Characterising and predicting cyber attacks using the Cyber Attacker Model Profile (CAMP)

Purpose Ethnographic studies of cyber attacks typically aim to explain a particular profile of attackers in qualitative terms. The purpose of this paper is to formalise some of the approaches to build a Cyber Attacker Model Profile (CAMP) that can be used to characterise and predict cyber attacks. Design/methodology/approach The paper builds a model using social and economic independent or predictive variables from several eastern European countries and benchmarks indicators of cybercrime within the Australian financial services system. Findings The paper found a very strong link between perceived corruption and GDP in two distinct groups of countries – corruption in Russia was closely linked to the GDP of Belarus, Moldova and Russia, while corruption in Lithuania was linked to GDP in Estonia, Latvia, Lithuania and Ukraine. At the same time corruption in Russia and Ukraine were also closely linked. These results support previous research that indicates a strong link between been legitimate economy and the black economy in many countries of Eastern Europe and the Baltic states. The results of the regression analysis suggest that a highly skilled workforce which is mobile and working in an environment of high perceived corruption in the target countries is related to increases in cybercrime even within Australia. It is important to note that the data used for the dependent and independent variables were gathered over a seven year time period, which included large economic shocks such as the global financial crisis. Originality/value This is the first paper to use a modelling approach to directly show the relationship between various social, economic and demographic factors in the Baltic states and Eastern Europe, and the level of card skimming and card not present fraud in Australia.

The impact of employment-level characteristics on work-life interference in school aged children

Work–life interference is important for school-aged workers because it influences their educational outcomes/career aspirations. Although research highlights the role of work hours in determining work–life interference for these workers, work/job-level characteristics have received limited attention. Using survey data from Queensland school students who work part-time, we assess the influence of a range of employment-level variables on work–life interference. The results of multiple regression analysis indicate work–life interference is exacerbated by having low trust in managers and limited scope to refuse work hours and stability in work hours, emphasising the importance of organisational variables in integrating work and non-work spheres for school-aged workers.

Commitment to internationalisation : an extension of the internationalisation process model

Notwithstanding the interest over many years by scholars in modeling the internationalization of the firm, the initial transition for the firm from domestic to international operations remains under-researched. We identify the behavioral factors that are important at the pre-internationalization state and discuss how they may interrelate to influence a decision to commit to internationalization through export commencement. We study export commitment by proposing and constructing an index that incorporates the factors that influence a firm’s propensity to commit to export activities. Utilizing the items from this index in a logistic regression analysis, we distinguish between the pre-internationalization characteristics of exporting and non-exporting firms to better understand the key influences in export commitment. Implications are discussed.

Self-efficacy moderation and mediation roles on BPSD and social support influences on subjective caregiver burden in Chinese spouse caregivers of dementia patients

Background: This study aims to explore moderation and mediation roles of caregiver self-efficacy between subjective caregiver burden and (a) behavioral and psychological symptoms (BPSD) of dementia; and (b) social support. Methods: A cross-sectional study with 137 spouse caregivers of dementia patients was conducted in Shanghai. We collected demographic information for the caregiver–patient dyads, as well as information associated with dementia-related impairments, caregiver social support, caregiver self-efficacy, and SF-36. Results: Multiple regression analysis showed that caregiver self-efficacy was a moderator both between BPSD and subjective caregiver burden, and social support and subjective caregiver burden. Results also showed a partial mediation effect of caregiver self-efficacy on the impact of BPSD on subjective caregiver burden, and a mediation effect of social support on subjective caregiver burden. Caregiver self-efficacy and subjective burden significantly influenced BPSD and social support. Conclusion: Caregiver self-efficacy played an important role in the paths by which the two factors influenced subjective burden. Enhancing caregiver self-efficacy for symptom management (particularly BPSD) can be an essential strategy for determining interventions to support dementia caregivers in China, and possibly in other countries.

