Proteomics science and society :the role of knowledge translation in moving towards clinical applications

Gaining support for proteomics science requires effective knowledge translation. Knowledge translation (KT) processes turn the evidence generated by scientific discovery into recommendations for clinical applications, funding priorities, and policy/regulatory reforms. Clinicians, regulators, and funders need to understand why emerging proteomics knowledge is relevant, and what are the potential applications of that knowledge. A lack of clarity remains about what KT means.

Post-genomic science & society : Getting our fangs into omics science and its implications

Genomics and genetic findings have been hailed with promises of unlocked codes and new frontiers of personalized medicine. Despite cautions about gene hype, the strong cultural pull of genes and genomics has allowed consideration of genomic personhood. Populated by the complicated records of mass spectrometer, proteomics, which studies the human protein, has not achieved either the funding or the popular cultural appeal proteomics scientists had hoped it would. While proteomics, being focused on the proteins that actually indicate and create disease states, has a more direct potential for clinical applications than genomic risk predictions, culturally, it has not provided the material for identity creation. In our ethnographic research, we explore how proteomic scientists attempting to shape an appeal to personhood through which legitimacy may be defined.

Aboriginal and Torres Strait Islander people in Australia, education and health literacy

Health literacy is a vital tool to build health knowledge and enable empowerment in health decision making at a community and individual level. There are different views of what constitutes health literacy with the most inclusive addressing broadly the skills and competencies required “to seek out, comprehend, evaluate, and use health information and concepts to make informed choices, reduce health risks, and increase quality of life” (Zarcadoolas 2005). Poor health literacy has been shown to impact health seeking behaviour, access and awareness to preventive health.

The next generation health intervention tool - Can smart phone applications help young people track and moderate alcohol use and potential harms?

Whilst alcohol is a common feature of many social gatherings, there are numerous immediate and long-term health and social harms associated with its abuse. Alcohol consumption is the world’s third largest risk factor for disease and disability with almost 4% of all deaths worldwide attributed to alcohol. Not surprisingly, alcohol use and binge drinking by young people is of particular concern with Australian data reporting that 39% of young people (18-19yrs) admitted drinking at least weekly and 32% drank to levels that put them at risk of alcohol-related harm. The growing market penetration and connectivity of smartphones may be an opportunities for innovation in promoting health-related self-management of substance use. However, little is known about how best to harness and optimise this technology for health-related intervention and behaviour change. This paper explores the utility and interface of smartphone technology as a health intervention tool to monitor and moderate alcohol use. A review of the psychological health applications of this technology will be presented along with the findings of a series of focus groups, surveys and behavioural field trials of several drink-monitoring applications. Qualitative and quantitative data will be presented on the perceptions, preferences and utility of the design, usability and functionality of smartphone apps to monitoring and moderate alcohol use. How these findings have shaped the development and evolution of the OnTrack app will be specifically discussed, along with future directions and applications of this technology in health intervention, prevention and promotion.

A statistical strategy to select optimal structural health monitoring data in operational modal analysis

Operational modal analysis (OMA) is prevalent in modal identifi cation of civil structures. It asks for response measurements of the underlying structure under ambient loads. A valid OMA method requires the excitation be white noise in time and space. Although there are numerous applications of OMA in the literature, few have investigated the statistical distribution of a measurement and the infl uence of such randomness to modal identifi cation. This research has attempted modifi ed kurtosis to evaluate the statistical distribution of raw measurement data. In addition, a windowing strategy employing this index has been proposed to select quality datasets. In order to demonstrate how the data selection strategy works, the ambient vibration measurements of a laboratory bridge model and a real cable-stayed bridge have been respectively considered. The analysis incorporated with frequency domain decomposition (FDD) as the target OMA approach for modal identifi cation. The modal identifi cation results using the data segments with different randomness have been compared. The discrepancy in FDD spectra of the results indicates that, in order to fulfi l the assumption of an OMA method, special care shall be taken in processing a long vibration measurement data. The proposed data selection strategy is easy-to-apply and verifi ed effective in modal analysis.

Secured e-health data retrieval in DaaS and Big Data

Big Data is a rising IT trend similar to cloud computing, social networking or ubiquitous computing. Big Data can offer beneficial scenarios in the e-health arena. However, one of the scenarios can be that Big Data needs to be kept secured for a long period of time in order to gain its benefits such as finding cures for infectious diseases and protecting patient privacy. From this connection, it is beneficial to analyse Big Data to make meaningful information while the data is stored securely. Therefore, the analysis of various database encryption techniques is essential. In this study, we simulated 3 types of technical environments, namely, Plain-text, Microsoft Built-in Encryption, and custom Advanced Encryption Standard, using Bucket Index in Data-as-a-Service. The results showed that custom AES-DaaS has a faster range query response time than MS built-in encryption. Furthermore, while carrying out the scalability test, we acknowledged that there are performance thresholds depending on physical IT resources. Therefore, for the purpose of efficient Big Data management in eHealth it is noteworthy to examine their scalability limits as well even if it is under a cloud computing environment. In addition, when designing an e-health database, both patient privacy and system performance needs to be dealt as top priorities.

