An analysis of the determinants of job satisfaction when individuals' baseline satisfaction levels may differ.

A growing literature seeks to explain differences in individuals' self-reported satisfaction with their jobs. The evidence so far has mainly been based on cross-sectional data and when panel data have been used, individual unobserved heterogeneity has been modelled as an ordered probit model with random effects. This article makes use of longitudinal data for Denmark, taken from the waves 1995-1999 of the European Community Household Panel, and estimates fixed effects ordered logit models using the estimation methods proposed by Ferrer-i-Carbonel and Frijters (2004) and Das and van Soest (1999). For comparison and testing purposes a random effects ordered probit is also estimated. Estimations are carried out separately on the samples of men and women for individuals' overall satisfaction with the jobs they hold. We find that using the fixed effects approach (that clearly rejects the random effects specification), considerably reduces the number of key explanatory variables. The impact of central economic factors is the same as in previous studies, though. Moreover, the determinants of job satisfaction differ considerably between the genders, in particular once individual fixed effects are allowed for.

Difference and dispersion : educational research in a postmodern context

Difference and Dispersion is the fourth in a series of annual research papers produced by doctoral students from The Graduate School of Education, The University of Queensland, following their presentation at the School’s annual Postgraduate Research Conference in Education. The work featured herein celebrates the diversity of cultural and disciplinary backgrounds of education researchers who come from as far afield as Germany, Hong Kong, China, Nigeria, Russia, Singapore, Thailand and of course different parts of Australia. In keeping with a postmodern epistemology, ‘difference’ and ‘dispersion’ are key themes in apprehending the multiplicity of their research topics, methodologies, methods and speaking/writing positions. From widely differing contexts and situations, these writers address the consequences, implications and possibilities for education at the beginning of the third millennium. Their interest ranges from location-specific issues in schools and classrooms, change in learning contexts and processes, educational discourses and relations of power in diverse geographical settings, and the differing articulations of the local and the global in situated policy contexts. Conceived and developed in a spirit of ongoing dialogue with and insight to alternative views and visions of education and society, this edited collection exemplifies the quality in diversity and the high levels of scholarship and supervision at one of Australia’s finest Graduate Schools of Education.

Evaluation of community participation for the development of culture-based fisheries in village reservoirs of Sri Lanka

In this paper an attempt is made to identify the socioeconomic characteristics of a community that influences the development and management of culture-based fisheries in village reservoirs of Sri Lanka. Socioeconomic data were collected from 46 agricultural farming communities associated with 47 village reservoirs in Sri Lanka. Principal component analysis indicated that scores of the first principal component were positively influenced by socioeconomic characteristics that are favorable for making collective decisions. These included leadership of the officers, age of the group, percentage of active members of the group, percentage of kinship of the group, percentage of common interest of the group, and percentage of participation of the group. The size of the group had negative effect on the first principal component. The principal component scores of communication were positively related to willingness to pay (P< 0.001). The communities with socioeconomic characteristics favouring collective decision making were in favor of culture-based fisheries. Homogeneity of group characteristics facilitated successful development of culture-based fisheries.

Culture independent analysis of greyback canegrub-associated microflora and microbial community comparison using subtractive hybridisation

