Maternity care experiences of Asia ethnic minorities in rural Tasmania, Australia : a mixed methods study

When migrating to Australia Asian women bring with them birthing cultural beliefs and practices, many of which are different from the Australian medical and cultural understanding of reproduction. Such cultural differences may result in conflicts between clients and health care providers especially when the migrants have a poor knowledge of English. The research investigates the maternity care experiences of Asian migrants in Tasmania. The barriers that Asian migrants face in accessing maternity care services and the factors that affect their views towards maternity care were also explored. A mix of quantitative and qualitative methods was employed. Ten women from different ethnic minorities were invited to semi-structured interviews. The qualitative data were analysed using grounded theory. Findings from the interviews were utilized to design a survey questionnaire. Of the 150 survey questionnaires posted, 121 questionnaires were returned. Descriptive statistics and Chi-square tests of independence were used to analyse the quantitative data. Asian migrants followed some traditional practices such as having good rest and eating hot food during the postpartum month. However, they tended to adapt or disregard traditional practices that were no longer applicable in the new environment including the practices of not washing or having a shower. Support is vital for women recovering after childbirth to prevent postnatal depression. Two main barriers migrant women face in accessing health care are language and cultural barriers. Country of origin, partner’s ethnicity, religion and length of stay in Australia are factors that shape the migrants’ views and attitudes towards and experience of maternity care. Providing interpreting services, social support for migrant women and improving the cross-cultural training for healthcare providers are recommended to improve available maternal care services. The factors that affect migrants’ view on maternity care should be taken into account when providing maternity care for Asian migrant women.

Does stage of illness impact treatment response in bipolar disorder? Empirical treatment data and their implication for the staging model and early intervention

Objective: The staging model suggests that early stages of bipolar disorder respond better to treatments and have a more favourable prognosis. This study aims to provide empirical support for the model, and the allied construct of early intervention.

Methods: Pooled data from mania, depression, and maintenance studies of olanzapine were analyzed. Individuals were categorized as having had 0, 1–5, 6–10, or >10 prior episodes of illness, and data were analyzed across these groups.

Results: Response rates for the mania and maintenance studies ranged from 52–69% and 10–50%, respectively, for individuals with 1–5 previous episodes, and from 29–59% and 11–40% for individuals with >5 previous episodes. These rates were significantly higher for the 1–5 group on most measures of response with up to a twofold increase in the chance of responding for those with fewer previous episodes. For the depression studies, response rates were significantly higher for the 1–5 group for two measures only. In the maintenance studies, the chance of relapse to either mania or depression was reduced by 40–60% for those who had experienced 1–5 episodes or 6–10 episodes compared to the >10 episode group, respectively. This trend was statistically significant only for relapse into mania for the 1–5 episode group (p = 0.005).

Conclusion: Those individuals at the earliest stages of illness consistently had a more favourable response to treatment. This is consistent with the staging model and

A novel semi-supervised approach for network traffic clustering

Network traffic classification is an essential component for network management and security systems. To address the limitations of traditional port-based and payload-based methods, recent studies have been focusing on alternative approaches. One promising direction is applying machine learning techniques to classify traffic flows based on packet and flow level statistics. In particular, previous papers have illustrated that clustering can achieve high accuracy and discover unknown application classes. In this work, we present a novel semi-supervised learning method using constrained clustering algorithms. The motivation is that in network domain a lot of background information is available in addition to the data instances themselves. For example, we might know that flow ƒ1 and ƒ2 are using the same application protocol because they are visiting the same host address at the same port simultaneously. In this case, ƒ1 and ƒ2 shall be grouped into the same cluster ideally. Therefore, we describe these correlations in the form of pair-wise must-link constraints and incorporate them in the process of clustering. We have applied three constrained variants of the K-Means algorithm, which perform hard or soft constraint satisfaction and metric learning from constraints. A number of real-world traffic traces have been used to show the availability of constraints and to test the proposed approach. The experimental results indicate that by incorporating constraints in the course of clustering, the overall accuracy and cluster purity can be significantly improved.