Did Brisbane grow smartly? Drivers of city growth 1991-2001 and lessons for current policies

Urban areas are growing unsustainably around the world; however, the growth patterns and their associated drivers vary between contexts. As a result, research has highlighted the need to adopt case study based approaches to stimulate the development of new theoretic understandings. Using land-cover data sets derived from Landsat images (30 m × 30 m), this research identifies both patterns and drivers of urban growth in a period (1991-2001) when a number of policy acts were enacted aimed at fostering smart growth in Brisbane, Australia. A linear multiple regression model was estimated using the proportion of lands that were converted from non-built-up (1991) to built-up usage (2001) within a suburb as a dependent variable to identify significant drivers of land-cover changes. In addition, the hot spot analysis was conducted to identify spatial biases of land-cover changes, if any. Results show that the built-up areas increased by 1.34% every year. About 19.56% of the non-built-up lands in 1991 were converted into built-up lands in 2001. This conversion pattern was significantly biased in the northernmost and southernmost suburbs in the city. This is due to the fact that, as evident from the regression analysis, these suburbs experienced a higher rate of population growth, and had the availability of habitable green field sites in relatively flat lands. The above findings suggest that the policy interventions undertaken between the periods were not as effective in promoting sustainable changes in the environment as they were aimed for.

Making decisions about antibiotic use in the Australian primary healthcare sector

Introduction Australia is contributing to the global problem of antimicrobial resistance with one of the highest rates of antibiotic use amongst OECD countries. Data from the Australian primary healthcare sector suggests unnecessary antibiotics were prescribed for conditions that will resolve without it. If left unchecked, this will result in more resistant micro-organisms, against which antibiotics will be useless. There is a lack of understanding about what is influencing decisions to use antibiotics – what factors influences general practitioners (GPs) to prescribe antibiotics, consumers to seek antibiotics, and pharmacists to fill old antibiotic prescriptions? It is also not clear how these individuals trade-off between the possible benefits that antibiotics may provide in the immediate/short term, against the longer term societal risk of antimicrobial resistance. Method This project will investigate (a) what factors drive decisions to use antibiotics for GPs, pharmacists and consumers, and (b) how these individuals discount the future. Factors will be gleaned from published literature and from a qualitative phase using semi-structured interviews, to inform the development of Discrete Choice Experiments (DCEs). Three DCEs will be constructed – one for each group of interest – to allow investigation of which factors are more important in influencing (a) GPs to prescribe antibiotics, (b) consumers to seek antibiotics, and (c) pharmacists to fill legally valid but old or repeat prescriptions of antibiotics. Regression analysis will be conducted to understand the relative importance of these factors. A Time Trade Off exercise will be developed to investigate how these individuals discount the future, and whether GPs and pharmacists display the same extent of discounting the future, as consumers. Expected Results Findings from the DCEs will provide an insight into which factors are more important in driving decision making in antibiotic use for GPs, pharmacists and consumers. Findings from the Time Trade Off exercise will show what individuals are willing to trade for preserving the miracle of antibiotics. Conclusion The emergence of antibiotic resistance is inevitable. This research will expand on what is currently known about influencing desired behaviour change in antibiotic use, in the fight against antibiotic resistance. Real World Implications Research findings will contribute to existing national programs to bring about a reduction in inappropriate use of antibiotic in Australia. Specifically, influencing (1) how key messages and public health campaigns are crafted to increase health literacy, and (2) clinical education and empowerment of GPs and pharmacists to play a more responsive role as stewards of antibiotic use in the community.