Greyback canegrubs cost the Australian sugarcane industry around $13 million per annum in damage and control. A novel and cost effective biocontrol bacterium could play an important role in the integrated pest management program currently in place to reduce damage and control associated costs. During the course of this project, terminal restriction fragment length polymorphism (TRFLP), 16-S rDNA cloning, suppressive subtractive hybridisation (SSH) and entomopathogen-specific PCR screening were used to investigate the little studied canegrub-associated microflora in an attempt to discover novel pathogens from putatively-diseased specimens. Microflora associated with these soil-dwelling insects was found to be both highly diverse and divergent between individual specimens. Dominant members detected in live specimens were predominantly from taxa of known insect symbionts while dominant sequences amplified from dead grubs were homologous to putativelysaprophytic bacteria and bacteria able to grow during refrigeration. A number of entomopathogenic bacteria were identified such as Photorhabdus luminescens and Pseudomonas fluorescens. Dead canegrubs prior to decomposition need to be analysed if these bacteria are to be isolated. Novel strategies to enrich putative pathogen-associated sequences (SSH and PCR screening) were shown to be promising approaches for pathogen discovery and the investigation of canegrubsassociated microflora. However, due to inter- and intra-grub-associated community diversity, dead grub decomposition and PCR-specific methodological limitations (PCR bias, primer specificity, BLAST database restrictions, 16-S gene copy number and heterogeneity), recommendations have been made to improve the efficiency of such techniques. Improved specimen collection procedures and utilisation of emerging high-throughput sequencing technologies may be required to examine these complex communities in more detail. This is the first study to perform a whole-grub analysis and comparison of greyback canegrub-associated microbial communities. This work also describes the development of a novel V3-PCR based SSH technique. This was the first SSH technique to use V3-PCR products as a starting material and specifically compare bacterial species present in a complex community.

The differential impact of holocaust trauma across three generations

In the current thesis, the reasons for the differential impact of Holocaust trauma on Holocaust survivors, and the differential intergenerational transmission of this trauma to survivors’ children and grandchildren were explored. A model specifically related to Holocaust trauma and its transmission was developed based on trauma, family systems and attachment theories as well as theoretical and anecdotal conjecture in the Holocaust literature. The Model of the Differential Impact of Holocaust Trauma across Three Generations was tested firstly by extensive meta-analyses of the literature pertaining to the psychological health of Holocaust survivors and their descendants and secondly via analysis of empirical study data. The meta-analyses reported in this thesis represent the first conducted with research pertaining to Holocaust survivors and grandchildren of Holocaust survivors. The meta-analysis of research conducted with children of survivors is the first to include both published and unpublished research. Meta-analytic techniques such as meta-regression and sub-set meta-analyses provided new information regarding the influence of a number of unmeasured demographic variables on the psychological health of Holocaust survivors and descendants. Based on the results of the meta-analyses it was concluded that Holocaust survivors and their children and grandchildren suffer from a statistically significantly higher level or greater severity of psychological symptoms than the general population. However it was also concluded that there is statistically significant variation in psychological health within the Holocaust survivor and descendant populations. Demographic variables which may explain a substantial amount of this variation have been largely under-assessed in the literature and so an empirical study was needed to clarify the role of demographics in determining survivor and descendant mental health. A total of 124 participants took part in the empirical study conducted for this thesis with 27 Holocaust survivors, 69 children of survivors and 28 grandchildren of survivors. A worldwide recruitment process was used to obtain these participants. Among the demographic variables assessed in the empirical study, aspects of the survivors’ Holocaust trauma (namely the exact nature of their Holocaust experiences, the extent of family bereavement and their country of origin) were found to be particularly potent predictors of not only their own psychological health but continue to be strongly influential in determining the psychological health of their descendants. Further highlighting the continuing influence of the Holocaust was the finding that number of Holocaust affected ancestors was the strongest demographic predictor of grandchild of survivor psychological health. Apart from demographic variables, the current thesis considered family environment dimensions which have been hypothesised to play a role in the transmission of the traumatic impact of the Holocaust from survivors to their descendants. Within the empirical study, parent-child attachment was found to be a key determinant in the transmission of Holocaust trauma from survivors to their children and insecure parent-child attachment continues to reverberate through the generations. In addition, survivors’ communication about the Holocaust and their Holocaust experiences to their children was found to be more influential than general communication within the family. Ten case studies (derived from the empirical study data set) are also provided; five Holocaust survivors, three children of survivors and two grandchildren of survivors. These cases add further to the picture of heterogeneity of the survivor and descendant populations in both experiences and adaptations. It is concluded that the legacy of the Holocaust continues to leave its mark on both its direct survivors and their descendants. Even two generations removed, the direct and indirect effects of the Holocaust have yet to be completely nullified. Research with Holocaust survivor families serves to highlight the differential impacts of state-based trauma and the ways in which its effects continue to be felt for generations. The revised and empirically tested Model of the Differential Impact of Holocaust Trauma across Three Generations presented at the conclusion of this thesis represents a further clarification of existing trauma theories as well as the first attempt at determining the relative importance of both cognitive, interpersonal/interfamilial interaction processes and demographic variables in post-trauma psychological health and transmission of traumatic impact.

