Evaluation of public hospital performance in Khanh Hoa Province : Vietnam in connection with patient and staff satisfaction surveys

This research aimed to develop a framework for performance evaluation of public hospitals in Vietnam that is culturally, socially, and politically appropriate. The research included both qualitative and quantitative methods and identified and validated novel instruments to measure patient satisfaction and job satisfaction of hospital staff and to determine a set of hospital indicators that reflect the quality of hospital performance. New models for understanding the determinants of patient and staff satisfaction were developed along with a new performance indicator framework for hospital performance. These instruments will now be applied to the evaluation of hospital services in Khanh Hoa Province, permitting longer term evaluation of their effectiveness in changing system wide performance and satisfaction.

Understanding Uncertainties in Non-Linear Population Trajectories: A Bayesian Semi-Parametric Hierarchical Approach to Large-Scale Surveys of Coral Cover

Recently, attempts to improve decision making in species management have focussed on uncertainties associated with modelling temporal fluctuations in populations. Reducing model uncertainty is challenging; while larger samples improve estimation of species trajectories and reduce statistical errors, they typically amplify variability in observed trajectories. In particular, traditional modelling approaches aimed at estimating population trajectories usually do not account well for nonlinearities and uncertainties associated with multi-scale observations characteristic of large spatio-temporal surveys. We present a Bayesian semi-parametric hierarchical model for simultaneously quantifying uncertainties associated with model structure and parameters, and scale-specific variability over time. We estimate uncertainty across a four-tiered spatial hierarchy of coral cover from the Great Barrier Reef. Coral variability is well described; however, our results show that, in the absence of additional model specifications, conclusions regarding coral trajectories become highly uncertain when considering multiple reefs, suggesting that management should focus more at the scale of individual reefs. The approach presented facilitates the description and estimation of population trajectories and associated uncertainties when variability cannot be attributed to specific causes and origins. We argue that our model can unlock value contained in large-scale datasets, provide guidance for understanding sources of uncertainty, and support better informed decision making

Recent surveys of bats (Mammalia: Chiroptera) from China. I. Rhinolophidae and Hipposideridae

We conducted surveys of bats in China between 1999 and 2007, resulting in the identification of at least 62 species. In this paper we present data on 19 species, comprising 12 species from the family Rhinolophidae and seven from the Hipposideridae. Rhinolophids captured were Rhinolophus affinis, R. ferrumequinum, R. lepidus, R. luctus, R. macrotis, R. siamensis, R. marshalli, R. rex, R. pearsonii, R. pusillus, R. sinicus and R. stheno. Because of extensive morphological similarities we question the species distinctiveness of R. osgoodi (may be conspecific with R. lepidus), R. paradoxolophus (which may best be treated as a subspecies of R. rex), R. huananus (probably synonymous with R. siamensis), and we are skeptical as to whether R. sinicus is distinct from R. thomasi. Hipposiderids captured were Hipposideros armiger, H. cineraceus, H. larvatus, H. pomona, H. pratti, Aselliscus stoliczkanus and Coelops frithii. Of these species, two rhinolophids (Rhinolophus marshalli and R. stheno) and one hipposiderid (Hipposideros cineraceus) represent new species records for China. We present data on species' ranges, morphology and echolocation call frequencies, as well as some notes on ecology and conservation status. China hosts a considerable diversity of rhinolophid and hipposiderid bats, yet threats to their habitats and populations are substantial.

Integrating field survey data with satellite image data to improve shallow water seagrass maps : the role of AUV and snorkeller surveys

