Internet information and medical consultations: experiences from patients' and physicians' perspectives

OBJECTIVE: Many patients use the Internet to obtain health-related information. It is assumed that health-related Internet information (HRII) will change the consultation practice of physicians. This article explores the strategies, benefits and difficulties from the patients' and physicians' perspective. METHODS: Semi-structured interviews were conducted independently with 32 patients and 20 physicians. Data collection, processing and analysis followed the core principles of Grounded Theory. RESULTS: Patients experienced difficulties in the interpretation of the personal relevance and the meaning of HRII. Therefore they relied on their physicians' interpretation and contextualisation of this information. Discussing patients' concerns and answering patients' questions were important elements of successful consultations with Internet-informed patients to achieve clarity, orientation and certainty. Discussing HRII with patients was appreciated by most of the physicians but misleading interpretations by patients and contrary views compared to physicians caused conflicts during consultations. CONCLUSION: HRII is a valuable source of knowledge for an increasing number of patients. Patients use the consultation to increase their understanding of health and illness. Determinants such as a patient-centred consultation and timely resources are decisive for a successful, empowering consultation with Internet-informed patients. PRACTICAL IMPLICATIONS: If HRII is routinely integrated in the anamnestic interview as a new source of knowledge, the Internet can be used as a link between physicians' expertise and patient knowledge. The critical appraisal of HRII during the consultation is becoming a new field of work for physicians.

Survey of public knowledge about Echinococcus multilocularis in four European countries: Need for proactive information

Background Public information about prevention of zoonoses should be based on the perceived problem by the public and should be adapted to regional circumstances. Growing fox populations have led to increasing concern about human alveolar echinococcosis, which is caused by the fox tapeworm Echinococcus multilocularis. In order to plan information campaigns, public knowledge about this zoonotic tapeworm was assessed. Methods By means of representative telephone interviews (N = 2041), a survey of public knowledge about the risk and the prevention of alveolar echinococcosis was carried out in the Czech Republic, France, Germany and Switzerland in 2004. Results For all five questions, significant country-specific differences were found. Fewer people had heard of E. multilocularis in the Czech Republic (14%) and France (18%) compared to Germany (63%) and Switzerland (70%). The same effect has been observed when only high endemic regions were considered (Czech Republic: 20%, France: 17%, Germany: 77%, Switzerland: 61%). In France 17% of people who knew the parasite felt themselves reasonably informed. In the other countries, the majority felt themselves reasonably informed (54–60%). The percentage that perceived E. multilocularis as a high risk ranged from 12% (Switzerland) to 43% (France). In some countries promising measures as deworming dogs (Czech Republic, Switzerland) were not recognized as prevention options. Conclusion Our results and the actual epidemiological circumstances of AE call for proactive information programs. This communication should enable the public to achieve realistic risk perception, give clear information on how people can minimize their infection risk, and prevent exaggerated reactions and anxiety.

Integrated data acquisition and processing to determine metabolite contents, relaxation times, and macromolecule baseline in single examinations of individual subjects

Absolute quantitation of clinical (1)H-MR spectra is virtually always incomplete for single subjects because the separate determination of spectrum, baseline, and transverse and longitudinal relaxation times in single subjects is prohibitively long. Integrated Processing and Acquisition of Data (IPAD) based on a combined 2-dimensional experimental and fitting strategy is suggested to substantially improve the information content from a given measurement time. A series of localized saturation-recovery spectra was recorded and combined with 2-dimensional prior-knowledge fitting to simultaneously determine metabolite T(1) (from analysis of the saturation-recovery time course), metabolite T(2) (from lineshape analysis based on metabolite and water peak shapes), macromolecular baseline (based on T(1) differences and analysis of the saturation-recovery time course), and metabolite concentrations (using prior knowledge fitting and conventional procedures of absolute standardization). The procedure was tested on metabolite solutions and applied in 25 subjects (15-78 years old). Metabolite content was comparable to previously found values. Interindividual variation was larger than intraindividual variation in repeated spectra for metabolite content as well as for some relaxation times. Relaxation times were different for various metabolite groups. Parts of the interindividual variation could be explained by significant age dependence of relaxation times.

