Twitter as a medium for professional networking

This study aims to explore the use of Twitter for professional purposes. The researcher discovered that Twitter is widely perceived as an information ground in online spaces. Information grounds are social settings where information, people, and places come together to create an information flow within a physical environment. Twitter provides a sense of place as well as a sense of belonging that enables IT professionals to use Twitter for professional development. The data for this study were collected using online observations and interviews. The online observations helped the researcher to distinguish the ‘information behaviours’ (the objective and observable actions) of the participants. The interviews were used to understand the way IT professionals use Twitter for professional purposes through their own individual perspectives. The data were analysed using a constructive grounded theory. The findings show that building professional networking is extremely important to IT professionals; rather than the information-seeking and information-sharing aspects of Twitter. Building professional networking in microblogging has a significant influence on an individual’s professional development. The results also demonstrate that IT professionals are more likely to exploit their weak-ties rather than their strong-ties on Twitter. In short, these users experience Twitter as a real place or ‘information grounds’ where they meet and socialise with experts.

Hospital in the Nursing Home program reduces emergency department presentations and hospital admissions from residential aged care facilities in Queensland, Australia: A quasi-experimental study

Background There has been considerable publicity regarding population ageing and hospital emergency department (ED) overcrowding. Our study aims to investigate impact of one intervention piloted in Queensland Australia, the Hospital in the Nursing Home (HiNH) program, on reducing ED and hospital attendances from residential aged care facilities (RACFs). Methods A quasi-experimental study was conducted at an intervention hospital undertaking the program and a control hospital with normal practice. Routine Queensland health information system data were extracted for analysis. Results Significant reductions in the number of ED presentations per 1000 RACF beds (rate ratio (95 % CI): 0.78 (0.67–0.92); p = 0.002), number of hospital admissions per 1000 RACF beds (0.62 (0.50–0.76); p < 0.0001), and number of hospital admissions per 100 ED presentations (0.61 (0.43–0.85); p = 0.004) were noticed in the experimental hospital after the intervention; while there were no significant differences between intervention and control hospitals before the intervention. Pre-test and post-test comparison in the intervention hospital also presented significant decreases in ED presentation rate (0.75 (0.65–0.86); p < 0.0001) and hospital admission rate per RACF bed (0.66 (0.54–0.79); p < 0.0001), and a non-significant reduction in hospital admission rate per ED presentation (0.82 (0.61–1.11); p = 0.196). Conclusions Hospital in the Nursing Home program could be effective in reducing ED presentations and hospital admissions from RACF residents. Implementation of the program across a variety of settings is preferred to fully assess the ongoing benefits for patients and any possible cost-savings.

Evaluating the specificity of community injury hospitalization data over time

This study identified the areas of poor specificity in national injury hospitalization data and the areas of improvement and deterioration in specificity over time. A descriptive analysis of ten years of national hospital discharge data for Australia from July 2002-June 2012 was performed. Proportions and percentage change of defined/undefined codes over time was examined. At the intent block level, accidents and assault were the most poorly defined with over 11% undefined in each block. The mechanism blocks for accidents showed a significant deterioration in specificity over time with up to 20% more undefined codes in some mechanisms. Place and activity were poorly defined at the broad block level (43% and 72% undefined respectively). Private hospitals and hospitals in very remote locations recorded the highest proportion of undefined codes. Those aged over 60 years and females had the higher proportion of undefined code usage. This study has identified significant, and worsening, deficiencies in the specificity of coded injury data in several areas. Focal attention is needed to improve the quality of injury data, especially on those identified in this study, to provide the evidence base needed to address the significant burden of injury in the Australian community.

Positive associations of serum Perfluoroalkyl substances with uric acid and hyperuricemia in children from Taiwan

To investigate the risk of hyperuricemia in relation to Perfluoroalkyl substances (PFASs) in children from Taiwan, 225 Taiwanese children aged 12-15 years were recruited from 2009 to 2010. Linear and logistic regression models were employed to examine the influence of PFASs on serum uric acid levels. Findings revealed that eight of ten PFASs analyses were detected in > 94% of the participants' serum samples. Multivariate linear regression models revealed that perfluorooctanic acid (PFOA) was positively associated with serum uric acid levels (β=0.1463, p<0.05). Of all the PFASs analyses, only PFOA showed a significant effect on elevated levels of hyperuricemia (aOR=2.16, 95%CI: 1.29-3.61). When stratified by gender, the association between serum PFOA and uric acid levels was only evident among boys (aOR=2.76, 95%CI: 1.37-5.56). In conclusion, PFOA was found to be associated with elevated serum levels of uric acid in Taiwanese children, especially boys. Further research is needed to elucidate these links.

