), and 2-5 years (M=4.87, SD=1.12). There were no other significant differences between the other length of time in current organisation groups for overall engagement scores. The impact of length of time in current role and length of time with current organisation indicates that as tenure increases, engagement is likely to increase as well. Because Pty Ltd 2012 P a g e 25