Activity recognition and abnormality detection with the switching hidden semi-Markov model

This paper addresses the problem of learning and recognizing human activities of daily living (ADL), which is an important research issue in building a pervasive and smart environment. In dealing with ADL, we argue that it is beneficial to exploit both the inherent hierarchical organization of the activities and their typical duration. To this end, we introduce the Switching Hidden Semi-Markov Model (S-HSMM), a two-layered extension of the hidden semi-Markov model (HSMM) for the modeling task. Activities are modeled in the S-HSMM in two ways: the bottom layer represents atomic activities and their duration using HSMMs; the top layer represents a sequence of high-level activities where each high-level activity is made of a sequence of atomic activities. We consider two methods for modeling duration: the classic explicit duration model using multinomial distribution, and the novel use of the discrete Coxian distribution. In addition, we propose an effective scheme to detect abnormality without the need for training on abnormal data. Experimental results show that the S-HSMM performs better than existing models including the flat HSMM and the hierarchical hidden Markov model in both classification and abnormality detection tasks, alleviating the need for presegmented training data. Furthermore, our discrete Coxian duration model yields better computation time and generalization error than the classic explicit duration model.

Comparisons between two empirical yield criteria for rock masses

In general, rock masses are inhomogeneous, discontinuous media composed of rock material and naturally occurring discontinuities such as joints, fractures and bedding planes. Because of these features, the strength of rock masses is notoriously difficult to assess. Nonetheless, many criteria have been proposed for estimating rock mass strength. Based on the finite element upper and lower bound limit analysis methods, this study examined two empirical yield criteria for rock masses, the Hoek-Brown failure criterion (2002) and the Douglas criterion (2002). The comparisons showed that very different results may be obtained using the same input parameters. Therefore, it is interesting to discuss the source of these differences.

Utilization of a population health survey in policy and practice: a case study

Background
There is growing interest by funding bodies and researchers in assessing the impact of research on real world policy and practice. Population health monitoring surveys provide an important source of data on the prevalence and patterns of health problems, but few empirical studies have explored if and how such data is used to influence policy or practice decisions. Here we provide a case study analysis of how the findings from an Australian population monitoring survey series of children’s weight and weight-related behaviors (Schools Physical Activity and Nutrition Survey (SPANS)) have been used, and the key facilitators and barriers to their utilization.

Methods
Data collection included semi-structured interviews with the chief investigators (n = 3) and end-users (n = 9) of SPANS data to explore if, how and under what circumstances the survey findings had been used, bibliometric analysis and verification using documentary evidence. Data analysis involved thematic coding of interview data and triangulation with other data sources to produce case summaries of policy and practice impacts for each of the three survey years (1997, 2004, 2010). Case summaries were then reviewed and discussed by the authors to distil key themes on if, how and why the SPANS findings had been used to guide policy and practice.

Results
We found that the survey findings were used for agenda setting (raising awareness of issues), identifying areas and target groups for interventions, informing new policies, and supporting and justifying existing policies and programs across a range of sectors. Reported factors influencing use of the findings were: i) the perceived credibility of survey findings; ii) dissemination strategies used; and, iii) a range of contextual factors.

Conclusions
Using a novel approach, our case study provides important new insights into how and under what circumstances population health monitoring data can be used to influence real world policy and practice. The findings highlight the importance of population monitoring programs being conducted by independent credible agencies, researchers engaging end-users from the inception of survey programs and utilizing existing policy networks and structures, and using a range of strategies to disseminate the findings that go beyond traditional peer review publications.

Policy and practice impacts of applied research: a case study analysis of the New South Wales Health Promotion Demonstration Research Grants Scheme 2000-2006

Background
Intervention research provides important information regarding feasible and effective interventions for health policy makers, but few empirical studies have explored the mechanisms by which these studies influence policy and practice. This study provides an exploratory case series analysis of the policy, practice and other related impacts of the 15 research projects funded through the New South Wales Health Promotion Demonstration Research Grants Scheme during the period 2000 to 2006, and explored the factors mediating impacts.