The association between the measurement of adherence to anti-diabetes medicine and the HbA1c

BACKGROUND: Adherence to medicines is important in subjects with diabetes, as nonadherence is associated with an increased risk of morbidity and mortality. However, it is not clear whether there is an association between adherence to medicines and glycaemic control, as not all studies have shown this. One of the reasons for this discrepancy may be that, although there is a standard measure of glycaemic control i.e. HbA1c, there is no standard measure of adherence to medicines. Adherence to medicines can be measured either qualitatively by Morisky or non-Morisky methods or quantitatively using the medicines possession ratio (MPR). AIMS OF THE REVIEW: The aims of this literature review are (1) to determine whether there is an association between adherence to anti-diabetes medicines and glycaemic control, and (2) whether any such association is dependent on how adherence is measured. Methods A literature search of Medline, CINAHL and the Internet (Google) was undertaken with search terms; 'diabetes' with 'adherence' (or compliance, concordance, persistence, continuation) with 'HbA1c' (or glycaemic control). RESULTS: Twenty-three studies were included; 10 qualitative and 12 quantitative studies, and one study using both methods. For the qualitative methods measurements of adherence to anti-diabetes medicines (non-Morisky and Morisky), eight out of ten studies show an association with HbA1c. Nine of ten studies using the quantitative MPR, and two studies using MPR for insulin only, have also shown an association between adherence to anti-diabetes medicines and HbA1c. However, the one study that used both Morisky and MPR did not show an association. Three of the four studies that did not show a relationship, did not use a range of HbA1c values in their regression analysis. The other study that did not show a relationship was specifically in a low income population. CONCLUSIONS: Most studies show an association between adherence to anti-diabetes medicines and HbA1c levels, and this seems to be independent of method used to measure adherence. However, to show an association it is necessary to have a range of HbA1c values. Also, the association is not always apparent in low income populations.

Examining the predictive value of combining the theory of planned behaviour and the volunteer functions inventory

The functions of the volunteer functions inventory were combined with the constructs of the theory of planned behaviour (i.e., attitudes, subjective norms, and perceived behavioural control) to establish whether a stronger, single explanatory model prevailed. Undertaken in the context of episodic, skilled volunteering by individuals who were retired or approaching retirement (N = 186), the research advances on prior studies which either examined the predictive capacity of each model independently or compared their explanatory value. Using hierarchical regression analysis, the functions of the volunteer functions inventory (when controlling for demographic variables) explained an additional 7.0% of variability in individuals’ willingness to volunteer over and above that accounted for by the theory of planned behaviour. Significant predictors in the final model included attitudes, subjective norms and perceived behavioural control from the theory of planned behaviour and the understanding function from the volunteer functions inventory. It is proposed that the items comprising the understanding function may represent a deeper psychological construct (e.g., self-actualisation) not accounted for by the theory of planned behaviour. The findings highlight the potential benefit of combining these two prominent models in terms of improving understanding of volunteerism and providing a single parsimonious model for raising rates of this important behaviour.

Amplitude of accommodation in type 1 diabetes

Purpose People with diabetes have accelerated age-related biometric ocular changes compared with people without diabetes. We determined the effect of Type 1 diabetes on amplitude of accommodation. Method There were 43 participants (33 ± 8 years) with type 1 diabetes and 32 (34 ± 8 years) age-balanced participants without diabetes. There was no significant difference in the mean equivalent refractive error and visual acuity between the two groups. Amplitude of accommodation was measured using two techniques: objective — by determining the accommodative response to a stimulus in a COAS-HD wavefront aberrometer (Wavefront Sciences), and subjective — with a Badal hand optometer (Rodenstock). The influences of age and diabetes duration (in years) on amplitude of accommodation were analyzed using multiple regression analysis. Results Across both groups, objective amplitude was less than subjective amplitude by 1.4 ± 1.2 D. People with diabetes had lower objective (2.7 ± 1.6 D) and subjective (4.0 ± 1.7 D) amplitudes than people without diabetes (objective 4.1 ± 2.1 D, subjective 5.6 ± 2.1 D). For objective amplitude and the whole group, the duration of diabetes contributed 57% of the variation as did age. For the objective amplitude and only the diabetes group this was 78%. For subjective amplitude, the corresponding proportions were 68% and 103%. Conclusions Both objective and subjective techniques showed lowered amplitude of accommodation in participants with type 1 diabetes when compared with age-matched controls. The loss correlated strongly with duration of diabetes. The results suggest that individuals with diabetes will experience presbyopia earlier in life than people without diabetes, possibly due to metabolic changes in the lens.

