Assessing the strain experienced by managers and professional Australian footballers using an augmented job strain model

Generic models of job stress, such as the Job Strain Model (JSM), have recently been criticised for focusing on a small number of general work characteristics while ignoring those that are occupation-specific (Sparks & Cooper, 1999). However this criticism is based on limited research that has not examined the relative influence of all three dimensions of the JSM - job demand, job control and social support - and job-specific stressors. The JSM is the most commonly used model underpinning large-scale occupational stress research (Fox, Dwyer, & Ganster, 1993) and is regarded as the most influential model in the research on the psycho-social work environment, stress and disease in recent times (Kristensen, 1995). This thesis addresses the lack of information on the relative influence of the JSM and job-specific stressors by assessing the capacity of an augmented JSM to predict the strain experienced by managers and professional Australian footballers. The augmented JSM consisted of job-specific stressors in addition to the generic components of the model. Managers and professional Australian footballers represent two very different occupational groups. While the day-today roles of a manager include planning, organising, monitoring and controlling (Carroll & Gillen, 1987), the working life of a professional Australian footballer revolves around preparing for and playing football (Shanahan, 1998). It was expected that the large differences in the work undertaken by managers and professional Australian footballers would maximise the opportunities for identifying job-specific stressors and measuring the extent that these vary from one group to the next. The large disparity between managers and professional footballers was also used to assess the cross-occupational versatility of the JSM when it had been augmented by job-specific stressors. This thesis consisted of three major studies. Study One involved a survey of Australian managers, while studies Two and Three focused on professional Australian footballers. The latter group was under-represented in the literature, and as a result of the lack of information on the stressors commonly experienced by this group, an in-depth qualitative study was undertaken in Study Two. The results from Study Two then informed the survey of professional footballers that was conducted in Study Three. Contrary to previous research examining the relative influence of generic and job-specific stressors, the results only provided moderate support for augmenting the JSM with job-specific stressors. Instead of supporting the versatility of the augmented JSM, the overall findings reinforced the broad relevance of the original JSM. Of the four health outcomes measured in Studies One and Three, there was only one - the psychological health of professional Australian footballers - where the proportion of total variance explained by job-specific stressors exceeded 13%. Despite the generally strong performance of the JSM across the two occupational groups, the importance of demand, control and support diminished when examining the less conventional occupation of professional football. The generic model was too narrow to capture the highly specific work characteristics that are important for this occupational group and, as a result, the job-specific stressors explained significantly more of the strain over and above that already provided by the generic model. These findings indicate that when investigating the stressors experienced by conventional occupational groups such as managers, the large amount resources required to identify job-specific stressors are unlikely to be cost-effective. In contrast, the influence of the more situation specific stressors is significantly greater in unconventional occupations and thus the benefits of identifying these non-generic stressors are more likely to outweigh the costs. Studies One and Three identified strong connections between job-specific stressors and important characteristics of the occupation being studied. These connections were consistent with previous research and suggest that before attempting to identify job-specific stressors, researchers need to first become familiar with the nature and context of the occupation. The final issue addressed in this thesis was the role of work and non-work support. The findings indicate that the support provided by supervisors and colleagues was a significant predictor of wellbeing for both managers and professional footballers. In contrast, the level of explained strain accounted for by non-work support was not significant. These results indicate that when developing strategies to protect and enhance employee well-being, particular attention should be given to monitoring and, where necessary, boosting the effectiveness of work-based support. The findings from this thesis have been fed back to the management and sporting communities via conference presentations and peer-reviewed journals (refer pp 220-221). All three studies have been presented at national and international conferences and, overall, were well received by participants. Similarly, the methods, results and major findings arising from Studies One and Two have been critiqued by anonymous reviewers from two international journals. These papers have been accepted for publication in 2001 and 2002 and feedback from the reviewers indicates that the findings represent a significant and unique contribution to the literature. The results of Study Three are currently under review by a sports psychology journal.