Discrete choice modelling of combined mode and departure time

Typical daily decision-making process of individuals regarding use of transport system involves mainly three types of decisions: mode choice, departure time choice and route choice. This paper focuses on the mode and departure time choice processes and studies different model specifications for a combined mode and departure time choice model. The paper compares different sets of explanatory variables as well as different model structures to capture the correlation among alternatives and taste variations among the commuters. The main hypothesis tested in this paper is that departure time alternatives are also correlated by the amount of delay. Correlation among different alternatives is confirmed by analyzing different nesting structures as well as error component formulations. Random coefficient logit models confirm the presence of the random taste heterogeneity across commuters. Mixed nested logit models are estimated to jointly account for the random taste heterogeneity and the correlation among different alternatives. Results indicate that accounting for the random taste heterogeneity as well as inter-alternative correlation improves the model performance.

Improving detection probabilities for pests in stored grains

BACKGROUND: The presence of insects in stored grains is a significant problem for grain farmers, bulk grain handlers and distributors worldwide. Inspections of bulk grain commodities is essential to detect pests and therefore to reduce the risk of their presence in exported goods. It has been well documented that insect pests cluster in response to factors such as microclimatic conditions within bulk grain. Statistical sampling methodologies for grains, however, have typically considered pests and pathogens to be homogeneously distributed throughout grain commodities. In this paper we demonstrate a sampling methodology that accounts for the heterogeneous distribution of insects in bulk grains. RESULTS: We show that failure to account for the heterogeneous distribution of pests may lead to overestimates of the capacity for a sampling program to detect insects in bulk grains. Our results indicate the importance of the proportion of grain that is infested in addition to the density of pests within the infested grain. We also demonstrate that the probability of detecting pests in bulk grains increases as the number of sub-samples increases, even when the total volume or mass of grain sampled remains constant. CONCLUSION: This study demonstrates the importance of considering an appropriate biological model when developing sampling methodologies for insect pests. Accounting for a heterogeneous distribution of pests leads to a considerable improvement in the detection of pests over traditional sampling models.

A simultaneous equations model of crash frequency by collision type for rural intersections

Safety at roadway intersections is of significant interest to transportation professionals due to the large number of intersections in transportation networks, the complexity of traffic movements at these locations that leads to large numbers of conflicts, and the wide variety of geometric and operational features that define them. A variety of collision types including head-on, sideswipe, rear-end, and angle crashes occur at intersections. While intersection crash totals may not reveal a site deficiency, over exposure of a specific crash type may reveal otherwise undetected deficiencies. Thus, there is a need to be able to model the expected frequency of crashes by collision type at intersections to enable the detection of problems and the implementation of effective design strategies and countermeasures. Statistically, it is important to consider modeling collision type frequencies simultaneously to account for the possibility of common unobserved factors affecting crash frequencies across crash types. In this paper, a simultaneous equations model of crash frequencies by collision type is developed and presented using crash data for rural intersections in Georgia. The model estimation results support the notion of the presence of significant common unobserved factors across crash types, although the impact of these factors on parameter estimates is found to be rather modest.

