Satisfaction of newly graduated nurses enrolled in transition-to-practice programmes in their first year of employment: a systematic review

To investigate job satisfaction and confidence levels of graduate nurses during their first year of employment and the impact various training programmes have on these factors.

Recidivism among participants of an employment assistance program for prisoners and offenders

Recidivism outcomes were examined over a 2-year postrelease period for participants of an Australian employment assistance program. The voluntary 12-month program operated from 17 Victorian correctional locations, 7 prisons, and 10 community corrections locations, targeting participants at moderate to high risk of reoffending. Recidivism outcomes included simple rates of reoffending for the whole program (N = 3,034 registered participants) and analyses of rate and seriousness of reoffending and extent of poly-offending for a random sample of 600 program participants and 600 nonparticipants. Offending among program participants' pre- and post-registration was also investigated. Results showed a very low rate of reoffending (7.46%) for the entire program participant group while engaged in the program. As well, program participants had significantly lower levels of recidivism than nonparticipants, and postregistration offending was significantly lower than preregistration offending. Findings indicate that long-term postrelease employment support programs provide positive benefits in terms of reduced reoffending.

Dilemmas concerning the employment of university graduates in China

This article draws on a ‘within-subject’ design of employment of university graduates in China over two different periods, namely 2008 and 2014. This research was conducted based on semi-structured interviews and secondary data analysis with four groups of key stakeholders including universities, government agencies, labor-market intermediaries and university graduates. The ‘within-subject’ design enabled an in-depth exploration of how changes at formal and informal institutions affect the employment of university graduates in a fast-changing labor market. The results show that lack of institutional interactions, socially constructed norms that influence graduates’ perceptions and ambiguous directions of educational policies significantly affect university graduates’ employment.

Rethinking the employer's summary dismissal power in the employment contract

 The principal subject of this thesis is the employer’s summary dismissal power under Australian contract law. Summary dismissal is by far the most brutal way that an employment relationship may end. Its suddenness can have long-lasting economic and psychological impacts upon the dismissed employee. However, the area has been neglected in legal scholarship. The result of this is that issues arising from the jurisprudence have not been the subject of critique and scrutiny, until now. This thesis addresses this gap in the scholarship. The thesis also proposes a new approach to resolving these disputes based on the proportionality concept. An employer's decision to dismiss its employees in this way should be commensurate to the detriment caused by the employee's actions. Therefore, one 'should not use a sledgehammer to crack a nut.'

Improved risk predictions via sparse imputation of patient conditions in electronic medical records

Electronic Medical Records (EMR) are increasingly used for risk prediction. EMR analysis is complicated by missing entries. There are two reasons - the “primary reason for admission” is included in EMR, but the co-morbidities (other chronic diseases) are left uncoded, and, many zero values in the data are accurate, reflecting that a patient has not accessed medical facilities. A key challenge is to deal with the peculiarities of this data - unlike many other datasets, EMR is sparse, reflecting the fact that patients have some, but not all diseases. We propose a novel model to fill-in these missing values, and use the new representation for prediction of key hospital events. To “fill-in” missing values, we represent the feature-patient matrix as a product of two low rank factors, preserving the sparsity property in the product. Intuitively, the product regularization allows sparse imputation of patient conditions reflecting common comorbidities across patients. We develop a scalable optimization algorithm based on Block coordinate descent method to find an optimal solution. We evaluate the proposed framework on two real world EMR cohorts: Cancer (7000 admissions) and Acute Myocardial Infarction (2652 admissions). Our result shows that the AUC for 3 months admission prediction is improved significantly from (0.741 to 0.786) for Cancer data and (0.678 to 0.724) for AMI data. We also extend the proposed method to a supervised model for predicting of multiple related risk outcomes (e.g. emergency presentations and admissions in hospital over 3, 6 and 12 months period) in an integrated framework. For this model, the AUC averaged over outcomes is improved significantly from (0.768 to 0.806) for Cancer data and (0.685 to 0.748) for AMI data.

Neoliberalism, economic restructuring and policy change: precarious housing and precarious employment in Australia

 Housing, employment and economic conditions in many nations have changed greatly over the past decades. This paper explores the ways in which changing housing markets, economic conditions and government policies have affected vulnerable individuals and households, using Australia as a case study. The paper finds a substantial number and proportion of low income Australians have been affected by housing and employment that is insecure with profound implications for vulnerability. Importantly, the paper suggests that in Australia the economic gains achieved as a consequence of mining-related growth in the early 2000s were translated as greater employment security for some on low incomes, but not all. Enhanced access to employment in this period was differentiated by gender, with women largely missing out on the growth in jobs. For the population as a whole, employment gains were offset by increased housing insecurity as accommodation costs rose. The paper finds low income lone parents were especially vulnerable because they were unable to benefit from a buoyant labour market over the decade 2000–2010. They were also adversely affected by national policy changes intended to encourage engagement with paid work. The outcomes identified for Australia are likely to have been mirrored in other nations, especially those that have embraced, or been forced to adopt, more restrictive welfare and income support regimes.