Opportunistic Content-Centric Data Transmission During Short Network Contacts

In this paper, we investigate content-centric data transmission in the context of short opportunistic contacts and base our work on an existing content-centric networking architecture. In case of short interconnection times, file transfers may not be completed and the received information is discarded. Caches in content-centric networks are used for short-term storage and do not guarantee persistence. We implemented a mechanism to extend caching on persistent storage enabling the completion of disrupted content transfers. The mechanisms have been implemented in the CCNx framework and have been evaluated on wireless mesh nodes. Our evaluations using multicast and unicast communication show that the implementation can support content transfers in opportunistic environments without significant processing and storing overhead.

Demo Abstract: Disseminating WMSN Data by Using Social Network and Web

For smart cities applications, a key requirement is to disseminate data collected from both scalar and multimedia wireless sensor networks to thousands of end-users. Furthermore, the information must be delivered to non-specialist users in a simple, intuitive and transparent manner. In this context, we present Sensor4Cities, a user-friendly tool that enables data dissemination to large audiences, by using using social networks, or/and web pages. The user can request and receive monitored information by using social networks, e.g., Twitter and Facebook, due to their popularity, user-friendly interfaces and easy dissemination. Additionally, the user can collect or share information from smart cities services, by using web pages, which also include a mobile version for smartphones. Finally, the tool could be configured to periodically monitor the environmental conditions, specific behaviors or abnormal events, and notify users in an asynchronous manner. Sensor4Cities improves the data delivery for individuals or groups of users of smart cities applications and encourages the development of new user-friendly services.

Approximate decoding approaches for network coded correlated data

This paper considers a framework where data from correlated sources are transmitted with the help of network coding in ad hoc network topologies. The correlated data are encoded independently at sensors and network coding is employed in the intermediate nodes in order to improve the data delivery performance. In such settings, we focus on the problem of reconstructing the sources at decoder when perfect decoding is not possible due to losses or bandwidth variations. We show that the source data similarity can be used at decoder to permit decoding based on a novel and simple approximate decoding scheme. We analyze the influence of the network coding parameters and in particular the size of finite coding fields on the decoding performance. We further determine the optimal field size that maximizes the expected decoding performance as a trade-off between information loss incurred by limiting the resolution of the source data and the error probability in the reconstructed data. Moreover, we show that the performance of the approximate decoding improves when the accuracy of the source model increases even with simple approximate decoding techniques. We provide illustrative examples showing how the proposed algorithm can be deployed in sensor networks and distributed imaging applications.

Food-safety hazards in the pork chain in Nagaland, North East India: implications for human health.

Pork occupies an important place in the diet of the population of Nagaland, one of the North East Indian states. We carried out a pilot study along the pork meat production chain, from live animal to end consumer. The goal was to obtain information about the presence of selected food borne hazards in pork in order to assess the risk deriving from these hazards to the health of the local consumers and make recommendations for improving food safety. A secondary objective was to evaluate the utility of risk-based approaches to food safety in an informal food system. We investigated samples from pigs and pork sourced at slaughter in urban and rural environments, and at retail, to assess a selection of food-borne hazards. In addition, consumer exposure was characterized using information about hygiene and practices related to handling and preparing pork. A qualitative hazard characterization, exposure assessment and hazard characterization for three representative hazards or hazard proxies, namely Enterobacteriaceae, T. solium cysticercosis and antibiotic residues, is presented. Several important potential food-borne pathogens are reported for the first time including Listeria spp. and Brucella suis. This descriptive pilot study is the first risk-based assessment of food safety in Nagaland. We also characterise possible interventions to be addressed by policy makers, and supply data to inform future risk assessments.

A Concept of Semantics Extraction from Web Data by Induction of Fuzzy Ontologies

Traditionally, ontologies describe knowledge representation in a denotational, formalized, and deductive way. In addition, in this paper, we propose a semiotic, inductive, and approximate approach to ontology creation. We define a conceptual framework, a semantics extraction algorithm, and a first proof of concept applying the algorithm to a small set of Wikipedia documents. Intended as an extension to the prevailing top-down ontologies, we introduce an inductive fuzzy grassroots ontology, which organizes itself organically from existing natural language Web content. Using inductive and approximate reasoning to reflect the natural way in which knowledge is processed, the ontology’s bottom-up build process creates emergent semantics learned from the Web. By this means, the ontology acts as a hub for computing with words described in natural language. For Web users, the structural semantics are visualized as inductive fuzzy cognitive maps, allowing an initial form of intelligence amplification. Eventually, we present an implementation of our inductive fuzzy grassroots ontology Thus,this paper contributes an algorithm for the extraction of fuzzy grassroots ontologies from Web data by inductive fuzzy classification.