Comparison of ocular modulation transfer function determined by a ray-tracing aberrometer and a double-pass system in early cataract patients

BACKGROUND: The evaluation of retinal image quality in cataract eyes has gained importance and the clinical modulation transfer functions (MTF) can obtained by aberrometer and double pass (DP) system. This study aimed to compare MTF derived from a ray tracing aberrometer and a DP system in early cataractous and normal eyes. METHODS: There were 128 subjects with 61 control eyes and 67 eyes with early cataract defined according to the Lens Opacities Classification System III. A laser ray-tracing wavefront aberrometer (iTrace) and a double pass (DP) system (OQAS) assessed ocular MTF for 6.0 mm pupil diameters following dilation. Areas under the MTF (AUMTF) and their correlations were analyzed. Stepwise multiple regression analysis assessed factors affecting the differences between iTrace- and OQAS-derived AUMTF for the early cataract group. RESULTS: For both early cataract and control groups, iTrace-derived MTFs were higher than OQAS-derived MTFs across a range of spatial frequencies (P < 0.01). No significant difference between the two groups occurred for iTrace-derived AUMTF, but the early cataract group had significantly smaller OQAS-derived AUMTF than did the control group (P < 0.01). AUMTF determined from both the techniques demonstrated significant correlations with nuclear opacities, higher-order aberrations (HOAs), visual acuity, and contrast sensitivity functions, while the OQAS-derived AUMTF also demonstrated significant correlations with age and cortical opacity grade. The factors significantly affecting the difference between iTrace and OQAS AUMTF were root-mean-squared HOAs (standardized beta coefficient = -0.63, P < 0.01) and age (standardized beta coefficient = 0.26, P < 0.01). CONCLUSIONS: MTFs determined from a iTrace and a DP system (OQAS) differ significantly in early cataractous and normal subjects. Correlations with visual performance were higher for the DP system. OQAS-derived MTF may be useful as an indicator of visual performance in early cataract eyes.

The epidemiological modelling of major depressive disorder : application for the global burden of disease study 2010

Background Although the detrimental impact of major depressive disorder (MDD) at the individual level has been described, its global epidemiology remains unclear given limitations in the data. Here we present the modelled epidemiological profile of MDD dealing with heterogeneity in the data, enforcing internal consistency between epidemiological parameters and making estimates for world regions with no empirical data. These estimates were used to quantify the burden of MDD for the Global Burden of Disease Study 2010 (GBD 2010). Method Analyses drew on data from our existing literature review of the epidemiology of MDD. DisMod-MR, the latest version of the generic disease modelling system redesigned as a Bayesian meta-regression tool, derived prevalence by age, year and sex for 21 regions. Prior epidemiological knowledge, study- and country-level covariates adjusted sub-optimal raw data. Results There were over 298 million cases of MDD globally at any point in time in 2010, with the highest proportion of cases occurring between 25 and 34 years. Global point prevalence was very similar across time (4.4% (95% uncertainty: 4.2–4.7%) in 1990, 4.4% (4.1–4.7%) in 2005 and 2010), but higher in females (5.5% (5.0–6.0%) compared to males (3.2% (3.0–3.6%) in 2010. Regions in conflict had higher prevalence than those with no conflict. The annual incidence of an episode of MDD followed a similar age and regional pattern to prevalence but was about one and a half times higher, consistent with an average duration of 37.7 weeks. Conclusion We were able to integrate available data, including those from high quality surveys and sub-optimal studies, into a model adjusting for known methodological sources of heterogeneity. We were also able to estimate the epidemiology of MDD in regions with no available data. This informed GBD 2010 and the public health field, with a clearer understanding of the global distribution of MDD.