Itinerant foreign harvest workers in Australia: the impact of precarious employment on occupational safety and health

Horticulture work in many high-income economies is increasingly performed by temporary migrant workers from low-wage economies. In Australia, such work is now performed predominantly by international backpackers – young well-educated workers with mostly sound English language skills. These workers are drawn to harvesting work by a government scheme which provides an incentive for completing a specified number of days work in horticulture. This article examines the health and safety experience of these workers, through focus groups, interviews and an online survey. Notwithstanding their distinctive backgrounds, the harvesting experience of these temporary migrant workers is similar to that of low-skilled migrants working in other high-income countries. Health and safety risks associated with work organisation and payment systems, and a lack of compliance with OHS legal requirements, are commonplace but potentially compounded by a sense of invincibility amongst these young travellers. Furthermore, a growing pool of undocumented workers is placing downward pressures on their employment conditions. The vulnerability associated with work and earnings uncertainty, and the harsh environment in which harvesting work occurs, remains a constant notwithstanding the background of these workers.

International education, the formation of capital and graduate employment : Chinese accounting graduates’ experiences of the Australian labour market

Since the late 1970s, international education has steadily gained in popularity in China.An emerging middle class seeks to strengthen its position in China’s rapidly stratifyingsociety under its socialist market economy with the shift from wealth creation for all towealth concentration for a few. Previously, a foreign qualification was considered apassport to success in either the host or home country’s labour market. But the growingpopularity of overseas study, coupled with the massification of the Chinese highereducation, means Chinese international students are seeking to distinguish themselvesin an increasingly competitive global labour market. This longitudinal study of internationalgraduates, backgrounded by Australian employer perceptions, examines thejourneys of 13 Chinese accounting graduates as they attempt to transition from anAustralian university into the Australian labour market. Bourdieu’s thinking tools offield, capital, disposition and habitus are utilised to consider how different cultural,social and linguistic capitals inform employer understandings of ‘employability’ meantChinese accounting graduates significantly adjusted their life goals.

Stabilizing sparse cox model using statistic and semantic structures in electronic medical records

Stability in clinical prediction models is crucial for transferability between studies, yet has received little attention. The problem is paramount in high dimensional data, which invites sparse models with feature selection capability. We introduce an effective method to stabilize sparse Cox model of time-to-events using statistical and semantic structures inherent in Electronic Medical Records (EMR). Model estimation is stabilized using three feature graphs built from (i) Jaccard similarity among features (ii) aggregation of Jaccard similarity graph and a recently introduced semantic EMR graph (iii) Jaccard similarity among features transferred from a related cohort. Our experiments are conducted on two real world hospital datasets: a heart failure cohort and a diabetes cohort. On two stability measures – the Consistency index and signal-to-noise ratio (SNR) – the use of our proposed methods significantly increased feature stability when compared with the baselines.

Hierarchical Bayesian nonparametric models for knowledge discovery from electronic medical records

Electronic Medical Record (EMR) has established itself as a valuable resource for large scale analysis of health data. A hospital EMR dataset typically consists of medical records of hospitalized patients. A medical record contains diagnostic information (diagnosis codes), procedures performed (procedure codes) and admission details. Traditional topic models, such as latent Dirichlet allocation (LDA) and hierarchical Dirichlet process (HDP), can be employed to discover disease topics from EMR data by treating patients as documents and diagnosis codes as words. This topic modeling helps to understand the constitution of patient diseases and offers a tool for better planning of treatment. In this paper, we propose a novel and flexible hierarchical Bayesian nonparametric model, the word distance dependent Chinese restaurant franchise (wddCRF), which incorporates word-to-word distances to discover semantically-coherent disease topics. We are motivated by the fact that diagnosis codes are connected in the form of ICD-10 tree structure which presents semantic relationships between codes. We exploit a decay function to incorporate distances between words at the bottom level of wddCRF. Efficient inference is derived for the wddCRF by using MCMC technique. Furthermore, since procedure codes are often correlated with diagnosis codes, we develop the correspondence wddCRF (Corr-wddCRF) to explore conditional relationships of procedure codes for a given disease pattern. Efficient collapsed Gibbs sampling is derived for the Corr-wddCRF. We evaluate the proposed models on two real-world medical datasets - PolyVascular disease and Acute Myocardial Infarction disease. We demonstrate that the Corr-wddCRF model discovers more coherent topics than the Corr-HDP. We also use disease topic proportions as new features and show that using features from the Corr-wddCRF outperforms the baselines on 14-days readmission prediction. Beside these, the prediction for procedure codes based on the Corr-wddCRF also shows considerable accuracy.