Measuring the biases in self-reported disability status : Evidence from aggregate data

Self-reported health status measures are generally used to analyse Social Security Disability Insurance's (SSDI) application and award decisions as well as the relationship between its generosity and labour force participation. Due to endogeneity and measurement error, the use of self-reported health and disability indicators as explanatory variables in economic models is problematic. We employ county-level aggregate data, instrumental variables and spatial econometric techniques to analyse the determinants of variation in SSDI rates and explicitly account for the endogeneity and measurement error of the self-reported disability measure. Two surprising results are found. First, it is shown that measurement error is the dominating source of the bias and that the main source of measurement error is sampling error. Second, results suggest that there may be synergies for applying for SSDI when the disabled population is larger. © 2011 Taylor & Francis.

Aligning off-balance sheet risk, on-balance sheet risk and audit fees: a PLS path modelling analysis

This study focuses on using the partial least squares (PLS) path modelling technique in archival auditing research by replicating the data and research questions from prior bank audit fee studies. PLS path modelling allows for inter-correlations among audit fee determinants by establishing latent constructs and multiple relationship paths in one simultaneous PLS path model. Endogeneity concerns about auditor choice can also be addressed with PLS path modelling. With a sample of US bank holding companies for the period 2003-2009, we examine the associations among on-balance sheet financial risks, off-balance sheet risks and audit fees, and also address the pervasive client size effect, and the effect of the self-selection of auditors. The results endorse the dominating effect of size on audit fees, both directly and indirectly via its impacts on other audit fee determinants. By simultaneously considering the self-selection of auditors, we still find audit fee premiums on Big N auditors, which is the second important factor on audit fee determination. On-balance-sheet financial risk measures in terms of capital adequacy, loan composition, earnings and asset quality performance have positive impacts on audit fees. After allowing for the positive influence of on-balance sheet financial risks and entity size on off-balance sheet risk, the off-balance sheet risk measure, SECRISK, is still positively associated with bank audit fees, both before and after the onset of the financial crisis. The consistent results from this study compared with prior literature provide supporting evidence and enhance confidence on the application of this new research technique in archival accounting studies.

Aligning off-balance sheet risk, on-balance sheet risk and audit fees: a PLS path modelling analysis

This study focuses on using the partial least squares (PLS) path modelling methodology in archival auditing research by replicating the data and research questions from prior bank audit fee studies. PLS path modelling allows for inter-correlations among audit fee determinants by establishing latent constructs and multiple relationship paths in one simultaneous PLS path model. Endogeneity concerns about auditor choice can also be addressed with PLS path modelling. With a sample of US bank holding companies for the period 2003-2009, we examine the associations among on-balance sheet financial risks, off-balance sheet risks and audit fees, and also address the pervasive client size effect, and the effect of the self-selection of auditors. The results endorse the dominating effect of size on audit fees, both directly and indirectly via its impacts on other audit fee determinants. By simultaneously considering the self-selection of auditors, we still find audit fee premiums on Big N auditors, which is the second important factor on audit fee determination. On-balance-sheet financial risk measures in terms of capital adequacy, loan composition, earnings and asset quality performance have positive impacts on audit fees. After allowing for the positive influence of on-balance sheet financial risks and entity size on off-balance sheet risk, the off-balance sheet risk measure, SECRISK, is still positively associated with bank audit fees, both before and after the onset of the financial crisis. The consistent results from this study compared with prior literature provide supporting evidence and enhance confidence on the application of this new research technique in archival accounting studies.

miR-126 in human cancers : clinical roles and current perspectives

miR-126 has been implicated in the processes of inflammation and angiogenesis. Through these processes, miR-126 is implicated in cancer biology, but its role there has not been well reviewed. The aim of this review is to examine the molecular mechanisms and clinicopathological significance of miR-126 in human cancers. miR-126 was shown to have roles in cancers of the gastrointestinal tract, genital tracts, breast, thyroid, lung and some other cancers. Its expression was suppressed in most of the cancers studied. The molecular mechanisms that are known to cause aberrant expression of miR-126 include alterations in gene sequence, epigenetic modification and alteration of dicer abundance. miR-126 can inhibit progression of some cancers via negative control of proliferation, migration, invasion, and cell survival. In some instances, however, miR-126 supports cancer progression via promotion of blood vessel formation. Downregulation of miR-126 induces cancer cell proliferation, migration, and invasion via targeting specific oncogenes. Also, reduced levels of miR-126 are a significant predictor of poor survival of patients in many cancers. In addition, miR-126 can alter a multitude of cellular mechanisms in cancer pathogenesis via suppressing gene translation of numerous validated targets such as PI3K, KRAS, EGFL7, CRK, ADAM9, HOXA9, IRS-1, SOX-2, SLC7A5 and VEGF. To conclude, miR-126 is commonly down-regulated in cancer, most likely due to its ability to inhibit cancer cell growth, adhesion, migration, and invasion through suppressing a range of important gene targets. Understanding these mechanisms by which miR-126 is involved with cancer pathogenesis will be useful in the development of therapeutic targets for the management of patients with cancer.