Repeatable and accurate seagrass mapping is required for understanding seagrass ecology and supporting management decisions. For shallow (< 5 m) seagrass habitats, these maps can be created by integrating high spatial resolution imagery with field survey data. Field survey data for seagrass is often collected via snorkelling or diving. However, these methods are limited by environmental and safety considerations. Autonomous Underwater Vehicles (AUVs) are used increasingly to collect field data for habitat mapping, albeit mostly in deeper waters (>20 m). Here we demonstrate and evaluate the use and potential advantages of AUV field data collection for calibration and validation of seagrass habitat mapping of shallow waters (< 5 m), from multispectral satellite imagery. The study was conducted in the seagrass habitats of the Eastern Banks (142 km2), Moreton Bay, Australia. In the field, georeferenced photos of the seagrass were collected along transects via snorkelling or an AUV. Photos from both collection methods were analysed manually for seagrass species composition and then used as calibration and validation data to map seagrass using an established semi-automated object based mapping routine. A comparison of the relative advantages and disadvantages of AUV and snorkeller collected field data sets and their influence on the mapping routine was conducted. AUV data collection was more consistent, repeatable and safer in comparison to snorkeller transects. Inclusion of deeper water AUV data resulted in mapping of a larger extent of seagrass (~7 km2, 5 % of study area) in the deeper waters of the site. Although overall map accuracies did not differ considerably, inclusion of the AUV data from deeper water transects corrected errors in seagrass mapped at depths to 5 m, but where the bottom is visible on satellite imagery. Our results demonstrate that further development of AUV technology is justified for the monitoring of seagrass habitats in ongoing management programs.

Clustering acoustic events in environmental recordings for species richness surveys

Environmental acoustic recordings can be used to perform avian species richness surveys, whereby a trained ornithologist can observe the species present by listening to the recording. This could be made more efficient by using computational methods for iteratively selecting the richest parts of a long recording for the human observer to listen to, a process known as “smart sampling”. This allows scaling up to much larger ecological datasets. In this paper we explore computational approaches based on information and diversity of selected samples. We propose to use an event detection algorithm to estimate the amount of information present in each sample. We further propose to cluster the detected events for a better estimate of this amount of information. Additionally, we present a time dispersal approach to estimating diversity between iteratively selected samples. Combinations of approaches were evaluated on seven 24-hour recordings that have been manually labeled by bird watchers. The results show that on average all the methods we have explored would allow annotators to observe more new species in fewer minutes compared to a baseline of random sampling at dawn.

Automating marine mammal detection in aerial images captured during wildlife surveys: A deep learning approach

Aerial surveys conducted using manned or unmanned aircraft with customized camera payloads can generate a large number of images. Manual review of these images to extract data is prohibitive in terms of time and financial resources, thus providing strong incentive to automate this process using computer vision systems. There are potential applications for these automated systems in areas such as surveillance and monitoring, precision agriculture, law enforcement, asset inspection, and wildlife assessment. In this paper, we present an efficient machine learning system for automating the detection of marine species in aerial imagery. The effectiveness of our approach can be credited to the combination of a well-suited region proposal method and the use of Deep Convolutional Neural Networks (DCNNs). In comparison to previous algorithms designed for the same purpose, we have been able to dramatically improve recall to more than 80% and improve precision to 27% by using DCNNs as the core approach.

Assistive classification for improving the efficiency of avian species richness surveys

Avian species richness surveys, which measure the total number of unique avian species, can be conducted via remote acoustic sensors. An immense quantity of data can be collected, which, although rich in useful information, places a great workload on the scientists who manually inspect the audio. To deal with this big data problem, we calculated acoustic indices from audio data at a one-minute resolution and used them to classify one-minute recordings into five classes. By filtering out the non-avian minutes, we can reduce the amount of data by about 50% and improve the efficiency of determining avian species richness. The experimental results show that, given 60 one-minute samples, our approach enables to direct ecologists to find about 10% more avian species.

The impact of a streamlined funding application process on application time: Two cross-sectional surveys of Australian researchers

Objective: To examine if streamlining a medical research funding application process saved time for applicants. Design: Cross-sectional surveys before and after the streamlining. Setting: The National Health and Medical Research Council (NHMRC) of Australia. Participants: Researchers who submitted one or more NHMRC Project Grant applications in 2012 or 2014. Main outcome measures: Average researcher time spent preparing an application and the total time for all applications in working days. Results: The average time per application increased from 34 working days before streamlining (95% CI 33 to 35) to 38 working days after streamlining (95% CI 37 to 39; mean difference 4 days, bootstrap p value <0.001). The estimated total time spent by all researchers on applications after streamlining was 614 working years, a 67-year increase from before streamlining. Conclusions: Streamlined applications were shorter but took longer to prepare on average. Researchers may be allocating a fixed amount of time to preparing funding applications based on their expected return, or may be increasing their time in response to increased competition. Many potentially productive years of researcher time are still being lost to preparing failed applications.

