Formal home health care, informal care, and family decision making

We use the 1993 wave of the Assets and Health Dynamics Among the Oldest Old (AHEAD) data set to estimate a game-theoretic model of families' decisions concerning the provision of informal and formal care for elderly individuals. The outcome is the Nash equilibrium where each family member jointly determines her consumption, transfers for formal care, and allocation of time to informal care, market work, and leisure. We use the estimates to decompose the effects of adult children's opportunity costs, quality of care, and caregiving burden on their propensities to provide informal care. We also simulate the effects of a broad range of policies of current interest. © (2009) by the Economics Department of the University of Pennsylvania and the Osaka University Institute of Social and Economic Research Association.

The effects of rurality on mental and physical health

The effects of rurality on physical and mental health are examined in analyses of a national dataset, the Community Tracking Survey, 2000-2001, that includes individual level observations from household interviews. We merge it with county level data reflecting community resources and use econometric methods to analyze this multi-level data. The statistical analysis of the impact of the choice of definition on outcomes and on the estimates and significance of explanatory variables in the model is presented using modern econometric methods, and differences in results for mental health and physical health are evaluated. © 2010 Springer Science+Business Media, LLC.

Shortages of rural mental health professionals

This study presents a conceptual model of the supply and demand for mental health professionals. It uses national data to profile differences in the supply of mental health professionals in different types of rural and urban areas. It contrasts the availability of general health and mental health professionals. It examines shortage areas identified in 2000 and their related community characteristics. Because of the absence of data on a national level to describe many types of mental health professionals state licensure data for one state were used to show the volume and distribution of these practitioners. To improve rural mental health service delivery it will be necessary to implement system changes to promote the increased availability, competency, and support of rural health professionals. Copyright 2003, Elsevier Science (USA). All rights reserved.

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.

Field validation of controlled Monte Carlo data generation for statistical damage identification employing Mahalanobis squared distance

This article presents the field applications and validations for the controlled Monte Carlo data generation scheme. This scheme was previously derived to assist the Mahalanobis squared distance–based damage identification method to cope with data-shortage problems which often cause inadequate data multinormality and unreliable identification outcome. To do so, real-vibration datasets from two actual civil engineering structures with such data (and identification) problems are selected as the test objects which are then shown to be in need of enhancement to consolidate their conditions. By utilizing the robust probability measures of the data condition indices in controlled Monte Carlo data generation and statistical sensitivity analysis of the Mahalanobis squared distance computational system, well-conditioned synthetic data generated by an optimal controlled Monte Carlo data generation configurations can be unbiasedly evaluated against those generated by other set-ups and against the original data. The analysis results reconfirm that controlled Monte Carlo data generation is able to overcome the shortage of observations, improve the data multinormality and enhance the reliability of the Mahalanobis squared distance–based damage identification method particularly with respect to false-positive errors. The results also highlight the dynamic structure of controlled Monte Carlo data generation that makes this scheme well adaptive to any type of input data with any (original) distributional condition.

Carcinoma ex pleomorphic adenoma : a comprehensive review of clinical, pathological and molecular data

Carcinoma ex pleomorphic adenoma (Ca ex PA) is a carcinoma arising from a primary or recurrent benign pleomorphic adenoma. It often poses a diagnostic challenge to clinicians and pathologists. This study intends to review the literature and highlight the current clinical and molecular perspectives about this entity. The most common clinical presentation of CA ex PA is of a firm mass in the parotid gland. The proportion of adenoma and carcinoma components determines the macroscopic features of this neoplasm. The entity is difficult to diagnose pre-operatively. Pathologic assessment is the gold standard for making the diagnosis. Treatment for Ca ex PA often involves an ablative surgical procedure which may be followed by radiotherapy. Overall, patients with Ca ex PA have a poor prognosis. Accurate diagnosis and aggressive surgical management of patients presenting with Ca ex PA can increase their survival rates. Molecular studies have revealed that the development of Ca ex PA follows a multi-step model of carcinogenesis, with the progressive loss of heterozygosity at chromosomal arms 8q, then 12q and finally 17p. There are specific candidate genes in these regions that are associated with particular stages in the progression of Ca ex PA. In addition, many genes which regulate tumour suppression, cell cycle control, growth factors and cell-cell adhesion play a role in the development and progression of Ca ex PA. It is hopeful that these molecular data can give clues for the diagnosis and management of the disease.

Performance measures for Australian laboratories reporting cervical cytology : a decade of data 1998–2008

Aim Performance measures for Australian laboratories reporting cervical cytology are a set of quantifiable measures relating to the profile and accuracy of reporting. This study reviews aggregate data collected over the ten years in which participation in the performance measures has been mandatory. Methods Laboratories submit annual data on performance measures relating to the profile of reporting, including reporting rates for technically unsatisfactory specimens, high grade or possible high grade abnormalities and abnormal reports. Cytology-histology correlation data and review findings of negative smears reported from women with histological high grade disease are also collected. Suggested acceptable standards are set for each measure. This study reviews the aggregate data submitted by all laboratories for the years 1998-2008 and examines trends in reporting and the performance of laboratories against the suggested standards. Results The performance of Australian laboratories has shown continued improvement over the study period. There has been a fall in the proportion of laboratories with data outside the acceptable standard range in all performance measures. Laboratories are reporting a greater proportion of specimens as definite or possible high grade abnormality. This is partly attributable to an increase in the proportion of abnormal results classified as high grade or possible high grade abnormality. Despite this, the positive predictive value for high grade and possible high grade abnormalities has continued to rise. Conclusion Performance measures for cervical cytology have provided a valuable addition to external quality assurance procedures in Australia. They have documented continued improvements in the aggregate performance, as well as providing benchmarking data and goals for acceptable performance for individual laboratories.