Tools of the trade: quick measures and validated tools for assessing health and wellness. How you can better help your clients/employees help themselves

Worksite wellness efforts can generate enormous health-care savings. Many of the methods available to obtain health and wellness measures can be confusing and lack clarity; for example it can be difficult to understand if measures are appropriate for individuals or population health. Come along and enjoy a hands-on learning experience about measures and better understanding health and wellness outcomes from baseline, midway and beyond.

Retrieval of health advice on the web: AEHRC at ShARe/CLEF eHealth Evaluation Lab Task 3

This paper details the participation of the Australian e- Health Research Centre (AEHRC) in the ShARe/CLEF 2013 eHealth Evaluation Lab { Task 3. This task aims to evaluate the use of information retrieval (IR) systems to aid consumers (e.g. patients and their relatives) in seeking health advice on the Web. Our submissions to the ShARe/CLEF challenge are based on language models generated from the web corpus provided by the organisers. Our baseline system is a standard Dirichlet smoothed language model. We enhance the baseline by identifying and correcting spelling mistakes in queries, as well as expanding acronyms using AEHRC's Medtex medical text analysis platform. We then consider the readability and the authoritativeness of web pages to further enhance the quality of the document ranking. Measures of readability are integrated in the language models used for retrieval via prior probabilities. Prior probabilities are also used to encode authoritativeness information derived from a list of top-100 consumer health websites. Empirical results show that correcting spelling mistakes and expanding acronyms found in queries signi cantly improves the e ectiveness of the language model baseline. Readability priors seem to increase retrieval e ectiveness for graded relevance at early ranks (nDCG@5, but not precision), but no improvements are found at later ranks and when considering binary relevance. The authoritativeness prior does not appear to provide retrieval gains over the baseline: this is likely to be because of the small overlap between websites in the corpus and those in the top-100 consumer-health websites we acquired.

Identify disorders in health records using Conditional Random Fields and Metamap: AEHRC at ShARe/CLEF 2013 eHealth Evaluation Lab Task 1

The Australian e-Health Research Centre (AEHRC) recently participated in the ShARe/CLEF eHealth Evaluation Lab Task 1. The goal of this task is to individuate mentions of disorders in free-text electronic health records and map disorders to SNOMED CT concepts in the UMLS metathesaurus. This paper details our participation to this ShARe/CLEF task. Our approaches are based on using the clinical natural language processing tool Metamap and Conditional Random Fields (CRF) to individuate mentions of disorders and then to map those to SNOMED CT concepts. Empirical results obtained on the 2013 ShARe/CLEF task highlight that our instance of Metamap (after ltering irrelevant semantic types), although achieving a high level of precision, is only able to identify a small amount of disorders (about 21% to 28%) from free-text health records. On the other hand, the addition of the CRF models allows for a much higher recall (57% to 79%) of disorders from free-text, without sensible detriment in precision. When evaluating the accuracy of the mapping of disorders to SNOMED CT concepts in the UMLS, we observe that the mapping obtained by our ltered instance of Metamap delivers state-of-the-art e ectiveness if only spans individuated by our system are considered (`relaxed' accuracy).

The health information practices of people living with chronic health conditions: Implications for health literacy

The reduction of the health literacy concept to a functional relationship with text, does not acknowledge the range of information sources that people draw from in order to make informed decision about their health and treatment. Drawing from two studies that explored how people with two different but complex and life-threatening chronic health conditions, chronic kidney disease and HIV, a socio-cultural understanding of the practise of health literacy is described. Health information is experienced by patients as a chronic health condition landscape, and develops from three information sources; namely epistemic, social and corporeal sources. Participants in both studies used activities that involved orienting, sharing and creating information to map this landscape which was used to inform their decision-making. These findings challenge the traditional conceptions of health literacy and suggest an approach that views the landscape of chronic illness as being socially, physically and contextually constructed. This approach necessitates a recasting of health literacy away from a sole interest in skills and towards understanding how information practices facilitate people becoming health literate.

Privacy oriented access control for electronic health records

Information privacy is a critical success/failure factor in information technology supported healthcare (eHealth). eHealth systems utilise electronic health records (EHR) as the main source of information, thus, implementing appropriate privacy preserving methods for EHRs is vital for the proliferation of eHealth. Whilst information privacy may be a fundamental requirement for eHealth consumers, healthcare professionals demand non-restricted access to patient information for improved healthcare delivery, thus, creating an environment where stakeholder requirements are contradictory. Therefore, there is a need to achieve an appropriate balance of requirements in order to build successful eHealth systems. Towards achieving this balance, a new genre of eHealth systems called Accountable-eHealth (AeH) systems has been proposed. In this paper, an access control model for EHRs is presented that can be utilised by AeH systems to create information usage policies that fulfil both stakeholders’ requirements. These policies are used to accomplish the aforementioned balance of requirements creating a satisfactory eHealth environment for all stakeholders. The access control model is validated using a Web based prototype as a proof of concept.