Methods
Data collection included semi-structured interviews with the chief investigators (n = 17) and end-users (n = 29) of each of the 15 projects to explore if, how and under what circumstances the findings had been used, as well as bibliometric analysis and verification using documentary evidence. Data analysis involved thematic coding of interview data and triangulation with other data sources to produce case summaries of impacts for each project. Case summaries were then individually assessed against four impact criteria and discussed at a verification panel meeting where final group assessments of the impact of research projects were made and key influences of research impact identified.

Results
Funded projects had variable impacts on policy and practice. Project findings were used for agenda setting (raising awareness of issues), identifying areas and target groups for interventions, informing new policies, and supporting and justifying existing policies and programs across sectors. Reported factors influencing the use of findings were: i) nature of the intervention; ii) leadership and champions; iii) research quality; iv) effective partnerships; v) dissemination strategies used; and, vi) contextual factors.

Conclusions
The case series analysis provides new insights into how and under what circumstances intervention research is used to influence real world policy and practice. The findings highlight that intervention research projects can achieve the greatest policy and practice impacts if they address proximal needs of the policy context by engaging end-users from the inception of projects and utilizing existing policy networks and structures, and using a range of strategies to disseminate findings that go beond traditional peer review publications.

Empirical investigation of decision tree ensembles for monitoring cardiac complications of diabetes

Cardiac complications of diabetes require continuous monitoring since they may lead to increased morbidity or sudden death of patients. In order to monitor clinical complications of diabetes using wearable sensors, a small set of features have to be identified and effective algorithms for their processing need to be investigated. This article focuses on detecting and monitoring cardiac autonomic neuropathy (CAN) in diabetes patients. The authors investigate and compare the effectiveness of classifiers based on the following decision trees: ADTree, J48, NBTree, RandomTree, REPTree, and SimpleCart. The authors perform a thorough study comparing these decision trees as well as several decision tree ensembles created by applying the following ensemble methods: AdaBoost, Bagging, Dagging, Decorate, Grading, MultiBoost, Stacking, and two multi-level combinations of AdaBoost and MultiBoost with Bagging for the processing of data from diabetes patients for pervasive health monitoring of CAN. This paper concentrates on the particular task of applying decision tree ensembles for the detection and monitoring of cardiac autonomic neuropathy using these features. Experimental outcomes presented here show that the authors' application of the decision tree ensembles for the detection and monitoring of CAN in diabetes patients achieved better performance parameters compared with the results obtained previously in the literature.

Evaluation of neck muscle size: long-term reliability and comparison of methods

Although it is important for prospective studies, the reliability of quantitative measures of cervical muscle size on magnetic resonance imaging is not well established. The aim of the current work was to assess the long-term reliability of measurements of cervical muscle size. In addition, we examined the utility of selecting specific sub-regions of muscles at each vertebral level, averaging between sides of the body, and pooling muscles into larger groups. Axial scans from the base of skull to the third thoracic vertebra were performed in 20 healthy male subjects at baseline and 1.5 years later. We evaluated the semi-spinalis capitis, splenius capitis, spinalis cervicis, longus capitis, longus colli, levator scapulae, sternocleidomastoid, anterior scalenes and middle with posterior scalenes. Bland-Altman analysis showed all measurements to be repeatable between testing-days. Reliability was typically best when entire muscle volume was measured (co-efficients of variation (CVs): 3.3-8.1% depending on muscle). However, when the size of the muscle was assessed at specific vertebral levels, similar measurement precision was achieved (CVs: 2.7-7.6%). A median of 4-6 images were measured at the specific vertebral levels versus 18-37 images for entire muscle volume. This would represent considerable time saving. Based on the findings we also recommend measuring both sides of the body and calculating an average value. Pooling specific muscles into the deep neck flexors (CV: 3.5%) and neck extensors (CV: 2.7%) can serve to reduce variability further. The results of the current study help to establish outcome measures for interventional studies and for sample size estimation.