What are pregnant women told about models of maternity care in Australia? A retrospective study of women's reports

Objective To describe women’s reports of the model of care options General Practitioners (GPs) discussed with them at the first pregnancy consultation and women’s self-reported role in decisionmaking about model of care. Methods Women who had recently given birth responded to survey items about the models of care GPs discussed, their role in final decision-making, and socio-demographic, obstetric history, and early pregnancy characteristics. Results The proportion of women with whom each model of care was discussed varied between 8.2% (for private midwifery care with home birth) and 64.4% (GP shared care). Only 7.7% of women reported that all seven models were discussed. Exclusive discussion about private obstetric care and about all public models was common, and women’s health insurance status was the strongest predictor of the presence of discussions about each model. Most women (82.6%) reported active involvement in final decision-making about model of care. Conclusion Although most women report involvement in maternity model of care decisions, they remain largely uninformed about the breadth of available model of care options. Practical implications Strategies that facilitate women’s access to information on the differentiating features and outcomes for all models of care should be prioritized to better ensure equitable and quality decisions.

Beliefs about infant regulation, early infant behaviors and maternal postnatal depressive symptoms

Background: Young infants may have irregular sleeping and feeding patterns. Such regulation difficulties are known correlates of maternal depressive symptoms. Parental beliefs regarding their role in regulating infant behaviours also may play a role. We investigated the association of depressive symptoms with infant feeding/sleeping behaviours, parent regulation beliefs, and the interaction of the two. Method: In 2006, 272 mothers of infants aged up to 24 weeks completed a questionnaire about infant behaviour and regulation beliefs. Participants were recruited from general medical practices and child health clinics in Brisbane, Australia. Depressive symptomology was measured using the Edinburgh Postnatal Depression Scale (EPDS). Other measures were adapted from the ALSPAC study. Results: Regression analyses were run controlling for partner support, other support, life events, and a range of demographic variables. Maternal depressive symptoms were associated with infant sleeping and feeding problems but not regulation beliefs. The most important infant predictor was sleep behaviours with feeding behaviours accounting for little additional variance. An interaction between regulation beliefs and sleep behaviours was found. Mothers with high regulation beliefs were more susceptible to postnatal depressive symptoms when infant sleep behaviours were problematic. Conclusion: Mothers of young infants who expect greater control are more susceptible to depressive symptoms when their infant presents challenging sleep behaviour.

An investigation of the impact of various geographical scales for the specification of spatial dependence

Ecological studies are based on characteristics of groups of individuals, which are common in various disciplines including epidemiology. It is of great interest for epidemiologists to study the geographical variation of a disease by accounting for the positive spatial dependence between neighbouring areas. However, the choice of scale of the spatial correlation requires much attention. In view of a lack of studies in this area, this study aims to investigate the impact of differing definitions of geographical scales using a multilevel model. We propose a new approach -- the grid-based partitions and compare it with the popular census region approach. Unexplained geographical variation is accounted for via area-specific unstructured random effects and spatially structured random effects specified as an intrinsic conditional autoregressive process. Using grid-based modelling of random effects in contrast to the census region approach, we illustrate conditions where improvements are observed in the estimation of the linear predictor, random effects, parameters, and the identification of the distribution of residual risk and the aggregate risk in a study region. The study has found that grid-based modelling is a valuable approach for spatially sparse data while the SLA-based and grid-based approaches perform equally well for spatially dense data.

Co-occurring anger in young people with Asperger's syndrome

Objectives: The co-occurrence of anger in young people with Asperger's syndrome (AS) has received little attention despite aggression, agitation, and tantrums frequently being identified as issues of concern in this population. The present study investigated the occurrence of anger in young people with AS and explores its relationship with anxiety and depression. Method: Sixty-two young people (12-23 years old) diagnosed with AS were assessed using the Beck Anger Inventory for Youth, Spence Children's Anxiety Scale, and Reynolds Adolescent Depression Scale. Results: Among young people with AS who participated in this study, 41% of participants reported clinically significant levels of anger (17%), anxiety (25.8%) and/or depression (11.5%). Anger, anxiety, and depression were positively correlated with each other. Depression, however, was the only significant predictor of anger. Conclusion: Anger is commonly experienced by young people with AS and is correlated with anxiety and depression. These findings suggest that the emotional and behavioral presentation of anger could serve as a cue for further assessment, and facilitate earlier identification and intervention for anger, as well as other mental health problems.