Poisson, Poisson-gamma and zero-inflated regression models of motor vehicle crashes: balancing statistical fit and theory

There has been considerable research conducted over the last 20 years focused on predicting motor vehicle crashes on transportation facilities. The range of statistical models commonly applied includes binomial, Poisson, Poisson-gamma (or negative binomial), zero-inflated Poisson and negative binomial models (ZIP and ZINB), and multinomial probability models. Given the range of possible modeling approaches and the host of assumptions with each modeling approach, making an intelligent choice for modeling motor vehicle crash data is difficult. There is little discussion in the literature comparing different statistical modeling approaches, identifying which statistical models are most appropriate for modeling crash data, and providing a strong justification from basic crash principles. In the recent literature, it has been suggested that the motor vehicle crash process can successfully be modeled by assuming a dual-state data-generating process, which implies that entities (e.g., intersections, road segments, pedestrian crossings, etc.) exist in one of two states—perfectly safe and unsafe. As a result, the ZIP and ZINB are two models that have been applied to account for the preponderance of “excess” zeros frequently observed in crash count data. The objective of this study is to provide defensible guidance on how to appropriate model crash data. We first examine the motor vehicle crash process using theoretical principles and a basic understanding of the crash process. It is shown that the fundamental crash process follows a Bernoulli trial with unequal probability of independent events, also known as Poisson trials. We examine the evolution of statistical models as they apply to the motor vehicle crash process, and indicate how well they statistically approximate the crash process. We also present the theory behind dual-state process count models, and note why they have become popular for modeling crash data. A simulation experiment is then conducted to demonstrate how crash data give rise to “excess” zeros frequently observed in crash data. It is shown that the Poisson and other mixed probabilistic structures are approximations assumed for modeling the motor vehicle crash process. Furthermore, it is demonstrated that under certain (fairly common) circumstances excess zeros are observed—and that these circumstances arise from low exposure and/or inappropriate selection of time/space scales and not an underlying dual state process. In conclusion, carefully selecting the time/space scales for analysis, including an improved set of explanatory variables and/or unobserved heterogeneity effects in count regression models, or applying small-area statistical methods (observations with low exposure) represent the most defensible modeling approaches for datasets with a preponderance of zeros

A systematic review of the association between physical activity and colorectal cancer risk

This review evaluated the strength of the evidence for a causal relationship between physical activity (PA) and colorectal cancer (CRC). A systematic review of databases through February 2008 was conducted to identify studies that assessed the association between total or recreational PA and incidence or mortality of CRC (including CRC, rectal cancer, colon cancer, and proximal or distal colon cancer). Studies were evaluated for significant associations between PA and risk of CRC endpoints and for evidence of dose–response relationships in the highest quality studies. Twenty cohort studies were evaluated; 11 were high-quality. Fifty percent of all studies and 64%of highest quality studies reported at least one significant association between PA and risk of a CRC endpoint (Po0.05).However, only 28%of all analyses (31% of analyses of highest quality studies) were significant (Po0.05). Only 40% of analyses of highest quality studies resulted in a significant P for trend (Po0.05); however, a non-significant inverse linear association between PA and colon cancer riskwas apparent.Heterogeneity in the evidence from all studies and from the highest quality studies was evident. Evidence from cohort studies is not sufficient to claim a convincing relationship exists between PA and CRC risk.

A new method to quantify the application thickness of sunscreen on skin

Proper application of sunscreen is essential as an effective public health strategy for skin cancer prevention. Insufficient application is common among sunbathers, results in decreased sun protection and may therefore lead to increased UV damage of the skin. However, no objective measure of sunscreen application thickness (SAT) is currently available for field-based use. We present a method to detect SAT on human skin for determining the amount of sunscreen applied and thus enabling comparisons to manufacturer recommendations. Using a skin swabbing method and subsequent spectrophotometric analysis, we were able to determine SAT on human skin. A swabbing method was used to derive SAT on skin (in mg sunscreen per cm2 of skin area) through the concentration–absorption relationship of sunscreen determined in laboratory experiments. Analysis differentiated SATs between 0.25 and 4 mg cm−2 and showed a small but significant decrease in concentration over time postapplication. A field study was performed, in which the heterogeneity of sunscreen application could be investigated. The proposed method is a low cost, noninvasive method for the determination of SAT on skin and it can be used as a valid tool in field- and population-based studies.