The methodology in empirical sales ethics research: 1980-2010

The study examines the research methodology of more than 200 empirical investigations of ethics in personal selling and sales management between 1980 and 2010. The review discusses the sources and authorship of the sales ethics research. To better understand the drivers of empirical sales ethics research, the foundations used in business, marketing, and sales ethics are compared. The use of hypotheses, operationalization, measurement, population and sampling decisions, research design, and statistical analysis techniques were examined as part of theory development and testing. The review establishes a benchmark, assesses the status and direction of the sales ethics research methodology, and helps inform researchers who need to deal with increasing amounts of empirical research. The investigation identified changing sources of publication with the Journal of Business Ethics and the Journal of Personal Selling & Sales Management maintaining their position as the main conduit of high quality empirical sales ethics research. The results suggest that despite the use of theoretical models for empirical testing, a greater variety of moral frameworks and wider use of marketing exchange theory is needed. The review highlights many sound aspects about the empirical sales ethics research statistical methodology but also raises concerns about several areas. Ways in which these concerns might be addressed and recommendations for researchers are provided. © 2013 Springer Science+Business Media Dordrecht.

Nurse plant effects of a dominant shrub (Duma florulenta) on understorey vegetation in a large, semi-arid wetland in relation to flood frequency and drying

 Questions: Do nurse plant interactions significantly influence understorey vegetation diversity in a large, semi-arid, shrub-dominated wetland? How do the modes and net effects of nurse plant interactions vary spatially along a flood frequency gradient, and temporally in response to drying? Location: Narran Lakes Ramsar site, New South Wales, Australia. Methods: Microhabitat characteristics, understorey vegetation and germinable soil seed banks were investigated in shrub and open habitats across a flood frequency gradient in a large, semi-arid wetland dominated by open shrubland under productive conditions following floodwater recession and again following 6 mo of drought. Split-plot ANOVA and multivariate analyses were used to determine the effects of shrubs on microhabitat character, understorey vegetation cover, species diversity, richness and composition and germinable soil seed banks. Results: Microhabitat characteristics, including canopy cover, litter cover and soil character, all differed between shrub and open habitats, especially in the most frequently flooded sites. Under productive conditions following flooding, lignum shrubs suppressed understorey vegetation cover but increased species richness at the site scale across the flood frequency gradient and, in the most frequently flooded sites, supported higher species density at a microhabitat scale. Under dry conditions, lignum shrubs had a positive effect on understorey vegetation cover, species richness and species density across the flood frequency gradient, but particularly in frequently flooded sites. A significant difference in soil seed bank composition between shrub and open habitats was only observed in frequently flooded sites. Conclusions: Nurse plant interactions appear to play an important role in determining understorey vegetation diversity in the lignum shrubland of the Narran Lakes wetland system. The modes and net effects of these nurse plant interactions vary in space and time in relation to flood history and drying. Positive interactions, probably involving microhabitat amelioration, appear to be particularly important to plant diversity and abundance under dry conditions. Under more favourable wetter conditions, lignum shrubs also contribute to understorey vegetation diversity by facilitating the establishment of different species than those dominating open habitats. Our findings have implications for the management of perennial shrubs and hydrological regimes in such wetlands.

Empirical evidence of recall bias for primary health care visits

BACKGROUND: While it is common for an economic evaluation of health care to rely on trial participants for self-reported health service utilisation, there is variability in the accuracy of this data due to potential recall bias. The aim of this study was to quantify the level of recall bias in self-reported primary health care general practitioner (GP) visits following inpatient rehabilitation over a 12 month period.