Using multi-label classification for acoustic pattern detection and assisting bird species surveys

Acoustics is a rich source of environmental information that can reflect the ecological dynamics. To deal with the escalating acoustic data, a variety of automated classification techniques have been used for acoustic patterns or scene recognition, including urban soundscapes such as streets and restaurants; and natural soundscapes such as raining and thundering. It is common to classify acoustic patterns under the assumption that a single type of soundscapes present in an audio clip. This assumption is reasonable for some carefully selected audios. However, only few experiments have been focused on classifying simultaneous acoustic patterns in long-duration recordings. This paper proposes a binary relevance based multi-label classification approach to recognise simultaneous acoustic patterns in one-minute audio clips. By utilising acoustic indices as global features and multilayer perceptron as a base classifier, we achieve good classification performance on in-the-field data. Compared with single-label classification, multi-label classification approach provides more detailed information about the distributions of various acoustic patterns in long-duration recordings. These results will merit further biodiversity investigations, such as bird species surveys.

Endangerment and Likeability of Wildlife Species: How Important are they for Payments Proposed for Conservation?

This paper examines empirically the relative influence of the degree of endangerment of wildlife species and their stated likeability on individuals' allocation of funds for their conservation. To do this, it utilises data obtained from the IUCN Red List, and likeability and fund allocation data obtained from two serial surveys of a sample of the Australian public who were requested to assess 24 Australian wildlife species from three animal classes: mammals, birds and reptiles. Between the first and second survey, respondents were provided with extra information about the focal species. This information resulted in the dominance of endangerment as the major influence on the allocation of funding of respondents for the conservation of the focal wildlife species. Our results throw doubts on the proposition in the literature that the likeability of species is the dominant influence on willingness to pay for conservation of wildlife species. Furthermore, because the public's allocation of fund for conserving wildlife species seems to be more sensitive to information about the conservation status of species than to factors influencing their likeability, greater attention to providing accurate information about the former than the latter seems justified. Keywords: Conservation of wildlife species; Contingent valuation; Endangerment of species; Likeability of species; Willingness to pay

Nonprofit Boards in Australia: A Distinctive Governance Appoach

This article reports the findings into patterns of governance on nonprofit boards in Australia. The research surveys 118 boards, upon which serve a total of 1405 directors. The findings indicate that nonprofit boards can mimic some aspects of a shareholder approach to governance. But nonprofit boards, in the main, indicate priorities and activities of a stakeholder approach to governance. The features of `isomorphism' that arise largely stem from legislative requirements in corporate governance. Generally, nonprofit directors are influenced by agenda and motivations that can be differentiated from the influences upon director activity in the corporate sector. The study indicates that nonprofit boards prize knowledge and loyalty to the sector when considering board composition. The survey suggests nonprofits ``compensate'' for the demands placed upon them about fiduciary duty and due diligence responsibilities with the diverse intellectual expertise of non-executive directors. Nonprofit boards possess greater diversity than boards in the corporate sector; they include more women as directors than corporate boards and they include a greater proportion of directors from minority groups. While strategic issues feature significantly as a task of the nonprofit board, they distinguish themselves from their corporate counterparts by engaging in operational management. The findings indicate that, in the main, directors on nonprofit boards deliberate and operate in ways distinctive from their corporate counterparts. Such findings offer a contribution to the reform of Corporations Law in other countries and the likely consequence on boards outside the corporate sector.