Burden of depressive disorders by country, sex, age, and year : findings from the Global Burden of Disease Study 2010

Background Depressive disorders were a leading cause of burden in the Global Burden of Disease (GBD) 1990 and 2000 studies. Here, we analyze the burden of depressive disorders in GBD 2010 and present severity proportions, burden by country, region, age, sex, and year, as well as burden of depressive disorders as a risk factor for suicide and ischemic heart disease. Methods and Findings Burden was calculated for major depressive disorder (MDD) and dysthymia. A systematic review of epidemiological data was conducted. The data were pooled using a Bayesian meta-regression. Disability weights from population survey data quantified the severity of health loss from depressive disorders. These weights were used to calculate years lived with disability (YLDs) and disability adjusted life years (DALYs). Separate DALYs were estimated for suicide and ischemic heart disease attributable to depressive disorders.Depressive disorders were the second leading cause of YLDs in 2010. MDD accounted for 8.2% (5.9%-10.8%) of global YLDs and dysthymia for 1.4% (0.9%-2.0%). Depressive disorders were a leading cause of DALYs even though no mortality was attributed to them as the underlying cause. MDD accounted for 2.5% (1.9%-3.2%) of global DALYs and dysthymia for 0.5% (0.3%-0.6%). There was more regional variation in burden for MDD than for dysthymia; with higher estimates in females, and adults of working age. Whilst burden increased by 37.5% between 1990 and 2010, this was due to population growth and ageing. MDD explained 16 million suicide DALYs and almost 4 million ischemic heart disease DALYs. This attributable burden would increase the overall burden of depressive disorders from 3.0% (2.2%-3.8%) to 3.8% (3.0%-4.7%) of global DALYs. Conclusions GBD 2010 identified depressive disorders as a leading cause of burden. MDD was also a contributor of burden allocated to suicide and ischemic heart disease. These findings emphasize the importance of including depressive disorders as a public-health priority and implementing cost-effective interventions to reduce its burden.Please see later in the article for the Editors' Summary.

Split leverage : attacking the confidentiality of linked databases by partitioning

This article considers the risk of disclosure in linked databases when statistical analysis of micro-data is permitted. The risk of disclosure needs to be balanced against the utility of the linked data. The current work specifically considers the disclosure risks in permitting regression analysis to be performed on linked data. A new attack based on partitioning of the database is presented.

Design, construction and evaluation of systems to predict risk in obstetrics

We present a systematic, practical approach to developing risk prediction systems, suitable for use with large databases of medical information. An important part of this approach is a novel feature selection algorithm which uses the area under the receiver operating characteristic (ROC) curve to measure the expected discriminative power of different sets of predictor variables. We describe this algorithm and use it to select variables to predict risk of a specific adverse pregnancy outcome: failure to progress in labour. Neural network, logistic regression and hierarchical Bayesian risk prediction models are constructed, all of which achieve close to the limit of performance attainable on this prediction task. We show that better prediction performance requires more discriminative clinical information rather than improved modelling techniques. It is also shown that better diagnostic criteria in clinical records would greatly assist the development of systems to predict risk in pregnancy. We present a systematic, practical approach to developing risk prediction systems, suitable for use with large databases of medical information. An important part of this approach is a novel feature selection algorithm which uses the area under the receiver operating characteristic (ROC) curve to measure the expected discriminative power of different sets of predictor variables. We describe this algorithm and use it to select variables to predict risk of a specific adverse pregnancy outcome: failure to progress in labour. Neural network, logistic regression and hierarchical Bayesian risk prediction models are constructed, all of which achieve close to the limit of performance attainable on this prediction task. We show that better prediction performance requires more discriminative clinical information rather than improved modelling techniques. It is also shown that better diagnostic criteria in clinical records would greatly assist the development of systems to predict risk in pregnancy.

The influence of internal communication on employee engagement: A pilot study

Internal communication is an important concept and integral to internal public relations with links to positive organizational and employee outcomes such as employee engagement. While scholars emphasize the importance of the relationship between internal communication and employee engagement, the association has not been empirically tested. Using surveys and regression analysis this study confirms that internal organizational communication and internal supervisor communication support workplace relationships based on meaning and worth, and have a significant part to play in developing and maintaining optimal employee engagement.