METHODS: This report is a secondary analysis from a larger randomised control trial of an economic evaluation of additional Saturday inpatient rehabilitation. Participants were adults who had been discharged into the community following admission to an acute general rehabilitation hospital. Participants were asked to recall primary health care visits, including community GP visits, via a telephone questionnaire which was administered at 6 and 12 months following discharge from inpatient rehabilitation. Participants were asked to recall health service utilisation over each preceding 6 month period. The self-reported data were compared to equivalent claims data from the national insurer, over the same period.

RESULTS: 751 participants (75% of the full trial) with a mean age of 74 years (SD 13) were included in this analysis. Over the 12 month period following discharge from rehabilitation there was an under-reporting of 14% in self-reported health service utilisation for GP visits compared to national insurer claims data over the same period. From 0 to 6 months following discharge from rehabilitation, there was an over-reporting of self-reported GP visits of 35% and from 7 to 12 months there was an under-reporting of self-reported GP visits of 36%, compared to national insurer claims data over the same period. 46% of patients reported the same or one number difference in self-reported GP visits between the 0 to 6 and the 7 to 12 month periods.

CONCLUSION: Based on these findings we recommend that an economic evaluation alongside a clinical trial for an elderly adult rehabilitation population include a sensitivity analysis that inflates self-reported GP visits by 16% over 12 months. However caution is required when utilising self-reported GP visits as the data may contain periods of both over and under reporting. Where general practitioner visits are expected to vary significantly between intervention and control groups we recommend that administrative data be included in the trial to accurately capture resources for an economic evaluation.

Methods to prioritise adaptation options for iconic seabirds and marine mammals impacted by climate change

Climate change is already impacting a wide range of marine species around Australia. Australia has a large number of marine mammals and seabirds, particularly when Australian Antarctic and Southern Ocean species are included: 110 species of seabird and 52 species of marine mammal. These iconic species are protected throughout Australia and in some cases are recovering from previous anthropogenic impacts including harvest. The first tool we developed is a simple 'cost-benefit- risk' (CBR) screening tool to evaluate each scenario-specific adaptation option against a number of semi-quantitative attributes. Awareness and identification of potentially contested options would be useful to managers charged with implementing adaptation options. Following on from specific application, testing some of the adaptation options in limited field trials would be a useful next step, further building the experience of researchers and managers charged with securing the status of these iconic species in the future.

A novel approach to needs assessment in curriculum development: going beyond consensus methods

BACKGROUND: Needs assessment should be the starting point for curriculum development. In medical education, expert opinion and consensus methods are commonly employed. AIM: This paper showcases a more practice-grounded needs assessment approach. METHODS: A mixed-methods approach, incorporating a national survey, practice audit, and expert consensus, was developed and piloted in thrombosis medicine; Phase 1: National survey of practicing consultants, Phase 2: Practice audit of consult service at a large academic centre and Phase 3: Focus group and modified Delphi techniques vetting Phase 1 and 2 findings. RESULTS: Phase 1 provided information on active curricula, training and practice patterns of consultants, and volume and variety of thrombosis consults. Phase 2's practice audit provided empirical data on the characteristics of thrombosis consults and their associated learning issues. Phase 3 generated consensus on a final curricular topic list and explored issues regarding curriculum delivery and accreditation. CONCLUSIONS: This approach offered a means of validating expert and consensus derived curricular content by incorporating a novel practice audit. By using this approach we were able to identify gaps in training programs and barriers to curriculum development. This approach to curriculum development can be applied to other postgraduate programs.

An empirical investigation of personality traits of software testers

Software testing is the process of an execution based investigation of some aspects of the software's quality. The efficiency of the process depends on the methods and technologies used, but crucially also on the human testers. Software testers typically attempt to anticipate and expose ways software may be defective, a fundamentally different task set to those of other software development practitioners. This raises the question of whether the personality of software testers may be different to other people involved in software development. To test this hypothesis, we collected personality profiles using the big five factor model of around 200 software development practitioners. Analysis of this data indicates that software testers are significantly higher on the conscientiousness factor than other software development practitioners, while other factors remain broadly consistent.