Improving the railway’s understanding of accident causation through an integrated approach to human factors analysis and technical safety data recording

This paper describes a safety data recording and analysis system that has been developed to capture safety occurrences including precursors using high-definition forward-facing video from train cabs and data from other train-borne systems. The paper describes the data processing model and how events detected through data analysis are related to an underlying socio-technical model of accident causation. The integrated approach to safety data recording and analysis insures systemic factors that condition, influence or potentially contribute to an occurrence are captured both for safety occurrences and precursor events, providing a rich tapestry of antecedent causal factors that can significantly improve learning around accident causation. This can ultimately provide benefit to railways through the development of targeted and more effective countermeasures, better risk models and more effective use and prioritization of safety funds. Level crossing occurrences are a key focus in this paper with data analysis scenarios describing causal factors around near-miss occurrences. The paper concludes with a discussion on how the system can also be applied to other types of railway safety occurrences.

Outbreak detection algorithms for seasonal disease data : a case study using Ross River virus disease

Background Detection of outbreaks is an important part of disease surveillance. Although many algorithms have been designed for detecting outbreaks, few have been specifically assessed against diseases that have distinct seasonal incidence patterns, such as those caused by vector-borne pathogens. Methods We applied five previously reported outbreak detection algorithms to Ross River virus (RRV) disease data (1991-2007) for the four local government areas (LGAs) of Brisbane, Emerald, Redland and Townsville in Queensland, Australia. The methods used were the Early Aberration Reporting System (EARS) C1, C2 and C3 methods, negative binomial cusum (NBC), historical limits method (HLM), Poisson outbreak detection (POD) method and the purely temporal SaTScan analysis. Seasonally-adjusted variants of the NBC and SaTScan methods were developed. Some of the algorithms were applied using a range of parameter values, resulting in 17 variants of the five algorithms. Results The 9,188 RRV disease notifications that occurred in the four selected regions over the study period showed marked seasonality, which adversely affected the performance of some of the outbreak detection algorithms. Most of the methods examined were able to detect the same major events. The exception was the seasonally-adjusted NBC methods that detected an excess of short signals. The NBC, POD and temporal SaTScan algorithms were the only methods that consistently had high true positive rates and low false positive and false negative rates across the four study areas. The timeliness of outbreak signals generated by each method was also compared but there was no consistency across outbreaks and LGAs. Conclusions This study has highlighted several issues associated with applying outbreak detection algorithms to seasonal disease data. In lieu of a true gold standard, a quantitative comparison is difficult and caution should be taken when interpreting the true positives, false positives, sensitivity and specificity.

The importance of good data, analysis and interpretation for showing the economics of reducing healthcare-associated infection

To the Editor—In a recent review article in Infection Control and Hospital Epidemiology, Umscheid et al1 summarized published data on incidence rates of catheter-associated bloodstream infection (CABSI), catheter-associated urinary tract infection (CAUTI), surgical site infection (SSI), and ventilator- associated pneumonia (VAP); estimated how many cases are preventable; and calculated the savings in hospital costs and lives that would result from preventing all preventable cases. Providing these estimates to policy makers, political leaders, and health officials helps to galvanize their support for infection prevention programs. Our concern is that important limitations of the published studies on which Umscheid and colleagues built their findings are incompletely addressed in this review. More attention needs to be drawn to the techniques applied to generate these estimates...

Health education and the control of intestinal worm infections in China : a new vision

Background: The transmission of soil-transmitted helminths (STHs) is associated with poverty, poor hygiene behaviour, lack of clean water and inadequate waste disposal and sanitation. Periodic administration of benzimidazole drugs is the mainstay for global STH control but it does not prevent re-infection, and is unlikely to interrupt transmission as a stand-alone intervention. Findings: We reported recently on the development and successful testing in Hunan province, PR China, of a health education package to prevent STH infections in Han Chinese primary school students. We have recently commenced a new trial of the package in the ethnically diverse Xishuangbanna autonomous prefecture in Yunnan province and the approach is also being tested in West Africa, with further expansion into the Philippines in 2015. Conclusions: The work in China illustrates well the direct impact that health education can have in improving knowledge and awareness, and in changing hygiene behaviour. Further, it can provide insight into the public health outcomes of a multi-component integrated control program, where health education prevents re-infection and periodic drug treatment reduces prevalence and morbidity.