Health Information Literacy and the Experience of 65 to 79 Year Old Australians

Information literacy is presented here from a relational perspective, as people’s experience of using information to learn in a particular context. A detailed practical example of such a context is provided, in the health information literacy experience of 65–79 year old Australians. A phenomenographic investigation found five qualitatively distinct ways of experiencing health information literacy: Absorbing (intuitive reception), Targeting (a planned process), Journeying (a personal quest), Liberating (equipping for independence) and Collaborating (interacting in community). These five ways of experiencing indicated expanding awareness of context (degree of orientation towards their environment), source (breadth of esteemed information), beneficiary (the scope of people who gain) and agency (amount of activity), across HIL core aspects of information, learning and health. These results illustrate the potential contribution of relational information literacy to information science.

Spectroscopic correlation analysis of NMR-based metabonomics in exercise science

Spectroscopic studies of complex clinical fluids have led to the application of a more holistic approach to their chemical analysis becoming more popular and widely employed. The efficient and effective interpretation of multidimensional spectroscopic data relies on many chemometric techniques and one such group of tools is represented by so-called correlation analysis methods. Typical of these techniques are two-dimensional correlation analysis and statistical total correlation spectroscopy (STOCSY). Whilst the former has largely been applied to optical spectroscopic analysis, STOCSY was developed and has been applied almost exclusively to NMR metabonomic studies. Using a 1H NMR study of human blood plasma, from subjects recovering from exhaustive exercise trials, the basic concepts and applications of these techniques are examined. Typical information from their application to NMR-based metabonomics is presented and their value in aiding interpretation of NMR data obtained from biological systems is illustrated. Major energy metabolites are identified in the NMR spectra and the dynamics of their appearance and removal from plasma during exercise recovery are illustrated and discussed. The complementary nature of two-dimensional correlation analysis and statistical total correlation spectroscopy are highlighted.

From science to management : using Bayesian networks to learn about Lyngbya

Toxic blooms of Lyngbya majuscula occur in coastal areas worldwide and have major ecological, health and economic consequences. The exact causes and combinations of factors which lead to these blooms are not clearly understood. Lyngbya experts and stakeholders are a particularly diverse group, including ecologists, scientists, state and local government representatives, community organisations, catchment industry groups and local fishermen. An integrated Bayesian Network approach was developed to better understand and model this complex environmental problem, identify knowledge gaps, prioritise future research and evaluate management options.

Experiencing information across the phenomenon of health information literacy

Interest in the concept of information literacy in different contexts is a topic that has steadily gained increased attention in information literacy discourse and research efforts over recent years. In particular the emergence of the term ‘health information literacy’ attests to this interest and has elevated awareness about the importance and relevance of information literacy in a health context. This paper reports on research that has taken a relational perspective to explore how people experience health information literacy. Initially established by Bruce (1997) the relational perspective draws from an experiential framework that emphasizes the relationship between users and information when learning in different contexts. This approach seeks outcomes that are deeply embedded in users’ informational life worlds and complements experiential phenomenological perspectives that have been used in health research. In keeping with the relational approach this research interprets health information literacy as being the different ways in which people experience using information to learn about health. Using interpretive phenomenography, this research explored variation in the lived experience of how people use information to learn about their health, and variation in what is constituted as information when learning about their health. Participants included 23 males and females aged between 45 and 64 years. All participants were residents from the Greater Brisbane area of Queensland, Australia. The research used semi-structured interviews for data collection. The types of questions posed during interviews included ‘Can you describe a time when you used information to learn about your health?’ and ‘What kinds of information have you used to learn about your health?’. This paper will focus on presenting one element of research findings that concerns the differences in ‘what’ participants experienced as information. Analysis of interview data identified significant variation in the experienced nature of information, specifically the different qualities or elements that comprised the ‘object’ of information, or in other words, what was perceived as ‘informing’. Illustrations of this variation include information experienced as traditional information sources, facts and experiences, something exhibiting particular qualities, physical or psychological changes, other people and role models. These findings provide new insights into what people may experience as information, and build upon existing literature regarding information as a theoretical construct. In addition the potential implications of these findings with respect to the design and delivery of health information literacy education will also be discussed. These research findings contribute to the emergence of information literacy investigations in everyday life and community. Although such settings have long been identified as a significant gap for exploration, research to date in this field has predominantly focused on educational and workplace environments. In this way the knowledge gained from this research has further revealed the contextual nature of information literacy, as well as its complexity as a phenomenon and focus of study.