Panel studies of new venture creation : a review and suggestions for future research

We review all journal articles based on “PSED-type” research, i.e., longitudinal, empirical studies of large probability samples of on-going, business start-up efforts. We conclude that the research stream has yielded interesting findings; sometimes by confirming prior research with a less bias-prone methodology and at other times by challenging whether prior conclusions are valid for the early stages of venture development. Most importantly, the research has addressed new, process-related research questions that prior research has shunned or been unable to study in a rigorous manner. The research has revealed an enormous and fascinating variability in new venture creation that also makes it challenging to arrive at broadly valid generalizations. An analysis of the findings across studies as well as an examination of those studies that have been relatively more successful at explaining outcomes give good guidance regarding what is required in order to achieve strong and credible results. We compile and present such advice to users of existing data sets and designers of new projects in the following areas: Statistically representative and/or theoretically relevant sampling; Level of analysis issues; Dealing with process heterogeneity; Dealing with other heterogeneity issues, and Choice and interpretation of dependent variables.

Correcting mean-field approximations for birth-death-movement processes

On the microscale, migration, proliferation and death are crucial in the development, homeostasis and repair of an organism; on the macroscale, such effects are important in the sustainability of a population in its environment. Dependent on the relative rates of migration, proliferation and death, spatial heterogeneity may arise within an initially uniform field; this leads to the formation of spatial correlations and can have a negative impact upon population growth. Usually, such effects are neglected in modeling studies and simple phenomenological descriptions, such as the logistic model, are used to model population growth. In this work we outline some methods for analyzing exclusion processes which include agent proliferation, death and motility in two and three spatial dimensions with spatially homogeneous initial conditions. The mean-field description for these types of processes is of logistic form; we show that, under certain parameter conditions, such systems may display large deviations from the mean field, and suggest computationally tractable methods to correct the logistic-type description.

Online alcohol interventions : a systematic review

Background: There has been a significant increase in the availability of online programs for alcohol problems. A systematic review of the research evidence underpinning these programs is timely. Objectives: Our objective was to review the efficacy of online interventions for alcohol misuse. Systematic searches of Medline, PsycINFO, Web of Science, and Scopus were conducted for English abstracts (excluding dissertations) published from 1998 onward. Search terms were: (1) Internet, Web*; (2) online, computer*; (3) alcohol*; and (4) E\effect*, trial*, random* (where * denotes a wildcard). Forward and backward searches from identified papers were also conducted. Articles were included if (1) the primary intervention was delivered and accessed via the Internet, (2) the intervention focused on moderating or stopping alcohol consumption, and (3) the study was a randomized controlled trial of an alcohol-related screen, assessment, or intervention. Results: The literature search initially yielded 31 randomized controlled trials (RCTs), 17 of which met inclusion criteria. Of these 17 studies, 12 (70.6%) were conducted with university students, and 11 (64.7%) specifically focused on at-risk, heavy, or binge drinkers. Sample sizes ranged from 40 to 3216 (median 261), with 12 (70.6%) studies predominantly involving brief personalized feedback interventions. Using published data, effect sizes could be extracted from 8 of the 17 studies. In relation to alcohol units per week or month and based on 5 RCTs where a measure of alcohol units per week or month could be extracted, differential effect sizes to post treatment ranged from 0.02 to 0.81 (mean 0.42, median 0.54). Pre-post effect sizes for brief personalized feedback interventions ranged from 0.02 to 0.81, and in 2 multi-session modularized interventions, a pre-post effect size of 0.56 was obtained in both. Pre-post differential effect sizes for peak blood alcohol concentrations (BAC) ranged from 0.22 to 0.88, with a mean effect size of 0.66. Conclusions: The available evidence suggests that users can benefit from online alcohol interventions and that this approach could be particularly useful for groups less likely to access traditional alcohol-related services, such as women, young people, and at-risk users. However, caution should be exercised given the limited number of studies allowing extraction of effect sizes, the heterogeneity of outcome measures and follow-up periods, and the large proportion of student-based studies. More extensive RCTs in community samples are required to better understand the efficacy of specific online alcohol approaches, program dosage, the additive effect of telephone or face-to-face interventions, and effective strategies for their dissemination and marketing.