The topography of multiple drug use among adolescent Australians : findings from the National Drug Strategy Household Survey

Introduction and aims: Despite evidence that many Australian adolescents have considerable experience with various drug types, little is known about the extent to which adolescents use multiple substances. The aim of this study was to examine the degree of clustering of drug types within individuals, and the extent to which demographic and psychosocial predictors are related to cluster membership. Design and method: A sample of 1402 adolescents aged 12-17. years were extracted from the Australian 2007 National Drug Strategy Household Survey. Extracted data included lifetime use of 10 substances, gender, psychological distress, physical health, perceived peer substance use, socioeconomic disadvantage, and regionality. Latent class analysis was used to determine clusters, and multinomial logistic regression employed to examine predictors of cluster membership. Result: There were 3 latent classes. The great majority (79.6%) of adolescents used alcohol only, 18.3% were limited range multidrug users (encompassing alcohol, tobacco, and marijuana), and 2% were extended range multidrug users. Perceived peer drug use and psychological distress predicted limited and extended multiple drug use. Psychological distress was a more significant predictor of extended multidrug use compared to limited multidrug use. Discussion and conclusion: In the Australian school-based prevention setting, a very strong focus on alcohol use and the linkages between alcohol, tobacco and marijuana are warranted. Psychological distress may be an important target for screening and early intervention for adolescents who use multiple drugs.

Impact of community pharmacist intervention discussing patients’ beliefs to improve medication adherence

Background Adherence to evidence based medicines in patients who have experienced a myocardial infarction remains low. Individual’s beliefs towards their medicines are a strong predictor of adherence and may influence other factors that impact on adherence. Objective To investigate if community pharmacists discussing patients’ beliefs about their medicines improved medication adherence at 12 months post myocardial infarction. Setting This study included 200 patients discharged from a public teaching hospital in Queensland, Australia, following a myocardial infarction. Patients were randomised into intervention (n = 100) and control groups (n = 100) and followed for 12 months. Method All patients were interviewed between 5 to 6 weeks, at 6 and 12 months post discharge by the researcher using the repertory grid technique. This technique was used to elicit the patient’s individualised beliefs about their medicines for their myocardial infarction. In the intervention group, patients’ beliefs about their medicines were communicated by the researcher to their community pharmacist. The pharmacist used this information to tailor their discussion with the patient about their medication beliefs at designated time points (3 and 6 months post discharge). The control group was provided with usual care. Main outcome measure The difference in non-adherence measured using a medication possession ratio between the intervention and control groups at 12 months post myocardial infarction. Results There were 137 patients remaining in the study (intervention group n = 72, control group n = 65) at 12 months. In the intervention group 29 % (n = 20) of patients were non-adherent compared to 25 % (n = 16) of patients in control group. Conclusion Discussing patients’ beliefs about their medicines for their myocardial infarction did not improve medication adherence. Further research on patients beliefs should focus on targeting non-adherent patients whose reasons for their non-adherence is driven by their medication beliefs.

A national satellite-based land-use regression model for air pollution exposure assessment in Australia

Land-use regression (LUR) is a technique that can improve the accuracy of air pollution exposure assessment in epidemiological studies. Most LUR models are developed for single cities, which places limitations on their applicability to other locations. We sought to develop a model to predict nitrogen dioxide (NO2) concentrations with national coverage of Australia by using satellite observations of tropospheric NO2 columns combined with other predictor variables. We used a generalised estimating equation (GEE) model to predict annual and monthly average ambient NO2 concentrations measured by a national monitoring network from 2006 through 2011. The best annual model explained 81% of spatial variation in NO2 (absolute RMS error=1.4 ppb), while the best monthly model explained 76% (absolute RMS error=1.9 ppb). We applied our models to predict NO2 concentrations at the ~350,000 census mesh blocks across the country (a mesh block is the smallest spatial unit in the Australian census). National population-weighted average concentrations ranged from 7.3 ppb (2006) to 6.3 ppb (2011). We found that a simple approach using tropospheric NO2 column data yielded models with slightly better predictive ability than those produced using a more involved approach that required simulation of surface-to-column ratios. The models were capable of capturing within-urban variability in NO2, and offer the ability to estimate ambient NO2 concentrations at monthly and annual time scales across Australia from 2006–2011. We are making our model predictions freely available for research.

