The main aim of the research study was to develop a holistic wellness model for managers at higher education institutions. The secondary aims were to measure the wellness behaviour levels of managers by focussing on the various wellness sub-dimensions, to identify their health risk factors, to calculate the health risk scores and to propose wellness interventions based on the measurement of wellness behaviour levels and the health risk scores. To accomplish these research aims or objectives, the study was designed to explore the following research questions:
1) What is the correlation between the health risk scores and the wellness behaviour levels of managers?
2) Is there a difference between the mean wellness behaviour levels and mean health risk scores of managers at the academic university and the technology university?
3) Is there a difference between the mean wellness behaviour levels and mean health risk scores of heads of academic departments and directors of support services?
4) Is there a difference between the mean wellness behaviour levels and mean health risk scores of male and female managers?
5) Is there a difference between the mean wellness behaviour levels and mean health risk scores of post-graduate and PhD post-graduate managers?
6) Is there a difference between the mean wellness behaviour levels and mean health risk scores of managers according to their age groups?
7) Can a wellness prediction model be used, as a holistic dependant variable, to measure wellness against all possible independent variables?
The first research question concerned the correlation between the health risk scores and the wellness behaviour levels of managers. The Pearson product moment correlation coefficient was used to determine the relationship between the wellness behaviour levels and the health risk scores of managers. The results suggested that there were no significant correlations between the mean physical fitness and nutrition, medical self-care, safety, environmental wellness, social awareness, intellectual wellness, spirituality and values sub-dimensions and the health risk scores of managers. However, there was a significant negative relationship between sexuality and emotional awareness and the health risk scores. The negative correlation indicated that with an increase in the sexuality and emotional awareness level, there would be a decrease in the health risk. There was a small negative
relationship between emotional management and the health risk score. The low negative correlation indicated that with an increase in the emotional management level, there would be a decrease in the health risk. There was also a negative relationship between occupational wellness and the health risk score. The low negative correlation indicated that with an increase in the occupational wellness levels, there would be a decrease in the health risk.
The second research question concerned the difference between the mean wellness behaviour levels and mean health risk scores of managers at the academic university and the technology university. The mean scores on the wellness behaviour levels and health risk between managers at the academic university and technology university were very similar, with the exception of emotional management. The average score on emotional management for the technology university managers was 40.40 out of a possible 50 (80.8%), while the average score for managers at the academic university was 38.28 out of a possible 50 (76.56%). On average the emotional management score of the technology managers was 4.24% higher than their counterparts at the academic university.
Since all the p-values are greater than 0.05, the null hypothesis of no difference between the mean scores could not be rejected. Thus, the observed means of the two universities did not differ significantly.
Figure 1: Mean Scores of Wellness Behaviour Levels of Managers at the Academic University and Technology University
The third research question concerned the difference between the mean wellness behaviour levels and mean health risk scores of heads of academic departments and directors of support services. The results indicated that there was no significant difference in the mean wellness behaviour levels and mean health risk scores of heads of academic departments and directors of support services. Thus, the null hypothesis postulating that there is no significant difference between the mean wellness behaviour levels and mean health risk scores of heads of academic departments and directors of support services could not be rejected.
Figure 2: Mean Scores of Wellness Behaviour Levels of Heads of Academic Departments and Directors of Support Services
The fourth research question was aimed at establishing if there was a difference between the mean wellness behaviour levels and mean health risk scores of male and female managers. Only in one wellness behaviour sub-dimension, namely, sexuality and emotional awareness, the p-value of 0.048, was less than 0.05. Thus, there were no significant differences between the mean scores of nine of the ten wellness behaviour levels and the mean health risk scores of female and male managers. The exception was sexuality and emotional awareness. Since there were no significant differences between the mean scores of nine of the ten wellness behaviour levels and the mean health risk scores, the null hypothesis postulating that there is no significant difference between the mean wellness behaviour levels and mean health risk scores of male and female managers could not be rejected.
Figure 3: Mean Scores of Wellness Behaviour Levels of Female and Male Managers
The fifth research question looked at the difference between the mean wellness behaviour levels and the mean health risk scores of post-graduate and PhD graduate managers. The results indicated that there were no differences between the mean physical fitness and nutrition, medical self-care, safety, environmental wellness, social awareness, sexuality and emotional awareness, occupational wellness, spirituality and values and the health risk
Male Female
100
80
60
40
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0
Average percentage
86 83
79 78
85 84 77 80
85 89
82 83 65 68 91 89
60 61 58 55
Spirituality & Values Occupational Wellness Intellectual Wellness Emotional Management Sexuality
Social Awareness Environmental Wellness Safety
Medical Self-Care Physical Fitness
Gender
scores. However, the exceptions were the emotional management value of 0.032) and intellectual wellness (p-value of 0.004) sub-dimensions. Since the results had shown no significant difference between the mean of eight of the ten behaviour levels and the health risk scores, the null hypothesis stating that there is no significant difference between the mean wellness behaviour levels and mean health risk scores between post-graduate and PhD graduate managers could not be rejected.
Figure 4: Mean Scores of Wellness Behaviour Levels of Post-Graduate and PhD Graduate Managers
The sixth research question investigated the difference between the mean wellness behaviour levels and mean health risk scores of managers according to their age groups. There were no differences in the mean physical fitness and nutrition, medical self-care, safety, social awareness, sexuality and emotional awareness, emotional management, intellectual wellness, occupational wellness, spirituality and values and the health risk scores.
Although an ANOVA indicated that the mean environmental wellness scores of the three age groups were different, the Post-hoc tests did not indicate which age groups differed. Thus, the null hypothesis stating that there is no significant difference between the mean wellness behaviour levels and mean health risk scores was maintained.
Figure 5: Mean Scores of Wellness Behaviour Levels of the Three Age Groups
The last research question was aimed at establishing whether a wellness prediction model could be used, as a holistic dependant variable, to measure wellness against the independent variables such as physical fitness and nutrition, medical self-care, safety, environmental wellness, social awareness, sexuality and emotional awareness, emotional management, intellectual wellness, occupational wellness, spirituality and values and the health risk scores. The data was of such a nature that a linear regression model could not be used, as the variables were not normally distributed. A logistical regression could only be done if a comparison was made between two groups of managers, namely, one group with high wellness behaviour levels and low health risk scores and one group with low wellness behaviour levels and high health risk scores. However, all the managers fell into one group characterised by high wellness behaviour levels and low health risk scores and as a result a comparison was not possible. The null hypothesis postulating that it is not possible to use a wellness prediction model as a holistic dependant variable to measure wellness against all possible variables, could not be rejected.
The results of the data analysis indicated that there was no significant difference in the health risk scores of managers. As such, the wellness behaviour levels and health risk scores of managers at the two sample universities were combined to determine their overall wellness status. The combined health risk scores were an average of 2.71 out of a possible 14 (19.36%), while the combined average wellness behaviour levels of managers at the two sample universities was 76.80%.
Figure 6: Combined Average Wellness Behaviour Levels of Managers at the Academic University and Technology University