A factor-augmented VAR approach : the effect of a rise in the US personal income tax rate on the US and Canada

In this paper a factor-augmented vector autoregressive (FAVAR) model is estimated to characterize the dynamic effects of shocks in the personal income tax rate in the United States on United States and Canadian economies. The representation and the estimate of the FAVAR model is based on Stock and Watson (2005) and the shocks are recovered applying the identification scheme proposed by Bernanke et al. (2005); this method allows impulse response functions to be generated for all the variables in the dataset and provides a description of the domestic and international transmission mechanisms of United States movements in the personal income tax rate. A distinguishing feature of our model is the disaggregation of traded goods sector where imports and exports are disaggregated into 12 and 13 industries, respectively. This provides extra information on the domestic and international transmission mechanism across the two countries. The results show that the FAVAR approach generates a reasonable characterisation of the effects of United States movements in the US personal income tax rate on the United States economy and its transmission to the Canadian economy.

Augmented optometry training simulator with multi-point haptics

Training of optometrists is traditionally achieved under close supervision of peers and superiors. With the rapid advancement in technology, medical procedures are performed more efficiently and effectively, resulting in faster recovery times and less trauma to the patient. However, application of this technology has made it difficult to effectively demonstrate and teach these manual skills as the education is now a combination of not only the medical procedure but also the use of the technology. In this paper we propose to increase the training capabilities of optometry students through haptically-enabled single-point and multi-point training tools as well as augmented reality techniques. Haptics technology allows a human to touch and feel virtual computer models as though they are real. Through physical connection to the operator, haptic devices are considered to be personal robots that are capable of improving the human-computer interaction with a virtual environment. These devices have played an increasing role in developing expertise, reducing instances of medical error and reducing training costs. A haptically-enabled virtual training environment, integrated with an optometry slit lamp instrument can be used to teach cognitive and manual skills while the system tracks the performance of each individual. These interactions would ideally replicate every aspect of the real procedure, consequently preparing the trainee for every possible scenario, without risking the health of a real patient.

Optometry training simulation with augmented reality and haptics

Optometry is an essential health care profession that has existed for many centuries and is still evolving. However, the training approaches for optometrists are not yet on par with the latest technological evolution. The traditional supervisor-student training mode could not provide good immersion and repeatability, while most existing vision-based computer-assisted simulations provide even worse immersion on screens. In this paper, we propose an effective system for optometry training simulation with two major components: augmented reality and haptics. These components are integrated with the actual slit lamp and are able to greatly enhance the immersion for typical optometry training tasks such as foreign body removal. Medical doctors are also involved in suggesting configurations and validating visual and haptic rendering results. Preliminary user studies show very positive feedbacks from optometry students.

On the estimation and inference in factor-augmented panel regressions with correlated loadings

In an influential paper, Pesaran [Pesaran, M.H. (2006). Estimation and inference in large heterogeneous panels with a multifactor error structure. Econometrica 74, 967–1012] proposes a very simple estimator of factor-augmented regressions that has since then become very popular. In this note we demonstrate how the presence of correlated factor loadings can render this estimator inconsistent.

Non-nested tests of a GDP-augmented Fama–French model versus a conditional Fama–French model in the Australian stock market

We extend Vassalou (2003) by conditioning the Fama–French model with the same macroeconomic variables used to construct a GDP factor. The motivation for doing so is to ascertain whether the ability of the GDP-augmented model to explain equity returns is actually due to news about future GDP growth or whether it is due to the macroeconomic conditioning variables used to construct the GDP factor. We compare the performance of a GDP-enhanced Fama–French model with the conditional Fama–French model using non-nested testing techniques. We find that the GDP-augmented model considerably underperforms the conditional version of the model.

Condensing a priori data for recognition based augmented reality

My research proposes novel methods to reduce the cardinality of a priori data used in recognition based augmented reality, whilst retaining distinctive and persistent features in the sets. This research will help reduce latency and increase accuracy in recognition based pose estimation systems, thus improving the user experience for augmented reality applications.