Predictors of mental health in midlife and older women : results from the Australian Healthy Aging of Women Study

Purpose: To examine the extent to which socio-demographic characteristics, modifiable lifestyle factors and health status influence the mental health of midlife and older Australian women from the Australian Healthy Aging of Women (HOW) study. Methods: Data on health status, chronic disease and modifiable lifestyle factors were collected from a random sample of 340 women aged 40-65 years, residing in Queensland, Australia in 2011. Structural equation modelling (SEM) was used to measure the effect of a range of socio-demographic characteristics (marital status, age, income), modifiable lifestyle factors (caffeine intake, alcohol consumption, exercise, physical activity, sleep), and health markers (self-reported physical health, history of chronic illness) on the latent construct, mental health. Mental health was evaluated using the Medical Outcomes Study Short Form 12 (SF-12®) and the Center for Epidemiologic Studies Depression Scale (CES-D). Results: The model was a good fit for the data (χ2 = 40.166, df =312, p 0.125, CFI = 0.976, TLI = 0.950, RMSEA = 0.030, 90% CI = 0.000-0.053); the model suggested mental health was negatively influenced by sleep disturbance (β = -0.628), sedentary lifestyle (β = -0.137), having been diagnosed with one or more chronic illnesses (β = -0.203), and poor self-reported physical health (β = - 0.161). While mental health was associated with sleep, it was not correlated with many other lifestyle factors (BMI (β = -0.050), alcohol consumption (β = 0.079), or cigarette smoking (β = 0.008)) or background socio-demographic characteristics (age (β = 0.078), or income (β = -0.039)). Conclusion: While research suggests that it is important to engage in a range health promoting behaviours to preserve good health, we found that only sleep disturbance, physical health, chronic illness and level of physical activity predicted current mental health. However, while socio-demographic characteristics and modifiable lifestyle factors seemed to have little direct impact on mental health, they probably had an indirect effect.

What predicts mental health in midlife and older women? Results from the Australian Healthy Aging of Women Study

Objectives: Previous research has linked unhealthy lifestyle with a range of negative health outcomes in women. As women age however, they may have fewer performance expectations, but may view their health more positively. Clearly, the experiences of midlife and older women in relation to health and wellbeing need further exploration. The purpose of this study is to examine the factors associated with poor health-related quality of life in midlife (HRQoL) and older Australian women. Methods: The Australian longitudinal Healthy Aging of Women (HOW) study prospectively examines HRQoL, chronic disease and modifiable lifestyle factors midlife and older women as they age. Random sampling was used to select rural and urban based women from South-East Queensland, Australia. Data were collected from 386 women at three time points over the last decade (2001, 2004 and 2011). Results: The average age of women in this study was 65 years (SD = 2.82). Almost three-quarters (73%, n = 248) of the sample were married or living as though married, nine per cent (n = 30) were separated or divorced and a small proportion were had never married (n = 13). Most (86%, n = 291) of the women sample reported being Australian born, around one quarter (34%, n = 114) had completed additional study since leaving school (university degree or diploma). Over half (55%, n = 186) of participants were retired, one quarter (25%, n = 85) were in paid employment and the remained were unemployed (1%, n = 4), unable to work because of illness (2%, n = 6) or worked within the home (17%, n = 56). Using data collected over time we examined the relationship between a range of modifiable lifestyle factors and mental health using structural equation modelling. The overall model exhibited a good fit with the data. Poor sleep quality was associated with reduced mental health while better mental health was reported in women who exercised regularly and satisfied with their currently weight. As hypothesized, past mental health was a significant mediator of current mental health. Conclusions: These findings demonstrate that the mental health of women is complex and needs to be understood not only in terms of current lifestyle but also in relation to previously reported health status.

miRPlant : an integrated tool for identification of plant miRNA from RNA sequencing data

Background Small RNA sequencing is commonly used to identify novel miRNAs and to determine their expression levels in plants. There are several miRNA identification tools for animals such as miRDeep, miRDeep2 and miRDeep*. miRDeep-P was developed to identify plant miRNA using miRDeep’s probabilistic model of miRNA biogenesis, but it depends on several third party tools and lacks a user-friendly interface. The objective of our miRPlant program is to predict novel plant miRNA, while providing a user-friendly interface with improved accuracy of prediction. Result We have developed a user-friendly plant miRNA prediction tool called miRPlant. We show using 16 plant miRNA datasets from four different plant species that miRPlant has at least a 10% improvement in accuracy compared to miRDeep-P, which is the most popular plant miRNA prediction tool. Furthermore, miRPlant uses a Graphical User Interface for data input and output, and identified miRNA are shown with all RNAseq reads in a hairpin diagram. Conclusions We have developed miRPlant which extends miRDeep* to various plant species by adopting suitable strategies to identify hairpin excision regions and hairpin structure filtering for plants. miRPlant does not require any third party tools such as mapping or RNA secondary structure prediction tools. miRPlant is also the first plant miRNA prediction tool that dynamically plots miRNA hairpin structure with small reads for identified novel miRNAs. This feature will enable biologists to visualize novel pre-miRNA structure and the location of small RNA reads relative to the hairpin. Moreover, miRPlant can be easily used by biologists with limited bioinformatics skills.