STAR : Predicting recombination sites from amino acid sequence

Background Designing novel proteins with site-directed recombination has enormous prospects. By locating effective recombination sites for swapping sequence parts, the probability that hybrid sequences have the desired properties is increased dramatically. The prohibitive requirements for applying current tools led us to investigate machine learning to assist in finding useful recombination sites from amino acid sequence alone. Results We present STAR, Site Targeted Amino acid Recombination predictor, which produces a score indicating the structural disruption caused by recombination, for each position in an amino acid sequence. Example predictions contrasted with those of alternative tools, illustrate STAR'S utility to assist in determining useful recombination sites. Overall, the correlation coefficient between the output of the experimentally validated protein design algorithm SCHEMA and the prediction of STAR is very high (0.89). Conclusion STAR allows the user to explore useful recombination sites in amino acid sequences with unknown structure and unknown evolutionary origin. The predictor service is available from http://pprowler.itee.uq.edu.au/star.

Using the Driver Behaviour Questionnaire to predict crashes and demerit point loss : does it get better with larger sample sizes?

The Driver Behaviour Questionnaire (DBQ) continues to be the most widely utilised self-report scale globally to assess crash risk and aberrant driving behaviours among motorists. However, the scale also attracts criticism regarding its perceived limited ability to accurately identify those most at risk of crash involvement. This study reports on the utilisation of the DBQ to examine the self-reported driving behaviours (and crash outcomes) of drivers in three separate Australian fleet samples (N = 443, N = 3414, & N = 4792), and whether combining the samples increases the tool’s predictive ability. Either on-line or paper versions of the questionnaire were completed by fleet employees in three organisations. Factor analytic techniques identified either three or four factor solutions (in each of the separate studies) and the combined sample produced expected factors of: (a) errors, (b) highway-code violations and (c) aggressive driving violations. Highway code violations (and mean scores) were comparable across the studies. However, across the three samples, multivariate analyses revealed that exposure to the road was the best predictor of crash involvement at work, rather than DBQ constructs. Furthermore, combining the scores to produce a sample of 8649 drivers did not improve the predictive ability of the tool for identifying crashes (e.g., 0.4% correctly identified) or for demerit point loss (0.3%). The paper outlines the major findings of this comparative sample study in regards to utilising self-report measurement tools to identify “at risk” drivers as well as the application of such data to future research endeavours.

Social support, self-efficacy, trauma and well-being in emergency medical dispatchers

Emergency Medical Dispatchers (EMDs) respond to crisis calls for ambulance; they dispatch paramedics and provide emotional and medical assistance to callers. Despite the stressful nature and exposure to potentially traumatising events in this role, there has been no published research specifically investigating well-being or posttraumatic growth among EMDs. Extrapolating from research conducted among other emergency services workers (e. g., paramedics, police), literature attests to the importance of self efficacy and social support in promoting mental health in emergency service workers. Therefore, this study assessed the impact of self efficacy, and giving and receiving social support on psychological well-being, posttraumatic growth (PTG), and symptoms of posttraumatic stress disorder (PTSD). Sixty EMDs (50% response rate) completed an online questionnaire. Three hierarchical multiple regression analyses were conducted to ascertain predictors of well-being, PTG and PTSD. Receiving social support emerged as a significant positive predictor of well-being and PTG, and a significant negative predictor of PTSD. Self efficacy was found to significantly and positively predict well-being, and shift-work was found to significantly and negatively predict PTSD. These results highlight that self efficacy and receiving social support are likely to be important for enhancing well-being within this population, and that receiving social support is also likely to facilitate positive post-trauma responses. Such findings have implications for the way emergency service personnel are educated with reference to aspects of mental health and how best to support personnel in order to achieve optimal mental health outcomes for all.

Available evidence does not support serosorting as an HIV risk reduction strategy

Recent data highlighted the association between penetration of antiretrovirals in the central nervous system (CNS) and neurocognitive impairment in HIVpositive patients. Existing antiretrovirals have been ranked according to a score of neuropenetration, which was shown to be a predictor of anti-HIVactivity in the CNS and improvement of neurocognitive disorders [1]. Main factors affecting drug penetration are known to be protein binding, lipophilicity and molecular weight [2]. Moreover, active translation by membrane transporters (such as p-glycoprotein) could be a key mechanism of passage [3]. The use of raltegravir (RGV), a novel antiretroviral drug targeted to inhibit the HIV preintegrase complex, is increasing worldwide due to its efficacy and tolerability. However, penetration of RGV in the CNS has not been yet elucidated. In fact, prediction of RGV neuropenetration according to molecular characteristics is controversial. Intermediate protein binding (83%) and large volume of distribution (273 l) could suggest a high distribution beyond extracellular spaces [4]. On the contrary, low lipophilicity (oil/water partition coefficient at pH 7.4 of 2.80) and intermediate molecular weight (482.51 Da) suggest a limited diffusion. Furthermore, in-vitro studies suggest that RGV is substrate of p-glycoprotein, although this efflux pump has not been identified to significantly affect plasma pharmacokinetics [5]. In any case, no data concerning RGV passage into cerebrospinal fluid of animals or humans have yet been published.