Development and evaluation of a spatial decision support system for malaria elimination in Bhutan

Background: Bhutan has reduced its malaria incidence significantly in the last 5 years, and is aiming for malaria elimination by 2016. To assist with the management of the Bhutanese malaria elimination programme a spatial decision support system (SDSS) was developed. The current study aims to describe SDSS development and evaluate SDSS utility and acceptability through informant interviews. Methods: The SDSS was developed based on the open-source Quantum geographical information system (QGIS) and piloted to support the distribution of long-lasting insecticidal nets (LLINs) and indoor residual spraying (IRS) in the two sub-districts of Samdrup Jongkhar District. It was subsequently used to support reactive case detection (RACD) in the two sub-districts of Samdrup Jongkhar and two additional sub-districts in Sarpang District. Interviews were conducted to ascertain perceptions on utility and acceptability of 11 informants using the SDSS, including programme and district managers, and field workers. Results: A total of 1502 households with a population of 7165 were enumerated in the four sub-districts, and a total of 3491 LLINs were distributed with one LLIN per 1.7 persons. A total of 279 households representing 728 residents were involved with RACD. Informants considered that the SDSS was an improvement on previous methods for organizing LLIN distribution, IRS and RACD, and could be easily integrated into routine malaria and other vector-borne disease surveillance systems. Informants identified some challenges at the programme and field level, including the need for more skilled personnel to manage the SDSS, and more training to improve the effectiveness of SDSS implementation and use of hardware. Conclusions: The SDSS was well accepted and informants expected its use to be extended to other malaria reporting districts and other vector-borne diseases. Challenges associated with efficient SDSS use included adequate skills and knowledge, access to training and support, and availability of hardware including computers and global positioning system receivers.

Mapping the risk of soil-transmitted helminthic infections in the Philippines

Background In order to increase the efficient allocation of soil-transmitted helminth (STH) disease control resources in the Philippines, we aimed to describe for the first time the spatial variation in the prevalence of A. lumbricoides, T. trichiura and hookworm across the country, quantify the association between the physical environment and spatial variation of STH infection and develop predictive risk maps for each infection. Methodology/Principal Findings Data on STH infection from 35,573 individuals across the country were geolocated at the barangay level and included in the analysis. The analysis was stratified geographically in two major regions: 1) Luzon and the Visayas and 2) Mindanao. Bayesian geostatistical models of STH prevalence were developed, including age and sex of individuals and environmental variables (rainfall, land surface temperature and distance to inland water bodies) as predictors, and diagnostic uncertainty was incorporated. The role of environmental variables was different between regions of the Philippines. This analysis revealed that while A. lumbricoides and T. trichiura infections were widespread and highly endemic, hookworm infections were more circumscribed to smaller foci in the Visayas and Mindanao. Conclusions/Significance This analysis revealed significant spatial variation in STH infection prevalence within provinces of the Philippines. This suggests that a spatially targeted approach to STH interventions, including mass drug administration, is warranted. When financially possible, additional STH surveys should be prioritized to high-risk areas identified by our study in Luzon.

Towards a typology of hashtag publics: A large-scale comparative study of user engagement across trending topics

Twitter’s hashtag functionality is now used for a very wide variety of purposes, from covering crises and other breaking news events through gathering an instant community around shared media texts (such as sporting events and TV broadcasts) to signalling emotive states from amusement to despair. These divergent uses of the hashtag are increasingly recognised in the literature, with attention paid especially to the ability for hashtags to facilitate the creation of ad hoc or hashtag publics. A more comprehensive understanding of these different uses of hashtags has yet to be developed, however. Previous research has explored the potential for a systematic analysis of the quantitative metrics that could be generated from processing a series of hashtag datasets. Such research found, for example, that crisis-related hashtags exhibited a significantly larger incidence of retweets and tweets containing URLs than hashtags relating to televised events, and on this basis hypothesised that the information-seeking and -sharing behaviours of Twitter users in such different contexts were substantially divergent. This article updates such study and their methodology by examining the communicative metrics of a considerably larger and more diverse number of hashtag datasets, compiled over the past five years. This provides an opportunity both to confirm earlier findings, as well as to explore whether hashtag use practices may have shifted subsequently as Twitter’s userbase has developed further; it also enables the identification of further hashtag types beyond the “crisis” and “mainstream media event” types outlined to date. The article also explores the presence of such patterns beyond recognised hashtags, by incorporating an analysis of a number of keyword-based datasets. This large-scale, comparative approach contributes towards the establishment of a more comprehensive typology of hashtags and their publics, and the metrics it describes will also be able to be used to classify new hashtags emerging in the future. In turn, this may enable researchers to develop systems for automatically distinguishing newly trending topics into a number of event types, which may be useful for example for the automatic detection of acute crises and other breaking news events.

Understanding data flow and security requirements in wireless Body Area Networks for healthcare

The Body Area Network (BAN) is an emerging technology that focuses on monitoring physiological data in, on and around the human body. BAN technology permits wearable and implanted sensors to collect vital data about the human body and transmit it to other nodes via low-energy communication. In this paper, we investigate interactions in terms of data flows between parties involved in BANs under four different scenarios targeting outdoor and indoor medical environments: hospital, home, emergency and open areas. Based on these scenarios, we identify data flow requirements between BAN elements such as sensors and control units (CUs) and parties involved in BANs such as the patient, doctors, nurses and relatives. Identified requirements are used to generate BAN data flow models. Petri Nets (PNs) are used as the formal modelling language. We check the validity of the models and compare them with the existing related work. Finally, using the models, we identify communication and security requirements based on the most common active and passive attack scenarios.