High body mass index is not a barrier to physical activity: Analysis of international rugby players' anthropometric data

Recent data indicate that levels of overweight and obesity are increasing at an alarming rate throughout the world. At a population level (and commonly to assess individual health risk), the prevalence of overweight and obesity is calculated using cut-offs of the Body Mass Index (BMI) derived from height and weight. Similarly, the BMI is also used to classify individuals and to provide a notional indication of potential health risk. It is likely that epidemiologic surveys that are reliant on BMI as a measure of adiposity will overestimate the number of individuals in the overweight (and slightly obese) categories. This tendency to misclassify individuals may be more pronounced in athletic populations or groups in which the proportion of more active individuals is higher. This differential is most pronounced in sports where it is advantageous to have a high BMI (but not necessarily high fatness). To illustrate this point we calculated the BMIs of international professional rugby players from the four teams involved in the semi-finals of the 2003 Rugby Union World Cup. According to the World Health Organisation (WHO) cut-offs for BMI, approximately 65% of the players were classified as overweight and approximately 25% as obese. These findings demonstrate that a high BMI is commonplace (and a potentially desirable attribute for sport performance) in professional rugby players. An unanswered question is what proportion of the wider population, classified as overweight (or obese) according to the BMI, is misclassified according to both fatness and health risk? It is evident that being overweight should not be an obstacle to a physically active lifestyle. Similarly, a reliance on BMI alone may misclassify a number of individuals who might otherwise have been automatically considered fat and/or unfit.

Why do so few hold stocks : theory and evidence

This study develops a life-cycle model where investors make investment decisions in a realistic environment. Model results show that personal illiquid projects (housing and children), fixed costs (once-off/per-period participation costs plus variable/fixed transaction costs) and endogenous risky human capital (with permanent, transitory and disastrous shocks) together are able to address both the non-participation puzzle and the age-effects puzzle. Empirical implications of the model are examined using Heckman’s two-step method with the latest five Surveys of Consumer Finance (SCF). Regression results show that liquidity, informational cost and human capital are indeed the major determinants of participation and asset allocation decisions at different stages of an investor’s life.

Creating a therapeutic environment : a non-randomised controlled trial of a quiet time intervention for patients in acute care

Background: Noise is a significant barrier to sleep for acute care hospital patients, and sleep has been shown to be therapeutic for health, healing and recovery. Scheduled quiet time interventions to promote inpatient rest and sleep have been successfully trialled in critical care but not in acute care settings. Objectives: The study aim was to evaluate as cheduled quiet time intervention in an acute care setting. The study measured the effect of a scheduled quiet time on noise levels, inpatients’ rest and sleep behaviour, and wellbeing. The study also examined the impact of the intervention on patients’, visitors’ and health professionals’ satisfaction, and organisational functioning. Design: The study was a multi-centred non-randomised parallel group trial. Settings: The research was conducted in the acute orthopaedic wards of two major urban public hospitals in Brisbane, Australia. Participants: All patientsadmitted to the two wards in the5-month period of the study were invited to participate, withafinalsample of 299 participants recruited. This sample produced an effect size of 0.89 for an increase in the number of patients asleep during the quiet time. Methods: Demographic data were collected to enable comparison between groups. Data for noise level, sleep status, sleepiness and well being were collected using previously validated instruments: a Castle Model 824 digital sound level indicator; a three point sleep status scale; the Epworth Sleepiness Scale; and the SF12 V2 questionnaire. The staff, patient and visitor surveys on the experimental ward were adapted from published instruments. Results: Significant differences were found between the two groups in mean decibel level and numbers of patients awake and asleep. The difference in mean measured noise levels between the two environments corresponded to a ‘perceived’ difference of 2 to 1. There were significant correlations between average decibel level and number of patients awake and asleep in the experimental group, and between average decibel level and number of patients awake in the control group. Overall, patients, visitors and health professionals were satisfied with the quiet time intervention. Conclusions: The findings show that a quiet time intervention on an acute care hospital ward can affect noise level and patient sleep/wake patterns during the intervention period. The overall strongly positive response from surveys suggests that scheduled quiet time would be a positively perceived intervention with therapeutic benefit.